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--- "a/annotate_aivin.jsonl"
+++ "b/annotate_aivin.jsonl"
@@ -1,240 +1,240 @@
-{"text": "home-based learning programs,\" or IRI 1.1,\n“Percentage of children provided access to programs and sensitization campaigns that aim at minimizing\nthe negative impacts of school closure like psychological impacts and gender-based violence.”\nNevertheless, these indicators were measured using a telephone survey implemented by the Bank, which\nwas originally intended as a secondary source for validation of the REB data (ICR, p. 32).\n\n\n**c. M&E Utilization**\n\nThe project M&E data were used for assessing progress on project activities and indicators, keeping\nproject implementation on track, informing the two project restructurings and reallocations, and serving\nas a basis for implementation support missions. Additionally, the project-supported strengthening of\nsupervision capacity at federal and REB levels contributed to utilization of the M&E system. Also,\nfollowing the second restructuring, in order to improve REBs’ familiarity with the M&E design, the Task\nTeam presented the RF and M&E findings to REB officials at a workshop that aimed to support both\nprocurement and environmental and social management (ICR, pp. 32-33).\n\n\n**M&E Quality Rating**\nSubstantial\n\n\n**10. Other Issues**\n\n\n**a. Safeguards**\n\nThe Environmental and Social (E&S) risk was rated Moderate throughout the project’s life. The activities\nfinanced by the project were not expected to cause irreversible environmental and social impacts,\nconversion of natural habitats, degradation of biodiversity, or loss of forest resources, as neither large-scale\n\n\nPage 17 of 21", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001527", "page": 16, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "telephone survey implemented by the Bank", "probe_tag": "keep", "probe_score": 0.9460279941558838, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 293, "end": 333, "key": "fcv_pads_east_africa:001527:16:1:0", "source": "camp2", "luna_reason": "Past telephone survey data measured indicators and validated REB data.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "project M&E data", "probe_tag": "confusion", "probe_score": 0.8128094673156738, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 462, "end": 478, "key": "fcv_pads_east_africa:001527:16:1:2", "source": "camp2", "luna_reason": "Project monitoring data used for implementation management, not an independent evidence resource.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": ".\n\n\n**Coordinated, community-linked interventions can reduce barriers to education for**\n**marginalized groups.** IERCs combined with itinerant teacher training and community\noutreach increased enrollment of children with special needs, while gender clubs in emerging\nregions supported girls' retention and were replicated beyond program schools. These experiences\nshowed that structured approaches linking education authorities, families, and service providers —\nsupported by capacity-building and awareness-raising — can meaningfully improve access and\nretention for the most excluded learners.\n\n\n**12. Assessment Recommended?**\n\n\nNo\n\n\n**13. Comments on Quality of ICR**\n\n\n**Quality of Evidence.** Evidence provided in the ICR was drawn from systematically collected administrative and\nmonitoring data, including strengthened national systems such as EMIS, textbook tracking, national and earlygrade assessments, and school inspections. Achievement of DLI/DLR targets was independently validated,\nenhancing the credibility of reported results. The ICR appropriately triangulated project monitoring data with\nexternal sources, including the World Bank’s 2025 Global Education Policy Dashboard for Ethiopia. While some\nindicators in the ICR’s results framework lacked baseline, target, or achievement values, this information was\navailable elsewhere in project documentation, including the ICR’s Efficacy section, the PAD, restructuring\n\n\nPage 24 of 25", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002925", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "project monitoring data", "probe_tag": "confusion", "probe_score": 0.08977673202753067, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1081, "end": 1104, "key": "fcv_pads_east_africa:002925:23:1:1", "source": "camp2", "luna_reason": "Project monitoring outputs are not external evidence under bookkeeping rules.", "drop_reason": "bookkeeping", "specificity": "descriptive"}, {"text": "2025 Global Education Policy Dashboard", "probe_tag": "keep", "probe_score": 0.9326975345611572, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1155, "end": 1193, "key": "fcv_pads_east_africa:002925:23:1:2", "source": "camp2", "luna_reason": "Named external dashboard used to triangulate project evidence.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "**g)  Failure to transfer Land into the Custody of ULC**\nI noted that out of the titled 1,909 land tittles held by 42 of the 45 MDAs\nin the sample, 15 MDAs did not transfer 167 land titles into the name\nand custody of the Uganda Land Commission for the benefit of the user\nMDAs. The Accounting Officers of public Universities and URA explained\nthat Universities were body corporate with a right to own and manage\ntheir own land.\n\n\nI advised the Attorney General to give a general guidance to corporate\ngovernment entities in regard to the custody of entity land with ULC.\n\n\n**h)  Recording and Reporting of Government Land**\nI noted that out of the 57 sampled entities, 20 entities did not record a\ntotal of 636 pieces of land measuring approximately 19,275.25 hectares\nin their respective Land registers rendering it difficult to confirm the\ncompleteness of their Land inventory.\nI also noted that 26 entities did not record a total of 1,355 pieces of land\nmeasuring approximately 21,603.08 hectares of land in their respective\nGFMIS fixed asset module thus affecting the accuracy of the nonproduced assets in the financial statements.\n\n\nThe non-recording of land in the land register and GFMIS Asset module\naffects the Government’s ability to keep track of all its land which could\neasily lead to loss and /or misstatement of the non-produced asset in the\nfinancial statements.\n\n\nI advised the Accountant General to ensure that the asset module under\nthe GFMIS is functioning properly. In addition, I advised the respective\nAccounting Officer to update both the fixed asset registers and the asset\nmodule under the GFMIS.\n\n\n**i)  Utilization of Government Land for Delivery of Service**\nI noted that out of the 57 sampled entities, 29 entities did not utilize a\ntotal of 258 pieces of land measuring approximately 10,066.8 hectares\nof land held by 30th June 2022. Non-utilization and use of land for", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003028", "page": 61, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "GFMIS Asset module", "probe_tag": "keep", "probe_score": 0.9179682731628418, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1190, "end": 1208, "key": "fcv_pads_east_africa:003028:61:0:3", "source": "camp2", "luna_reason": "Named asset module is mentioned, but its data are not shown informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "fixed asset registers", "probe_tag": "confusion", "probe_score": 0.8224775195121765, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1564, "end": 1585, "key": "fcv_pads_east_africa:003028:61:0:4", "source": "camp2", "luna_reason": "Routine asset-register updating and project administration, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nEthiopia UIIDP (P163452)\n\n\nThis indicator was monitorable and related to the revenue mobilization (through own-source revenue) efforts\nof the eligible ULGs. This indicator is directly related to the sustainability of the urban infrastructure and is\nrated as substantial.\n\n\n**Rating**\nSubstantial\n\n# **DLI 9**\n\n**DLI**\nDLI # 9. Regional Public Procurement and Property Administration Agencies (RPPAA) had conducted timely\nand quality procurement audit of eligible ULG's accounts and performance.\n\n\n**Rationale**\nThis indicator was intended to ensure that the regional public procurement agencies conduct timely and\nquality procurement audits of eligible ULGs accounts. The indicator was monitorable. The indicator is rated as\nsubstantial.\n\n\n**Rating**\nSubstantial\n\n# **DLI 10**\n\n**DLI**\nDLI# 10. Strengthening institutional performance, infrastructure and service delivery, maintenance and job\ncreation for 44 ULGs.\n\n\n**Rationale**\nThe team clarified that DLI was a legacy DLI, grounded in historical performance data from the 2017/18\nAnnual Performance Assessment (APA). This DLI guaranteed the sustainability of previously attained results,\nThe legacy DLI was vital for the 44 ULGs to ensure performance consistency, while new ULGs, due to their\nearly-stage capacity, were not considered under this DLI. This DLI was monitorable. Since this DLI would\nhelp the 44ULGs to show sustained improvements in urban governance and infrastructure development\nachieved over time, this DLI is rated as substantial.\n\n\n**Rating**\nSubstantial\n\n\nOVERALL RELEVANCE DLI TBL\n\n# **OVERALL RELEVANCE RATING**\n\n**Rationale**\n\n\nPage 8 of 16", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003596", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "historical performance data", "probe_tag": "confusion", "probe_score": 0.651159405708313, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1074, "end": 1101, "key": "fcv_pads_east_africa:003596:7:0:0", "source": "camp2", "luna_reason": "Existing performance data from the 2017/18 assessment grounded the DLI.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "2017/18\nAnnual Performance Assessment", "probe_tag": "keep", "probe_score": 0.9181606769561768, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1111, "end": 1148, "key": "fcv_pads_east_africa:003596:7:0:1", "source": "camp2", "luna_reason": "Historical assessment data grounded the DLI indicator.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "data leaves important considerations unaccounted for, such as reverse causality and the migration\ntransition’s longitudinal dimension, as the transition takes place over an extended time period in a given\norigin country. Other studies have tested for a hump shape using panel data (Mayda, 2010; Bertoli and\nHuertas-Moraga, 2013). However, these papers use a limited number of country-time points, which restricts\nthe empirical strength of their results. Other papers test the inverted-U relationship using solely migration\nflows to OECD destinations (Lull, 2016; Benček and Schneiderheinze, 2019). These studies, however,\nexclude the possibility that migrants from low-income countries can also migrate to other low- or mediumincome countries. Since the average share of migration from all origins to non-OECD destinations is 50%\nover the 1960-2017 period, <sup>4</sup> [^4: Computed using the World Bank’s Global Bilateral Migration (Özden _et al._, 2011) and the United Nations’ Trends in International] we include such migration flows in order to incorporate all migration corridors\nin the analysis.\n\n\nThe aim of this paper is to test for the inverted U-shape between emigration and development using\na large panel database. We employ a comprehensive global panel data set with 180 origin and destination\ncountries on a 50-year timeframe (1970-2020). <sup>5</sup> [^5: Data on international migrant stocks in 2019 is used as a proxy for 2020.] This allows us to empirically test for bilateral migration\ndynamics not only across countries but also across time with a relatively large number of observations.\nBecause of its large longitudinal dimension, it is well suited for testing the migration transition hypothesis’\ncentral prediction, which is a long-run phenomenon per origin country (De Haas, 2010). Our empirical\nspecification is based on the random utility-maximization (RUM) model, which provides the microfoundations for a migration version of the gravity model. <sup>6</sup> We employ a gravity-migration specification with\na large number of", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000028", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "panel data", "probe_tag": "confusion", "probe_score": 0.8931313753128052, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 270, "end": 280, "key": "prwp:000028:4:0:0", "source": "camp2", "luna_reason": "Existing panel data supported prior empirical tests of the migration hump hypothesis.", "usage_type": "evidential", "specificity": "vague"}, {"text": "comprehensive global panel data set", "probe_tag": "keep", "probe_score": 0.9287710189819336, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1240, "end": 1275, "key": "prwp:000028:4:0:2", "source": "camp2", "luna_reason": "Existing panel dataset is explicitly used for empirical migration analysis.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "combines these indicators according to the bureau’s judgment of what factors are important (using a\n\n\ndecision rule not trained on data). Subscribers were matched to their financial histories based on an\n\n\nencrypted, anonymized identifier.\n\n\nThe mobile phone data include metadata for each call and SMS, with identifiers for the other party,\n\n\ntime stamps, tower locations, and durations. It does not include top-ups, balances, data access, charges,\n\n\nhandset models used, or mobile money transactions; thus performance is expected to improve with richer\n\n\ndata. The data do not include any information on the content of any communication.\n\n\nWe aim to predict default based on the information available at the time credit was granted, and so\n\n\ninclude only mobile phone transactions that precede the date of plan switching. Descriptive statistics for\n\n\nthe sample are presented in Table 1. Although 85% of our sample has a file at the credit bureau, many of\n\n\nthese files are thin: 59% have at least one entity currently reporting an account, 31% have at least two, and\n\n\nonly 16% have at least three. By construction, 100% of the sample has a prepaid mobile phone account.\n\n\nThe median individual places 26 calls per week, speaking 32 minutes, and sends 24.4 SMS. The data\n\n\nincludes the median individual’s phone usage for 16 weeks; an implementation that can obtain longer\n\n\nhistories is likely to perform better.\n\n\n**3.** **METHOD**\n\n\nThe goal is to predict the likelihood of repayment using behavioral features derived from mobile\n\n\nphone usage. We consider a sample of completed plan transitions, and consider whether information that\n\n\nwas available at the time the credit was extended could have predicted its repayment. Because this sample\n\n\nof individuals did obtain credit, risk is reported among those who received credit based on the selection\n\n\ncriteria at the time, which was relatively permissive and spanned the distribution of credit histories\n\n\n(including no history at all).\n\n\nThe credit data provide an indicator for whether", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000103", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "mobile phone data", "probe_tag": "confusion", "probe_score": 0.8785539269447327, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 246, "end": 263, "key": "prwp:000103:10:0:0", "source": "camp2", "luna_reason": "Existing phone-usage data are used to derive behavioral features predicting repayment.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "credit data", "probe_tag": "keep", "probe_score": 0.9190052151679993, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 2001, "end": 2012, "key": "prwp:000103:10:0:1", "source": "camp2", "luna_reason": "Existing credit data provide an indicator used for repayment prediction.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "Lastly, the education policy literature reports the importance of community support in\nsustaining reform efforts. In particular, support from local stakeholders is a strong positive\npredictor of successful institutionalization of school reforms (Bryk et al. 2010).\n\nThis paper considers each of these factors together rather than individually. As such, it\ncontributes not only to the literature on sustainability of development projects but also offers\noperational lessons for project designers. We leverage rich panel data on playgroups in rural\nIndonesia to demonstrate how characteristics of the playgroups during the funded project period\npredict their sustainability several years after donor funding ends. This is an improvement from\nexisting research on sustainability in health and education, which typically uses cross-sectional\ndata (Scheirer and Dearing 2011). While the focus of this paper is on the sustainability of services\nestablished under an early childhood education project, the findings also provide lessons and\ninsights for designing other types of community-based development projects.\n\nWe present six key findings in this paper. First, we show that the vast majority (86%) of\nplaygroups established under the project remained open three years after project funding ended. In\nparticular, those that remained open balanced the reduction in donor funding by introducing\nstudent fees. Both our survey data and qualitative interview data show that the playgroups that\nclosed were those that struggled to find the financial and human resources needed to continue\noperating.\n\nSecond, we show that the playgroups that allocated a larger share of expenditure to teacher\nsalaries during the project period were significantly more likely to remain in operation after the\nproject ended. We find evidence that playgroups reallocated their resources towards teacher\nsalaries by cutting down on supplementary services such as weekly food programs.\n\nThird, we find that the quality of the project playgroups – as measured by direct observation\nof the playgroup – is a key predictor of sustainability. We find that such observations capture\nelements of the quality of these playgroups that are predictive of sustainability, over and above\nwhat can be predicted", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000125", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "panel data on playgroups in rural\nIndonesia", "probe_tag": "keep", "probe_score": 0.9641355872154236, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 513, "end": 556, "key": "prwp:000125:6:0:0", "source": "camp2", "luna_reason": "Existing panel data are analyzed to predict playgroup sustainability.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "cross-sectional\ndata", "probe_tag": "confusion", "probe_score": 0.499006986618042, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 822, "end": 842, "key": "prwp:000125:6:0:1", "source": "camp2", "luna_reason": "Existing research is described as using cross-sectional data.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "qualitative data is collected, for instance, to understand patterns of well-being across a large country\nwhich would follow the familiar logic of stratified probability sampling (Alexander, 2017).\n\n4) Integrating qualitative and quantitative work can be done in different ways. Following classical\ninferential logic, small-N qualitative work can be conducted using the case study method to develop\nhypotheses, which can then be tested for their generalizability, possibly mediated by a theoretical model,\nwith quantitative data collected from a representative sample of respondents (Rao, 1997b). The integrated\ncollection and analysis of qualitative and quantitative information can also be analyzed using Bayesian\ninference (Humphries and Jacobs 2015).\n\n5) Machine learning and Natural Language Processing are a double-edged sword. They offer tremendous\nadvantages in moving us towards analyzing narrative data at scale. Yet, supervised methods that rely on\nbiased training sets, such as sentiment dictionaries developed for western contexts applied to non-western\nlinguistic cultures, can result in substantial bias. Furthermore, as Woolcock (2021) has argued, when\nmachines are used for analyzing data, narratives have the danger of being analyzed out of context and\nwithout nuance, resulting in misinterpretation. In other words, relying on machines without sensitive\nhuman intervention has the danger of turning reflexively collected data into non-reflexive analysis.\n\n6) Process, studied carefully with qualitative methods, can be extremely valuable to understand the\nmechanisms of change and thus complement time-variant quantitative studies, particularly impact\nevaluations. Understanding process matters not just for research but also for policy, where an exclusive\nemphasis on policies that can only be assessed using experiments or impact evaluations can sharply limit\nour capacity to imagine and create a better world (Rao, 2019).\n\n7) The potential for the direct participation of “respondents,” “beneficiaries,” and “subjects” in research is\nvastly unexplored. If our purpose as researchers is to assist in the process by which people", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000135", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "quantitative data", "probe_tag": "confusion", "probe_score": 0.5204384922981262, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 510, "end": 527, "key": "prwp:000135:20:0:1", "source": "camp2", "luna_reason": "Data are described as collected for a prospective representative-sample analysis.", "drop_reason": "production", "specificity": "vague"}, {"text": "narrative data", "probe_tag": "drop", "probe_score": 0.03809043765068054, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 897, "end": 911, "key": "prwp:000135:20:0:2", "source": "camp2", "luna_reason": "Generic data concept with no attributed finding or concrete existing dataset use.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "<u>11,530</u>** **<u>27,302</u>** **<u>Jun-Sep</u>**\n\n\n\nSample distribution by geographical strata,\nfollowed by random selection of districts, and\n<u>convenience sampling for household selection.</u>\n\nSample distribution by geographical strata, and\nsimple random selection of households from cash\n<u>enrolment lists.</u>\n\nTwo strata (collective sites vs. private\naccommodation); random selection of districts and\n<u>convenience sampling for household selection.</u>\n\n\n### **Limitations**\n\nThe statistical significance of the MSNA results is\nlimited by the non-probabilistic selection of\nrespondents. Moreover, the use of convenience\nsampling likely led to a larger share of data being\ncollected from more vulnerable households.\n\n\nThere was also a notably high non-response rate\nregarding questions related to income and\nexpenditure, which likely resulted in non-response\nbias. The income module of the MSNA was also\nmaterially different from the one employed by EU\nSILC, which may limit comparability of this data to\nthat of host populations.\n\n\n\nIt is also important to highlight that there were slight\ndifferences in the questionnaire across countries.\nNot all questions were consistently included in all\ncountry-level surveys, and some answer options\nwere individually adjusted. To mitigate the impact of\nthese differences, the regional analysis focused on\ndata that could be matched. Certain indicators that\nmay have been available by country have thus been\nexcluded from this assessment.\n\n\nLastly, the survey was conducted during the\nsummer months, coinciding with both host country\nand Ukraine school holidays. This period often sees\nmany households temporarily visiting Ukraine,\nwhich impacted the accessibility of households and\nposed challenges in meeting targets, particularly in\ncertain countries and geographic locations.\n\n\n**11**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "enrolment lists", "probe_tag": "confusion", "probe_score": 0.5108, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 300, "end": 315, "key": "sample:jad_paddy_docs:000000:10:1:0", "source": "gold", "luna_reason": "Existing enrolment lists are used as a sampling frame for household selection.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "country-level surveys", "probe_tag": "drop", "probe_score": 0.0037, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1206, "end": 1227, "key": "sample:jad_paddy_docs:000000:10:1:1", "source": "gold", "luna_reason": "Existing country surveys explain questionnaire differences affecting the regional analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## **1.** Ukrainian refugees in Poland\n\n##### The large influx of refugees since February 2022, added to a hefty and growing Ukrainian migrant population in Poland (1.1). Refugees have changed the demographics of the local Ukrainian residents, with most of them being women and children and many households led by women alone (1.2). In the past year, refugee household income sources have become more Poland-based (1.3).\n\n#### **1.1 Influx since February 2022**\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 1. Poland-Ukraine border movement balance and registered/active PESEL data**\n\n\n\n**Prior to the 2022 conflict in Ukraine,**\n**the population of Ukrainians in**\n**Poland was already significant and**\n**on the rise, but the exact number of**\n**migrants was challenging to quantify.**\nSince the onset of the armed conflict\nin eastern Ukraine in 2014, there was a\nconsistent influx of Ukrainians into Poland.\nMany of them sought work as Ukraine’s\neconomy declined and the currency\ndevalued. Most of the migrants came as\nguest workers, a status brought in by a\n2011 law enabling Ukrainians and five other\nnations to work in Poland for six months\n\n\n\nSource: Deloitte own elaboration based on Polish\nBorder Guard Headquarter and PESEL data.\n\n\n\n\n\nPESEL-UKR data Total entries-exits of the\nPolish-Ukrainian border\n\n\n\n\n\nduring a year without a work permit,\nbased on an employer’s declaration. This\nwas a circular migration, with Ukrainians\ncoming to Poland for half of the year,\nthen returning to Ukraine for another six\nmonths, and coming back to Poland. The\ndata on employers’ declarations do not\nreveal the actual number of Ukrainian\ncitizens who followed this system – a", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PESEL data", "probe_tag": "confusion", "probe_score": 0.8761882781982422, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 686, "end": 696, "key": "jad_paddy_docs:000001:3:0:0", "source": "camp2", "luna_reason": "PESEL data underpin the chart analyzing Poland-Ukraine border movements.", "usage_type": "evidential", "specificity": "named"}, {"text": "PESEL-UKR data", "probe_tag": "keep", "probe_score": 0.9175825715065002, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1360, "end": 1374, "key": "jad_paddy_docs:000001:3:0:1", "source": "camp2", "luna_reason": "Named PESEL-UKR data are presented in a chart of border entries and exits.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " less about\n‘desire’ and more about 'capacity', what in\ndevelopment terms includes social capital,\nhuman capital (like education and skills),\nand even psychological readiness. That\ncapacity is shaped by a combination of\npublic policies and personal circumstance. <sup>6</sup>\n\n© UNHCR / Anna Liminowicz\n\n\n6 Crucial will also be the ‘pull’ factors in Ukraine, which will be determined by the conditions of future peace. The longer the full-scale war continues, the smaller will\nbe the percentage of refugees who are willing to return to Ukraine (Tokariuk, 2025). Some 1.3 million refugees have already returned to Ukraine. However, report that\neconomic opportunities in areas of return are inferior than what they had expected before returning, and while half of respondents are currently working, only around\na quarter reported being able to cover all or most of their basic needs, and only around a third report feeling safe in their current locations (UNHCR, 2025c).\n\n\n13\n\n\n\n**Chart 8. Ukrainian refugee household incomes from Poland and Ukraine in 2023 and 2024**\n\n\nMSNA 2023 SEIS 2024 MSNA 2023 SEIS 2024 MSNA 2023 SEIS 2024\n\nIncome from Poland Income from Ukraine Unclassified income\n\n\nWork Benefits Remittances Other\n\n\nNote: There are minor differences in the MSNA and SEIS income categories, as in MSNA remittances refer to all remittances from friends and family, while in SEIS\nto remittances from Ukraine.\n\nSource: Deloitte own elaboration based on MSNA (July-August 2023) and SEIS (May-June 2024) UNHCR (2024, 2023) surveys.\n\n\n12", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 6, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "MSNA", "probe_tag": "keep", "probe_score": 0.9618069529533386, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1458, "end": 1462, "key": "jad_paddy_docs:000001:6:2:0", "source": "camp2", "luna_reason": "Named survey cited as the source for charted refugee household income data.", "usage_type": "evidential", "specificity": "named"}, {"text": "UNHCR (2024, 2023) surveys", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1507, "end": 1533, "key": "jad_paddy_docs:000001:6:2:1", "source": "camp2", "luna_reason": "Surveys are cited as sources for the chart's income analysis.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " shock\nto the total factor productivity growth. This\nyields GDP higher by 1.5-2.6% by 2030,\nsignificantly higher than our long-term\nestimate – the higher result is likely due to\nthe increase in TFP that we do not include\nin our modelling. Fourth, Monitor Deloitte\n(2022) provided an early wide estimate of\nthe economic impact of Ukrainian refugees.\nThis would translate into 0.9-2.4% higher\nGDP, also due to the possibility of a positive\nproductivity shock. We review the relevant\nliterature on the impacts of immigration on\nproductivity in Chapter 4.\n\n\n\nrefugees, we have adjusted all the results\nproportionally to a 1.4-2.2% employment\ngrowth. First, Gradzewicz, Jabłon\nowski, Sasiela, and Żółkiewski (2021)\nuse the NBP CGE model to estimate the\neconomic impact of pre-2022 Ukrainian\nmigrants over the 2015-2018 period,\ntreating their inflow as a positive unskilled\nlabour shock. If the Ukrainian refugee\ninflow had the same characteristics, it\nwould yield a 0.5-0.8% higher GDP – the\nlower bound of our estimate. Second,\nStrzelecki, Growiec, and Wyszyński (2022)\nperform a growth accounting exercise to\ngauge the economic impact of the pre-2022\nUkrainian migrants over the 2014-2018\nperiod, accounting for hours and worker\ncharacteristics to arrive at a productivityadjusted labour supply. If Ukrainian\nrefugees had the same characteristics, they\n\n\n© UNHCR / Anna Liminowicz\n\n\n\nAs such **4 scenarios** were calculated with options corresponding to different mixes\nof low and high estimation for employment and productivity while keeping stable\nimpact on consumption: high or low employment level, similar (baseline) or lower\n(conservative) productivity. In the conservative productivity scenario,\nwe assumed approximately 10% lower refugee productivity estimated based\non incomes reported in MSNA Poland 2023 and data from Statistics Poland.\n\n\n**Table 2", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "MSNA Poland 2023", "probe_tag": "keep", "probe_score": 0.9387843608856201, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1795, "end": 1811, "key": "jad_paddy_docs:000007:17:1:0", "source": "camp2", "luna_reason": "Named survey data informs the estimated refugee productivity assumption.", "usage_type": "evidential", "specificity": "named"}, {"text": "data from Statistics Poland", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1816, "end": 1843, "key": "jad_paddy_docs:000007:17:1:1", "source": "camp2", "luna_reason": "Statistics Poland data informs the estimated 10% lower refugee productivity.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nSupport for Social Recovery Needs of Vulnerable Groups in Beirut (P176622)\n\n\nand most recently, to 157.9% in March 2021.” <sup>5</sup> Importantly, inflation is a highly regressive tax, affecting\nthe poor and vulnerable disproportionately, as well as people on fixed income, such as pensioners. <sup>6</sup>\n\n\n3. **Compounded by the global economic shock presented by COVID-19, disruptions in international food**\n**supply chains and trade networks exacerbate Lebanon’s food security vulnerabilities.** Lebanon's\nremittances dropped by 20%, from 3.9 billion U.S. dollars in the first half of 2019 to 3.1 billion dollars in\nthe first half of 2020, according to Bank Byblos' Lebanon This Week report released on Tuesday February\n9, 2021. <sup>7</sup> Furthermore, the restrictions on movement to combat the pandemic have hindered foodrelated logistic services, disrupting food supply chains and jeopardizing food security for millions of\npeople. The higher levels of export restrictions particularly leave food-importing countries vulnerable to\ncommodity price fluctuations. The World Bank’s Spring 2021 LEM found average food inflation to have\ngrown by a record 254 percent over 2020. <sup>8</sup> Meanwhile, the World Food Program (WFP) reported that the\nConsumer Price Index (CPI) experienced annual inflation of 133% between October 2019 and November\n2020, representing an all-time high since it began monthly price monitoring in 2007. <sup>9</sup> This is particularly\nrelevant as Lebanon imports at least 80% of its food supplies (ESCWA 2016). Real GDP growth is estimated\nto have contracted by 20.3 % in 2020, on the back of a 6.7 % contraction in 2019.\n\n4.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000002", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Spring 2021 LEM", "probe_tag": "keep", "probe_score": 0.9428209662437439, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1109, "end": 1124, "key": "jdc_operational:000002:3:0:0", "source": "camp2", "luna_reason": "Named World Bank report supports the stated 2020 food-inflation finding.", "usage_type": "evidential", "specificity": "named"}, {"text": "Consumer Price Index", "probe_tag": "confusion", "probe_score": 0.7490697503089905, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1274, "end": 1294, "key": "jdc_operational:000002:3:0:1", "source": "camp2", "luna_reason": "WFP-reported CPI inflation provides a concrete finding for Lebanon.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nSupport for Social Recovery Needs of Vulnerable Groups in Beirut (P176622)\n\n\nnational poverty line. <sup>15</sup> [^15: Lebanon Economic Monitor, Spring 2021. World Bank] These developments increase pressures for emigration, especially among the\nmiddle class. Such deprivations have further degraded the relationship between people and the state.\nGrievances with the political system and dissatisfaction with the state’s mismanagement of the economy\nand its entrenched corruption resulted in nationwide protests in late 2019. Since, intermittent social\nunrest highlights the needs for a new social contract between citizens and the government. In a survey\nconducted by the World Bank among victims of the blast, the overwhelming majority of respondents\nreport having “no trust at all” in political parties, the Council for Development and Reconstruction, or\nmunicipalities. <sup>16</sup> [^16: Ranking on a 5-point scale, where 1 = “no trust at all” and 5= “complete trust.” Average score was 1.2 for political parties, 1.5 for CDR, and 1.7\nfor municipalities. Survey not strictly representative due to its design. Source:\nhttp://documents1.worldbank. org/curated/en/899121600677984471/pdf/Beirut-Residents-Perspectives-on-August-4-Blast-Findings-from-aNeeds-andPerception-Survey.pdf]\n\n6. **The formation of a new government of “determination and hope” in September 2021, and the**\n**subsequent vote of parliamentary confidence this received, lays an important potential foundation for**\n**solving these challenges** . However, even in a political best case scenario, the deep socio-economic\nimpacts of the above crises upon the people of Lebanon will take considerable time and investment in\npublic sector service delivery reform to address sustainably. As such, stop-gap measures to meet the\nimmediate socio-economic needs of vulnerable groups remains important for both alleviating emergency\nhardship and setting the stage for longer-term recovery.\n\nSectoral and Institutional Context\n\n7. **The World Bank Group (WBG)", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000002", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Lebanon Economic Monitor", "probe_tag": "confusion", "probe_score": 0.8792276382446289, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 139, "end": 163, "key": "jdc_operational:000002:4:0:0", "source": "camp2", "luna_reason": "Named World Bank monitor cited as the source for the poverty-line context.", "usage_type": "evidential", "specificity": "named"}, {"text": "survey\nconducted by the World Bank", "probe_tag": "keep", "probe_score": 0.975434422492981, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 668, "end": 702, "key": "jdc_operational:000002:4:0:1", "source": "camp2", "luna_reason": "World Bank survey provides reported trust findings among blast victims.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "25</sup>\n\n20. **The risk of being exposed to GBV may also discourage women from entering more profitable sectors or growing**\n**a business if it threatens norms around the role of a male provider** . The relationship between women's empowerment\nand the experience of violence is an empirical question and programs that attempt to economically empower women\nneed to consider the possibility of backlash from the community at large. There is a growing evidence base that programs\nthat combine targeted economic support to women with training that engages male partners and community members\ncan mitigate the risk of GBV. <sup>26</sup> [^26: Center for Domestic Violence Prevention. 2013. _Economic Costs of Domestic Violence in Uganda_ .]\n\n21. **Refugee women face barriers to starting and growing businesses, especially regarding accessing technology and**\n**finance.** A survey of refugee settlements found that a lack of national identification, as well as charges and fees, present\nsignificant barriers to accessing financial services, especially for women. The study found financial inclusion is relatively\nlow, with 37 percent and 46 percent of adults having access to formal financial services, and 36 and 46 percent holding a\nmobile money account, respectively. A 2018 survey by the World Bank Group reported that less than fewer than 5 percent\nof all refugees had received any kind of skills or job training, and most who were engaged in agricultural production were\nnot using improved inputs and were heavily reliant on rainfall. <sup>27</sup> [^27: Musime, David. 2019. “Financial Markets for Refugees and Host Communities in Arua and Isingiro Districts.” November.\nWashington DC: World Bank.]\n\n**_Relationship to the Country Partnership Framework_**\n\n\n22. **The proposed project aligns with the World Bank’s Country Partnership Framework (CPF) for Uganda (2015/16–**\n**2020/21)** . The CPF (report 101173-UG", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000005", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey of refugee settlements", "probe_tag": "confusion", "probe_score": 0.8681411147117615, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 871, "end": 900, "key": "jdc_operational:000005:7:1:0", "source": "camp2", "luna_reason": "Survey findings identify barriers and financial-service access among refugees.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "2018 survey by the World Bank Group", "probe_tag": "keep", "probe_score": 0.9828687906265259, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1270, "end": 1305, "key": "jdc_operational:000005:7:1:1", "source": "camp2", "luna_reason": "Existing World Bank survey supports an attributed refugee training finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " other development partners have shown the scope for efficiency gains, notably through profitable\ninvestments in technologies and processes for resource efficiency and cleaner production.\n\n\n16. **In addition, the regulatory and enabling environment is not supportive of new growth sectors.**\nDiscussions with Ugandan private sector actors and government officials indicate significant challenges with\nregulatory enforcement, contract enforcement, and the public private interface. A countrywide survey\ncommissioned in 2017 by the Uganda National Bureau of Standards (UNBS) found that 54 percent of the products\nin the Ugandan market are either fake or counterfeit. The number of backlogged civil suits in the commercial court\nsystem (which account for most of all substantive cases) has increased. Private investors have reported that the\nprocess to obtain an investment license is cumbersome.\n\n\n17. **There is lack of investment in new production locations and markets, that is caused by inadequate**\n**access to basic private sector services.** Land officially earmarked for industrial use—with appropriate access to\ninfrastructure services and reflecting sound environmental and social (E&S) planning—is not easily accessible\noutside of the main Southern Corridor along the Kampala road to the east and west, particularly for new and/or\nforeign investors. Government services in support of new investors (permits, certification, and so on) are generally\ndifficult to access outside greater Kampala. An investment outside Kampala faces significantly longer lead times\nand higher transactions costs than comparable investments within the Kampala region. As a result, the cost of\nlocating into new regions and markets of Uganda is prohibitively high and deters potential first-movers from\ninvesting.\n\n\n**Refugees and Host Sector Specific Issues**\n\n\n18. **There are few medium-to-large enterprises in RHDs that could stimulate the local product or labor**\n**market.** The business census recorded a total of 165 enterprises in Arua district that employ more than 10 workers\n(less than 1 firm per square kilometer", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 18, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "countrywide survey\ncommissioned in 2017", "probe_tag": "keep", "probe_score": 0.9213029742240906, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 483, "end": 522, "key": "jdc_operational:000021:18:1:0", "source": "camp2", "luna_reason": "Existing survey supports the attributed finding that 54 percent of products were counterfeit.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "business census", "probe_tag": "confusion", "probe_score": 0.8713653683662415, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1971, "end": 1986, "key": "jdc_operational:000021:18:1:1", "source": "camp2", "luna_reason": "Census recorded 165 enterprises, providing concrete evidence about local firms.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nUganda Climate Smart Agricultural Transformation Project (P173296)\n\n\nprocurement of machinery; installation of irrigation systems for post control evaluation; seed inspection,\nverification and certification; and procurement and deployment of seed traceability systems.\n\n\n_Subcomponent 1.3. Strengthening Agro-Climate Monitoring and Information Systems (US$10.6 million -_\n_IDA)_\n\n\n20. The subcomponent will finance the generation and timely transmission of accurate weather data\nand climate information thereby strengthening weather forecasting and its dissemination tools. Financing\nwill be for:(a) acquisition and establishment of functional automated weather stations and related\nequipment in locations where gaps have been identified to improve agro-meteorological forecasting and\nmonitoring; (b) rehabilitation and upgrading of existing weather stations in project areas; (c) acquisition\nand utilization of big data to develop a climate smart, agro-weather information system and advisories;\n(d) establishing partnerships with local and international institutions to support the generation of climate\ninformation using global data sources such as satellites; (e) upgrading and operationalizing the weather\ninformation dissemination system; (f) building the technical capacity of MAAIF and extension staff for\nagro-meteorological observation and forecasting and real-time delivery of weather information and\nadvisories to target farmers in project districts including RHDs and refugee settlements; (g) development\nof agroclimatic and climate smart digital tools to facilitate access to early warning, agroclimatic, and pest\nand disease surveillance information; (h) establishment of soil organic carbon monitoring reporting and\nverification of GHG removals including lab analysis for tracking application, adoption, and impact of TIMPs;\nand (i) facilitating partnership with Uganda National Meteorological Authority (UNMA) to build capacity\nof MAAIF and local governments in agro-met data collection, management, analysis and dissemination;\nand (j) enhancement of UNMA’s capacity in agro-met data collection, management, analysis and\ndissemination.\n\n\n_Sub", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000001", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "big data", "probe_tag": "confusion", "probe_score": 0.11579310148954391, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 931, "end": 939, "key": "refugee_pads:000001:20:0:1", "source": "camp2", "luna_reason": "Planned acquisition and utilization for a future information system, not existing data use.", "drop_reason": "promissory", "specificity": "vague"}, {"text": "agro-met data", "probe_tag": "drop", "probe_score": 0.020496297627687454, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1998, "end": 2011, "key": "refugee_pads:000001:20:0:2", "source": "camp2", "luna_reason": "Data collection and management are planned project activities.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": ">in the refugee beneficiaries’<br>communities|Bi-annually,<br>MTR,EOP<br>|Project MIS<br>|H/H survey -<br>beneficiaries<br>assessment<br>|NPCU<br>|\n|Host Community beneficiaries|This will assess the<br>increased hectare<br>developed for sustainable<br>land management practices<br>in the host communities|Bi-annually,<br>MTR, EOP<br>|Project MIS<br>|H/H survey -<br>beneficiaries<br>assessment<br>|NPCU<br>|\n|National beneficiaries|This will assess the<br>increased hectare|Bi-annually,<br>MTR, EOP|Project MIS<br>|HH surveys -<br>evaluations -|NPCU<br>|\n\n\n\nPage 46 of 81", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000001", "page": 51, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "H/H survey", "probe_tag": "drop", "probe_score": 0.020992137491703033, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 350, "end": 360, "key": "refugee_pads:000001:51:1:0", "source": "camp2", "luna_reason": "Planned beneficiary assessment survey for project monitoring, not existing data use.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "HH surveys", "probe_tag": "confusion", "probe_score": 0.06780824065208435, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 515, "end": 525, "key": "refugee_pads:000001:51:1:1", "source": "camp2", "luna_reason": "Survey phrase appears within a table monitoring row.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
-{"text": "HDs. z\n\nThere is strong progress on: the commitment to integrate refugee services into national service delivery systems.\nAs outlined in the National Development Plan III (NDP III), refugee planning is integrated into national, sectoral and\nlocal government plans and data collection. The CRRF has developed sectoral plans for refugees and host\ncommunities and included both groups under the Uganda Intergovernmental Fiscal Transfer to support service\nprovision through district development plans. Refugees and hosts have been included in the 2022 Uganda\nDemographic Health Survey. Although a refugee sample was not collected in the Uganda National Household\nSurvey that was conducted in 2019/20 due to COVID-19 pressures, the Uganda Bureau of Statistics remains\ncommitted to include refugees in national data exercises.\n\nOn the commitments to: ensure access for refugees and host population to quality, efficient and integrated basic\nsocial services; and enhance social infrastructure in refugee hosting areas, strong progress is being made on health\nand education service provision. The second Education Response Plan for Refugees and Host Communities was\nendorsed in September 2022. Under the Uganda intergovernmental Fiscal Transfer (UgIFT) program WHR, refugee\nchildren have been included in the education capitation grant for RHDs and 51 schools are being transferred from\nhumanitarian partners into the national education system. The Uganda Secondary Education Expansion Project\n(USEEP) will strengthen infrastructure in 61 secondary schools in RHDs.\n\nAccording to the just concluded Health Sector Integrated Refugee Response Plan a mid-term review, under the\nUgIFT, 15 health centers are being transitioned from humanitarian partners into national systems and refugee\npopulations have been included in the per capita recurrent cost allocations to RHDs. Two blood banks to service\nRHDs are also being constructed under UgIFT. Refugees were integrated into the National COVID-19 Health\nPrevention and Response Plan. The Uganda COVID 19 Response and Emergency Preparedness Project is supporting\n\n\nPage 79 of 81", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000001", "page": 84, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2022 Uganda\nDemographic Health Survey", "probe_tag": "keep", "probe_score": 0.9091878533363342, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 543, "end": 580, "key": "refugee_pads:000001:84:1:0", "source": "camp2", "luna_reason": "Named existing survey cited as including refugees.", "usage_type": "declaration", "specificity": "named"}, {"text": "Uganda National Household\nSurvey", "probe_tag": "confusion", "probe_score": 0.8341273665428162, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 633, "end": 665, "key": "refugee_pads:000001:84:1:1", "source": "camp2", "luna_reason": "Existing national survey cited to establish that refugees were not sampled.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "\neconomic participation and opportunities and to 133 for educational attainment. <sup>6</sup> The 2022 Global Findex Survey <sup>7</sup> found\n\n\n1 International Monetary Fund, 2023. Website, accessed November 14th: imf.org/en/Countries/ETH#featured\n2 Drought is the most destructive climate-related natural hazard. Through 2100, there is a likely 20 percent increase in extreme high rainfall events.\nFlash floods and seasonal river floods are becoming more frequent and widespread. World Bank, 2021, Ethiopia Climate Risk Profile.\n3 This is particularly due to dependence on key sectors that are highly affected by climate change such as agriculture, water, tourism, and forestry\n(World Food Programme. Ethiopia Annual Country Report 2022).\n4 Ethiopia Country Climate Development Report, 2023, draft, World Bank.\n5 World Bank, 2021, Ethiopia Climate Risk Profile.\n6 World Economic Forum. 2022. Global Gender Gap Report, published July 2022. URL: https://www3.weforum.org/docs/WEF_GGGR_2022.pdf.\n7 World Bank. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the age of COVID-19.\nhttps://www.worldbank.org/en/publication/globalfindex#sec1.\n\n\nPage 1 of 39", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000005", "page": 11, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "2022 Global Findex Survey", "probe_tag": "keep", "probe_score": 0.9686962366104126, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 98, "end": 123, "key": "refugee_pads:000005:11:2:0", "source": "camp2", "luna_reason": "Named survey cited as finding's data source.", "usage_type": "evidential", "specificity": "named"}, {"text": "Findex Database 2021", "probe_tag": "confusion", "probe_score": 0.8074421882629395, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1026, "end": 1046, "key": "refugee_pads:000005:11:2:1", "source": "camp2", "luna_reason": "Named World Bank database cited as the source for survey findings.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**Data disaggregated by AGD enriched the assessment**\n**and analysis of needs, capacities and programming**\n**gaps.** Most UNHCR operations reported gathering and\nanalysing AGD-disaggregated data in their consultations\nwith persons of concern as part of assessment\nprocesses.\n\n\nIn **Sudan,** data disaggregated by AGD demonstrated\nthat efforts to include persons with disabilities and\nolder persons in interventions needed to go beyond the\nprovision of assistive devices. It also showed that better\nunderstanding of the attitudinal, physical and systemic\nbarriers experienced by persons with disabilities is\nneeded to ensure that the operation’s programming\naddresses such barriers in an optimum way.\n\n\nThe **Argentina** Multi-Country Office based its planning\nexercise for 2021 on a joint needs assessment of\nVenezuelan refugees’ and migrants’ humanitarian\nneeds, conducted in October 2019.\n\n\nIn **Lebanon,** UNHCR used AGD-disaggregated data,\ngenerated through inter-agency coordination, to inform\njoint situation analysis and sectoral strategies, and to\ncoordinate sectoral activities.\n\n\n**AGD approaches and disaggregated data improved**\n**planning and the prioritization of interventions.**\nUNHCR operations used the findings of assessments\nand consultations with persons of concern to inform\nthe design of programmes, to set out their strategic\ndirections and to incorporate responses that address\nAGD-related risks and barriers, including those created\nor exacerbated by the COVID-19 pandemic.\n\n\nFor example, in **Ethiopia,** consultations with persons\nof concern and the use of disaggregated data from\nthe Profile Global Registration System (proGres) led to\nthe prioritization of emergency one-off food or cash\ndistributions to refugee female-headed households at\nheightened protection risk.\n\n\nIn **Nepal,** the analysis of AGD-disaggregated data about\nschool-age children highlighted the need to facilitate,\nsupport and strengthen the enrolment of children in\npre-primary and secondary level public schools. The", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000271", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data disaggregated by AGD", "probe_tag": "confusion", "probe_score": 0.5951586961746216, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 2, "end": 27, "key": "reliefweb:000271:16:0:0", "source": "camp2", "luna_reason": "Disaggregated data enriched an assessment and analysis of needs and programming gaps.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "AGD-disaggregated data", "probe_tag": "drop", "probe_score": 0.0406450480222702, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 173, "end": 195, "key": "reliefweb:000271:16:0:1", "source": "camp2", "luna_reason": "Existing disaggregated data were analyzed in consultations and assessment processes.", "usage_type": "declaration", "specificity": "vague"}, {"text": "Profile Global Registration System", "probe_tag": "keep", "probe_score": 0.9216738343238831, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1614, "end": 1648, "key": "reliefweb:000271:16:0:4", "source": "camp2", "luna_reason": "ProGres data informed prioritization of assistance to high-risk refugee households.", "usage_type": "evidential", "specificity": "named"}, {"text": "AGD-disaggregated data about\nschool-age children", "probe_tag": "confusion", "probe_score": 0.7524005174636841, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1832, "end": 1880, "key": "reliefweb:000271:16:0:5", "source": "camp2", "luna_reason": "Analysis of disaggregated data highlighted school enrollment needs.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "Though the voluntary character of the return was emphasized by the authorities during the\nplanning phase, the Protection cluster believed in the importance to follow the SOPs on\nreturn as a guide for the humanitarian when providing support to the authorities in the\nreturn process and in the importance of consulting the population to better ascertain the\nintentions and needs of the population.\n\n\n**II.** **Methodology**\n\n\nBased on the information received from FDMA on the denotification of the 50 tehsil, data\nwithin UNHCR database of registered IDPs were compared and 4549 were found as from Ali\nSherzai tribe.\n\n\nThe protection cluster established a representative sample capturing a significant portion of\nthe displaced population from Central Kurrum from Ali Sherzai tribe. IVAP provided the\nphone numbers of the registered families and IOM conducted phone calls with the IDPs.\n\n\n259 families were consulted and the RIS was conducted by 7 enumerators who contacted\ndisplaced families from a call centre using the contact information available through the\nIVAP records. This RIS was conducted using a specific tool/questionnaire developed in 2012\nfor previous consultations and slightly adapted in 2013. <sup>1</sup> [^1: See Annex1]\n\n\nThe enumerators were trained on 23rd January by protection cluster coordinator on the\ntool as well as on basic principles of confidentiality, informed consent and interviewing\ntechniques. The data collection was conducted from 29.1. to 5.2.\n\n\nIn total, 259 interviews were conducted- 98 families currently residing in Hangu, 94 in\nKohat, 42 in Peshawar, 17 in New Durrani, 4 in Nowshera, 3 in Charsadda, 1 in Tank.\n\n\n**III.** **Main findings of the Return Intention Survey 2014**\n\n\n**1)** **Profile of the interviewed population**\n\n\nMostly heads of families were interviewed during the return intention survey (89%), only in\n28 cases other family members were interviewed, depending on", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000116", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR database of registered IDPs", "probe_tag": "keep", "probe_score": 0.9606614112854004, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 520, "end": 553, "key": "reliefweb:000116:1:0:0", "source": "camp2", "luna_reason": "UNHCR database data were compared and yielded a concrete population count.", "usage_type": "evidential", "specificity": "named"}, {"text": "IVAP records", "probe_tag": "confusion", "probe_score": 0.8956030607223511, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1061, "end": 1073, "key": "reliefweb:000116:1:0:1", "source": "camp2", "luna_reason": "Existing IVAP records supplied contact information for surveying displaced families.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "even when these sub-populations were included by\ndesign in the survey. To help change this situation,\nand following the recommendation from the\nIRRS and IRIS, a battery of easy-to-use questions,\nbased on harmonized definitions, should be made\nwidely available, and standard surveys should be\nencouraged to include them. The Compilers’ Manual\nhas already made progress in this area, as part of\nEGRIS’s phase 3 of work focusing on refinement and\nimplementation.\n\n\n\n3. MAIN DATA SOURCES\n\n\nIt is worth bearing in mind that large-scale surveys\nstrive to keep questionnaires and interview times as\nshort as possible. Adding questions that allow the\nproduction of SDG indicators disaggregated by FDP\nsubpopulations is likely to face resistance unless\nthese are easy to implement and do not represent\na significant increase in the time of the interview.\nIt is important to avoid unnecessary burden on\nrespondents (and potential harm), especially when\ndealing with vulnerable groups and/or conducting\nsurveys in humanitarian or fragile contexts.\n\n\n\n**Examples: The South Sudan HFS Wave 4 (2017) and the Somalia HFS Wave 2 (2017-2018)**\n\n\n**South Sudan HFS Wave 4**\n\n\nThis is likely the best example of a dataset that allows calculation of SDG indicators for IDPs.\n\n\nThe crisis recovery survey portion of this dataset is one of the most complete sources of data for IDPs,\nas the depth of the survey allowed for more indicators to be calculated than in any other survey, and the\nsampling focus on IDP camps meant that the sample size was large, not only for households but also\nhousehold members. Hence, it was possible to calculate indicators for education as enough children\nwere recorded in the data. This is compared to the DHS, for example, where after filtering, there were no\nchildren in the households born within the past five years to allow calculation of birth registration.\n\n\n**South Sudan HFS Wave 2**\n\n\nThis survey included questions and sampling methods designed to capture", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000141", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "crisis recovery survey", "probe_tag": "confusion", "probe_score": 0.8752490878105164, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1261, "end": 1283, "key": "reliefweb:000141:19:0:3", "source": "camp2", "luna_reason": "Survey depth and sampling enabled calculation of multiple IDP indicators.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "DHS", "probe_tag": "keep", "probe_score": 0.9214687943458557, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1717, "end": 1720, "key": "reliefweb:000141:19:0:4", "source": "camp2", "luna_reason": "DHS data are compared after filtering to assess birth-registration indicator calculation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " los\ndatos de localización subnacionales.\n\n\n**b. Estadísticas vitales**\n\n\nLa actualización periódica y la cobertura exhaustiva\nde los principales acontecimientos de la vida es\nun componente importante de las estadísticas de\npoblación. Las estadísticas vitales del ACNUR incluyen\nla recopilación bianual de datos sobre nacimientos\ny muertes de personas refugiadas. Sin embargo,\nla precisión en la información y el registro de estas\nestadísticas vitales sigue siendo difícil. En 2020,\nmenos de un tercio de los países que acogen al menos\na 1.000 personas refugiadas notificaron al menos\nun nacimiento o una muerte. La información varía\nsignificativamente según la región, con la cobertura más\nbaja en las Américas y en Europa, y la más alta en las\ntres regiones del África subsahariana, donde el ACNUR\ndirige el registro y otras actividades de apoyo para las\npersonas refugiadas.\n\n\nEn 2020, el ACNUR aplicó enfoques de modelo\nestadístico para los datos disponibles, incluidos los\ndatos demográficos, para estimar la cantidad total de\nniñas y niños nacidos como refugiadas y refugiados,\nmejorando así la estimación al minimizar el impacto de\nlos datos que faltan (consulte la página 10).\n\n\n**c. Estimación de las cifras de población**\n\n\nLas estadísticas de población precisas y fiables son la\nbase del diseño, la ejecución y la eficacia de muchas", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000160", "page": 67, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "datos de localización subnacionales", "probe_tag": "confusion", "probe_score": 0.3853926956653595, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 5, "end": 40, "key": "reliefweb:000160:67:3:0", "source": "camp2", "luna_reason": "Generic location data is merely mentioned without an attached finding or analytical use.", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "datos demográficos", "probe_tag": "keep", "probe_score": 0.9637299180030823, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 978, "end": 996, "key": "reliefweb:000160:67:3:2", "source": "camp2", "luna_reason": "Existing demographic data modeled to estimate total refugee births.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017781", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9652993679046631, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1978, "end": 2008, "key": "fcv_pads_east_africa:017781:38:1:2", "source": "camp2", "luna_reason": "Household Survey data support the concrete finding about girls’ school withdrawal.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020602", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9347544312477112, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 870, "end": 881, "key": "fcv_pads_east_africa:020602:38:1:1", "source": "camp2", "luna_reason": "Survey data underpin enrollment comparisons and document an education-level separation limitation.", "usage_type": "evidential", "specificity": "vague"}, {"text": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9652993679046631, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1978, "end": 2008, "key": "fcv_pads_east_africa:020602:38:1:2", "source": "camp2", "luna_reason": "Household survey data supports a concrete finding about girls’ school attendance.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nUganda Investing in Forests and Protected Areas for Climate-Smart Development Project (P170466)\n\n\n4. **Poverty reduction has not yet achieved set targets.** The percentage of people living below the\nnational poverty line (US$1 per day) was 21.4 percent in FY2017/18 compared to the NDP 2 target of\n14.2 percent. For the first time in more than a decade, there was a reversal in the poverty levels in 2017\nlargely due to droughts and crop failures. Average life expectancy is 63 years <sup>2</sup>, and the fertility rate is\namong the highest in the world. Uganda ranked 127th out of 162 countries in the 2018 Gender Inequality\nIndex. <sup>3</sup> Prevalence rates of gender-based violence (GBV) in Uganda are high compared to both global and\nregional averages. <sup>4</sup> The Government of Uganda recognizes GBV as a serious problem and approved a\nNational Policy on the Elimination of GBV in October 2016.\n\n\n5. **Poor and vulnerable people typically live in rural areas, have large families, and derive their**\n**income predominantly from farming, with high dependency on forests.** One in four rural Ugandans lives\nin poverty compared to just one in ten urban Ugandans. Rural poverty has become further entrenched as\na disproportionate percentage of the population remains trapped in subsistence agriculture. A heavy\nreliance on rain-fed and subsistence agriculture continues to expose the economy to risks from adverse\nweather, and these risks are likely to grow under most scenarios for future climate change. <sup>5</sup> Uganda is\nvulnerable to climate change, and its impacts are already being experienced in the region. <sup>6</sup> Increased\noccurrences of drought conditions and reduced or more variable rainfall across", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019014", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2018 Gender Inequality\nIndex", "probe_tag": "keep", "probe_score": 0.9547758102416992, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 623, "end": 651, "key": "fcv_pads_east_africa:019014:3:0:0", "source": "camp2", "luna_reason": "Named index supports Uganda's reported international gender-inequality ranking.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "3\n\n\n**2. Project development objective** (see Annex 1)\n\nThe objective of the project is to enhance the quality of education and to increase enrollment in\nprimary schools.\n\n\n**3. Key performance indicators:** (see Annex 1)\n\nThe key performance indicator is an increased number of students enrolled in grades 1-9, especially\namong girls.\n\n\nB. **STRATEGIC CONTEXT**\n\n\n**1. Sector-related Country Assistance Strategy (CAS) goal supported by the project** (see Annex 1)\n\n\n**Document number:** P 7403 DJI **Date of latest CAS discussion:** (scheduled for) 12/19/00\n\nThe CAS has been prepared in the context of the country's economic difficulties and deepening\npoverty. Despite Djibouti's relatively high nominal per capita income (US$790 versus an average of\nUS$510 for Sub-Saharan Africa, and US$100 for Ethiopia), Djibouti has one of the poorest social\nindicators in the world (poverty, illiteracy, maternal and infant mortality, and morbidity), according to\nthe UNDP Human Development Index, ranking 157th among 174 countries.\n\n\nThe Republic of Djibouti has very few natural resources and the economy is mainly dependent on the\nport, external financial assistance, the French military and associated services. However, with the\n\ndecreased amount of external assistance, and deepening structural problems, the country has suffered\neconomic stagnation over the past decade and a half. As a result, per capita Gross Domestic Product\n(GDP) declined by 50% in real terms since 1985. The switch of Ethiopia's transit traffic from Assab in\nEritrea to Djibouti in mid-1998 and the consequent four-fold increase in port traffic has opened new,\nas yet not fully exploited, opportunities for investment and growth. Djibouti's open economic policies\nand relative stability, characterized by a liberal trade policy and exchange system, which operates free\n\nof capital or", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015648", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNDP Human Development Index", "probe_tag": "keep", "probe_score": 0.9622568488121033, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 959, "end": 987, "key": "fcv_pads_east_africa:015648:6:0:0", "source": "camp2", "luna_reason": "Named index supports Djibouti's poverty and social-indicator ranking.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018928", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9347544312477112, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 870, "end": 881, "key": "fcv_pads_east_africa:018928:38:1:1", "source": "camp2", "luna_reason": "Survey data supports reported enrollment disparities and separation limitation.", "usage_type": "evidential", "specificity": "vague"}, {"text": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9652993679046631, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1978, "end": 2008, "key": "fcv_pads_east_africa:018928:38:1:2", "source": "camp2", "luna_reason": "Household Survey data support the finding that parents withdraw girls from school.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": ",000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and teachers. The state of shelter in many <sup>areas is one</sup> <sup>of</sup>\nthe factors constraining the return of government employees and the revitalization of district and local\neconomic activity. The agricultural sector is particularly important because it currently <sup>employs 75%</sup> <sup>of</sup>\nthe country's labor force. The 2000 Baseline Service Delivery Survey reported that between <sup>65%</sup> <sup>and</sup>\n85% of the population do not have access to safe drinking water and sanitation facilities. Recent\nestimates in the most neglected communities of the \"newly accessible areas\", such as Bombali, <sup>suggest</sup>\nthat access to potable water and adequate sanitation are as low as 5% and 3%, respectively.\n\n\n\nWidespread human rights abuses during the civil war included the forced recruitment of children\nas combatants, porters and sex slaves. In addition, tens of thousands of people continue to suffer <sup>from</sup>\nthe traumatic effects of amputation and other injuries, sexual violence, loss of parents, and the general\nstress of living through a civil war. This has greatly increased the need for a kind of <sup>social service</sup>\nsupport that was not as widely needed before the war, integrating traditional health services <sup>with</sup>\npsycho-social care, counselling, foster homes and disability programs. The challenges ahead <sup>will include</sup>\n\nthe provision of community-", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018073", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2000 Baseline Service Delivery Survey", "probe_tag": "keep", "probe_score": 0.9403358101844788, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 568, "end": 605, "key": "fcv_pads_east_africa:018073:9:1:0", "source": "camp2", "luna_reason": "Named survey reports concrete access rates for drinking water and sanitation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**8** Agricultu Procurement **of** **3.106** Activity re-scheduled\nral consultant to pending approval of the\nWater undertake **NFASS** rollout strategy **by**\nManage feasibility **Top** Management\nment studies, and\nInvestm detailed\nent engineering\ndesign for 5No.\n\nirrigation\nschemes\n**9** Agricultu Establishment of **1.335** 12 of the selected/granted\nral **5No.** **(3-5** acre) farmers have not provided\nWater smallholder proof of funding. Whereas\nManage coffee irrigation **10** out of the **38** are going\nment systems in **9** through the procurement\nInvestm districts. evaluation report.\nent ________\n**10** Agricultu Operationalize **2.502** Initially the Ministry had\nral Routine planned to use service\nStatistics Agriculture providers for the rollout\nAdministrative using funds allocated **by**\nData System in USAID however this\n**52** districts (12 proposal was not approved\nclusters) by USAID. Therefore, the\n**MAAIF** Statistics Division is\nset to rollout training of\n______________national level stakeholders.\n**11** Agricultu Improving **0.527** Field visits were dependent\nral Coordination **&** on approval of the **NFASS**\nStatistics Management rollout strategy **by** Top\namongst Management which was\nagriculture never obtained\nstatistics\n\nproducing\ninstitutions\n\n\n\n12 Agricultu Strengthening **0.903** The nine data collection\nral capacity for the tool to be administered was\nStatistics Food and still being digitalized and\nAgricultural was not ready for roll-out.\nStatistics System The activity has been rolled\n\nover to", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006052", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data System in USAID", "probe_tag": "confusion", "probe_score": 0.7603543400764465, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 806, "end": 826, "key": "fcv_pads_east_africa:006052:9:0:0", "source": "camp2", "luna_reason": "Names a data system without showing its data informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "The World Bank\n\n\n\n\n\nReport No: ISR12522\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|Col3|Col4|Col5|by the schools. The response<br>rate from private schools<br>(which have 48% of<br>secondary students has been<br>low (e.g. 64% in 2008; 68% in<br>2009 compared to 100% of<br>public schools due to<br>capitation fund requirements.<br>Over the years, the sector<br>was scaling up the EMIS<br>figures through computational<br>replacements up to the year<br>2010. From 2011 this method<br>was dropped and actual<br>responses are now being<br>used for data generation in a<br>bid to improve data accuracy.<br>The sector in partnership with<br>the Uganda Bureau of<br>Statistics (UBOS) agreed to<br>use the years 2011-12 as<br>observational years for data<br>stability and restart trend<br>analysis with a new baseline<br>using 2013 data.|Col7|\n|---|---|---|---|---|---|---|\n|Boys||Percentage<br>Sub Type<br> Breakdown|Value|28.00|39.00|42.00|\n|Boys||Percentage<br>Sub Type<br> Breakdown|Date|27-Nov-2008|15-Oct-2013|31-Jul-2014|\n|Boys||Percentage<br>Sub Type<br> Breakdown|Comments||||\n|Girls||Percentage<br>Sub Type<br> Breakdown|Value|25.00|35.00|40.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007931", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "EMIS", "probe_tag": "confusion", "probe_score": 0.4287193715572357, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 365, "end": 369, "key": "fcv_pads_east_africa:007931:3:0:0", "source": "camp2", "luna_reason": "EMIS figures are computationally adjusted and used for sector trend analysis.", "usage_type": "evidential", "specificity": "named"}, {"text": "2013 data", "probe_tag": "confusion", "probe_score": 0.5020025968551636, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 805, "end": 814, "key": "fcv_pads_east_africa:007931:3:0:1", "source": "camp2", "luna_reason": "Existing 2013 data is used to establish a baseline and analyze trends.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017158", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "1997 Poverty\n\nAssessment", "probe_tag": "confusion", "probe_score": 0.8166454434394836, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 420, "end": 444, "key": "fcv_pads_east_africa:017158:23:1:0", "source": "camp2", "luna_reason": "Existing poverty assessment supports the cited social-issues findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "* Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** **Objective** **to Goal)**\n**Objective:** **Indicators:**\n**Assist** **war affected** - Improved social capital and - Initial Social Assessment - Communities in the NSAP\n**communities** **to restore** organizational development; (to establish indicators and target areas are assisted to\n**infrastructure,** **services** **and** - Increased access to and use methodologies for social ensure a reduced risk of\n**build** **local** **capacity for** of social and economic capital and organizational conflict\n**collective** **action.** Priority infrastructure and services development)\nwill be given to areas not - Proportion of NSAP - Annual social assessments; - NACSA complements and\npreviously serviced by investments targeted to newly - NaCSA M&E data; extends the work of other\ngovernment, newly accessible accessible areas, & areas - M&E data of relevant line agencies and rninistries\nand the most vulnerable previously not served, and mninistries; in support of the PRSP's\npopulation groups within those vulnerable people within these - Beneficiary Assessment poverty reduction and\nareas. areas; (BAs) biannually; decentralization objectives\n\n                  - Proportion of sub-projects                   - Participatory evaluation\nthat reflect priorities of reports for a random sample of                   - NACSA is fully integrated\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010478", "page": 29, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.2118355929851532, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 862, "end": 876, "key": "fcv_pads_east_africa:010478:29:1:0", "source": "camp2", "luna_reason": "Names project monitoring data without showing substantive analysis or data use.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "community monitoring of natural resources. The lack of a sound information system that\nlinks monitored outcomes to adaptive decision-making (that relies less on ‘control’\nmeasures and more on market signaling and incentive measures) is a gap that needs to be\naddressed in strengthening the policy framework.\nThe project will strengthen the ongoing efforts by supporting assessment of changes in\nland use and planning for sustainable resource use by:\n\n  - Establishment of a baseline and developing a simplified monitoring framework\nfor the collection and use of socio-economic and environmental data relevant to\nimproving land and natural resources management at the local level, which can\nthen be aggregated upwards for decision-making at the district, provincial and\nnational levels;\n\n  - Capacity building for the use of data for adaptive management;\n\n  - Capacity to identify and address links to poverty and cross-sectoral issues\n(overlay of resource degradation data and mapping with poverty indicators and\nmapping towards improved targeting); and\n\n  - Valuing the economic cost of degradation and benefits from alternate approaches.\nThe component will seek to identify and address inconsistencies, perverse incentives and\nopportunities for further policy support for sustainable land and natural resources\nmanagement within legislative and policy frameworks. It aims to remove the broader\npolicy and legal barriers to improved land management through a participative process\ninvolving communities, CBOs, government agencies and research institutions. This\nincludes mainstreaming SLM into sectoral program areas such as energy (demand\nmanagement for woodfuel, improving efficiencies for biomass, strengthening institutional\nplanning), forests (link with the new Forest Act, 2005 which shifts the emphasis for\nmanagement and conservation of forests to local communities and the private sector),\nwildlife (coordination with KWS to reduce incidence of wildlife related conflicts),\nbiodiversity (addressing alien invasive species, maintaining and enhancing agrobiodiversity and indigenous species), water resources (support for integrated water\nresources management and coordination with the Water Resources Management\nAuthority) as well as including related priorities such as gender issues and technology\ndissemination,  KAPP has a broad institutional", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015761", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "socio-economic and environmental data", "probe_tag": "confusion", "probe_score": 0.17827731370925903, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 562, "end": 599, "key": "fcv_pads_east_africa:015761:19:0:0", "source": "camp2", "luna_reason": "Data collection is planned as part of establishing a baseline and monitoring framework.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "resource degradation data", "probe_tag": "confusion", "probe_score": 0.5445126891136169, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 947, "end": 972, "key": "fcv_pads_east_africa:015761:19:0:1", "source": "camp2", "luna_reason": "Planned overlay and targeting activity, not demonstrated use of existing data.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": " in the district and provisional health management teams. This is being done with support\nfrom a US$ 1 million Project Preparation Facility (PPF) from the Bank, and also parallel support\nfrom DANIDA.\n\n36. **Innovative projects to improve public private partnerships (PPP) will also be piloted**\n**within the HSSF framework.**\n\n\n- First, there will be a partnership with the FBOs. The approved scope for the HSSF includes\nfunding for facilities being operated by FBOs, and a phased approach will be followed for\nexpanding HSSF to some of them.\n\n- Second, the HSSF will address imbalances in regional development by supporting\ndevelopment projects at the constituency level. In recent years, many health facilities have\nbeen established under the Constituency Development Fund (CDF) Act. While these\nfacilities are gradually being taken over by the MOPHS, there will be a pilot testing of a PPP\nthrough which the private sector will take over the management of some of these facilities.\nFor making these facilities operational, extensive piloting with different approaches ranging\nfrom contracting-in providers by communities to contracting-out will be undertaken during\nthe first 2 years in 25 facilities. A gradual scale-up is planned subsequently covering 50 and\n100 facilities in the third and fourth years respectively. For the selection of CDF/community\nfacilities, priority will be given to those located in underserved areas, as part of the poverty\nfocus of the Project. This PPP is being developed with support from the IFC in collaboration\n\n\n15 The completion of the baseline survey is a condition of effectiveness for the Project. It is recognized that it will\ntake time for all of the results to be fully analyzed, but the key criterion for the condition to be met is for the field\nwork to have been completed and work at least to have started on the analysis of the results.\n16 Gazette Notice Supplement No. 25 of June 5, 2009.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008550", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "baseline survey", "probe_tag": "confusion", "probe_score": 0.06946220993995667, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1575, "end": 1590, "key": "fcv_pads_east_africa:008550:12:1:0", "source": "camp2", "luna_reason": "Project baseline survey is a required data-collection activity, not existing data use.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": " over the 8-year repayment period), of which US$ 4.92 million\nwas covered by the OBA grant <sup>5</sup>, US$ 5.35 million by NCWSC, and US$ 0.28 million by households.\n\n\n27. **Economic Rate of Return (ERR).** The economic analysis used the amount payable for services by consumers as\none part of the gross benefit, assuming this to be their willingness to pay for the services. The other part of the gross\nbenefit was calculated using assumptions about health benefits accruing to residents as a result of the project. Based on\nthe economic costs and benefits mentioned above, the economic internal rate of return was estimated to be 34 percent\nprior to the project and was revised down to 23 percent at the time of the restructuring.\n\n\n28. Based on figures provided by Nairobi County Public Health Office (see Annex 4) the health assumptions appear to\nbe realistic and have not been modified as part of the final ERR calculation. Following revisions to the assumptions based\non the actual project outputs and expenditure, the revised calculation places the ERR at 21 percent, which demonstrates\n\n\n5 US$ 4.75 million for OBA subsidies for water and sanitation services and US$ 0.17 million for consultancy services\n\n\nPage 10 of 29", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014487", "page": 13, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "figures provided by Nairobi County Public Health Office", "probe_tag": "confusion", "probe_score": 0.5148308873176575, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 750, "end": 805, "key": "fcv_pads_east_africa:014487:13:3:0", "source": "camp2", "luna_reason": "Existing county health figures support assumptions used in the revised ERR calculation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012216", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.11965898424386978, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 412, "end": 437, "key": "fcv_pads_east_africa:012216:31:0:1", "source": "camp2", "luna_reason": "Names administrative data as a verification source without showing actual analytical use.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1188, "end": 1214, "key": "fcv_pads_east_africa:012216:31:0:2", "source": "camp2", "luna_reason": "Administrative data is merely listed as a verification source without demonstrated use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": " well\nlooking after the family well-being), is mainly the responsibility of women.\n\n\nBesides their role in reproduction, women’s share of productive activities and burdens of household\nchores are bulky as is the case in most societies. Agriculture (crop production and Livestock\nrearing) is the major productive activity across the entire project area. Men’s work is supposed to\nbe agricultural activities, house construction, protecting community against attacks by wild\nanimals, shepherding, and trading. This is mainly true for the Amhara Region, however, in Afar\nregion, all these activities are the responsibilities of the women. A female discussant in Ada’ar\nWoreda has confirmed the same.\n\n\nThe above gender survey result reveals that in the absence of well-developed social services and\ninfrastructures women’s workload is much worse than places that have improved social service\nfacilities. Women travel long distances to fetch water for household consumption, use traditional\nstone grinding mills which are highly tiresome and time consuming. Poor road and transport\nnetwork cause women to travel long distance to market places carrying commodities weighing 2550 Kg. In general, the gender division of labor in the project corridor is defined in favor of men and\nhas subjected women to bear too much responsibility in the society without being recognized and\nappreciated.\n\n\nThe construction of the project road is expected to provide socio economic support to women in\nboth the productive and reproductive activities by improving their situation.\n\n\n  - Productive activities **:** The construction of the project road is expected to provide and\nintroduce women with labour and time saving tools and equipment, and at the same time\nimprove their productive capacity. This could be realized with availability of improved\nroad and communication services.\n\n\nAssociated Engineering Consultants PLC Ethiopian Roads Authority\nMarch 2012", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014974", "page": 25, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "gender survey result", "probe_tag": "confusion", "probe_score": 0.8389090299606323, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 708, "end": 728, "key": "fcv_pads_east_africa:014974:25:1:0", "source": "camp2", "luna_reason": "Survey result supports a concrete finding about women’s workload.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": ", credit have accessed finance and\nstarted running micro-businesses. Livelihood’s beneficiaries have reported saving as a result of their\nparticipation and learning from the livelihood support; and (vii) In EFY 2016, 327,707 hectares of land was\ntreated through area enclosure, rangeland management, soil and water conservations, and forage and\nforestry activities.\n\n\n7. While these achievements are noted, the following issues were observed require GoE’s attention: (i) high\nlevel oversight is critical to implement the increased EFY 2017 budget and targets; (ii) the need for GoE’s\nofficials’ commitment to ensure timely utilization of the increased livelihood budget while ensuring quality\nof implementation; (iii) delays in food procurement; (iv) achievement of Performance-Based Conditions\n(PBCs); and (v) timely initiation of the next phase design.\n\n\n<mark>8.</mark> <mark>The PSNP’s rating, based on World Bank implementation support ratings during this period are as follows:</mark>\n\n\n\n\n\n\n\n|Project Ratings|Previous|Current|\n|---|---|---|\n|Project Development Objective (PDO)|MS|MS|\n|Implementation Progress|MS|MS|\n|Component 1: Adaptive Productive Safety Net|MS|MS|\n|Component 2:<br>Improve Shock Responsiveness of the Rural Safety Net|S|MS|\n|Component 3: Systems, Capacity Development, and<br>Program Management Support|MS|MS|\n|Financial Management|MS|MS|\n|Project Management|MS|MS|\n|Counterpart Financing|MS|MS|\n|Procurement|MU|MS|\n|Environmental and Social|MS|MS|\n|Monitoring and Evaluation|MS|MS|\n\n\n**III. PRIORITY STRATEGIC ISSUES**\n\n\n**Strategic issue 1: High level oversight is critical", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001304", "page": 1, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "World Bank implementation support ratings", "probe_tag": "confusion", "probe_score": 0.5404422879219055, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 907, "end": 948, "key": "fcv_pads_east_africa:001304:1:1:0", "source": "camp2", "luna_reason": "World Bank ratings provide the basis for the PSNP project rating table.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "timely, relevant, understandable, and accessible information, and consult with them in a culturally\nappropriate manner, which is free of manipulation, interference, coercion, discrimination, or intimidation.\n\n## **2. Objective/Description of SEP**\n\nThe overall objective of this SEP is to define a program for stakeholder engagement, including public\ninformation disclosure and consultation throughout the entire project cycle. The SEP outlines the ways in\nwhich the project team will communicate with stakeholders and includes a mechanism by which people\ncan raise concerns, provide feedback, or make complaints about project activities or any activities related\nto the project.\n\n## **3. Stakeholder identification and analysis**\n#### **3.1. Methodology**\n\nData to prepare this document are collected from five region and one city administration through\nstakeholders’ consultations, key informant interviews, and desk review. Field data from sample regions\nand a city administration were collected by MOE’s professionals. The sources of the field data were school\ncommunities, local communities, and selected regional bureaus and woreda offices. The experiences of\nthe stakeholders in environmental and social risks on previous WB financed projects which are similar to\nETOL project have been thoroughly explored. Stakeholders also forecasts the anticipated E&S risks of ETOL\nand suggest the mitigation strategies. The photos during the discussions and the attendance sheets are\nannexed to this plan.\n\n\nStakeholder engagement shall be informed by a set of principles defining core values underpinning\ninteractions with stakeholders. Common principles based on International Best Practice include the\nfollowing::\n\n- _Openness and life-cycle approach:_ Public consultations for the project(s) will be arranged during the\nwhole life cycle, carried out in an open manner, free of external manipulation, interference, coercion,\nor intimidation.\n\n- _Informed participation and feedback:_ Information will be provided to and widely distributed among all\nstakeholders in an appropriate format; opportunities are provided for communicating stakeholder\nfeedback, and for analyzing and addressing comments", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005321", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Field data from sample regions\nand a city administration", "probe_tag": "confusion", "probe_score": 0.42031988501548767, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 927, "end": 983, "key": "fcv_pads_east_africa:005321:5:0:0", "source": "camp2", "luna_reason": "Field data were collected by MOE professionals, indicating data production.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "field data", "probe_tag": "confusion", "probe_score": 0.5304762721061707, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1042, "end": 1052, "key": "fcv_pads_east_africa:005321:5:0:1", "source": "camp2", "luna_reason": "Field data were collected by MOE for preparing the project document.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": " for the country and the climate, and how best to deal\nwith the operations and maintenance issues for school upkeep.\n\n\nThe list of sites for the Phase I schools follows. Note that the first year sites are fixed while there\nmay be some adjustments on the second year sites.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020644", "page": 32, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "list of sites for the Phase I schools", "probe_tag": "confusion", "probe_score": 0.0955224558711052, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 123, "end": 160, "key": "fcv_pads_east_africa:020644:32:2:0", "source": "camp2", "luna_reason": "Project site planning list, not existing data used for analysis or decisions.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "21\n\n\nthey have to purchase water from trucks which costs four times as high than a household connection;\nand qat consumption poses a major social, income and productivity issue.\n\n\nIn order to capture as much of the school-age population presently out of school due to the lack of\nexisting places, the project will construct additional/rehabilitate classrooms. In addition, sanitation\n\nservices will be rehabilitated, and a study will be undertaken on which sanitation services best serve\nthe area, especially in a drought-prone area, and the most cost-effective methods of implementation\nand maintenance. The project will finance a study to analyze the factors that hinder girls' attendance\nand achievement, and of the feasibility of measures to overcome them, including the issues\n\nsurrounding access to education by the poor. The problems are cross-sectoral which the project, in\nPhase I, will not address (unemployed youth, health issues, non-Djiboutian school-age population,\netc.). See Section C above for program details.\n\n\nThe IDA's regional team will discuss with Government on updating the initial 1997 poverty\n\nassessment in order to produce a better picture of the issues as they exist now. In addition, it is\nenvisaged that IDA will discuss the rising health issues with the Government and the best ways for\naddressing these problems.\n\n\n_6.2 Participatory Approach: How are key stakeholders participating in the project?_\n\n\nKey stakeholders participated in the National Educational Forum _(Etats-Generaux de l'Education)_\nwhich was held in December 1999. This included officials, teachers, parents, students, members of\nparliament and the general public. The project is based on the outcome of the conference. The new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019187", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "1997 poverty\n\nassessment", "probe_tag": "confusion", "probe_score": 0.6263846755027771, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1107, "end": 1131, "key": "fcv_pads_east_africa:019187:24:0:0", "source": "camp2", "luna_reason": "Existing dated poverty assessment is referenced as the basis for planned updating.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**the Bank’s right to sanction and the Bank’s inspection and audit**\n**rights. The form of the Letter of Acceptance is attached in Appendix**\n**1** .\n\n\n**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables: **Not Applicable.**\n\n\n**_Procurement of Second Hand Goods_** _as specified under paragraph 5.11_\nof the Procurement Regulations – is allowed for those contracts identified in\nthe Procurement Plan tables: **Not Applicable.**\n\n\n**_Domestic_** **_preference_** _as_ _specified_ _under_ _paragraph_ _5.51_ of the\nProcurement Regulations **_(Goods and Works)_** .\n\n\nGoods : **Applicable for those contracts identified in the**\n**Procurement Plan tables**\n\n\nWorks: **applicable** **for** **those** **contracts** **identified** **in** **the**\n**Procurement Plan tables**\n\n\nThis being an emergency project, increased thresholds for Requests for\nQuotations (RFQ) to US$1 million for goods and services and US$5 million for\nworks **;**\n\n\n**Other Relevant Procurement Information:-**\n\n\n**Prior Procurement Arrangements:**\n\n\nThe Procurement Arrangements as indicated in the below table and within\nthe thresholds indicated in the below tables will be used. The thresholds for\nthe Bank’s prior review requirements are also provided in the table below:\n\n\nTable: **Prior review Thresholds**\n\n|Procurement Type|High<br>Risk|\n|---|---|\n|Works|5.0|", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000568", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "confusion", "probe_score": 0.06569124013185501, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 298, "end": 321, "key": "fcv_pads_east_africa:000568:1:0:0", "source": "camp2", "luna_reason": "Procurement planning documentation, not a substantive data resource or data use.", "drop_reason": "bookkeeping", "specificity": "descriptive"}, {"text": "Procurement Plan tables", "probe_tag": "confusion", "probe_score": 0.05065480247139931, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 298, "end": 321, "key": "fcv_pads_east_africa:000568:1:0:2", "source": "camp2", "luna_reason": "Routine procurement planning tables, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "Annex 11\nPage 2 of 4\n\n\nThe country's General Environmental Law, expected to be promulgated very shortly, is divided into four\nmajor titles:\n\n\nTitle 1: Concepts, Objectives and General Principles, and Institutional\nOrganization\nTitle 2: Protection of Environments\nTitle 3: Protection of Animal and Plant Species\nTitle 4: Regulation of Pollution\n\n\nImplementing decrees should quickly specify the conditions for putting the main chapters of this\nframework legislation into effect.\n\n\n_Other Agencies And Bodies Involved_\n\n\nAs regards environmental education, the Directorate of the Environment maintains close collaboration\nwith the National Education Research and Pedagogic Information Center _[Centre de Recherche, et de_\n_Production dInformation de l 'Education Nationale-_ CRIPEN], in particular through the formulation of an\n\nawareness campaign strategy on environmental problems.\n\n\nInfrastructure facilities in the education sector are provided by the Directorate of Housing, Urban\nDevelopment, Environment, and Regional Development (DHU). However, as the current reform process\nis not yet completed, a number of serious malfunctions are preventing the Directorate from perforning\nthe role of executing agency assigned to it in the past. The Planning Unit of the Ministry of Education\nwill be the contracting authority's representative for implementation of this project.\n\n\nBecause the system for gathering and analyzing data on the public health system is no longer operational,\nas was confirmed during the visit made to Djibouti's Pelletier Hospital and to the Djibouti-City health\ndistrict, reliable country-wide epidemiological data are unfortunately unavailable. This state of affairs\napplies to the school population in particular. Under these conditions, it will be difficult to define and use\nindicators capable of measuring the success of actions to mitigate the environmental impacts of the\nproject.\n\n\n**Potential Impacts of the Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017208", "page": 65, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "country-wide epidemiological data", "probe_tag": "confusion", "probe_score": 0.33640798926353455, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1605, "end": 1638, "key": "fcv_pads_east_africa:017208:65:0:0", "source": "camp2", "luna_reason": "States data are unavailable without using findings or substitute estimates.", "drop_reason": "availability", "specificity": "descriptive"}]}
-{"text": ".7 million; actual cost US$1.80 million).\n\n\n**d. Comments on Project Cost, Financing, Borrower Contribution, and Dates:**\nDelays occurred in the beginning of the project with respect to community -driven implementation arrangements. In\naddition, at project closure (on December 31, 2006), 114 sub-projects had been initiated but not yet completed . The\nGovernment has assured the Bank that these sub -projects will be completed utilizing resources from other sources\nas appropriate. However, according to the ICR, information on the current status of these sub -projects including\nactual availability of resources and the expected timeline for their completion is not available . Project records suggest\n<u>that 99.93 % of the funds were disbursed. Undisbursed funds amount to US$47,609.81, which will be cancelled.</u>\n\n\n**3. Relevance of Objectives & Design:**\nThe relevance of the project objectives is substantial, since the Bank's FY 2006-2007 Interim Country Assistance\nStrategy (ICAS) emphasizes broad-based growth and managing vulnerabilities. Project objectives were also in line\nwith the Bank’s Country Assistance Strategy (CAS) for Ethiopia for 2003-06, which was endorsed two weeks after the\nEDRP was approved by the Board. In particular, the EDRP was consistent with the third pillar of the CAS, which\nexplicitly referred to the need to provide safety nets to vulnerable households with a view to helping them sustain and\nbuild assets.\nThe relevance of project design is substantial, since it stressed not just the need to deal with food insecurity but also\nto improve longer-term coping capacities, especially through the build -up of productive assets and sustainable\nlivelihoods. According to the ICR, the project included the following innovative design features : (i) a blend of various\nkinds of support from macro-stabilization to targeted household-level assistance, to help in", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008497", "page": 1, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Project records", "probe_tag": "confusion", "probe_score": 0.8075528144836426, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 680, "end": 695, "key": "fcv_pads_east_africa:008497:1:1:0", "source": "camp2", "luna_reason": "Routine project records support a disbursement accounting claim, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "data.worldbank.org/](https://data.worldbank.org/)\n\n4 _KNBS and ICF. 2023. Kenya Demographic and Health Survey 2022._\n5 The OPCT is an individual entitlement, not household. 730,000 is the approximate number of households in which OPCT\nbeneficiaries reside.\n6 HSNP emergency cash transfers are triggered by external monitoring of a Vegetation Cover Index (VCI) through satellite data.\n\n\nOfficial Use Only", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002873", "page": 4, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Kenya Demographic and Health Survey", "probe_tag": "confusion", "probe_score": 0.8723464012145996, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 74, "end": 109, "key": "fcv_pads_east_africa:002873:4:3:0", "source": "camp2", "luna_reason": "Named existing demographic and health survey cited as a source.", "usage_type": "declaration", "specificity": "named"}, {"text": "satellite data", "probe_tag": "confusion", "probe_score": 0.3580322861671448, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 368, "end": 382, "key": "fcv_pads_east_africa:002873:4:3:1", "source": "camp2", "luna_reason": "Satellite data triggers emergency cash transfers through external VCI monitoring.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "Kenya Power and Lighting Company PLC\n\nKenya **Off** grid Solar Access Project (KOSAP)\nAnnual Report and Financial Statements for the financial year ended June **30, 2025**\n\n\n**_2.8_** Summary of Overall Project Performance:\n\n\na) Budget Performance against Actual Amounts\n\nTo date the Project has received a total Kshs **136** million, which is 2.4 **%** of the budget.\n\n**b)** Physical Progress and Achievement of the Project\n\nUnder the KPLC component, the project entails the development of **83** mini-grids and 343\nsolar stand-atone systems, targeting to connect over **37,500** households, enterprises,\nand public facilities. Implementation progress to date includes handover of project sites,\ncompletion of site surveys, and ongoing detailed design works.\n\nDuringthe year under review, the Project absorbed **5.1 %** of the budget in the FY20242025\n\n\nc) Implementation Challenges and way forward\n\nThe acquisition of land for the construction of mini grids experienced significant delays.\nInitially, the adopted approach-donation of unregistered community land-was found\nto be inconsistent with the prevailing legal framework. Following extensive consultations,\nthe World Bank approved a Com pensation-in -Kind Strategy, whereby the Project would\nprovide community infrastructure, such as the construction of classrooms or the desitting of water pans, in lieu of cash payments.\nThe Ministry subsequently mobilized the required resources and engaged the National\nLand Commission **(NLC)** to lead the land acquisition process. Key milestones, including\ngazettement of the land, grantingof eartyentry, site inspections, and public inquiries, have\n\nbeen completed. Final surveys have also been undertaken jointly **by** the Directorate of\nSurveys and technical teams from KPLC and REREC and wilt be submitted to the Ministry\nof Lands for final vesting.\nThe", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000418", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "site surveys", "probe_tag": "confusion", "probe_score": 0.10653789341449738, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 712, "end": 724, "key": "fcv_pads_east_africa:000418:9:0:0", "source": "camp2", "luna_reason": "Site surveys are reported as completed project activities, not existing data used for analysis.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "GFF Grant; thereafter<br>SDR 2.764 million from<br>AF Credit, for each 1%<br>increase|11,056,000|5,000,000|0|\n|(4.1)   Contraceptive<br>prevalence rate (for<br>rural women only)|(a) Increase in<br>contraceptive prevalence<br>rate in rural women up to<br>a maximum of 38% from<br>baseline of 32%<br> <br>US$2.5 million from GFF<br>Grant; thereafter SDR<br>2.211 million from AF<br>Credit for each 1%<br>increase <br>|8,844,000|5,000,000|0|\n|(5)   Health centers<br>reporting HMIS data<br>in time|(a) Increase up to a<br>maximum of 86% from<br>baseline of 68%<br> <br> US$0.9989 million<br>from GFF Grant;<br>thereafter SDR 0.1844<br>million from AF Credit,<br>for each 1% increase|2,950,000|2,000,000|0 <br> <br> <br> <br> <br> <br> <br> <br>|\n|(7)   Development and<br>implementation of<br>Annual Rapid Facility<br>Assessment<br>|(c) Upon undertaking<br>Rapid Facility<br>Assessment and<br>disclosing results with<br>actions to address<br>weaknesses as envisaged<br>by the Program, for each<br>of the calendar years|<br>2,984,000<br>|0|0", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009550", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "HMIS data", "probe_tag": "drop", "probe_score": 0.0413319431245327, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 474, "end": 483, "key": "fcv_pads_east_africa:009550:5:1:0", "source": "camp2", "luna_reason": "Indicator cell in a results table, not a cited use of HMIS data.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010872", "page": 62, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "1999 data", "probe_tag": "drop", "probe_score": 0.02271115779876709, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 688, "end": 697, "key": "fcv_pads_east_africa:010872:62:2:0", "source": "camp2", "luna_reason": "Bare date-qualified data phrase lacks an attributed finding or identifiable source.", "drop_reason": "ref_list", "specificity": "vague"}, {"text": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9823695421218872, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 758, "end": 796, "key": "fcv_pads_east_africa:010872:62:2:1", "source": "camp2", "luna_reason": "Named database cited as the source producing the table.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012953", "page": 62, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "1999 data", "probe_tag": "drop", "probe_score": 0.02271115779876709, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 688, "end": 697, "key": "fcv_pads_east_africa:012953:62:2:0", "source": "camp2", "luna_reason": "Generic data reference lacks an attributed finding or concrete claim.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018595", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Project Financing Data", "probe_tag": "drop", "probe_score": 0.04618202894926071, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1106, "end": 1128, "key": "fcv_pads_east_africa:018595:4:0:0", "source": "camp2", "luna_reason": "Standalone project financing table heading, not a data resource used as evidence.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018645", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9347544312477112, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 870, "end": 881, "key": "fcv_pads_east_africa:018645:38:1:1", "source": "camp2", "luna_reason": "Existing survey data supports enrollment-rate comparisons, despite lacking education-level separation.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "\ncontrol soil erosion and enhance soil fertility. The survey results show that 92.8 percent of interviewed\nhouseholds have constructed bunds on their farmlands, which was by far larger than the baseline year. The\nfarmland area treated with bunds was also higher than the baseline year. The survey data reports that check\ndams were constructed on at least 44.6 percent of interviewed households’ land in contrast to 15.7 percent\nduring the baseline year. Integrating cutoff drains with bunds and terraces was also one of the conservation\nactivities aiming at the sustainability of bunds and terraces and preventing soil erosion. The results of\nhousehold surveys reveal that about 30 percent of households have implemented cutoff drains. The\nproportion of farmers who carried out this conservation structure has increased in the past six years.\n\n\n9. **Gully prevention and controlling measures.** Different kinds of gully prevention and controlling\nmeasures have been implemented to reduce impacts and increase production and productivity of the project\narea. The prevention measures included property development (such as locate and construct roads, fences,\nand laneways so that they cause minimal concentration and diversion of runoff); grazing management (such\nas fence off and exclude livestock from land vulnerable to gully erosion); and cropping management (such\nas control erosion on slopping cultivated land by stubble retention and the construction and maintenance of\ncontour banks and waterways). Gully erosion control measures include use of vegetation, gully reshaping\nand filling, controlling gully heads, and gully floor stabilization. Both prevention and control measures\nhave been implemented in all five sub-watersheds since 2008.\n\n\n10. **Forestry and agroforestry.** New community forests and household woodlots are planted, and\nbackyard plantation has been enhanced through the project support. In the past six years, plantation of trees\naiming at income generation, enrichment of soil fertility, and control of soil erosion and production of\nlivestock fodder was widely practiced. The results showed that about 94.9 percent of", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018181", "page": 73, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9603673219680786, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 290, "end": 301, "key": "fcv_pads_east_africa:018181:73:1:0", "source": "camp2", "luna_reason": "Survey data reports concrete household construction percentages.", "usage_type": "evidential", "specificity": "vague"}, {"text": "household surveys", "probe_tag": "keep", "probe_score": 0.9449095129966736, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 643, "end": 660, "key": "fcv_pads_east_africa:018181:73:1:1", "source": "camp2", "luna_reason": "Past household surveys support an attributed 30 percent finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019321", "page": 62, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9823695421218872, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 758, "end": 796, "key": "fcv_pads_east_africa:019321:62:2:1", "source": "camp2", "luna_reason": "Named database cited as source for the presented economic data table.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015645", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9347544312477112, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 870, "end": 881, "key": "fcv_pads_east_africa:015645:38:1:1", "source": "camp2", "luna_reason": "Survey data support reported enrollment-rate gaps and education-level comparison.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012429", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9347544312477112, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 870, "end": 881, "key": "fcv_pads_east_africa:012429:38:1:1", "source": "camp2", "luna_reason": "Existing survey data underpin enrollment comparisons and a stated disaggregation limitation.", "usage_type": "evidential", "specificity": "vague"}, {"text": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9652993679046631, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1978, "end": 2008, "key": "fcv_pads_east_africa:012429:38:1:2", "source": "camp2", "luna_reason": "Household Survey data support a concrete finding about girls’ school attendance.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "age 12 months, while the overall under-5 mortality rate was 64 deaths per 1,000 live\nbirths. The most at risk populations regarding HIV/ AIDS in Eastern Uganda include\nfemale sex workers (mostly youths). Death due HIV/AIDs leads to an increase in\nnumber of orphans as well as children in extremely poor households are at high risk\nof dropping out of school and becoming working children. Many children, with low\nhuman capital and in poor health, tend to grow up to become at-risk and\nunemployed youth. The proposed project, poses a risk of child labour due to a\nsignificant number of unemployed youths and children in the area.\n\nChild abuse takes many forms including child labour. Child labour (children below 17\nyears) within the district of Mbale is recorded at 25, 560 cases (24.7% of the total\nnumber of children), and in Busia District 24,919 (34.7%). (National Population and\nHousing Census, Area Specific Profiles, 2014). This indicates that a significant\npercentage of children is already working and as such, there is a risk that the proposed\nproject will employ children if the risk is not guarded against.\n\n\nEconomic Activities\n\nIn the eastern region, majority of the population depend on subsistence agriculture\nfor food, income and employment. According to the Population and Housing Census,\n2002, the main economic activities for majority of the households in the project areas\nwere dealing in crop farming as their main economic activity. The crops grown\ninclude millet, vegetables, sweet potatoes maize, sugar cane, and sorghum. Most of\nthe population in most of the districts, notably, in the age group 20 to 24 is involved\nin unpaid family work, followed by those self-employed commonly found in the age\ngroups 18 to 19 years.\n\nIn study area, people grow a variety of food and cash crops. 85% of the farmers are\nengaged in crop production as their main activity, 12% are", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018691", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Population and Housing Census", "probe_tag": "keep", "probe_score": 0.9673011898994446, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1275, "end": 1304, "key": "fcv_pads_east_africa:018691:33:0:1", "source": "camp2", "luna_reason": "2002 census data supports claims about households’ main economic activities.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013795", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Human Development Index", "probe_tag": "confusion", "probe_score": 0.8185583353042603, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 251, "end": 274, "key": "fcv_pads_east_africa:013795:7:1:0", "source": "camp2", "luna_reason": "Index supports a concrete lowest-in-world development ranking.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nET - Health SDG Program for Results (P123531)\n\n\n**8. M&E Design, Implementation, & Utilization**\n\n\n**a. M&E Design**\n\nThe objective of the program was clearly stated and reflected by the selected indicators. M&E\narrangements were well embedded institutionally and would use HSDP IV information system\ncomplemented by household and health facility surveys (p. 21). For population-based surveys, the program\nwould utilize the reliable data of the Demographic and Health Survey whose implementation is\ncoordinated by the Central Statistical Agency, an entity independent of FMOH. The provision of data would\nbe coordinated by FMOH and the Ethiopian Health and Nutrition Research Institute, assisted by the Gates\nFoundation, UNICEF and WHO. The PforR was planned to support ongoing government efforts to further\nstrengthen HMIS.\n\n\n**b. M&E Implementation**\n\nM&E Implementation was adequate overall, but with challenges encountered during the latter years of\nimplementation in view of the COVID-19 pandemic combined with security concerns that made\npopulation-based surveys more challenging. The balanced score card was dropped because the scheme\nwas replicated nationwide at an early stage (ICR, p. 27). Regular reporting facilitated verification\nprocesses and disbursements.\n\n\nThere were other surveys and studies conducted during the life of the program and they provided\npolicymakers with valuable information for decision making, such as the nutrition reports with a wide\nrange of data and recommendations for improving interventions supported by the program, e.g., Iron\nFolic Acid utilization, Vitamin A supplementation, and Growth Monitoring and Promotion.\n\n\n**c. M&E Utilization**\n\nM&E findings were used for program monitoring, including to: (i) take stock of progress on DLIs and\nidentify remedial actions if needed; (ii) identify areas requiring technical assistance; (iii) hold", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001913", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "HSDP IV information system", "probe_tag": "confusion", "probe_score": 0.7432048320770264, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 359, "end": 385, "key": "fcv_pads_east_africa:001913:16:0:0", "source": "camp2", "luna_reason": "Future planned use of the information system, not demonstrated existing data use.", "drop_reason": "promissory", "specificity": "named"}, {"text": "household and health facility surveys", "probe_tag": "confusion", "probe_score": 0.10437433421611786, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 402, "end": 439, "key": "fcv_pads_east_africa:001913:16:0:1", "source": "camp2", "luna_reason": "Planned M&E use of surveys, not an existing survey cited as used.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": " (in **E** number 4.7 4.7 4.7 4.9 **5.3** **5.3** Monthly Progress MEMD/REA\nthousands).\n\n\n\n**1.3** Number of households using Solar E number 12 **16.3** **17** 20 **27** **32** Monthly Progress MEMD/REA\nPV systems (in thousands). report\n\n1.4 Capacity of solar PV systems sold\n**by** private companies supported **by** **E** kW 1400 **1738** **1750** **1800** 2000 2400 Monthly Progress MEMD/REA\nERT-2 (kW) report\n**1.5** Percent reduction in large Progress\nindustrial/commercial loads in target H percent **0** **30** **30** **30** **30** **30** Monthly report MEMD/REA\nlocations **(%)**\n2.1 Number of Community Progress\nInformation Centers established in un- H number **1533** **1533** **1533** **1833** **2083** **2083** Monthly report **PCU/UCC**\nserved and underserved areas\n2.2 Number of sub-counties with\npublic broadband Internet access **E** number **0** **0** **0** **7** **16** **16** Monthly Progress **PCU/UCC**\npoints\n\n\n**17** Para **10** of the text explains the breakdown of the connections as funded **by IDA,** and the OBA program.\n\n\n**_", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016331", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Monthly report MEMD/REA\nlocations", "probe_tag": "confusion", "probe_score": 0.6179968118667603, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 546, "end": 579, "key": "fcv_pads_east_africa:016331:20:1:2", "source": "camp2", "luna_reason": "Planned project monitoring report, not an independently analyzed data resource.", "drop_reason": "promissory", "specificity": "named"}]}
+{"text": "|USO|KSH|USO<br>CUMMULATIVE<br>|\n|OPENlNGBALANCEATlSTJULY2013|<br>4,479,006|<br>385,529,080|-|\n|||||\n|Add;||||\n|Totalamountdepositedbv WorldBank|8,406,256<br>|723,l 24,880<br>|18,065,709|\n|Totalinterestearnedifdepositedinaccount|-|-|-<br>|\n|Amountrefundedfor ineligibleexpenditure|-|-|~~-~~|\n|TOTAL|12,885,262|1,108,419,960|18,065,709|\n|Deduct;||||\n|Totalamountwithdrawn:||||\n|TransferredtoProject Account|2,660,111|228,828,676|7,840,558|\n|InTransitMEWNR|8,912,322|766,658,807|<br>8,912,322|\n|Total servicechar~e|-|-|-|\n|||||\n|CLOSINGBALANCEAT30JUNE2014|1,312,829|112,932,477|1,312,829|\n\n\nT'·e cumulative figures have been reconciled and agree to the Bank's Loan/Grants records as per Client\n\n~ nnection. The inf01mation used to prepare this Statement is obtained from Statement of special Aecom\nActivity prepared and signed by Treasury and Central Bank of Kenya (CBK) and attached as Annex 4 1\ntJ !Se financial statements. The conversion of the figures to Kenya shillings equivalent and the compilation<\n: ~nulative figures have been done by the Project based", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012447", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Statement of special Aecom\nActivity", "probe_tag": "confusion", "probe_score": 0.6033514142036438, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 769, "end": 804, "key": "fcv_pads_east_africa:012447:14:1:1", "source": "camp2", "luna_reason": "Project financial account statement used for routine financial reporting", "drop_reason": "bookkeeping", "specificity": "named"}]}
+{"text": "The application of digital data collection regarding sidewalk conditions and user surveys, combined with\n\n\nthe use of several analytical tools, including a georeferenced inventory database and global walkability\n\n\nindex, helped the team test the innovative method in the studied corridor and allowed for the revealing\n\n\nof a comprehensive picture of sidewalk conditions and walkability from an urban design, road safety,\n\n\nand user experience perspective.\n\n\nIt is reassuring that the sidewalk network within the study area is adequately wide, with 39% over 2.5\n\n\nmeters, and secondly, 29% between 1.5 meters and 2.5 meters. Street lighting can be found in 48% of\n\n\nthe sidewalk network. The urban inventory also showed that sidewalk features are clearly better in the\n\n\nrecently built segments.\n\n\nNevertheless, even in this bustling urban corridor with LRT service, walkability is far from ideal for\n\n\npedestrians and public transport users. Considering key sidewalk features, nearly two-thirds of\n\n\ncrossings are inaccessible, and it is important to remember that most dangerous pedestrian behaviors\n\n\noccur at crossings. More than half of the network in this urban center corridor has no tactile pavement\n\n\nfor visually impaired users and no adequate street lighting. **As a result, 67% of the network falls**\n\n\n**under the C and D category levels of the Global Walkability Index, confirming the deficient,**\n\n\n**unsafe sidewalk conditions** .\n\n\nUsers further corroborated analytical findings with their own experience, citing that sidewalks are\n\n\ninaccessible (75%), unsafe in terms of infrastructure quality (66%) and unsafe in terms of exposure to\n\n\ntraffic (63%), and the majority of sidewalk users (70%) considers that streets are obstructed by street\n\n\nvendors, parking, or other obstacles.\n\n\nThese analytical findings will feed into the study’s formulation of short-term strategies and guidelines for\n\n\nsidewalk design and maintenance.\n\n\n**_Page 40 of 72_**", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006691", "page": 45, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "georeferenced inventory database", "probe_tag": "confusion", "probe_score": 0.8753434419631958, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 156, "end": 188, "key": "fcv_pads_east_africa:006691:45:0:0", "source": "camp2", "luna_reason": "Database data informed sidewalk analysis and produced concrete infrastructure findings.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "global walkability\n\n\nindex", "probe_tag": "confusion", "probe_score": 0.8467814922332764, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 193, "end": 219, "key": "fcv_pads_east_africa:006691:45:0:1", "source": "camp2", "luna_reason": "Global Walkability Index data supports the reported sidewalk-condition finding.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nHealth Sustainable Development Goals Program-for-Results (P123531)\n\n\naudit backlog from a decade earlier). <sup>25</sup> [^25: Soon after the Program got off the ground there was a need to conduct a level 2 restructuring to extend the closing for the PFSA audits for\nFY2002 and FY2002 as the client was unable to comply in a timely manner (ISR#3).] There was also strong alignment with indicators in key government documents\n(i.e., GTP, HSDP) as well as the World Bank’s country assistance strategies for Ethiopia. One shortcoming noted was the\narticulation of the DLI on financial protection (‘functionality of the CBHI scheme’) which could have been more clearly\nstated.\n\n\n**M&E Implementation**\n\n\n46. **M&E Implementation was generally well conducted.** Regular DHS were carried out and funded through various\nsources; annual rapid health facility readiness surveys were integrated with the SPA+ surveys; and a balanced score card\nwas planned but had to be dropped as the scheme was replicated nationwide. There were other surveys and studies\nconducted during the life of the Program which provided policymakers valuable information for enhanced decision\nmaking, such as the nutrition reports which generated national or regional data on a wide range of indicators and\nrecommendations on improving critical interventions supported by the Program (i.e., IFA, VAS, GMP).\n\n\n47. **During the initial phase of implementation Program monitoring went smoothly with consistent data availability,**\n**strong compliance with DLIs, and a solid disbursement record** . During the phase following the approval of the AF, M&E\nimplementation experienced more difficulties and delays, as the Program covered a wider range of areas and as the\nCOVID-19 pandemic combined with security concerns made it difficult to conduct population-based surveys. On a\ngeneral note, the MOH/MDGPF/SDGPF produced regular reports to verify compliance with DLIs and enable the World\nBank team", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007106", "page": 32, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SPA+ surveys", "probe_tag": "confusion", "probe_score": 0.6345509886741638, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 913, "end": 925, "key": "fcv_pads_east_africa:007106:32:0:1", "source": "camp2", "luna_reason": "Named existing survey integrated into the program’s M&E implementation.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "* The project aimed at establishing four sectoral\nregulatory agencies in communication, electricity, transport and water and sewerage sectors, but only two (the\nUganda Communications Commission and the Electricity Regulatory Authority ) were established by project closure.\nFurthermore, while by close of the project an effort was underway to establish the regulatory institution for transport,\nit was decided that the water and sewerage sector would continue to be regulated by the line ministry responsible for\nthe sector. In effect, the design of the project in this area was over -ambitious and failed to recognize the capacity\n<u>constraints and time required to build consensus in reforms of this kind .</u>\n\n\n**5. Efficiency (not applicable to DPLs):**\nBecause of data limitations, the ICR could not calculate the NPV and the ERR using the original appraisal\nmethodology for all components. Instead, the NPV and the ERR were calculated at project completion for\ncomponents of the project related to severance payments and redeployment support for retrenched workers, which\naccounted for about 63 percent of total project costs (including both IDA and GOU). The estimated ex-post NPV is\nUS$114m for a 12 percent discount rate and ERR of 76 percent, compared to appraisal NPV of US$8.6m and ERR\nof 14.9 percent respectively for similar components. The large disparity between the appraisal and ex -post estimates\nof NPV/ERR could be explained by the poor quality of data at appraisal relative to those generated by the monitoring\nsystem set-up for the project (especially the Retrenched Employees Tracer Study and the Privatization Impact\nAssessment). Financial rates of return were not calculated.\n\n\n**a. If available, enter the Economic Rate of Return (ERR)/Financial Rate of Return** **(FRR) at appraisal and the**\n\n**re-estimated value at evaluation** **:**\n\n\nRate", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012452", "page": 2, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Privatization Impact\nAssessment", "probe_tag": "confusion", "probe_score": 0.7304052710533142, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1623, "end": 1654, "key": "fcv_pads_east_africa:012452:2:2:1", "source": "camp2", "luna_reason": "Assessment data were generated by the project’s monitoring system.", "drop_reason": "production", "specificity": "named"}]}
+{"text": "**1.3 Procurement exclusions**\n\n\n4. There are no activities or high value contracts in the Government’s program that should be\nexcluded from the PforR component in accordance with the World Bank's Policy and Directive on\nProgram-for-Results Financing. Therefore, the Program procurement does not involve procurements\nwithin the World Bank Operations Procurement Review Committee (OPRC) thresholds.\n\n\n**2. Scope**\n\n\n5. The scope covers MoE and TSC to determine whether the fiduciary systems provide reasonable\nassurance that there are in place systems that ensure increased transparency and efficiency in\nprocurement processes and contract management, and financial management to undertake the PforR\nprogram, the program under preparation for the Global Partnership for Education (GPE) for Kenya Basic\nEducation Equity in Learning Program (P176867).\n\n\n6. The PforR will focus resources on specific outcomes or results which are relevant for the Country\nto achieve equitable and quality basic education.\n\n\n**3. Review of Public Financial Management Cycle**\n\n\n**3.1 Planning and Budgeting**\n\n\n**3.1.1 Planning & Budgeting**\n\n\nOverall FM objective - the Program budget is realistic, is prepared with due regard to government policy\n<u>and is implemented in an orderly and predictable manner.</u>\n\n7. The government budgeting is anchored in the PFM Act 2012 and PFM Act Regulation 2015. The\nannual budget estimates are captured in the IFMIS using the standard chart of accounts (SCOA). The\nprogram budget and expenditures will be captured and reported through the specific SCOA codes in the\nIFMIS. The staff in Planning and Finance are well qualified and experienced.\n\n\n8. The program expenditure framework selected expenditures under State Department of Early\nLearning & Basic Education- primary education and cross cutting issues in all state departments focusing\non primary school, school capitation grants in lagging counties and camp-based refugee schools; activities\nsupported under primary education", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006419", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "IFMIS", "probe_tag": "confusion", "probe_score": 0.11164884269237518, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1430, "end": 1435, "key": "fcv_pads_east_africa:006419:1:0:0", "source": "camp2", "luna_reason": "IFMIS records routine budget estimates and program expenditures for financial management.", "drop_reason": "bookkeeping", "specificity": "named"}, {"text": "IFMIS", "probe_tag": "confusion", "probe_score": 0.42957383394241333, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1430, "end": 1435, "key": "fcv_pads_east_africa:006419:1:0:1", "source": "camp2", "luna_reason": "Names a financial management system without showing its data informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": " At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA M&E data - NaCSA maintains lean and\n**community** **sub-projects and** decision-making by NaCSA; efficient organizational\n**NSAP** **partners monitored** structure\n**and evaluated** **in order to**\n**improve** **program**\n**effectiveness.**\n\n\n**3(d)** **Technical** **Assistance** 3d. 1 NaCSA staff indicate - IDA aide-memoires and\n**services** **effectively** **provided** satisfaction with technical project status reports\n**to support program** assistance, including skill\n**implementation** transfer activities\n\n\n**3(e)** NaCSA **management** 3e. 1 Project management - IDA Project Status reports\n**systems** **functioning** costs (NaCSA staff salaries at (including disbursement\n**effectively** **to ensure** all levels as well as operating reports);\n**program success** expenditures) are 13.5% or - NaCSA proposed annual\nless than total budgeted annual work program and budget\nexpenditures;                 - Annual audit reports;\n3e.2 NaCSA staff and                  - GOSL semi-annual PETS\npartners indicate satisfaction reports\nwith the performance of\nNaCSA's management;\n3e.3 NaCSA performance in\n\n\n                                  - 27", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017677", "page": 31, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.14897601306438446, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 170, "end": 184, "key": "fcv_pads_east_africa:017677:31:1:0", "source": "camp2", "luna_reason": "Names project monitoring data without showing an attributed finding or substantive analysis.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "completed sub-projects local authorities provide\nconform to ministry standards, resources and staff to operate\ndesigns and norms. and maintain facilities (e.g.\nprovision of teachers and\n\ntextbooks in the case of\nprimary schools);\n\n\nl(b) Targeted communities are lb. 1 At <sup>least 90%</sup> <sup>of</sup> - Beneficiary/ impact - Sub-projects reflect\nempowered to carry out projects are assessed as assessments and other beneficiary needs and\npriority investments. successful by communities evaluation reports improved access to social and\n(achieve rmnimum expected economic services;\noutputs and\noutcomes/imnpacts).\n\n                                     - Supervision missions                                     - PPA methodology is\nlb.2 All supported                  - Beneficiary Assessments internalized by NaCSA and\ncommunities have conducted                - NSAP quarterly progress partners;\nparticipatory needs reports\nassessments and project                 - Participatory M&E results\nidentification using PPA\napproach.                 - Continuous social                 - Capacity building efforts\nI assessment process provided and/or coordinated\nlb.3 100% of communities                  - Participatory M&E results by NaCSA are appropriate and\nhave project management effective;\nstructures in place and trained\ncommunity members.\n\n**2.** Pilot and Special 2a.1 100 km. of feeder roads - Supervision <sup>missions;</sup> - NaCSA's commitment to\n\n**Programs in** Newly rehabilitated. - NSAP quarterly reports; pilot both programs remains\n**Accessible** **Areas** - Annual technical audits; strong\n2a.2 800,000 person days of                  - NaCSA M&E data\n**2(a)** **Rural Public Works** temporary employment\n**Program:** created.\n\nInfrastructure constructed 2a.3 250,000 \"woman days\" of\nand/or upgraded using labor temporary employment\nintensive techniques. created.\n\n\n2a.4 At mid-term review the\ncost per day", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019228", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1658, "end": 1672, "key": "fcv_pads_east_africa:019228:30:0:0", "source": "camp2", "luna_reason": "Verification entry embedded in a logframe table, not an independent data-use mention.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": "**2.5** **Training of Asset Surveyors and Field Enumerators**\nThe training was conducted by the Sociologist and Resettlement Specialist, and covered the\nfollowing topics:\n\n  - Background to the Project;\n\n  - Principles of quantitative and qualitative research;\n\n  - Interviewing ethics and techniques, including exercises and role-playing;\n\n  - Questionnaire content;\n\n  - Practical use of equipment – GPS and camera; and\n\n  - Fieldwork logistics.\n\nThe training concluded with a practical application of the Socio-Economic survey, which also\nfunctioned as the pilot study. The group was responsible for interviewing one selected PAP –\nwith enumerators taking turns to ask questions. Thereafter all met in plenary with the trainers, to\nraise points for discussion and clarification before starting the full survey, and to edit the\nquestionnaire based on appropriateness to the social environment. Interviewers then worked in\npairs for a full day before working individually with the PAP. The additional enumerators were\ngiven personalized intensive training in preparation for the work at the time of employment.\n\n**2.6** **Data Analysis and Quality Control**\nQuantitative PAP census data was analyzed using the Statistical Package for Social Sciences\n(SPSS). The quantitative data has been presented in the form of descriptions, frequencies, tables\nand percentages.  Qualitative data from community dialogues and key institutional stakeholders\nwas manually analyzed around the major themes/objectives of the RAP.\n\n\n11", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014651", "page": 34, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PAP census data", "probe_tag": "confusion", "probe_score": 0.538893461227417, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1172, "end": 1187, "key": "fcv_pads_east_africa:014651:34:0:1", "source": "camp2", "luna_reason": "Existing census data were analyzed and presented through frequencies, tables, and percentages.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "Qualitative data", "probe_tag": "confusion", "probe_score": 0.7588643431663513, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1367, "end": 1383, "key": "fcv_pads_east_africa:014651:34:0:3", "source": "camp2", "luna_reason": "Qualitative data from dialogues and stakeholders was analyzed for RAP themes.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " any other measure of student performance\nwith/without the project. According to the ICR (p. 15), when the Uganda National Examinations Board\nconducted the EGRAs it did not include a control group of students whose teachers had not received\nEGR training. Furthermore, the ICR stated that a direct comparison of the EGRA results with results\nfrom UNICEF’s School Health and Reading Program (which was implemented between 2012 and\n2017 in 31 districts) and USAID’s Literacy Achievement and Retention Activity (LARA, which was\nimplemented between 2015 and 2020 in 28 districts) was not possible because the local languages\nand orthographies differed across the impacted regions under the three programs. Looking at results\ntrends, the ICR noted that, for USAID’s LARA program, there was a jump in the percentage of\nstudents reading 20 or more words per minute from 1 percent at P1 to 5.4 percent at P2 to 24.2\npercent at P3, which is a slightly lower level of improvement than that demonstrated by the cohort\nmeasured under this project. However, it is not clear for what time period the LARA program data was\nprovided and how the LARA program activities were comparable to this project, making it challenging\nto draw conclusions from the comparison. Overall, the data on student outcomes do not allow\nconvincing attribution of observed results to the project's interventions.\n\n\nAlthough there were achievements at the output level (training of teachers, improved teacher attendance, and\nschool inspections) and intermediate outcome level (student-textbook ratios), no information is provided on\nthe results of the school inspections with regard to teacher effectiveness (which measured, among other\nthings, teacher preparation and quality of teaching). As a result, there is limited evidence on the extent to\n\n\nPage 8 of 22", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020317", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on student outcomes", "probe_tag": "confusion", "probe_score": 0.18554575741291046, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1261, "end": 1285, "key": "fcv_pads_east_africa:020317:7:1:1", "source": "camp2", "luna_reason": "Existing student-outcome data are assessed as insufficient for attribution.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": " Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the adverse effects of the situation on\nthe students. The keeping of photographic archives was begun during this mission.\n\n\nThe impacts considered will not be due solely to the project but also to the prevailing situation, which is\ncharacterized by significant degradation of the existing facilities. Since a particular aim of the project is\nto increase the capacity of schools, the main environmental measure to be included in the project will be\nto construct or rehabilitate the sanitary facilities of these schools, and to design a system of upkeep and\nmaintenance that will ensure the appropriate functioning of the schools.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008267", "page": 65, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "photographic archives", "probe_tag": "confusion", "probe_score": 0.21480418741703033, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 363, "end": 384, "key": "fcv_pads_east_africa:008267:65:1:0", "source": "camp2", "luna_reason": "Photographic archives were begun during the mission, indicating new data production.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": " the Registrar General in\nimplementation and coordination of all elements under this component to ensure that the silo approach to implementation is eliminated for better results.\nThe WBG technical team will support the PIU and URSB to re-focus implementation on the results framework and in particular, the outcomes. The\nmission team has also agreed to support the URSB in identifying quick wins that can be targeted for recognition in the 2017 Doing Business\nassessment. The team also noted that licensing reforms are largely focused on introduction of an ICT solution and very little has been done to ensure\nthat the administrative reforms are implemented in tandem with the ICT improvements for realization of the desired goal.\n_Component 3: Tourism Competitiveness Development_ has begun in a newly enhanced institutional environment including the strengthening of UTB.\nTORs for significant activities including the feasibility study and business plan for the Hotel and Tourism Training Institute have been prepared.\n_Component 4: Matching Grant Facility has progressed._ The PCU has completed the recruitment of MFG Unit staff and they have reported to work. They\ncomprise of: Fund Manager (1); Monitoring and Evaluation Officer (1); Business Advisors (4) – one for agriculture (coffee, edible oils, grains and pulse\nand horticulture; one for tourism; one for fisheries and One for ICT); and Accountant (1). Other staff to be shared with CEDP/PCU include:\nCommunication Officer and Environmental Officer. Additional 4 M&E regional staff will be hired on need-basis for monitoring of enterprise funded\nactivities. In the next 6 months, the studies to be undertaken include (i) Update the value chain analysis on the seven targeted subsectors, to be\ncompleted by end August, 2015. (ii) Undertake Baseline Data collection: which will be completed by end August, 2015 and following the availability of\nthe Baseline data, the Business Advisors will identify key performance indicators for their subsectors which will enable the MGF KPIs", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012703", "page": 1, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Baseline Data", "probe_tag": "confusion", "probe_score": 0.14648768305778503, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1800, "end": 1813, "key": "fcv_pads_east_africa:012703:1:1:0", "source": "camp2", "luna_reason": "Baseline data collection is planned for completion by August 2015.", "drop_reason": "production", "specificity": "vague"}, {"text": "Baseline data", "probe_tag": "confusion", "probe_score": 0.5416642427444458, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1908, "end": 1921, "key": "fcv_pads_east_africa:012703:1:1:1", "source": "camp2", "luna_reason": "Baseline data collection is planned for future production.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011711", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.11965898424386978, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 412, "end": 437, "key": "fcv_pads_east_africa:011711:31:0:1", "source": "camp2", "luna_reason": "Standalone source entry within a results-framework table", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
+{"text": "|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period|Closing Period|\n|Indicator Name|Result|Month/Year|Result|Date|Result|Date|Result|Month/Year|\n|Update and Implement National<br>Health Adaptation Plan to Climate<br>Change (Yes/No)|No|Jun/2022|Yes|27-Mar-2025|Yes|27-Mar-2025|Yes|Jun/2026|\n|Update and Implement National<br>Health Adaptation Plan to Climate<br>Change (Yes/No)|Comments on achieving targets|Comments on achieving targets|• National HNAP to climate change finalized and endorsed • Training provided to regional climate change focal<br>persons • Regional HNAP prepared|• National HNAP to climate change finalized and endorsed • Training provided to regional climate change focal<br>persons • Regional HNAP prepared|• National HNAP to climate change finalized and endorsed • Training provided to regional climate change focal<br>persons • Regional HNAP prepared|• National HNAP to climate change finalized and endorsed • Training provided to regional climate change focal<br>persons • Regional HNAP prepared|• National HNAP to climate change finalized and endorsed • Training provided to regional climate change focal<br>persons • Regional HNAP prepared|• National HNAP to climate change finalized and endorsed • Training provided to regional climate change focal<br>persons • Regional HNAP prepared|\n\n\n**Disbursement Linked Indicators (DLI)**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|DLI Name|Col2|Baseline|Actual (Previous)|Col5|Actual (Current)|Col7|End Target|\n|---|---|---|---|---|---|---|---|\n|DLI Name|DLI", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002859", "page": 15, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Disbursement Linked Indicators", "probe_tag": "confusion", "probe_score": 0.07251551747322083, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1334, "end": 1364, "key": "fcv_pads_east_africa:002859:15:1:0", "source": "camp2", "luna_reason": "Standalone table heading, not an independently used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "**_ABBREVIATED RESETTLEMENT ACTION PLAN (ARAP) REPORT_**\n**_FOR PROPOSED WATAMU SANITATION FACILITIES_**\n**_<u>FOR MAWASCO</u>_**\n\n\n**_5.1.2 Cut-off Date_**\n\n\nThe practical Cut-off Date for implementation of the ARAP which is the date of the commencement of the PAPs census and the socioeconomic\nsurvey was initiated and is as detailed below:\n\n\n**_Table 5-1: Cutoff Dates_**\n\n**Name of Facility** **Cutoff Date**\n\nMatsangoni AB 9 <sup>th</sup> of November 2020\n\nGede Mkt AB 11th of April 2019\n\nNo structure, businesses or any other asset established in the Project-Affected Area after the said dates shall be eligible for compensation.\n\nIt is worth noting that the Matsangoni site slightly changed to an adjacent plot following the construction of the Matsangoni Market under the County\nGovernment of Kilifi which consumed part of the identified site resulting to a slight change of PAPS. However, additional consultations were done\nduring the COVID-19 period through focused group discussions to adhere to the Government of Kenya rules aimed at minimizing the spread of the\npandemic necessitating for the change of the cut-off date from 30 <sup>th</sup> November 2018 to 09 <sup>th</sup> November 2020 where a fresh PAPS Census and social\neconomic survey was carried out and report updated accordingly.\n\n\n**_5.1.3 Eligibility_**\n\n\nAssets, including structures which were surveyed in the Project-Affected Area by the Cut-Off Date are eligible for compensation. People residing in\nthe Project-Affected Area by the Cut-Off Date are eligible for compensation even", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007334", "page": 18, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PAPs census", "probe_tag": "confusion", "probe_score": 0.7441481351852417, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 262, "end": 273, "key": "fcv_pads_east_africa:007334:18:0:0", "source": "camp2", "luna_reason": "The census is being initiated and carried out for the ARAP.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "PAPS Census and social\neconomic survey", "probe_tag": "confusion", "probe_score": 0.6523483395576477, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1217, "end": 1255, "key": "fcv_pads_east_africa:007334:18:0:2", "source": "camp2", "luna_reason": "Sentence states the census and survey were carried out as project data production.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": ">collected by<br>Kenya<br>Continuous<br>Household<br>Survey (KCHS)|<br>KCHS poverty<br>estimates<br>produced and<br>disseminated|<br>Kenya<br>Integrated<br>Household<br>Budget Survey<br>KIHBS<br>2020/21<br>fieldwork<br>started|Annual|<br>Program<br>Progress<br>Report|<br>KNBS|\n|<br>**Produce better**<br>**real and external**<br>**sector economic**<br>**data**|<br>☐|<br>☒|<br>Yes/No|<br>Insufficient<br>capacity to meet<br>SDDS criteria in<br>all real and<br>external sector<br>data categories|Foreign<br>Investment<br>Survey (FIS)<br>conducted and<br>report produced<br>and available<br>on-line|Business<br>register<br>upgraded and<br>updated|Rebased<br>Consumer Price<br>Index (CPI)<br>series produced<br>and available<br>on-line|Rebased<br>Producer Price<br>Index (PPI)<br>series produced<br>and available<br>on-line|Rebased<br>National<br>Accounts<br>produced and<br>report available<br>on-line|Annual|<br>Program<br>Progress<br>Report/<br>SDDS<br>expert|<br>KNBS|\n|<br>**Improve access to**<", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011647", "page": 43, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "KIHBS", "probe_tag": "confusion", "probe_score": 0.12055926024913788, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 186, "end": 191, "key": "fcv_pads_east_africa:011647:43:3:0", "source": "camp2", "luna_reason": "Table cell identifies KIHBS while reporting ongoing fieldwork, not used existing data.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": " investigating<br>COVID-19 that are returned<br>within 72 hours of sample|<br> <br>Quarterly/<br>Annual<br>|Weekly IDSR<br>reports,<br>Periodic<br>Surveillance<br>Reports<br>|Desk review for<br>retrospective data,<br>periodic data collection.<br>|Ministry of Health<br>Integrated<br>Epidemiology, Epidemic<br>preparedness &<br>Response<br>|\n\n\nPage 42 of 55", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020825", "page": 46, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "retrospective data", "probe_tag": "drop", "probe_score": 0.006123184692114592, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 194, "end": 212, "key": "fcv_pads_east_africa:020825:46:1:0", "source": "camp2", "luna_reason": "Planned desk review and periodic collection, not demonstrated use of existing data.", "drop_reason": "promissory", "specificity": "vague"}]}
 {"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008440", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.027876049280166626, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 240, "key": "fcv_pads_east_africa:008440:31:0:0", "source": "camp2", "luna_reason": "Logframe M&E verification source, not existing data used for analysis", "drop_reason": "promissory", "specificity": "named"}, {"text": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.11965898424386978, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 412, "end": 437, "key": "fcv_pads_east_africa:008440:31:0:1", "source": "camp2", "luna_reason": "Named administrative data source listed for program performance indicators.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "also be provided to properly levy, collect and account for local duties and taxes. NaCSA staff would be\ngiven an opportunity to visit Community Driven Development Projects in comparable countries to\ncapitalize on their experiences. Regional and district line ministry staff would be trained in community\nmobilization, conflict resolution, social capital building, and technical appraisal skills.\n\n\n(b) Substantial IEEC activities linked to the various sub-projects are envisaged. These activities\nwould be undertaken using existing IEC materials endorsed by the various line ministries. For example,\nin the case of the rehabilitation of a health post, IEC messages could be envisaged to inform the\npopulation on the proper use of insecticide treated bed nets as a means of preventing malaria.\n\n\n(c) Monitoring and evaluation at the community, district, regional and central levels would be\ngiven high priority, and linked regularly and directly with NaCSA decision making on NSAP policy,\nstrategy and operational matters. These activities would be directly undertaken, or commissioned by,\nstaff of NaCSA's Planning, Monitoring and Evaluation Directorate. The Project Design Matrix (logical\nframework, Annex 1) would form the basis for monitoring NSAP outputs, outcomes and impact. An\nassessment of project status would accompany each NaCSA work program and budget submitted\nsemi-annually to the NaCSA Board. Other M&E activities would include a pre-project Social\nAssessment; establishment of NSAP baseline data (in conjunction with the collection of data for the\nCRRP Implementation Completion Report); social assessments during implementation; annual technical\naudits; beneficiary assessments; incorporation of NaCSA into GOSL's semi-annual public expenditure\ntracking surveys (PETS); and independent impact assessments.\n\n\nIn addition to conventional sub-project monitoring and evaluation (incorporated in the\nsub-project cycle as outlined in the Operations Manual), a pilot participatory monitoring and evaluation\nsystem would be introduced in a representative sample of the predominant types of CDP sub-projects.\nBeneficiary communities would identify quantitative and qualitative indicators", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021266", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NSAP baseline data", "probe_tag": "drop", "probe_score": 0.030066322535276413, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1493, "end": 1511, "key": "fcv_pads_east_africa:021266:36:0:0", "source": "camp2", "luna_reason": "Baseline data establishment is a planned project data-production activity.", "drop_reason": "production", "specificity": "named"}]}
-{"text": "</sup>\n\n\n\nversions of the Global Procurement <sup>Plan and the following year's</sup> <sup>annual</sup> <sup>procurement</sup> <sup>plan.</sup> <sup>Participating</sup>\n\n\n\nService Providers will be required <sup>to</sup> <sup>include</sup> <sup>procurement</sup> <sup>plans in</sup> <sup>their subproject proposals.</sup> <sup>The</sup>\n\n\n\ntechnical team reviewing community <sup>subproject proposals must ensure adequacy of a</sup> <sup>sub-project</sup>\n\n\n\nprocurement plan before the <sup>proposal</sup> <sup>is</sup> <sup>approved.</sup> <sup>Each</sup> <sup>quarter,</sup> <sup>NaCSA will</sup> <sup>submit</sup> <sup>to IDA a</sup>\n\n\n\nprocurement monitoring report <sup>as part of the Financial</sup> <sup>Management Report (FMR),</sup> <sup>to show how</sup> <sup>each</sup>\n\n\n\ncontract on the procurement <sup>plan</sup> <sup>has progressed.</sup> <sup>The POM</sup> <sup>will include</sup> <sup>sample formats</sup> <sup", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012216", "page": 45, "chunk": 6, "split": "holdout_annotate", "spans": [{"text": "procurement monitoring report", "probe_tag": "drop", "probe_score": 0.005396621767431498, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 641, "end": 670, "key": "fcv_pads_east_africa:012216:45:6:0", "source": "camp2", "luna_reason": "Routine procurement monitoring report for project administration.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "\n|18|**% OF CLIENT HOUSEHOLDS REPORTING THAT THEIR**<br>**LIVELIHOOD HAS BENEFITTED FROM PW CREATED ASSETS**|**% OF CLIENT HOUSEHOLDS REPORTING THAT THEIR**<br>**LIVELIHOOD HAS BENEFITTED FROM PW CREATED ASSETS**|||0||\n||RAW DATA<br>SOURCES:||||||\n||COMMENTS||Will be available after midline survey evaluation in Sept 2018|Will be available after midline survey evaluation in Sept 2018|Will be available after midline survey evaluation in Sept 2018|Will be available after midline survey evaluation in Sept 2018|\n|19<br>|**% OF PSNP HHS REPORTING NEW INCOME SOURCE AS A RESULT**<br>**OF PROGRAM SUPPORT - DISAG BY SEX **|**% OF PSNP HHS REPORTING NEW INCOME SOURCE AS A RESULT**<br>**OF PROGRAM SUPPORT - DISAG BY SEX **|||0||\n||RAW DATA<br>SOURCES:||||||\n||COMMENTS<br>|<br>|||||\n|20|**% OF HH THAT SAVE REGULARLY **|**% OF HH THAT SAVE REGULARLY **|885,375|1,135,065|78.0%||\n||RAW DATA<br>SOURCES:||||||\n||COMMENTS||EFY 2010 Annual Report based on savings through MFIs<br>RUSSACOS and VSLA only. Note that during the MTR, it<br>was agreed that PSNP clients may have accounts in more than<br>one financial institution, by tracking savings through each of<br>these accounts may result in double", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017191", "page": 54, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "RAW DATA", "probe_tag": "confusion", "probe_score": 0.11380413174629211, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 221, "end": 229, "key": "fcv_pads_east_africa:017191:54:1:0", "source": "camp2", "luna_reason": "Standalone table header, not a cited or used data resource", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "RAW DATA", "probe_tag": "drop", "probe_score": 0.0430060550570488, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 221, "end": 229, "key": "fcv_pads_east_africa:017191:54:1:1", "source": "camp2", "luna_reason": "Standalone table header, not an independently used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "RAW DATA", "probe_tag": "confusion", "probe_score": 0.18169642984867096, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 221, "end": 229, "key": "fcv_pads_east_africa:017191:54:1:2", "source": "camp2", "luna_reason": "Standalone table header, not an actual data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "*a**</sup> <sup>true</sup> <sup>and</sup> <sup>fair view of</sup>\n\nthe state of affairs of the Project for the financial <sup>year</sup> <sup>**eided**</sup> <sup>on June</sup> <sup>**30, 2025.**</sup>\nThis responsibility includes (i) Maintaining <sup>adequate</sup> <sup>financial</sup> <sup>management</sup> <sup>arrangements</sup> <sup>and</sup>\nensuring that these continue to **be** effective throughout the reporting period, (ii) Maintaining proper\naccounting records, which disclose with reasonable <sup>accuracy</sup> <sup>**at**</sup> <sup>any</sup> <sup>time the</sup> <sup>financial</sup> <sup>position of the</sup>\n\nproject, (iii) Designing, implementing and <sup>maintaining</sup> <sup>internal</sup> <sup>controls</sup> <sup>relevant</sup> <sup>to</sup> <sup>the</sup> <sup>preparation</sup>\nand fair presentation of the financial statement, and ensuring <sup>that</sup> <sup>they</sup> <sup>are</sup> <sup>free<", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000432", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "accounting records", "probe_tag": "drop", "probe_score": 0.026805737987160683, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 455, "end": 473, "key": "fcv_pads_east_africa:000432:20:1:0", "source": "camp2", "luna_reason": "Routine accounting records documenting project financial position, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "During my review, I observed some **inade** acies in the system; however, they are not senrous\n\n\n\nenough to withhold certification. hav detailed these inadequacies in the attachment, and\nincluded an action plan for remedy thsituation that was agreed upon with the Borrower.\n\n\n\nSigned by: _0 1_\nProcurement Specialist _\"_ i **°S** **TQI** 3 _1_ _,L_\nChristi fitAccraiT&~ Date\nProcureme taff, MNSt\n\n\n\n**Part III: Physical Monitorable Indicators and Overall Assessment**\n\nI have reviewed the project's system for monitoring physical implementation progress, including\nits monitorable indicators for major outputs. In my view, the system cannot provide the\nappropriate data on physical progress (PMR-Section 2) required by IDA.\n\nDuring my review, I observed some inadequacies in the system; however, they are not serious\nenough to withhold certification. I have detailed these inadequacies in the attachment, and\nincluded an action plan for remedying the situation that was agreed upon with the Borrower.\n\nSigned by: i A\n### Task Team Leader 1/ 4 -L- UJ 2, dO\n\nQaiser Khan, MNSHD Date\n\n\n**Part** IV: **Concurrence of** LOA for Eligibility of Project for PMR-Based Disbursements\n\n\nI have conducted a reasonable review of the process followed by the Task Team in assessing the\nproject, and I concur with its recommendation that this project is not eligible for PMR-Based\nDisbursements.\n\nSigned by: C____ __a _\nFMS-LOAADO Andrina Ambrose, LOAEL Date\n\n\nT.\n\n\nThu-Ha Nguyen, LOAEL Date", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019780", "page": 55, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on physical progress", "probe_tag": "drop", "probe_score": 0.017835386097431183, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 665, "end": 690, "key": "fcv_pads_east_africa:019780:55:0:0", "source": "camp2", "luna_reason": "States required progress data are unavailable, without analyzing or substituting estimates.", "drop_reason": "availability", "specificity": "vague"}]}
-{"text": "br>Program (Number)|Comments on achieving targets|Comments on achieving targets|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|\n|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|\n|Indicator Name|Baseline|Baseline|Actual (Previous)|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period|Closing Period|\n|Indicator Name|Result|Month/Year|Result|Date|Result|Date|Result|Month/Year|\n|Participating urban board with up-to-<br>date business enterprise database<br>(Percentage)|0.00|Jun/2023|0.00|14-Mar-2025|0.00|14-Mar-2025|50.00|Jun/2028|\n|Participating urban board with up-to-<br>date business enterprise database<br>(Percentage)|Comments on achieving targets|Comments on achieving targets|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|\n|Participating urban boards operating<br>within the county government's", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001991", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "business enterprise database", "probe_tag": "drop", "probe_score": 0.04906463250517845, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 906, "end": 934, "key": "fcv_pads_east_africa:001991:14:2:0", "source": "camp2", "luna_reason": "Indicator-table fragment, not an independently used data resource", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "business enterprise database", "probe_tag": "drop", "probe_score": 0.012327725067734718, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 906, "end": 934, "key": "fcv_pads_east_africa:001991:14:2:1", "source": "camp2", "luna_reason": "Fragment inside an indicator table, not an independently usable data mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021039", "page": 29, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "M&E data", "probe_tag": "drop", "probe_score": 0.02301034703850746, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 530, "end": 538, "key": "fcv_pads_east_africa:021039:29:2:0", "source": "camp2", "luna_reason": "Fragment embedded in an output-indicator table, not an independent data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "**4.2. Robustness checks**\n\n_Cost-of-living differences_\n\nThe consumption aggregates across the TZNPS survey rounds are expressed in 2022 prices\n\n\nusing the World Bank Global Database of Inflation (Ha _et al._ 2021), as discussed earlier (Section\n\n\n2.2). To assess the sensitivity of our results to the approach to standardizing prices – namely the\n\n\ndegree of disaggregation of price adjustments by types of commodities, and by frequency of\n\n\nadjustment – alternative approaches were evaluated. Our preferred models relying on deflating\n\n\nprices using annual inflation at the level of commodity groups – food, utilities, and other non-food\n\n\ncommodities – are compared to models relying on deflation by the traditionally used overall CPI\n\n\ndeflators provided by the International Monetary Fund. <sup>13</sup> [^13: To access the database, visit: https://data.imf.org/?sk=4ffb52b2-3653-409a-b471-d47b46d904b5.] Deflation using the annual CPI\n\n\ndisaggregated by groups is also compared to that using the quarterly CPI between the midpoints\n\n\nof survey rounds (Q1-2009, Q1-2011, Q2-2013, Q2-2015, Q2-2019, Q2-2021, and Q2-2022) and\n\n\nthe monthly CPI (3/2009, 3/2011, 6/2013, 6/2015, 7/2019, 6/2021, 6/2022). <sup>14</sup> [^14: Quarterly and monthly inflation rates for food and energy are not available prior to February 2010. For years 2009–\n2010, annual inflation rates for those sub-aggregates are used.]\n\n\nFigures 3–5 reveal that, across all models and pairs of base-target survey rounds (with a single\n\n\nexception for Model 4 in imputing into TA 1), annual commodity-disaggregated deflation\n\n\nperforms not worse than and frequently better than non-disaggregated deflation. The advantage of\n\n\ncommodity-disaggregated deflation is particularly notable in Models 8-9 when imputing into TA\n\n\n1, Model 8 when imputing into TA 2, and Model 2 when imputing into TA 3.\n\n\nRegarding the frequency of deflation, there appears to be no advantage to going below", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001579", "page": 22, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "World Bank Global Database of Inflation", "probe_tag": "keep", "probe_score": 0.971524715423584, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 157, "end": 196, "key": "prwp:001579:22:0:1", "source": "camp2", "luna_reason": "Named inflation database used to standardize prices and deflate survey consumption aggregates.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The EU-LFS data could not be used for this study as it only has information on the wage distribution**\n\n**in deciles rather than specific point estimates.** This poses a challenge when analyzing the data, as point\n\nestimates are often needed to estimate labor income accurately. To overcome this issue, one option is\n\nto use imputation techniques to fill in the missing values. Specifically, we could use the EUSILC data,\n\nwhich provides detailed demographic characteristics and income information, to impute the missing\n\npoint estimates on the LFS data. This can help provide a more accurate representation of the wage\n\ndistribution and enable a more nuanced analysis. However, it is important to carefully consider the\n\nimputation process's potential biases and limitations and evaluate the quality of the resulting\n\nestimates, especially when several data sources (including administrative tax data) need to be imputed.\n\n\n**In this study, we match income data from the 2020 tax administrative dataset with the 2021 EU-SILC**\n\n**(reference income year 2020) using data matching techniques; then, we assess the degree of tax**\n\n**compliance and possible overestimation of the share of minimum wage earners in the tax data.**\n\nFollowing the literature, we assume that the \"true\" income is reported in the survey, while \"reported\"\n\nincome is reported to the tax authority. After imputing tax income into the EU-SILC, we assess the\n\ndegree of tax evasion and the impact of tax evasion on the share of minimum wage earners.\n\n\n**Before matching the administrative tax data and the EU-SILC datasets, it is essential to carefully**\n\n**evaluate the comparability of the datasets before conducting any analysis.** We must evaluate the\n\ncomparability of the two datasets regarding the target population and income. This involves\n\ndetermining whether the datasets are compatible and suitable for comparison. The extent of\n\ncomparability determines the accuracy of the results and the", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001472", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "LFS data", "probe_tag": "keep", "probe_score": 0.9405447840690613, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 547, "end": 555, "key": "prwp:001472:12:0:2", "source": "camp2", "luna_reason": "Existing labor-force survey data used to impute missing wage point estimates.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "EU-SILC datasets", "probe_tag": "keep", "probe_score": 0.9770495295524597, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1579, "end": 1595, "key": "prwp:001472:12:0:7", "source": "camp2", "luna_reason": "Named EU-SILC datasets are matched and used to assess tax compliance.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " is built out of the school\nquestionnaire from PISA 2012 using the methodology from Anderson [2008]. All specifications include PISA _school_ _final_ _weights_\nand country fixed effects. School controls include school location, student-teacher ratio, log of the number of students, share of\ngovernment funding relative to total school funding, ratio of computers connected to the web as a proxy for school resources,\nand average student socio-economic status. For control variables, missing variables are replaced with a value of -99 and we\ninclude an indicator variable with a value of 1 for each imputed value, for each variable with imputed values dummies are added\nto the specifications.\n\n\nApp. 2", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001847", "page": 54, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "school\nquestionnaire from PISA 2012", "probe_tag": "keep", "probe_score": 0.9596311450004578, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 21, "end": 56, "key": "prwp:001847:54:1:0", "source": "camp2", "luna_reason": "PISA 2012 school questionnaire is used to construct the analysis measure.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "A. Sanghi and D. Johnson\n\n\ndata from 130 countries and explicitly assesses the long-term behavior of income distributions,\ntracking demographic and educational changes over time.\n\n\n**Wealthier** **households** **in** **Sub-Saharan** **Africa** **benefit** **from** **demographic** **changes** **and** **wage**\n**changes across sectors** The wealthiest 40 percent of households will have higher per capita income growth from demographic changes, but the poorest 40 percent of households will see no\nbenefit. The poorest 20 percent of households will experience slower per capita income growth\nwhen demographic changes cause changes in relative wages across sectors. Upper middle income\nhouseholds —those between the 60th and 80th percentile of the income distribution —will gain\nthe most from the wage changes, earning the fastest per capita income growth <sup>8</sup>\n\n\n**Poorer** **households** **are** **hurt** **by** **changes** **in** **food** **to** **non-food** **relative** **prices,** **but** **gain** **overall**\n**from Chinese slowdown and rebalancing** Changes in food to non-food prices leave the poorest\n40 percent of households worse off: per capita income growth is 2.9 percent compared to the 3.07\npercent if China had continued to grow at seven percent. But thanks to greater Chinse consumption, the bottom 40 percent will increase their incomes; the number of people living in extreme\npoverty will fall by an additional 4.04 million people. The Chinese slowdown scenario increases\npoverty initially, but the rebalancing reduces poverty enough for an overall drop", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006646", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data from 130 countries", "probe_tag": "keep", "probe_score": 0.9056505560874939, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 27, "end": 50, "key": "prwp:006646:24:0:0", "source": "camp2", "luna_reason": "Existing country data are used to assess long-term income-distribution behavior.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "on taxpayers in various tax brackets and interpolation using the Pareto distribution. But Piketty\n\n(2003:1007) notes that he could check the reliability of such methods because tax microdata was\n\navailable for later periods, in addition to the tax tables.\n\n\nPiketty’s work stimulated the creation of the World Top Incomes Database (WTID) in 2011, which\n\ncreated top income inequality statistics for 30 countries using similar data to that used in Piketty’s\n\noriginal work (Alvaredo et al., 2016). WTID was later subsumed into the World Inequality Database,\n\nwhich extended WTID to create Distributional National Accounts (DINA). The DINA project aims to\n\nprovide estimates of the distributions of income and wealth that are consistent with national accounts\n\nand harmonized over time and countries (Alvaredo et al. 2016). To do so requires household survey\n\ndata, national accounts data and ideally either tax microdata or aggregated data. And since\n\ncomparisons of these data sources often show that household surveys do under-capture incomes and\n\nwealth, some of the research on measuring the top tail of the income distribution and the challenges\n\nof doing so that we discuss in the next section has come from researchers associated with the DINA\n\nproject directly.\n\n\nThe Extent of Income Inequality\nA reasonable definition of the top tail of the income distribution is the top 10 percent. Using the World\n\nInequality Database (WID) we briefly describe the share of the top 10% of the income distribution,\n\nusing the most recent estimate for each region or country. Across all countries for which there is data,\n\nand excluding extrapolated or interpolated statistics, the share of the top 10% is 47%. It is only 37% in\n\nEurope but is 48% in the US, 56% in Sub-Saharan Africa, 58% in Latin America, 43% in China and 57%\n\nin India. These estimates are from a variety of sources and are of varying quality, but the bottom line\n\nis", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001259", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "World Top Incomes Database", "probe_tag": "keep", "probe_score": 0.9707615971565247, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 304, "end": 330, "key": "prwp:001259:5:0:1", "source": "camp2", "luna_reason": "The sentence describes creation of the database, not use of existing data.", "drop_reason": "production", "specificity": "named"}, {"text": "Distributional National Accounts", "probe_tag": "keep", "probe_score": 0.9753172397613525, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 588, "end": 620, "key": "prwp:001259:5:0:3", "source": "camp2", "luna_reason": "WTID extended to create the accounts; the resource is being generated, not used.", "drop_reason": "production", "specificity": "named"}]}
-{"text": "##### Figures\n\n**Figure 1: Sowing/transplanting and harvesting periods of paddy in**\n\n**<u>Bangladesh</u>**\n\n\n\n\n\n\n\nSource: BBS 2004\n\n\n**<u>Figure 2: Seasonality in borrowing in 1998/99</u>**\n\n\nSource: World Bank-BIDS survey 1998/99\n\n\n32", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006981", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "World Bank-BIDS survey", "probe_tag": "keep", "probe_score": 0.9138402938842773, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 201, "end": 223, "key": "prwp:006981:33:0:0", "source": "camp2", "luna_reason": "Named survey cited as the source for a presented figure.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "Table 2 shows the mean growth rates of external and internal imports before\n\nand after 1993. While several factors beyond AFTA have probably affected trade\n\ngrowth rates in the ASEAN countries (the currency crisis of 1997-1998 being only the\n\nmost prominent one), a few regularities are worth noting. First, intra-AFTA trade\n\ngrows faster than external trade in five of the six original members even in the _pre_ \nagreement period (the only exception being Indonesia). This suggests that the choice\n\nof members was not random, but rather influenced by their growing trade ties. In the\n\npost-agreement period, internal trade growth was faster than external import growth in\n\nall countries, and by a significantly larger margin than it was before 1993.\n\n\nAlthough using aggregate trade data obviously makes the sample very small,\n\nwe can still perform t-tests on the difference in the means of the pre-union and post\nunion growth rates and also between the growth rate of internal trade and trade with\n\nnonmembers. As the results reported in table 2 show, the t-tests of the difference in\n\nthe mean growth rates before and after the agreement are not conclusive. On the other\n\nhand, the difference in the mean growth rates of imports from members and\n\nnonmembers are different enough for Indonesia and the Philippines in the post-AFTA\n\nperiod that the t-test on their difference is statistically significant, despite the very\n\nsmall sample.\n\n\nFurthermore, if increased trade with bloc members displaced imports from\n\nthird countries, we would expect to see a decline in the correlation between internal\n\nand external trade growth subsequent to the formation of AFTA. However, as shown\n\nin the last column of table 2, the correlation between external trade growth and\n\ninternal trade goes up in five out of the six countries—and by a large amount in\n\nThailand and the Philippines. The correlation falls in the post-1993 period only in\n\nBrunei, and the drop was minimal.\n\n\n**IV. The effect of tariffs on", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004155", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "aggregate trade data", "probe_tag": "confusion", "probe_score": 0.6400030255317688, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 768, "end": 788, "key": "prwp:004155:15:0:0", "source": "camp2", "luna_reason": "Aggregate trade data are used for t-tests and reported trade-growth findings.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": " not\nsystematic, we would risk bias in the analysis if we included only the available data.\n\n**We use data for the 2003 to 2017 period, from Eurostat, the Organisation for Economic**\n**Co-operation and Development (OECD), and** **_fDi Markets_** **(Financial Times).** Given our\nempirical goal, and considering data availability constraints, we have collected the largest possible\nset of data at the NUTS-3 level from three main sources to cover the longest possible time period,\nnamely from 2003 to 2017. On economic growth and industrial structure, we use Eurostat data from\nthe _Regio_ database on GDP, population, employment, land area, and sectoral Gross Value Added\n(GVA) – for agriculture, industry (mining; electricity; manufacturing), construction, market\nservices, <sup>13</sup> [^13: Wholesale and retail trade; transport; accommodation and food service activities; information and communication; financial and\ninsurance activities; real estate activities; professional, scientific and technical activities; administrative and support service activities.] and non-market services. <sup>14</sup> [^14: Public administration and defence; compulsory social security; education; human health and social work activities; arts,\nentertainment and recreation; other service activities; activities of household and extra-territorial organisations and bodies.] Missing values in the NUTS-3 level regional series have been\nfilled in by linearly interpolating NUTS-2 level data. On innovation, we use microdata on patents\nfiled under the Patent Co-operation Treaty (PCT) from the _REGPAT_ database provided by the OECD,\naggregated at the NUTS-3 level by priority year and inventor’s residence using the fractional count\ncriterion. On FDI, we use data on inward ‘greenfield’ FDI from the _fDi Markets_ database provided\nby the Financial Times. Of particular interest for our purposes, the _fDi Markets_ database collects\ninformation on individual investment projects in terms of year, destination region at the NUTS-3 (or\ncity) level", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000335", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NUTS-2 level data", "probe_tag": "confusion", "probe_score": 0.14596961438655853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1459, "end": 1476, "key": "prwp:000335:6:1:1", "source": "camp2", "luna_reason": "Existing regional data are used to interpolate missing NUTS-3 values.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "_fDi Markets_ database", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1786, "end": 1808, "key": "prwp:000335:6:1:4", "source": "camp2", "luna_reason": "Named database provides inward greenfield FDI data used in analysis.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": ", similar levels of materials, and less capital and land than rural plants do. There is a\n0.43 correlation between the urban-rural intensity difference and the urbanization rate for labor\nusage; the correlation to materials usage differentials is likewise high at 0.44. Capital intensity\ndifferentials are less correlated at 0.26, and land usage differentials are not correlated with\noverall urbanization levels. <sup>6</sup>\n\n\nThese descriptive tables refine one of the key trends noted in the introduction. Overall,\nmanufacturing activity is becoming more urbanized as measured by employment and plants,\nwhile it is becoming less urbanized as measured by output. These trends are mainly explained by\nthe share of organized and unorganized sectors for each metric and the differences in the\nurbanization trends for these sectors. The details in Tables 2-3b also show that urbanization\nincreases are concentrated, rather than broad-based, even for employment. Only 8 of the 17\nstates and 7 of the 22 industries exhibit an increase in urbanization from 1994-2005. The\n\n\n6 These metrics are developed using data for the year 2000 from the organized sector. We use the year 2000\nto match our district traits taken from the 2001 Census described in Section 4. Several of these variables are not\nconsistently available for unorganized sector. These correlations and our analyses below are robust to winsorizing\nthese industry traits at their 5%/95% values.\n\n\n7", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005431", "page": 8, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data for the year 2000", "probe_tag": "confusion", "probe_score": 0.6895152926445007, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1105, "end": 1127, "key": "prwp:005431:8:1:0", "source": "camp2", "luna_reason": "Existing sector data are used to develop metrics and support correlation analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "Huizinga, Harry and Lars Jonung. 2005. _The Internalization of Asset Ownership in Europe_ .\n(Cambridge Univerity Press).\n\nIwaisako, Tokuo. 2003. “Household Portfolios in Japan.” NBER Working Paper 9647.\n\nJäntti, Markus and Eva Sierminska. 2006. “Wealth Distribution in OECD Countries.” Paper\nprepared for WIDER Project.\n\nJohnson, S., McMillan, J. and Woodruff, C. 2002. ”Property Rights and Finance”. _American_\n_Economic Review_ 92(5): 1335–1356.\n\nKapteyn, Arie and Constantijn Panis. 2003. “The Size and Composition of Wealth Holdings in\nthe United States, Italy, and the Netherlands,” RAND Labor and Population Program Working\nPaper 03-05 (DRU-3002)\n\nKar, Pratip, M.T. Raju and S.P. Batra. 2003. “Survey of Indian Investors.” (Mumbai: Securities\nand Exchange Board of India)\n\nKelly, Morgan. 1995. “All their Eggs in One Basket: Portfolio Diversification of US\nHouseholds.” _Journal of Economic Behavior and Organization_ 27(1): 87-96.\n\nKennickell, Arthur B. 2003. “A Rolling Tide: Changes in the Distribution of Wealth in the U.S.,\n1989-2001” _Levy Economics Institute of Bard College_ Working Paper 393.\n\nKing, Mervyn A., and Jonathan I. Leape, 1998, “Wealth and Portfolio Composition:\nTheory and Evidence.” _Journal of Public Economics_ 69, 155-193.\n\nLevine, Ross. E. 2005. ‘Finance and Growth: Theory, Mechanisms and Evidence’, in Aghion, P.\nand Durlauf, S.N. (eds.). _Handbook of Economic Growth_ . Elsevier.\n\nLi", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003178", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Survey of Indian Investors", "probe_tag": "confusion", "probe_score": 0.24186785519123077, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 700, "end": 726, "key": "prwp:003178:30:0:0", "source": "camp2", "luna_reason": "Bibliographic title in a reference list, not evidence used in the passage.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": " for these tasks. We specified a list of sanitation measures, and asked the Gram\nPanchayat members who was responsible for carrying them out, and whether these were ever\ndone in the village. Tables 1 and 2 summarize this information. To collect the direct\nobservation data, our investigators first constructed detailed maps of the village showing all\nthe roads and paths. They then assessed the condition of each road along the dimensions\ndetailed in Table 3, and noted the characteristics of the inhabitants by the side of that road. In\nparticular they noted the caste and religion of the inhabitants, whether they were GP\nmembers, and whether important village institutions such as schools, health centers, were by\nthe side of the road. Compared with the respondents’ reported perception of whether a task\nwas ever done, the direct observation data give us much more objective information on the\nactual sanitary conditions on the ground.\n\nIn addition to the sanitation outcomes, we have additional village-level information, collected\nin a previous survey conducted the previous year in 2002. This information was collected\nfrom the official census (population, literacy, area), interviews with GP members (whether\nthe village is the GP headquarter and whether the village is the GP president’s village), and\nfrom participatory appraisal methods (the fraction Scheduled Castes/Tribes in the village, the\nfraction land owned by the upper castes, and oligarchy – the extent to which the GP members\ncontrol the important functions in the village.)\n\n**4.** **Analytical Methods**\n\nTo analyze the determinants of information about GP responsibilities we use the village level\ndata. To examine the inter- and intra-village distribution of sanitation outcomes we use the road\nlevel dataset onto which we merged the village level information. Hence, the unit of observation\n\n7 The state-wise break up is AP: 69 villages, KA: 182 villages, KE: 126 wards; TN 129 villages.\n\n\n4", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003998", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "direct\nobservation data", "probe_tag": "confusion", "probe_score": 0.5249890685081482, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 249, "end": 272, "key": "prwp:003998:6:1:0", "source": "camp2", "luna_reason": "Investigators collected and generated the observation data through this exercise.", "drop_reason": "production", "specificity": "vague"}, {"text": "village level\ndata", "probe_tag": "keep", "probe_score": 0.9516411423683167, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1659, "end": 1677, "key": "prwp:003998:6:1:3", "source": "camp2", "luna_reason": "Village-level data are explicitly used as the basis for determinant analysis.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**Annex 1. Respondents to the WB-ASBA Survey**\n\n\n\n\n\n\n\n\n\n\n|Country|Head of<br>Supervision|Head of Research<br>Central Bank|\n|---|---|---|\n|Argentina<br>Bolivia<br>Brazil<br>Colombia<br>Costa Rica<br>Chile<br>Ecuador<br>El Salvador<br>Guatemala<br>Honduras<br>Mexico<br>Nicaragua<br>Panama<br>Paraguay<br>Peru<br>Dominican Republic<br>Uruguay<br>Venezuela<br>Aruba<br>Bahamas<br>Barbados<br>Belize<br>Cayman Islands<br>Haiti<br>Netherland Antilles<br>Suriname<br>Trinidad and Tobago<br>British Virgin Islands<br>Guyana<br>Jamaica<br>Eastern Caribbean Islands|X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X|X <br>X <br>X <br>X <br>X <br>X <br>X <br>X <br>X|\n\n\n\n32", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005116", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "WB-ASBA Survey", "probe_tag": "confusion", "probe_score": 0.08905591815710068, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 30, "end": 44, "key": "prwp:005116:33:0:0", "source": "camp2", "luna_reason": "Survey name appears in an annex table heading listing respondents.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": " budget\nsurveys. Typically, only one price is recorded for each item in each community. A major disadvantage\nof market price surveys is the lack of detailed quality information. Without detailed information about\nitem descriptions, it is not possible to compare prices of the same products across regions. Gibson, Le,\nand Kim (2017) explain that Vietnam’s price survey was carefully designed to record detailed\ninformation for each product.\n\nAs stated earlier, CPI price data are another potential source for spatial price adjustment. Unlike\nmarket price surveys, CPI price data exist in almost all countries (Berry et al. 2019). Since the CPI is\nan indicator of inflation, it does not indicate spatial differentials in costs of living. <sup>10</sup> However, it is\npossible to calculate the spatial price index by using the CPI price data (not CPI values per se). The\nproblem is that many countries collect price information only in urban areas (see Table A2 in Appendix\nA). Nevertheless, if the geographic coverage of the data is adequate, using the same price data for\nspatial and temporal price adjustment can be an efficient approach in terms of the data collection costs,\nand it could also enhance consistency between temporal and spatial price patterns. <sup>11</sup> [^11: Inconsistency in temporal and spatial price movements is not uncommon. Let us consider a spatial price index\nat year 0 (𝑆 **𝑆** 𝑆𝑆𝑡𝑡0) and year 1 (𝑆 **𝑆** 𝑆𝑆𝑡𝑡1). By applying the regional CPIs between _t_ 0 and _t_ 1 to 𝑆 **𝑆** 𝑆𝑆𝑡𝑡0, one can obtain] In addition,\ncompared to market price surveys, a wide variety of food and non-food price information is collected\nin the CPI data, and the data collection is frequent (for example, monthly). A well-known issue is that\nthe basket used for the calculation of the CPI is often skewed toward higher-income households. For\n\n\n\n10 Some countries report", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000539", "page": 8, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "market price surveys", "probe_tag": "confusion", "probe_score": 0.6807094216346741, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 112, "end": 132, "key": "prwp:000539:8:2:0", "source": "camp2", "luna_reason": "Survey data are analyzed for their lack of detailed quality information.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": ">\ncorrelated with satellite-derived indicators that affect the probability of selection of the village\n\ninto the HIES. We therefore adjust the weights based on the predicted probability of the\n\nvillage being sampled in HIES, based on satellite indicators available for all villages (Horvitz\n\nand Thompson, 1952; Wooldridge, 2002). This probability is obtained from the following\n\nprobit model:\n\n\n_INHIESv_ = _α_ + _βlassov_ + _λv,_ (4)\n\n\nwhere _INHIESv_ is a binary indicator for whether village _v_ is sampled into HIES, and _lassov_\n\nrepresents all LASSO-selected variables from the Poisson model. We estimate this model\n\nusing data for all 1,360 villages in the 55 sub-districts. The predicted probability of the\n\nvillage selection into the HIES, _INHIES_ - _v_ is used for correcting the weights in the following\nway : _V illagePopulation X_ <u>1</u> _INHIES_ - _v_ <sup>.</sup>\nUsing these above two sets of weights, we estimate the model in HIES-villages. Then,\n\nwe predict out-of-sample densities for the remaining 946 non-HIES villages and report out\nof-sample accuracy measures by comparing them with the actual census density. To provide\n\nadditional context, we compare the accuracy of this model to predictions from a similar census\nbased model and with density estimates from the publicly available “top-down” population\n\nproducts. Further, we calculate population count predictions by multiplying these density\n\npredictions with village-level area, and report their accuracy with respect to the census pop\nulation.\n\n\n17 Out-of-bag _R_ 2 is an out-of- sample statistic that refers to the average variance explained by the random\nforest predictions, across all villages, when", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007669", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "satellite indicators", "probe_tag": "confusion", "probe_score": 0.6548032164573669, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 234, "end": 254, "key": "prwp:007669:11:1:0", "source": "camp2", "luna_reason": "Existing indicators are used to predict village selection probabilities and adjust survey weights.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "data for all 1,360 villages", "probe_tag": "confusion", "probe_score": 0.7435092926025391, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 630, "end": 657, "key": "prwp:007669:11:1:1", "source": "camp2", "luna_reason": "Existing village data used to estimate the probability model and correct sampling weights.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**Figure 1: Number of Job Listings on Babajob and Average Number of Applciations per Listing by**\n\n|Col1|Col2|Occupational Category, 2015|Col4|\n|---|---|---|---|\n|||||\n|Total number of ads (bar)|||Applicants per ad|\n||Managers<br>Professionals|Clerical support<br>workers<br>Service workers<br>Sales workers<br>Skilled<br>agricultural<br>workers<br>Construction,<br>Craft and related<br>trades workers<br>Plant and<br>machine<br>operators,<br>Assemblers,<br>Drivers<br>Elementary<br>occupations||\n\n\n\nSource: Authors’ calculations using Babajob data\n\n\n**5.** **Using Big Data to Analyze Labor Market Dynamics in India: the Case of Babajob**\n\n\nA review of the existing literature and a thorough analysis of Babajob data revealed five ways in which\n\n\nonline job-portal data can be used to formulate and refine labor market policies. These include (i) labor\n\n\nmarket monitoring and analysis, (ii) assessing demand for workforce skills, (iii) observing job-search\n\n\nbehavior and improving skills matching, (iv) predictive analysis of skills demand, and (v) experimental\n\n\nstudies.\n\n\n**5.1.** **Labor Market Monitoring and Analysis**\n\n\nOnline job-portal data can be used to monitor and analyze labor market trends in real time. Big data can\n\n\ncomplement official government statistics and other traditional forms of employment information-gathering,\n\n\nsuch as sample-based labor force and enterprise surveys, to provide richer and more granular data. Labor\n\n\nforce surveys capture information on the personal characteristics, wages and experience levels of employees", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006962", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "labor force and enterprise surveys", "probe_tag": "confusion", "probe_score": 0.10752123594284058, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1367, "end": 1401, "key": "prwp:006962:9:0:3", "source": "camp2", "luna_reason": "Generic surveys are mentioned as information sources without an attributed finding.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "42 0.1928* 0.1746* 0.1535* 0.1309* 0.0038 1\n<u>9. commodityexporter</u> <u>0.1811*</u> <u>-0.0416</u> <u>-0.2165*</u> <u>-0.1099*</u> <u>-0.0383</u> <u>-0.1039</u> <u>0.2697*</u> <u>-0.0128</u>\n\nPerson’s correlation coefficients are examined using five-year average data. * indicates significance at 5% level.\n\n\n**Annex Table A5-3: Person’s correlations between manufacturing share and determinants**\n\n\n<u>Variables</u> <u>1</u> <u>2</u> <u>3</u> <u>4</u> <u>5</u> <u>6</u> <u>7</u> <u>8</u> <u>9</u> <u>10</u>\n\n\n1. manuf._share 1\n2. ln_hhcredit -0.1755* 1\n3. ln_nfccredit -0.1717* 0.6932* 1\n4. fdi -0.2204* 0.1583* 0.3575* 1\n5. enrolment -0.2897* 0.5140* 0.4168* 0.1911* 1\n6. ln_initialgdppc -0.3214* 0.6438* 0.5748* 0.2056* 0.77", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007067", "page": 26, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "five-year average data", "probe_tag": "confusion", "probe_score": 0.6915453672409058, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 248, "end": 270, "key": "prwp:007067:26:2:0", "source": "camp2", "luna_reason": "Data are used to calculate and examine correlation coefficients.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "22\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Survey|Title in full|Core topics|No. of countries|History|Data collection<br>method|Sample size|Further<br>information on<br>data and access|\n|---|---|---|---|---|---|---|---|\n|MCSS|Multi-Country<br>Survey Study on<br>Health and<br>Responsiveness|Adult health state descriptions,<br>health conditions, screening,<br>health state valuations, health<br>system responsiveness, adult<br>mortality|60 countries of all income<br>levels and worldwide, 35 in<br>HEFPI (postal surveys<br>excluded, several countries to<br>be added)|2000-2001|Face-to-face<br>interviews,<br>telephone<br>interviews,<br>postal survey|Typically<br>600-6,000<br>adults|http://apps.who.i<br>nt/healthinfo/syst<br>ems/surveydata/i<br>ndex.php/catalog/<br>mcss/about|\n|MICS|Multiple <br>Indicator Cluster<br>Survey|Population, health, and<br>nutrition, with a focus on <br>reproductive, maternal and<br>child health|108 LMIC with completed<br>surveys, 89 with available<br>data, 73 in HEFPI (MICS 5 to<br>be added, a number of earlier<br>wave surveys to be added)|Ongoing since<br>1995, first<br>HEFPI data<br>from 1999|", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007497", "page": 23, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "HEFPI", "probe_tag": "confusion", "probe_score": 0.07145678997039795, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 480, "end": 485, "key": "prwp:007497:23:0:0", "source": "camp2", "luna_reason": "Standalone table cell fragment, not an independently cited data resource.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "HEFPI data", "probe_tag": "confusion", "probe_score": 0.12765614688396454, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1089, "end": 1099, "key": "prwp:007497:23:0:2", "source": "camp2", "luna_reason": "Fragment appearing inside a table cell, not an independently used data source.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "The purpose of the study is to examine gender and inclusion differences in education, and to suggest\npolicy actions as well as future analytical and operational work to address these differences.\n### 2. Methodology\n\nThe research design for the study was informed by several sources of data. Data examination of the\nNational Social-economic Household Survey (Susenas), the National Labor Force Survey (Sakernas),\nDapodik, EMIS, and the 2010 Population Census was conducted to collect gender-disaggregated data on\nstudent enrollment rates, and the composition of teacher and administrative staff in the workforce, as\nwell as disability information. This review and analysis of existing data sources allowed for the\nidentification of areas of subnational gender variation in education attainment and other indicators.\n\nSusenas collects data at the household and individual levels on many aspects of social and economic\ncharacteristics, such as: consumption, labor, health and other household variables. Sakernas is a survey\nthat is specifically designed for labor data collection. Both Susenas and Sakernas are nationally\nrepresentative surveys conducted by BPS ( _Biro Pusat Statistik_ /Central Bureau of Statistics) and used by\nthe government for national planning documents. The population census, also conducted by BPS, records\nthe number, composition, distribution, and selected characteristics of the population with national\ncoverage.\n\nAdministrative data used in this study is the MoEC’s Dapodik and the MoRA’s EMIS. Dapodik records selfreported information on: (i) school-level data (public-private, ownership status, establishment date,\naccreditation status, availability of Internet, the number of school facilities and their condition); (ii)\nstudent-level data (sex, learning groups, parents’ information); and (iii) teacher-level data (sex,\nemployment status, certification status, education qualification). EMIS records data on Islamic schools\nunder the Mo", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001690", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Susenas", "probe_tag": "confusion", "probe_score": 0.7237557768821716, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 358, "end": 365, "key": "prwp:001690:6:0:7", "source": "camp2", "luna_reason": "Susenas data were examined to analyze gender-disaggregated education indicators.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "mark>\n<mark>yield vis-à-vis their crop cutting-based counterparts, particularly in the lower half of the plot area</mark>\n<mark>distribution.</mark> <mark>Though our findings contribute to a larger (and renewed) body of literature</mark>\n<mark>questioning the inverse scale-productivity relationship based on omitted explanatory variables or</mark>\n<mark>alternative formulations of the agricultural productivity measures, the analysis, together with</mark>\n<mark>Desiere and Jolliffe (2017), is the first documenting how the IR could be a statistical artifact, driven</mark>\n<mark>by errors in self-reported survey data on crop production.</mark>\n\n\nThe paper is organized as follows. Section 2 discusses the conceptual basis for errors in farmerreported crop production and their potential implications for the IR. Section 3 provides relevant\nbackground on the Ugandan context. Section 4 describes the data. Section 5 lays out the empirical\nstrategy. Section 6 presents the results. Section 7 concludes.\n\n\n**2.** **Conceptual Basis for Potential Errors in Farmer-Reported Crop Production**\n\n\nThe quality of farmer-reported estimates of production is degraded by a myriad of issues,\nsummarized in Table 1. Human performance and behavior are subject to a number of constraints,\none of them being finite memory. Recall bias can, therefore, pose a serious threat to the quality of\nfarmer-reported estimates of production. This is especially relevant if there is partial green harvest\n(for immediate consumption or sale) or if permanent or extended-harvest crops, such as cassava,\n\n\n4", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000209", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "self-reported survey data", "probe_tag": "confusion", "probe_score": 0.8249045610427856, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 595, "end": 620, "key": "prwp:000209:5:1:0", "source": "camp2", "luna_reason": "Survey data are analyzed as causing statistical artifacts in crop productivity measures.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**<u>Variables</u>** **<u>Measures</u>** **<u>Sources</u>**\n**<u>Crisis measure:</u>**\nSignificant drop in stock market returns Basis for the crisis measure is the\npercentage change in US $ national,\ntotal return, stock market indices\nrelative to the previous month. A\nmonth is counted as a crisis month if\nthe total return drops at least 2\nstandard deviations below the sample\nmean. Subsequent months are also\ncounted as crisis months until returns\nmove back into the one standard\ndeviation band around the sample\n<u>mean.</u>\n\n\n\n2 sets of crisis measures: 1) IFC\ninvestable, total return indices,\n2) MSCI total return indices. For\nboth cases, we have to use local\nsources for Romania, Slovakia\nand Romania. To convert returns\nfrom these three national indices\ninto US dollars, we use end of\nperiod data on exchange rates\nfrom the IMF's International\nFinancial Statistics (IFS).\n\n\n\n**<u>Explanatory Variables:</u>**\nUncertainty measure Monthly data of the weighted\naverage of the standard deviations of\nthe current and following year\nforecast of GDP growth across\nsurvey respondents. In January, the\nstandard deviation of the current year\nforecast is given a weight of 11/12\nwhile the standard deviation of the\nfollowing year forecasts is given a\nweight of 1/12. In February, the\ncurrent year forecast receives a\nweight of 10/12 while the follwing\nyear forecast is weighted by 2/12.\nThis scheme continues until\nDecember where a weighting of 0/12\nis given for the current year forecast\nand 12/12 for the following year\nforecast.\n\nMean growth expectations Monthly data of the weighted\naverage of the mean forecast by\nsurvey respondents of the current and\nfollowing year GDP growth. The\nweighting scheme is the same as for\nthe standard deviation.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004188", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "International\nFinancial Statistics", "probe_tag": "keep", "probe_score": 0.9486220479011536, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 838, "end": 872, "key": "prwp:004188:31:0:1", "source": "camp2", "luna_reason": "IMF exchange-rate data are used to convert national stock returns to US dollars.", "usage_type": "evidential", "specificity": "named"}, {"text": "Monthly data", "probe_tag": "confusion", "probe_score": 0.48858898878097534, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 937, "end": 949, "key": "prwp:004188:31:0:3", "source": "camp2", "luna_reason": "Generic data phrase defines a measure without an attributed finding or concrete claim.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "OCHA. 2017. Yemen: 2017 Humanitarian Needs Overview. Report, United Nations Office for\nthe Coordination of Humanitarian Affairs, Sanaa, Yemen.\n\n\nOCHA. 2018. Yemen: 2018 Humanitarian Needs Overview. Report, United Nations Office for\nthe Coordination of Humanitarian Affairs, Sanaa, Yemen.\n\n\nOCHA. 2019a. Yemen: 2019 Humanitarian Needs Overview. Report, United Nations Office\nfor the Coordination of Humanitarian Affairs, Sanaa, Yemen.\n\n\nOCHA. 2019b. Yemen: 2019 Humanitarian Response Plan. Report, United Nations Office for\n\nthe Coordination of Humanitarian Affairs, Sanaa, Yemen. https://reliefweb.int/report/yemen/2019yemen-humanitarian-response-plan-january-december-2019-enar.\n\n\nOCHA. 2020. Yemen: 2020 Humanitarian Needs Overview. Report, United Nations Office for\nthe Coordination of Humanitarian Affairs, Sanaa, Yemen.\n\n\nPeoples’ Dispatch. 2019. “Saudis Retake Aden as Reports of Talks with the Houthis Surface.”\n\nNews Report, Peoples’ Dispatch, October 16, https://peoplesdispatch.org/2019/10/16/saudisretake-aden-as-reports-of-talks-with-the-houthis-surface/.\n\n\nShemyakina, O. 2011. “The Effect of Armed Conflict on Accumulation of Schooling: Results\nfrom Tajikistan.” _Journal of Development Economics_ 95, 186-200.\n\n\nSundberg, R. and E. Melander. 2013. “Introducing the UCDP Georeferenced Event Dataset.”\n_Journal of Peace Research_ 50 (4), 523-532.\n\n\nSwee, E. 2015. “On War and Schooling Attainment: The Case of Bosnia and Herzegovina.”\n_European Journal of Political Economy_ 40, 158-172.\n\n\nTandon, S. and T. Vishwanath. 2019. Potential Famine and the Aid Response", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000036", "page": 26, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UCDP Georeferenced Event Dataset", "probe_tag": "confusion", "probe_score": 0.2773936986923218, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1280, "end": 1312, "key": "prwp:000036:26:0:0", "source": "camp2", "luna_reason": "Bibliographic reference entry, not demonstrated data use in the passage.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": "study their export participation and entry decisions. <sup>10</sup>\n\n\nFinally, we use two alternative measures to proxy for the regulation intensity at\n\nthe product level. First, we use the WTO Specific Trade Concerns (STC) Database,\n\nwhich provides product-level (HS4) information on trade concerns raised in the WTO’s\n\nSPS and TBT committees. The main advantage of this database is that it captures\n\nthe “revealed” stringency of standards, as perceived as important trade barriers by\n\nexporters, rather than counting the number of standards that may or may not be trade\n\nimpeding (Fontagné et al., 2015; Fontagné and Orefice, 2018). We classify products\n\nto be regulation intensive if at least a concern was raised to one of the committees.\n\nThere are 312 specific concerns raised on 124 products in the SPS committee and 317\n\nspecific concerns raised on 848 products in the TBT committee, together covering a\n\nbroad range of 863 products across different industries (see Appendix Table A.4 for the\n\ndistribution of STC-products across industries). Second, we use an alternative measure\n\nof regulation intensity based on prior notice requirements by the United States’ Food\n\nand Drug Administration (FDA). This measure covers a total of 272 HS4-products,\nmainly in food, drugs, and medical devices, which require prior notice to the FDA. <sup>11</sup>\n\n\nTo construct the data set needed for the first part of our analysis (firm-level), we\n\nexpand the initial exporters database to make it squared so that every firm-destination\nyear combination is an observation. For the second part of our analysis using the\n\nproduct-level data, we first aggregate firms’ exports data (available at HS6-level) to the\n\nHS4-level, which is the level available in the WTO STC data set. Then, we expand\n\nthe data set so that each firm-product", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002312", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "product-level data", "probe_tag": "confusion", "probe_score": 0.32981598377227783, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1613, "end": 1631, "key": "prwp:002312:7:0:2", "source": "camp2", "luna_reason": "Existing export data are aggregated for product-level analysis.", "usage_type": "declaration", "specificity": "vague"}]}
-{"text": "**Table 1.** Household censuses and surveys containing employment information in 2001-17.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Note:** ALCS: Afghanistan Living Conditions Survey, EUS: Employment Unemployment Survey, HIES: Household Income and Expenditure Survey, HIES (for\n\nPakistan): Household Integrated Economic Survey, HIICS: Household Integrated Income and Consumption Survey, LFS: Labor Force Survey, NRVA:\nNational Risk and Vulnerability Assessment, NSS: National Sample Survey, PIHS: Pakistan Integrated Household Survey, PSLM: Pakistan Social and\nLiving Standards Measurement. Access to primary data is indicated in **bold** . Surveys placed in between two years were collected in both years, for\nexample, in Afghanistan the NRVA was collected in 2007-08.\n\n\n4", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007672", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Household Integrated Income and Consumption Survey", "probe_tag": "confusion", "probe_score": 0.21675248444080353, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 330, "end": 380, "key": "prwp:007672:5:0:4", "source": "camp2", "luna_reason": "Named household survey identified as a source containing employment information.", "usage_type": "declaration", "specificity": "named"}, {"text": "Labor Force Survey", "probe_tag": "confusion", "probe_score": 0.7156160473823547, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 387, "end": 405, "key": "prwp:007672:5:0:5", "source": "camp2", "luna_reason": "Named survey identified as an employment-information source in the table.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "In addition to improving the measurement of inequality, the new proposed methodology is\n\n\nuseful for assessing the distributional effects of fiscal policies on the income distribution,\n\n\nsince it also allows to recover the full unconditional distribution of income by combining\n\n\nthe conditional distributions observed in the household surveys and in the tax records.\n\n\n17", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006305", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "household surveys", "probe_tag": "confusion", "probe_score": 0.8994653224945068, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 326, "end": 343, "key": "prwp:006305:19:0:0", "source": "camp2", "luna_reason": "Household surveys provide observed distributions used to recover income distribution.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": ".929<br> <br>8.892***<br> <br>Household<br>880<br>0.448|-1.309<br> <br>6.590*<br> <br>Parcel<br>316<br>0.423|-1.449<br> <br>9.253***<br> <br>Parcel<br>316<br>0.454|-0.906<br> <br>8.553***<br> <br>Parcel<br>594<br>0.458|\n\n\n**Notes:** - Sample excludes plots that were subject to full-plot crop cut in MAPS II. † denotes a dummy variable. ***/**/* denote statistical significance at the 1/5/10 percent\nlevel, respectively.\n\n\n51", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000209", "page": 52, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "MAPS II", "probe_tag": "drop", "probe_score": 0.04388388246297836, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 300, "end": 307, "key": "prwp:000209:52:1:0", "source": "camp2", "luna_reason": "Named prior study used to define the sample exclusion criterion.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "D Thesis - The University of North Carol|\n|**Data source**<br>YLS<br>NLSY<br>HILDA<br>ECLS-K<br>**Years**<br>2007 & 2009-2010<br>biannually from 1986-1998<br>2,007<br>fall 1998, spring 1999, fall 1999, spring<br>2000, spring 2002, spring 2004<br>**Sample size**<br>3,725<br>16,650 child-year observations from 6283<br>mothers; sample size for FE ranges from<br>4,159 for child FE to 7919 for sibling FE<br>907 (IV), 430 (mother FE)<br>18,990 person-years for 6,330 indivdiuals<br>**Location**<br>India (state of Andhra Pradesh)<br>US<br>Australia<br>US<br>**Sample restrictions/**<br>**Mother characteristics**<br>Sample restricted to households  in rural<br>areas in both periods<br>**Sample**|**Data source**<br>YLS<br>NLSY<br>HILDA<br>ECLS-K<br>**Years**<br>2007 & 2009-2010<br>biannually from 1986-1998<br>2,007<br>fall 1998, spring 1999, fall 1999, spring<br>2000, spring 2002, spring 2004<br>**Sample size**<br>3,725<br>16,650 child-year observations from 6283<br>mothers; sample size for FE ranges from<br>4,159 for", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001080", "page": 25, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NLSY", "probe_tag": "drop", "probe_score": 0.02192189171910286, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 721, "end": 725, "key": "prwp:001080:25:1:0", "source": "camp2", "luna_reason": "Named survey identified as the study’s data source.", "usage_type": "declaration", "specificity": "named"}, {"text": "HILDA", "probe_tag": "drop", "probe_score": 0.02192189171910286, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 729, "end": 734, "key": "prwp:001080:25:1:1", "source": "camp2", "luna_reason": "Named survey listed as the study's data source.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "<u>Switzerland-Italian</u> <sup>~~2~~</sup> <u>6.8</u> <u>5.3</u> <u>5.4</u>\n\nItaly <sup>2</sup> 4.7 3.4 4.0\n\nChile <sup>1</sup> 9.3 6.9 10.0\n\nNuevo Leon <sup>1</sup> 13.4 11.4 14.8\n\nKorea <sup>2</sup> 7.2 6.5 6.9\n\n**Bermuda** <sup>**2**</sup> 8.3 5.0 5.2\n\n_Mean_ _6.7_ _5.5_ _5.3_\n\n<u>1: Using IALS</u>\n\n\n2. Using ALL\n\n\nThe two sets of estimates (using estimated coefficients β1 and δ1) suggest that the cross-country\n\n\naverage of the component of the return to schooling associated with skills acquired outside school is\n\n\nabout 70-80 percent of the gross return; that is, about 70-80 percent of what the labor market rewards\n\n\nin schooling is its non-literacy component (with the set of estimates associated with estimated\n\n\ncoefficient δ1, on average slightly lower); however, there is significant heterogeneity and a\n\n\ndichotomy between the two subgroups of countries – the educationally advanced and the less\n\n\neducationally advanced.\n\n\nIn Table 2, we divide the 14 countries in two groups of 7 after ranking the countries by average\n\n\nachievement score. We see that there is a strong negative association between country achievement\n\n\nscore and dispersion of score. Chile, Slovenia and Italy rank at the bottom in average score and at the\n\n\ntop in score dispersion; the opposite is the case for countries such as", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005823", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "IALS", "probe_tag": "drop", "probe_score": 0.03376627340912819, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 295, "end": 299, "key": "prwp:005823:15:0:0", "source": "camp2", "luna_reason": "Named survey used for cross-country skills and returns analysis.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " costs for SSN–plus programs, compared to 18 percent of the\ntotal cost for L&J programs, which tend to be more complex, with multiple program components.\n\n**_Component Dosage and Adequacy_** <sup>**_35_**</sup> [^35: Adequacy is calculated as cost ($ 2011 PPP) of a component (e.g., grant size) divided by average annual per capita\nconsumption ($ 2011 PPP) of the bottom 20 percent of households in the relevant country.]\n\n\nThe following analysis explores component dosage and adequacy for those programs that provided\ndisaggregated data on underlying components. The sample of programs varies across different\ninterventions, and components reported by three or fewer programs are not included.\n\nCash grants (for productive investments) are provided more often, of higher value, and in more\ninstallments, in L&J programs than in SSN-plus programs. The average grant size for L&J\nprograms it is $416 (PPP 2011), <sup>36</sup> [^36: This data set excludes the project in Burkina Faso, which, by design, provides a substantially higher grant to youth\nselected through business plan competitions to create small business and microenterprises, rather than for selfemployment.] as compared to $222 (PPP 2011) for SSN–plus programs. Fewer\nSSN–plus programs provide any cash grants to their beneficiaries compared to L&J programs.\nThis may be because L&J programs aim to improve productive outcomes, while SSN-plus\ninitiatives primarily aim to improve consumption and, for a subset of beneficiaries, their productive\noutcomes as well. In addition, L&J programs tend to provide cash grants in two installments, which\n\n\n33 Delivery and staff costs refers to (1) cost of implementing certain components such as savings groups and training,\nand (2) the human resource cost of administering other components such as grants, inputs and cash transfers.\n34 Both government-led and NGO-led programs incur higher delivery-led", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000078", "page": 22, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "disaggregated data", "probe_tag": "drop", "probe_score": 0.044085629284381866, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 519, "end": 537, "key": "prwp:000078:22:1:0", "source": "camp2", "luna_reason": "Analysis uses existing disaggregated component data to examine program adequacy.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**Table A2: UN classification of energy-intensive manufacturing sectors**\n\n\n\n\n\n\n\nSource: UNIDO (2010).\n\n\n**Table A3: Descriptive statistics WBES among sectors with at least one politically connected**\n**firm versus sectors with zero connected firms by types of connection**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Sectors<br>with PC All other<br>CEOs sectors|Sectors<br>with PC All other<br>owners sectors|Sectors<br>with any All other<br>PC firm sectors|\n|---|---|---|---|\n|||||\n|Share of firms acquired Land from Government<br>Share of firms in Industrial City<br>Share of firms with Bank Loan<br>Waiting days for construction permit<br>CoV (waiting days construction permit)|48%<br>37%<br>47%<br>36%<br>21%<br>17%<br>595<br>642<br>0.56<br>0.45|44%<br>33%<br>42%<br>33%<br>19%<br>17%<br>608<br>681<br>0.54<br>0.33|44%<br>30%<br>41%<br>34%<br>19%<br>13%<br>610<br>696<br>0.53<br>0.30|\n\n\nSource: WBES.\n\n\n38", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006410", "page": 39, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "WBES", "probe_tag": "drop", "probe_score": 0.038207631558179855, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 140, "end": 144, "key": "prwp:006410:39:0:0", "source": "camp2", "luna_reason": "Span is part of a table title, so it is a table artifact.", "drop_reason": "table_artifact", "specificity": "named"}, {"text": "WBES", "probe_tag": "confusion", "probe_score": 0.16013450920581818, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 140, "end": 144, "key": "prwp:006410:39:0:1", "source": "camp2", "luna_reason": "Span occurs within a table title, so it is a table artifact.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": "Fifth, misclassification of goods may create huge revenue losses. Low-tax headings should\ntherefore be closely monitored.\n\n\nAgainst this backdrop, a new multipronged strategy is being implemented in Madagascar,\nwith the aim not only of curtailing fraud, but also of facilitating legal trade. A reform strategy\nfor the 2015–2018 period was adopted in September 2014.\n\nSeveral significant reform measures have recently been adopted or are in the process of being\nadopted:\n\n   - A system has been instituted whereby the performance of each customs office will be\nmonitored based on monthly indicators. This should enable better scrutiny of the\nCustoms Authority and make monitoring more effective, thus facilitating trade.\n\n   - The post-clearance audit unit has been reinforced with the recruitment of additional\nauditors, and several major importers have since been audited and have been found to\nhave committed fraud.\n\n   - A new circular has been signed by the Minister of Finance revising the criteria under\nwhich companies are eligible for fast-track customs clearance.\n\n   - Moreover, in the context of the “quick results” approach adopted, the Customs\nAuthority is making every effort to scale back physical inspections, given their\nnegligible impact.\n\n   - Finally, the risk analysis and statistics departments have been reinforced to provide\nmore targeted monitoring.\n\n**VII. Concluding Remarks**\n\nThis paper proposes a simple methodology aiming to identify some risky import operations.\nThe mirror analysis first helps to identify and target products or sectors with the greatest risk.\nAnalysis of declaration patterns (that is, mining of customs data) is then performed to identify\nand target the most high-risk companies. In the specific case of Madagascar, and within the\ncurrent context of customs reform, this paper suggests that there was sizeable fraud in the\nareas of customs valuation and tariff classification in 2014.\n\n\nRecent studies (Yang (2008), Carrillo et al. (2014)) have highlighted that many tax evaders\nrespond to the implementation of corrective measures (such as increased monitoring,\nestablishment of cross-checking systems, etc.)", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006657", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "customs data", "probe_tag": "drop", "probe_score": 0.04230355843901634, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1647, "end": 1659, "key": "prwp:006657:19:0:0", "source": "camp2", "luna_reason": "Customs data are mined to identify and target high-risk companies.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "## WPS6097 Policy Research Working Paper 6097\n\n# Collecting High Frequency Panel Data in Africa Using Mobile Phone Interviews\n\n##### _Kevin Croke_ _Andrew Dabalen_ _Gabriel Demombynes_ _Marcelo Giugale_ _Johannes Hoogeveen_ The World Bank Africa Region Poverty Reduction and Economic Management Unit June 2012", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005268", "page": 0, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "High Frequency Panel Data", "probe_tag": "drop", "probe_score": 0.02230917476117611, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 60, "end": 85, "key": "prwp:005268:0:0:0", "source": "camp2", "luna_reason": "Title describes collecting panel data, a data-production activity.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "Ordered probit,<br>conditional fe logit and<br>re probit|Oredered Probit|Ordered logit|Ordered logit|Ordered probit|Ordered Logit|\n|**Data**|Ad-hoc questionnaire in<br>two villages in Israel|US-GSS 1989-1996|8 countries study 1972-<br>1994|GSOEP 1985-1998|BHPS 1991-2002<br>(Employed)|WVS ( 1980 – 1982,<br>1990 – 1991, and 1995<br>– 1997 waves)|US-GSS 1972-1997|EU Eurobarometer<br>1975-1992|RLMS 1994-2000|Latinobarometro 2004,<br>17 LAM countries|\n|**Study**|Morawetz et al., 1977|Hagerty 2000|Hagerty 2000|Schwarze and Harpfer,<br>2002|Clark, 2003|Helliwell, 2003|Alesina et al. 2004|Alesina et al. 2004|Senik, 2004|Graham and Felton,<br>2006|\n\n\n\n27", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004758", "page": 29, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "US-GSS", "probe_tag": "drop", "probe_score": 0.024692637845873833, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 191, "end": 197, "key": "prwp:004758:29:3:4", "source": "camp2", "luna_reason": "Named survey dataset listed as the data source for the study's analysis.", "usage_type": "evidential", "specificity": "named"}, {"text": "EU Eurobarometer", "probe_tag": "confusion", "probe_score": 0.26732510328292847, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 363, "end": 379, "key": "prwp:004758:29:3:5", "source": "camp2", "luna_reason": "Named Eurobarometer survey series identified as the study's data source.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "<u>Figure 48. Credit Card EACR (household level, LITS)</u>\n\n\nSweden\n\n\nTurkey\n\n\nGreat Britain\n\n\nHungary\n\n\nFrance\n\n\nSlovenia\n\n\nItaly\n\n\nCzech Republic\n\n\nSlovak Republic\n\n\nCroatia\n\n\nGermany\n\n\nLatvia\n\n\nMacedonia\n\n\nAll\n\n\nEstonia\n\n\nMongolia\n\n\nSerbia\n\n\nUkraine\n\n\nMontenegro\n\n\nPoland\n\n\nKosovo\n\n\nAlbania\n\n\nBulgaria\n\n\nBosnia and Herzegovina\n\n\nRomania\n\n\nLithuania\n\n\nBelarus\n\n\nRussian Federation\n\n\nArmenia\n\n\nGeorgia\n\n\nKazakhstan\n\n\nAzerbaijan\n\n\nMoldova\n\n\nTajikistan\n\n\nKyrgyzstan\n\n\nUzbekistan\n\n\n\n\n\n0 10 20 30 40 50 60 70 80 90 100\n\n\nEACR Dissimilarity Coverage\n\n\n35 countries sorted by coverage rates. Coverage rates are labeled\n_<u>Sources</u>_ <u>: LITS</u>\n\n\n50", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006585", "page": 51, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "LITS", "probe_tag": "drop", "probe_score": 0.014063349924981594, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 636, "end": 640, "key": "prwp:006585:51:0:0", "source": "camp2", "luna_reason": "Named LITS source provides data underlying the reported figure and coverage rates.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**Appendix A**\n\n**<u>Table 1</u>** **<u>Characteristics of sample districts</u>**\n\n\n\n|District name|Literacy rate,<br>Census 2001|% population below<br>poverty line|\n|---|---|---|\n|**Karnataka**|||\n|Chikmagalur|73|8|\n|Kolar|63|22|\n|Bellary|58|43|\n|Gulbarga|51|42|\n|**MP**|||\n|Raisen|73|38|\n|Katni|65|27|\n|Guna|60|32|\n|Dhar|53|46|\n|**UP**|||\n|Kanpur rural|67|43|\n|Hathras|63|28|\n|Pratapgarh|59|22|\n|Sitapur|49|37|\n\n\n**<u>Table 2</u>** **<u>Summary of sample school and student characteristics at baseline</u>**\n\n\n\n\n\n|Col1|UP|Col3|Col4|MP|Col6|Col7|Karnataka|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|**Student characteristics**|Treatment|Control|p*|Treatment|Control|p*|Treatments<br>1 and 2|Control|p*|\n|Age|8.69|8.76|.36|8.89|9.01|.08|10|10|.77|\n|Gender (1 if male", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003978", "page": 28, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Census 2001", "probe_tag": "drop", "probe_score": 0.012266057543456554, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 118, "end": 129, "key": "prwp:003978:28:0:0", "source": "camp2", "luna_reason": "Standalone table header identifying a census year, not an independent data-use mention.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": "Swierzbinski, J. E. and Mendelsohn, R. O.: 1989, Exploration and Exhaustible\n\n\nResources: The Microfoundations of Aggregate Models, International Eco\n\nnomic Review 30(1), 175\u001586.\n\n\nToman, M. A. and Jemelkova, B.: 2003, Energy and Economic Development:\n\n\nan Assessment of the State of Knowledge, The Energy Journal (4), 93\u0015112.\n\n\nUmmel, K. and Wheeler, D.: 2008, Desert Power: The Economics of Solar\n\n\nThermal Electricity for Europe, North Africa, and the Middle East, Working\n\n\nPaper 156, Center for Global Development.\n\n\nUSGS: 2009, Minerals Yearbook, U.S. Geological Survey.\n\n\nUSGS: 2011, Mineral Commodity Summaries, U.S. Geological Survey.\n\n\nViebahn, P., Lechon, Y. and Trieb, F.: 2011, The Potential Role of Concen\n\ntrated Solar Power (CSP) in Africa and Europe  - A Dynamic Assessment of\n\n\nTechnology Development, Cost Development and Life Cycle Inventories until\n\n\n2050, Energy Policy 39(8), 4420\u00154430.\n\n\nWadia, C., Alivisatos, A. P. and Kammen, D. M.: 2009, Materials Availability\n\n\nExpands the Opportunity for Large-Scale Photovoltaics Deployment, Envi\n\nronmental Science & Technology 43(6), 2072\u00152077.\n\n\nWilliges, K., Lilliestam, J. and Patt, A.: 2010, Making Concentrated Solar\n\n\nPower Competitive with Coal: the Costs of a European Feed-In Tari\u001b, Energy\n\n\nPolicy 38(6), 3089\u00153097.\n\n\nWise, M., Calvin, K., Thomson, A., Clarke, L., Bond-Lamberty, B., Sands, R.,\n\n\nSmith, S., Janetos, A. and Edmonds, J.:", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006255", "page": 29, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Minerals Yearbook", "probe_tag": "confusion", "probe_score": 0.12045669555664062, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 534, "end": 551, "key": "prwp:006255:29:0:0", "source": "camp2", "luna_reason": "Bibliography entry naming a publication, not data used in the passage.", "drop_reason": "ref_list", "specificity": "named"}, {"text": "Mineral Commodity Summaries", "probe_tag": "drop", "probe_score": 0.04452291876077652, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 591, "end": 618, "key": "prwp:006255:29:0:1", "source": "camp2", "luna_reason": "Bibliographic reference entry, not an in-text data-use mention.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": "**<u>Table 5. Interactions of Business-As-Usual Survey Approach (T1/IHS4) with Individual and Household Attributes</u>**\n\n\n\n**<u>Men</u>**\n\n\n\n**<u>Women</u>**\n\n\n\n**<u>Reported</u>** **<u>Economic</u>** **<u>SDG</u>** **<u>Reported</u>** **<u>Economic</u>** **<u>SDG</u>**\n**Owner** **Owner**\n\n**Exclusive** **Joint** **Exclusive** **Joint** **Exclusive** **Joint** **Exclusive** **Joint**\n**<u>(1)</u>** **<u>(2)</u>** **<u>(3)</u>** **<u>(4)</u>** **<u>(5)</u>** **<u>(6)</u>** **<u>(7)</u>** **<u>(8)</u>** **<u>(9)</u>** **<u>(10)</u>**\nT1/IHS4 <u>0.024</u> <u>0.027</u> <u>0.080*</u> <u>0.085</u> <u>0.018</u> <u", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000484", "page": 26, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "T1/IHS4", "probe_tag": "drop", "probe_score": 0.030604571104049683, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 65, "end": 72, "key": "prwp:000484:26:0:1", "source": "camp2", "luna_reason": "Survey code appears within a table title and header.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": " not\nanticipate a significant negative impact\non wages due to increased competition.\nEnhancing language fluency is one way\nto address occupational downgrading. To\navoid double counting, we estimated that\naround PLN 1 billion has been already\nincluded in the previously estimated gains\nfrom reduced downgrading.\n\n\n\n**A further increase in labour**\n**participation of refugees would**\n**yield significant macroeconomic**\n**benefits.** Although the employment rate\nof Ukrainian refugees in Poland is already\nhigh when compared to other countries,\nthere is still room for improvement.\nIncreasing the employment of refugees by\n15 thousand people, which would close\nhalf of the gap between the employment\nrate of refugees and Poles, would yield at\nleast PLN 1 billion of value added in the\neconomy. This calculation is made under\nan assumption that those newly hired\nwould be paid minimum wage and should\nbe considered a lower-bound estimate, as\nit understates potential benefits. In part,\nthe higher productivity of workers might\nboost the profits for employers, further\nenhanced by increased investment.\n\n\n#### **4.4 Persons not previously in employment**\n\n\n\n**Employment rates among Ukrainian**\n**refugees are exceptionally high, with**\n**only a minority requiring targeted**\n**assistance to enter the labour market,**\n**in particular those who were not**\n**employed before their displacement.**\nIn the SEIS survey, employment rates\namong refugees aged 18-64 previously\nemployed or self-employed in Ukraine, are\n81% and 91% respectively. That is already\nvery high and any further increase would\nbe marginal. On the other hand, those who\nback in Ukraine managed the household\nhave an employment rate in Poland of\n38%. Even before becoming refugees, they\nwould have required support to enter the\nworkforce and now, in the host country,\nthey would be likely to benefit from such\nhelp even more. Some of them may be\ndiscouraged by not having been able", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 17, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "SEIS survey", "probe_tag": "keep", "probe_score": 0.9295, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1400, "end": 1411, "key": "sample:jad_paddy_docs:000001:17:2:0", "source": "gold", "luna_reason": "Named survey provides employment-rate findings for Ukrainian refugees.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\nJust like last year, employment rates demonstrated disparity by age group, gender, education level, the\npresence of a disability, and being in need of MHPSS. Disability was found to be associated with the largest\ndrop in employment, with this factor halving the probability of working in 2024 when compared to the sample\noverall. Having MHPSS needs and being female were also associated with a lower employment likelihood,\nalthough to significantly smaller degrees.\n\n\nCompared to the host population, the refugee sample demonstrated higher employment rates at lower age\nbrackets (15-19 and 20-24), which, considering the findings on poverty, can be interpreted as a coping strategy\nassociated with low income. Higher age brackets (55-59 and 60-64) saw the highest gap in the employment\nrate compared to hosts, supporting the hypothesis that older age individuals have more difficulty integrating\ninto the local labor market.\n\n\n**<u>REGIONAL EMPLOYMENT RATE BY AGE AND POPULATION</u>**\n\n\nRefugees (2023) Refugees (2024) Hosts (2023)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n52%\n\n\n\n\n\n\n\n15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64\n\n\nSource: Survey data, ILO\n\n\n\n**<u>REGIONAL REFUGEE EMPLOYMENT RATE BY POPULATION</u>**\n\n**GROUP (2024)**\n\n\n\n**<u>EMPLOYMENT RATE BY EDUCATION LEVEL</u>**\n\n\nRefugees (2023) Refugees (2024) Hosts (2023)\n\n\n96%\n92%\n86%\n\n\n\nOverall\n\n\nMale\n\n\nFemale\n\n\nWith severe psychological\n\ndistress\n\n\nWith a disability\n\n\nSource: Survey data, SAG estimates\n\n\n\n64%\n\n\n67%\n\n\n63%\n\n\n57%\n\n\n\n72%\n\n\n\n\n\n49%\n\n\n\n\n\n\n\nTechnical or\n\nVocational\n\n\n\nBachelor's Master'", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Survey data, ILO", "probe_tag": "keep", "probe_score": 0.9987, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1238, "end": 1254, "key": "sample:jad_paddy_docs:000010:10:0:0", "source": "gold", "luna_reason": null}, {"text": "SAG estimates", "probe_tag": "keep", "probe_score": 0.9922, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1552, "end": 1565, "key": "sample:jad_paddy_docs:000010:10:0:1", "source": "gold", "luna_reason": "Source-line attribution identifies estimates underlying the presented employment-rate chart.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "including information on targeting, environment and social impacts and the GRM.\n\n**Enhanced Social Assessment and Consultation (ESAC)**\nThe project will conduct consultations to capture the views of disadvantaged and vulnerable members of\nthe community. Due to the Covid-19 pandemic, consultations that were scheduled to take place prior to\nappraisal have been postponed. Phase one social assessment with primary focus on desk review has been\nconducted. Following the lifting of State of Emergency, additional consultations planned to be conducted\nin selected new and old woredas taking into consideration COVID 19 restriction measures.\n\n**Communication materials**\nWritten information will be disclosed to the public through a variety of communications materials,\nincluding brochures, flyers, posters, etc. The communications materials will be produced by the\nFSCD.FSCD will also create a webpage on the Ministry of Agriculture’s website, to be updated regularly\nwith key project updates and reports on the project’s performance. The website will also provide\ninformation about the grievance mechanism for the project’s GRM.\n\n**Information table at the woreda level**\nInformation tables at the Woreda Food Security Desk will provide information to local residents, PAPs and\nstakeholders on SEASN’s project interventions and contact details of the stakeholder engagement focal\npoint. Brochures and fliers on various project related social and environmental issues will be made available\nat these information tables.\n\n**Program Review and Monitoring Surveys**\nFSCD will organize a number of surveys to assess the quality of program implementation. These will\ninclude: Impact Assessments, PW and Livelihoods Review, GRM Reviews, PW impact assessment, and\nGSD and nutrition (see Table 6).\n\n**Grievance Redress Mechanism**\nIn compliance with the World Bank’s ESS10, a project- specific grievance mechanism will be set up for\nthe project to handle complaints and issues (see Chapter 8). Detailed communications materials\n(specifically a GRM brochure or", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013523", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Program Review and Monitoring Surveys", "probe_tag": "drop", "probe_score": 0.047686800360679626, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1519, "end": 1556, "key": "fcv_pads_east_africa:013523:21:0:0", "source": "camp2", "luna_reason": "Surveys will be organized by the project to assess implementation.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020600", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "statistical data", "probe_tag": "drop", "probe_score": 0.040239110589027405, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 379, "end": 395, "key": "fcv_pads_east_africa:020600:16:0:0", "source": "camp2", "luna_reason": "Planning unit generates the statistical data; it is project-produced data.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "|OP 4.12|Kenyan Legislation|Comparison|Recommendation to<br>Address Gap|\n|---|---|---|---|\n|claim to such land or<br>assets—provided<br>that<br>such<br>claims<br>are<br>recognized<br>under<br>the<br>laws of the country or<br>become<br>recognized<br>through<br>a <br>process<br>identified<br>in<br>the<br>resettlement<br>plan<br>(see<br>Annex 10 A, para. 7(f));<br>and19<br>(c) those who have no<br>recognizable legal right<br>or claim to the land they<br>are occupying<br>_To determine eligibility:_<br>Carry out resettlement<br>census. Cut off date for<br>eligibility<br>is<br>the<br>day<br>when the census begins.|‘occupants of land even if<br>they do not have titles’ and<br>payment made in good faith<br>to those occupants of land.<br>However,<br>this<br>does<br>not<br>include those who illegally<br>acquired land<br> <br> <br>Land Act 2012 provides for<br>census<br>through<br>NLC<br>inspection<br>and<br>valuation<br>process<br>|has an obligation to pay<br>in<br>good<br>faith<br>when<br>compulsory acquisition<br>is made.<br> <", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019521", "page": 45, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "census", "probe_tag": "drop", "probe_score": 0.014280598610639572, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 529, "end": 535, "key": "fcv_pads_east_africa:019521:45:0:1", "source": "camp2", "luna_reason": "The recommendation calls for carrying out a future resettlement census.", "drop_reason": "production", "specificity": "vague"}, {"text": "census", "probe_tag": "confusion", "probe_score": 0.6346419453620911, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 529, "end": 535, "key": "fcv_pads_east_africa:019521:45:0:2", "source": "camp2", "luna_reason": "The recommendation plans to carry out a resettlement census.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": " be disaggregated<br>by sex. Citizen engagement is an indicator. Annual targets.<br>The survey for the beneficiary satisfaction has not been done, due to the initial delay in<br>disbursing grants to the CIGs. However, Phases I, II and III of the grants have been disbursed<br>to the CIGs, and the survey is scheduled by February 2026.|This indicator estimates demand-side social accountability through engagement with project<br>beneficiaries and the extent to which project activities and outcomes are meeting<br>beneficiaries' demands. This is based on a perception survey administered to a<br>representative sample of beneficiaries including, VMGs and focus on fisheries and<br>aquaculture management and livelihood diversification. Survey results will be disaggregated<br>by sex. Citizen engagement is an indicator. Annual targets.<br>The survey for the beneficiary satisfaction has not been done, due to the initial delay in<br>disbursing grants to the CIGs. However, Phases I, II and III of the grants have been disbursed<br>to the CIGs, and the survey is scheduled by February 2026.|This indicator estimates demand-side social accountability through engagement with project<br>beneficiaries and the extent to which project activities and outcomes are meeting<br>beneficiaries' demands. This is based on a perception survey administered to a<br>representative sample of beneficiaries including, VMGs and focus on fisheries and<br>aquaculture management and livelihood diversification. Survey results will be disaggregated<br>by sex. Citizen engagement is an indicator. Annual targets.<br>The survey for the beneficiary satisfaction has not been done, due to the initial delay in<br>disbursing grants to the CIGs. However, Phases I, II and III of the grants", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000382", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey for the beneficiary satisfaction", "probe_tag": "drop", "probe_score": 0.04104848578572273, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 843, "end": 882, "key": "fcv_pads_east_africa:000382:5:1:1", "source": "camp2", "luna_reason": "The beneficiary satisfaction survey has not been conducted and remains scheduled for the future.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Not Applicable\n\n\n**Procurement of Second Hand Goods** as specified under paragraph 5.11 of\nthe Procurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables: Not Applicable\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** .\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables\n\n\n**Other** **_Relevant Procurement Information._**\n\n\n_None_", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002007", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.03880133852362633, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 258, "end": 281, "key": "fcv_pads_east_africa:002007:1:0:0", "source": "camp2", "luna_reason": "Routine procurement planning tables, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019177", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.027876049280166626, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 240, "key": "fcv_pads_east_africa:019177:31:0:0", "source": "camp2", "luna_reason": "Logframe verification data, not an already analyzed data use.", "drop_reason": "promissory", "specificity": "named"}, {"text": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1188, "end": 1214, "key": "fcv_pads_east_africa:019177:31:0:2", "source": "camp2", "luna_reason": "Listed as planned indicator verification data, not shown as already analyzed or used.", "drop_reason": "promissory", "specificity": "named"}]}
+{"text": "**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Not Applicable\n\n\n**Procurement of Second Hand Goods** as specified under paragraph 5.11 of\nthe Procurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables: Not Applicable\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** .\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables\n\n\n**Other** **_Relevant Procurement Information._**\n\n\n_None_", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012143", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.03880133852362633, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 258, "end": 281, "key": "fcv_pads_east_africa:012143:1:0:0", "source": "camp2", "luna_reason": "Procurement planning tables are routine administrative paperwork, not substantive data use.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "|Col1|c) Ensure that transaction level budget monitoring system is<br>strengthened at all implementing entities; maintain in excel<br>spread sheet,<br>d) Provide specific explanation for major budget variances by<br>component and implementing entities.<br>e) Consider supplementary budget if actual expenditure<br>exceeds proclaimed budget|d) As part of 3rd quarter IFR<br>e) June 30, 2024|d) PIU/MinT<br>e) PIU/MInT|\n|---|---|---|---|\n||**_Accounting_**<br>a) Share project FM manual to MoF<br>b) Consider incorporating segment reporting representing<br>implementing entity into the Peachtree chart of account to<br>facilitate identification of expenditures and balances of by<br>project implementing entities.<br>|<br>a) Immediate<br>b) Immediate|<br>a) PIU/MInT<br>b) PIU/MInT<br> <br>|\n||**_Internal control_**<br>a) Perform bank reconciliation monthly at MoF<br>b) All payment supporting documents to be marked as<br>“PAID”<br>c) Update fixed asset register to include newly acquired asset<br>and complete missing key information<br>d) Follow up receivable balances focusing on balances aged<br>b/n six months to one year for timely settlement. Follow<br>up supplier advance guarantees for timely renewal.<br>e) Follow up on travel advance for timely settlement.<br>f) <br>Reconcile<br>the<br>difference<br>b/n<br>", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002366", "page": 23, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "fixed asset register", "probe_tag": "drop", "probe_score": 0.0314788892865181, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 942, "end": 962, "key": "fcv_pads_east_africa:002366:23:0:0", "source": "camp2", "luna_reason": "Routine fixed-asset bookkeeping record, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": " environmental impacts of this urban improvement project are less substantial,\nEIAs and/or EMPs will be prepared for all sub-projects, and a screening process will be\nfollowed to ensure no sub-projects are located in the immediate vicinity of Nairobi\nNational Park or any other National Parks in the NMR. Sub-projects that would involve\ndestruction of the limited forest cover in the NMR will be excluded from NaMSIP.\nWhile assistance on resettlement and environmental plans will be provided by existing\nlocal authorities/counties, the MoNMD and particularly local authorities/county\nenvironmental and social officers will require substantial help and additional training to\nundertake the socio-economic surveys, censuses, and Resettlement Action Plans that will\nbe necessary under NaMSIP. This can be achieved through additional MoNMD staff or\nexternal consultants (the former being the preferred option). Cut-off dates will be\nestablished as soon as project sites are definitively selected and the censuses are ready to\ncommence.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014908", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "censuses", "probe_tag": "drop", "probe_score": 0.04782126098871231, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 713, "end": 721, "key": "fcv_pads_east_africa:014908:4:1:1", "source": "camp2", "luna_reason": "Censuses are planned to be undertaken under the project.", "drop_reason": "production", "specificity": "vague"}, {"text": "censuses", "probe_tag": "confusion", "probe_score": 0.10172291845083237, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 713, "end": 721, "key": "fcv_pads_east_africa:014908:4:1:2", "source": "camp2", "luna_reason": "Censuses are planned for future resettlement work and have not yet been conducted.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": " for baseline in 56 cities<br>(especially new cities and<br>cities that have not used<br>consultancy) on asset<br>management, asset<br>inventories baseline and for<br>revenue enhancement<br>strategies, plans and<br>implementation<br>|IDA / D2770||Post|Quality And Cost-<br>Based Selection|Open - International<br>||250,000.00|0.00|Pending<br>Implementation|2018-05-10||2018-05-31||2018-07-14||||2018-08-11||2018-09-10||2018-10-15||2018-11-19||2019-04-18||\n|ET-MUDH-60160-CS-QCBS /<br>computerized comprehensive<br>municipal revenue file<br>management and data base<br>formation<br>|IDA / D2770||Prior|Quality And Cost-<br>Based Selection|Open - International<br>||1,500,000.00|1,611,730.75|Signed|2018-06-08|2019-06-21|2018-06-29|2019-07-16|2018-08-12|2020-02-11|||2018-09-09|2020-03-27|2018-10-09|2020-06-29|2018-11-13|2020-11-16|2018-12-18|2020-12-01|2020-06-10||\n|ET-MUDH-56602-CS-QCBS /<br>Strategic TA/Studies - Gender<br>(ULGs gender audit, ULGs<", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018029", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "municipal revenue file", "probe_tag": "drop", "probe_score": 0.00476381229236722, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 514, "end": 536, "key": "fcv_pads_east_africa:018029:4:1:0", "source": "camp2", "luna_reason": "Fragment from a procurement table entry, not evidence of revenue data use.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "could match 275 to the 1928 census.\n\n\n**4.1.3** **Integration outcomes of refugees**\n\n\nI measure the integration of refugees by examining different generations of refugees: (i) those\n\n\nborn in turkey who were forcibly resettled in Greece at a different age (ii) those born in Greece to\n\n\nrefugee parents, i.e. the second-generation.\n\n\n**First-generation** I measure the socio-economic integration of first-generation refugees by compar\n\ning the educational attainment of refugees displaced at a different age, i.e., either when adults\n\n\n(above 15) or when children (below 15). I rely on the 1928 census to obtain the literacy rate of\n\n\nrefugees at arrival, and focus on those older than 15 years in 1923. To measure the socio-economic\n\n\noutcomes of refugees at a later period, I unfortunately cannot draw on population censuses as no\n\n\ninformation on country of birth is available. The earliest census to provide this information is the\n\n2001 census and I use the 10 percent extract provided by IPUMS. <sup>19</sup> I identify as refugees the 3,486\n\n\nsampled individuals born in Turkey between 1908 and 1922, who represent about 9% of the pop\n\nulation born in the same period. Reassuringly, the share of individuals born in Turkey drops to\n\n\nless than 2% among cohorts born after 1922, while the share of foreign-born (in other countries\n\n\nthan Turkey) remains stable across cohorts and start increasing only after the 1950s (see Figure\n\n\nA.1 in the appendix). The 2001 census also allows to construct the rate of intermarriage between\n\n\nrefugees and natives. Among the 2,102 refugee women in the sample, 293 report to be married\n\n\nwith a currently co-residing husband - the other women being mostly widowed. When the hus\n\nband belongs to the surveyed household, I can identify mixed refugee-native couple", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001815", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "1928 census", "probe_tag": "keep", "probe_score": 0.9533177614212036, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 23, "end": 34, "key": "prwp:001815:14:0:0", "source": "camp2", "luna_reason": "Census data provide refugees’ literacy rates at arrival.", "usage_type": "evidential", "specificity": "named"}, {"text": "population censuses", "probe_tag": "keep", "probe_score": 0.9599789381027222, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 808, "end": 827, "key": "prwp:001815:14:0:1", "source": "camp2", "luna_reason": "Census data absence motivates use of the later 2001 census.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": " on indicators for each country, with Malawi as the base case, along with an indicator equal to 1 if the\nhousehold was located in an urban area, as opposed to a rural area. Data come from the most recent round of phone\nsurvey data available. This is round 3 in Ethiopia and Nigeria, round 2 in Malawi, and round 1 in Uganda. Robust\nstandard errors are reported in parentheses (*** p<0.01, ** p<0.05, * p<0.10).\n\n\n\nRelied on\n\n\n\nSale of\n\n<u>Assets</u>\n\n\n\nFood\n<u>Consumption</u>\n\n\n\nReduced\nNon-Food\n<u>Consumption</u>\n\n\n\n<u>Saving</u>\n\n\n\n51", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002105", "page": 52, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "phone\nsurvey data", "probe_tag": "keep", "probe_score": 0.9333711862564087, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 213, "end": 230, "key": "prwp:002105:52:3:0", "source": "camp2", "luna_reason": "Existing phone survey rounds are declared as the source for reported indicators.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000171", "page": 51, "chunk": 202, "split": "holdout_annotate", "spans": [{"text": "data from CIESIN", "probe_tag": "keep", "probe_score": 0.946039080619812, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1, "end": 17, "key": "prwp:000171:51:202:0", "source": "camp2", "luna_reason": "CIESIN data underpin authors’ analysis of infant mortality rates.", "usage_type": "evidential", "specificity": "named"}, {"text": "data from CIESIN", "probe_tag": "keep", "probe_score": 0.946039080619812, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1, "end": 17, "key": "prwp:000171:51:494:0", "source": "camp2", "luna_reason": "CIESIN data underpin authors’ analysis of infant mortality rates.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "the Indonesian Classification of Occupation 1982 that is used in the Sakernas.</mark>\nIn this process we mapped 899 occupations from the 914 occupation that were originally in the\nO*Net database. Using the ISCO 2008 we identify the same six occupational groups we identify\nin the STEP survey and that can be match to the Sakernas survey: <mark>administrative and managerial</mark>\n<mark>workers; professionals and technicians; clerical workers; sales and services workers; agriculture,</mark>\n<mark>animal husbandry, forestry workers, fishermen and hunters; and production workers, transport and</mark>\n<mark>equipment operators, and laborers.</mark>\n\n\n55", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000535", "page": 56, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "O*Net database", "probe_tag": "confusion", "probe_score": 0.793269157409668, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 180, "end": 194, "key": "prwp:000535:56:2:0", "source": "camp2", "luna_reason": "Database occupations were mapped to support occupational classification analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**Figure** **2:** **Variation** **in** **correlation** **between** **wealth** **and** **pollution** **across** **countries–**\n**Panel a** plots the coefficients from country-level regressions of pollution measured as the average\nover the sample estimated against RWI. The unit of observation is a grid-cell within a country.\ngrid-cells are weighted by the inverse of the reported error in the RWI data. Grey spikes indicate\nthe 99% CI. The inset ( **Panel** **d** ) shows how the coefficients change when using the raw PM2 _._ 5\ndata (diamonds) versus the PM2 _._ 5 data with dust and sea salt removed (squares). **Panel** **b**\nmaps the coefficients from the same regression using raw PM2 _._ 5 data and **Panel** **c** maps the\nsame using data from the dust and sea salt removed PM2 _._ 5 data. The general pattern is robust to\ndefining pollution based on median and highest monthly exposure. In the maps the coefficients\nare bottom and top coded to -4, 4 respectively.\n\n\n8", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001241", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "raw PM2 _._ 5 data", "probe_tag": "confusion", "probe_score": 0.37515559792518616, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 682, "end": 700, "key": "prwp:001241:9:0:2", "source": "camp2", "luna_reason": "Raw PM2.5 data are used in regressions mapping pollution coefficients.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " A5 in the Appendix that confirm the robustness of these\n\n\nresults to the inclusion of market baseline controls or keeping randomization strata alone.\n\n\n**IV.2.1** **What** **did** **facilities** **invest** **in?**\n\n\nOne concern is that, in the absence of data on health outcomes, improvements in the JHIC score\n\n\ncould have been cosmetic with little likelihood of affecting downstream outcomes. As Section 3\n\n\nof the [Supplemental](https://www.dropbox.com/s/ygw3z4q98cmsd6i/KePSIE_Supplemental_Material.pdf?raw=1) Material shows, several checklist items could be fulfilled simply by printing\n\n\n18", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000910", "page": 19, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data on health outcomes", "probe_tag": "confusion", "probe_score": 0.34328600764274597, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 256, "end": 279, "key": "prwp:000910:19:2:0", "source": "camp2", "luna_reason": "States data absence without presenting analysis or substitute estimates.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": "farmers. <sup>16</sup> [^16: In the pre-treatment survey, only 31 farmers accurately reported their plot size; this increases to 125 in the posttreatment survey .] Of those who over- (under-)estimated initially, 76 (48) percent still over- (under-)\n\nestimated post-treatment.\n\n\n**Table 5: Information-induced changes in reporting behavior (treatment group plots only)**\n\n\n\nSR: SR: SR: number of\n\n<u>Post-planting reporting behavior</u> <u>Overestimate</u> <u>Underestimate</u> <u>Accurate</u> <u>observations</u>\n\nSR: Overestimated 76.0 15.5 8.5 647\nSR: Underestimate 36.5 48.4 15.1 304\n<u>SR: Accurate</u> <u>22.6</u> <u>0.00</u> <u>77.4</u> <u>31</u>\n<u>Total number of observations</u> <u>610</u> <u>247</u> <u>125</u>\n**<u>Notes:</u>** <u>Values are shares or percentage of plots over(under)-estimated across the post-planting and post-harvest rounds.</u>\n\n\n\n<u>Post-planting reporting behavior</u>\n\n\n\n<u>Post-harvest reporting behavior</u> <u>Total</u>\nSR: SR: SR: number of\n<u>Overestimate</u> <u>Underestimate</u> <u>Accurate</u> <u>observations</u>\n\n\n\nSR:\n<u>Underestimate</u>\n\n\n\nSecond, the response of farmers to accurate information appears highly asymmetric. Those\n\nwho overestimated their plot size pre-treatment", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001922", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "pre-treatment survey", "probe_tag": "confusion", "probe_score": 0.3757077753543854, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 36, "end": 56, "key": "prwp:001922:20:0:0", "source": "camp2", "luna_reason": "Pre-treatment survey provides reported plot-size findings with observed counts.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "coverage that allows obtaining results in 4 of the 5 regions, in which the national territory is divided:\nAtlantic, Eastern, Central, Pacific and finally the capital cities of departments of the Amazon and Orinoco.\nAdditionally, the survey is representative of the 32 capital cities of the country's departments and the\nfollowing 6 prioritized municipalities: Rionegro, Soledad, San Andres de Tumaco, Barrancabermeja,\nBuenaventura, and Yumbo.\n\n**_Administrative Data_**\n\n\nAdditional information was required to complement the household survey information. Some of the\nsources used in the development of the model are the following <sup>28</sup> [^28: For more information on the administrative data used in each section see the annexes in Nuñez et, al. (2019).] : (i) DIAN administrative data: Amount\nin returns for each of the income types and exempt income; (ii) Utilities Information System; (iii) Energy\nand gas rate bulletins; (iv) Investment Project monitoring system; (v) School Meals Program Report for\nJanuary-December 2017; (vi) The information available in the Pension Fund; (vii) Local Fiscal Account; (viii)\nInformation from the General System of Transfers; (ix) Resolution 6411 of 2016; (x) The tax statute in\nforce in 2017 which is Law 1819 of December 29, 2016; (xi) The 2010 input-output matrix on 2005 basis <sup>29</sup> [^29: In this version of the document, the 2010 input-output matrix was used since that for 2015 had not yet been published by DANE.] ;\n(xii) The matching between the products of the ENPH, the CPC 2.0 and the national accounts; and (xiii)\nThe reference prices of alcoholic beverages and tobacco products for the year 2017.\n\n###### ii. Methodology\n\nFor the incidence analysis of each one of the fiscal interventions, and the impact on poverty and inequality\nof each one of the taxes", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002179", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "DIAN administrative data", "probe_tag": "confusion", "probe_score": 0.8701078295707703, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 768, "end": 792, "key": "prwp:002179:15:0:0", "source": "camp2", "luna_reason": "Named administrative data source used to develop the fiscal incidence model.", "usage_type": "declaration", "specificity": "named"}, {"text": "Local Fiscal Account", "probe_tag": "confusion", "probe_score": 0.7834675908088684, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1092, "end": 1112, "key": "prwp:002179:15:0:5", "source": "camp2", "luna_reason": "Named administrative source listed among data used to develop the model.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "#### ONLINE APPENDICES **A Additional Figures and Tables**\n\nFigure A.1: Test of differential pre-trends in under-5 mortality by firstborn sex separately for boys\nand girls\n\n\nNOTES: This figure tests for parallel trends in under-5 mortality by firstborn sex during the pre-ultrasound\nperiod (1973-1984) for male and female births of parity _>_ 1. The graphs plot the coefficients of the _First_ _girl_\nx _Year_ indicator variables (and the 95% confidence intervals) from the regression of under-5 mortality on the\nfull set of interactions between indicators for _First_ _girl_ and _Year_, without other controls, for girls in the top\nfigure and for boys in the bottom figure. The omitted year is 1973. Data: NFHS.\n\n\n47", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001935", "page": 49, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NFHS", "probe_tag": "confusion", "probe_score": 0.7179062366485596, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 707, "end": 711, "key": "prwp:001935:49:0:0", "source": "camp2", "luna_reason": "NFHS data underpin the figure testing mortality pre-trends.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "Gunasekera et al., 2015; Rentschler and Salhab, 2020; Ward et al., 2020). Gross Domes\ntic Product (GDP) is a critical economic indicator in the measurement and monitoring of\n\nan economy in a country that is typically only available at national and occasionally sub\nnational levels. Regional indicators play a key role in the necessary variation to forecast\n\nregional GDP (Lehmann and Wohlrabe, 2015) and food security (Andree et al., 2020). Pre\nvious efforts to estimate local GDP use high resolution spatial auxiliary information such as\n\nluminosity or population data to provide local variation. Methods by Kummu, Taka, and\n\nGuillaume (2018), Murakami and Yamagata (2019), Nordhaus (2006), and World Bank and\n\nUNEP (2011) took advantage of gridded population data, which is the result of a model\n\ndisaggregating the most detailed level population data into grids (e.g. see review in Leyk et\n\nal., 2019). However, wealth is not evenly distributed among people nor infrastructure (Berg,\n\nBlankespoor, and Selod, 2018). In fact, the divide between the rich and poor is even widening\n\nin our time (Dabla-Norris et al., 2015). The method used in World Bank and UNEP (2011)\n\nstratify the population by rural and urban, yet definition of these geographic areas can vary\n\nbased on the selection of the population model (Leyk et al., 2019). These measurements\n\nmatter in application to stylized facts such as the strong negative correlation of the level of\n\nurbanization with the size of its agricultural sector (Roberts et al., 2017). Also, the uniform\n\ndistribution of labor in agriculture is another key concern (Gollin, Lagakos, and Waugh,\n\n2014). Other methods used land cover such as vegetation and built-up indices, however did\n\nnot incorporate", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000596", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "gridded population data", "probe_tag": "confusion", "probe_score": 0.6356279850006104, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 742, "end": 765, "key": "prwp:000596:4:0:1", "source": "camp2", "luna_reason": "Existing modeled population data were used to provide local GDP variation.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " which\nenables us to study the heterogeneity of implications of school closures for mobility across different parts of\nthe world. Second, unlike Neidhofer et al. (2021), which is based on pre-pandemic survey data and relies on\nassumptions of pandemic learning modalities based on policies deployed by different countries and certain\nhousehold characteristics, we are able to draw from some observed data from the World Bank’s high-frequency\nphone surveys on what types of learning (if any) children from different types of households are reported to\nhave engaged in during periods of school closures, and the latest learning-loss simulation scenarios from\nAzevedo et al (2022) which now include observed actual school closure data from the <u>[UNESCO school](https://en.unesco.org/covid19/educationresponse#durationschoolclosures)</u>\n<u>[closures tracker.](https://en.unesco.org/covid19/educationresponse#durationschoolclosures)</u>\n\n\nThe main findings of the paper are that the learning losses associated with the extensive school closures around\nthe world due to COVID-19 are likely to translate into economically significant reductions in both absolute\nand relative educational mobility across generations. We estimate that in high-income and in upper middleincome countries the average share of children with more years of education than their parents would decline\nby 8-9 percentage points, with smaller average declines estimated for low-income countries. The results imply\nthat the impact of the learning losses associated with the pandemic would worsen the pre-existing trend of\ndeclining absolute mobility in Upper-Middle Income (henceforth, UMIC) and High-Income (HIC) groups of\ncountries, and reverse the improvements in absolute mobility for Low-Income (LIC) and Lower-Middle\nIncome (LMIC) country groups. <sup>3</", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001124", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "pre-pandemic survey data", "probe_tag": "confusion", "probe_score": 0.7916110157966614, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 188, "end": 212, "key": "prwp:001124:4:1:0", "source": "camp2", "luna_reason": "Existing survey data is identified as the basis of a cited study.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " school closures, partial closures<br>are assumed to affect 85% of the student population.<br>|Schools assumed to be closed uniformly for 5 months<br>in a 10-month school year.<br>|\n|School closure assumptions:<br>Pessimistic|Observed country-level school closures, partial closures<br>are treated as full closures.|Schools assumed to be closed uniformly for 7 months<br>in a 10-month school year.|\n|<br>School closure assumptions:<br>Very Pessimistic|<br>N/A|<br>Schools assumed to be closed uniformly for 9 months<br>in a 10-month school year.|\n\n\n\n15 We impute missing values for share of school system closed by using the regional average by income level for countries with\nlearning data (LAYS, LP, or PISA). The countries are: Belarus; Burundi; the Democratic Republic of Congo; the Republic of Congo;\nthe Arab Republic of Egypt; Hong Kong SAR, China; the Islamic Republic of Iran; the Republic of Korea; Kosovo; Macao SAR,\nChina; Micronesia, Fed Sts.; Nauru; St Kitts and Nevis; St Lucia; St Vincent and the Grenadines; Tajikistan; and the Repbulci of\nYemen.\n\n\n6", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000989", "page": 7, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "LP", "probe_tag": "drop", "probe_score": 0.03130940720438957, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 698, "end": 700, "key": "prwp:000989:7:3:2", "source": "camp2", "luna_reason": "Acronym alone names no eligible data resource or independent source.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": "**Table A.4.2: Comparing weighted Internet Survey data with GMD for the model variables, Arab**\n\n|Col1|Republic|of Egypt|Col4|Col5|\n|---|---|---|---|---|\n||GMD|RIWI-wave1|RIWI-wave2|RIWI-wave3|\n|Age between 15 and 24|31.71%|30.00%|35.13%|43.59%|\n||(29.91,33.51)|(25.40,34.60)|(27.64,42.63)|(33.30,53.88)|\n|Age between 25 and 54|51.93%|52.14%|56.92%|52.95%|\n||(47.53,56.32)|(35.02,69.27)|(38.75,75.09)|(44.16,61.74)|\n|Age between 55 and 100|16.36%|17.86%|7.95%|3.46%|\n||(10.45,22.27)|(0.25,35.47)|(-3.89,19.78)|(-4.77,11.69)|\n|Female|49.25%|51.31%|43.23%|44.87%|\n||(47.95,50.55)|(40.75,61.87)|(34.20,52.26)|(23.39,66.35)|\n|Urban|66.15%|72.91%|72.10%|72.82%|\n||(", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000811", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "weighted Internet Survey data", "probe_tag": "confusion", "probe_score": 0.6280109882354736, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 25, "end": 54, "key": "prwp:000811:33:0:0", "source": "camp2", "luna_reason": "Span is part of a table title/header, not an independent data mention.", "drop_reason": "table_artifact", "specificity": "descriptive"}, {"text": "RIWI-wave3", "probe_tag": "drop", "probe_score": 0.018777554854750633, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 182, "end": 192, "key": "prwp:000811:33:0:1", "source": "camp2", "luna_reason": "Standalone table column header fragment.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": "Jain, M., P. Mondal, G. L. Galford, G. Fiske, and R. S. DeFries (2017a), “An automated approach to map\n\nwinter cropped area of smallholder farms across large scales using MODIS imagery.” _Remote_ _Sensing_, 9,\n566, URL `https://doi.org/10.3390/rs9060566` .\n\n\nJain, M., P. Mondal, G. L. Galford, G. Fiske, and R. S. DeFries (2017b), “India annual winter cropped area,\n\n2001-2016.” URL `https://doi.org/10.7927/H47D2S3W` .\n\n\nMerfeld, Joshua D (2019), “Spatially heterogeneous effects of a public works program.” _Journal_ _of_ _Develop-_\n\n_ment_ _Economics_, 136, 151–167.\n\n\nModanesi, Sara, Christian Massari, Stefania Camici, Luca Brocca, and Giriraj Amarnath (2019), “Perfor\nmance of a drought standardized soil moisture index based on ESA CCI Soil Moisture product: validation\nin India using crop data.” In _Geophysical_ _Research_ _Abstracts_, volume 21.\n\n\nMukherjee, Abhijit, Dipankar Saha, Charles F Harvey, Richard G Taylor, Kazi Matin Ahmed, and Soumen\ndra N Bhanja (2015), “Groundwater systems of the Indian sub-continent.” _Journal_ _of_ _Hydrology:_ _Regional_\n_Studies_, 4, 1–14.\n\n\nMuralidharan, Karthik, Paul Niehaus, and Sandip Sukhtankar (2016), “Building state capacity: Evidence\n\nfrom biometric smartcards in India.” _American_ _Economic_", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001627", "page": 28, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "crop data", "probe_tag": "drop", "probe_score": 0.019311251118779182, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 793, "end": 802, "key": "prwp:001627:28:0:0", "source": "camp2", "luna_reason": "Generic phrase within a bibliography entry, not an independently used data source.", "drop_reason": "ref_list", "specificity": "vague"}]}
+{"text": " 19<br>20 − 99<br>100+<br>Keep formal account|\n|0<br>20<br>40<br>60<br>80 100<br>Burkina Faso (2015)<br>1 − 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Keep formal account (SYSCOA)|0<br>20<br>40<br>60<br>80 100<br>Cameroon (2008)<br>1 − 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Tax registeration|0<br>20<br>40<br>60<br>80 100<br>Ghana (2013)<br>1 − 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Tax registeration|0<br>20<br>40<br>60<br>80 100<br>Rwanda (2013)<br>1 − 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Tax registeration|\n\n\n\n52", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000985", "page": 53, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Tax registeration", "probe_tag": "drop", "probe_score": 0.00491316057741642, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 281, "end": 298, "key": "prwp:000985:53:1:0", "source": "camp2", "luna_reason": "Standalone chart label, not an independently cited or used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "Tax registeration", "probe_tag": "drop", "probe_score": 0.005379773676395416, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 281, "end": 298, "key": "prwp:000985:53:1:1", "source": "camp2", "luna_reason": "Standalone chart category, not a cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": ">Stocktaking of Global Forced Displacement Data.</mark>_ <mark>Policy Research working paper,</mark>\n<mark>no. WPS 7985; Policy Research Working Paper; No. 7985. World Bank, Washington, DC. ©</mark>\n<mark>[World Bank. URL: https://openknowledge.worldbank.org/handle/10986/26183](https://openknowledge.worldbank.org/handle/10986/26183)</mark> <mark>License: CC BY</mark>\n<mark>3.0 IGO.</mark>\n\n\nSingh, N. S., et al. (2021). _Research in forced displacement: guidance for a feminist and decolonial_\n_approach._ [The Lancet, 397(10274), 560-562. URL: https://doi.org/10.1016/ S0140-](https://doi.org/10.1016/S0140-6736%0x2821%0x2900024-6)\n<u>[6736(21)00024-6](https://doi.org/10.1016/S0140-6736%0x2821%0x2900024-6)</u>\n\n\nShemyakina, O. (2011). The effect of armed conflict on accumulation of schooling: Results from\nTajikistan. Journal of Development Economics, 95(2), 186-200. URL:\n<u>[https://www.sciencedirect.com/science/article/abs/pii/S0304387810000441](https://www.sciencedirect.com/science/article/abs/pii/S0304387810000441)", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000892", "page": 22, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Global Forced Displacement Data", "probe_tag": "drop", "probe_score": 0.043537214398384094, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 16, "end": 47, "key": "prwp:000892:22:1:0", "source": "camp2", "luna_reason": "Standalone publication title in a bibliography entry", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": "**Table A.12:** Effects on Self-Reported Bureaucratic Knowledge\n\n\n<u>Training</u> <u>Village Law</u> <u>Knowledge index</u>\n\n\n(1) (2) (3)\n\n\nNew village head -0.089 0.019 0.088\n(0.117) (0.107) (0.119)\n\n\nObservations 1067 1065 1065\nControl mean 0.61 0.76 0.12\n\n\nRobust p-value 0.313 0.886 0.391\nMSE-opt. bandwidth 19.1 17.8 28.4\nEffective obs. 500 476 662\n\n\n_Notes_ : This table reports RD estimates of _γ_ in equation (1) obtained via the non-parametric method from Calonico et al.\n(2014). Units of observation are bureaucrats in all columns. The dependent variable is: in column 1, a dummy equal to 1 if\nthe bureaucrat received any training in the past 12 months; in column 2, a dummy equal to 1 if the bureaucrat reports being\ninformed about Village Law regulations; in column 3, a standardized index of self-reported knowledge across 5 topics:\ndevelopment management & accountability, financial management, village regulations, drafting development plans, and\nthe Village Law. See Section 4 for details.\n\n- p _<_ 0.1, ** p _<_ 0.05, *** p _<_ 0.01. Robust bias-corrected standard errors clustered by village in parentheses.\n\n\n**Table A.13:** Effects on Village Transfers and Budgets\n\n\n**Administrative data** **Village head survey**\n\n\nVillage Funds: <u>Allocated</u> <u>Utilized</u> <u>% Spent</u> <u>Fully Spent</u> <u>Budget</u", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001457", "page": 54, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Administrative data", "probe_tag": "drop", "probe_score": 0.022985924035310745, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1189, "end": 1208, "key": "prwp:001457:54:0:0", "source": "camp2", "luna_reason": "Standalone table header naming an administrative data source.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " to 9; higher scores indicate greater protection against<br>noncommunicable diseases. Data are for individuals ≥15 years of age from the 2021 Gallup World Poll for<br>2022<br>|World Gallup Poll<br>(GDQP) / Food systems<br>dashboard<br>|\n|**NCD-Risk** score among adults ≥ 15<br>|NCD-Risk scores are on a scale of 0 to 9; higher scores indicate greater risk for noncommunicable diseases.<br>Data are for individuals ≥15 years of age from the 2021 Gallup World Poll for 2022<br>|World Gallup Poll<br>(GDQP) / Food systems<br>dashboard<br>|\n|Prevalence of**overweight & obesity** <br>among women (20 - 49 years) %<br>|Percentage of women 20–49 years of age with a BMI greater than or equal to 25 kg/m2 in 2016<br>|UNICEF Global Database<br>(based on NCD-RisC)<br>|\n|Prevalence of**underweight** among<br>women (20 - 49 years) %<br>|Percentage of women 20–49 years of age with a BMI less than 18.5 kg/m2 in 2016<br>|UNICEF Global Database<br>(based on NCD-RisC)|\n|Adult**diabetes**prevalence<br>|Proportion of adults aged 18+ years with diabetes. Diabetes is defined as having a fasting glucose of 7.0<br>mmol/L or higher, being on medication for raised blood glucose, or having a past diagnosis of diabetes. Data<br>for 2014, except 1 country 2003, 1 country 2005, 2 countries 2010, 1 country 2012", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001312", "page": 33, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NCD-RisC", "probe_tag": "confusion", "probe_score": 0.08230678737163544, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 747, "end": 755, "key": "prwp:001312:33:1:3", "source": "camp2", "luna_reason": "Named source underlying the reported overweight and obesity prevalence indicator.", "usage_type": "evidential", "specificity": "named"}, {"text": "NCD-RisC", "probe_tag": "drop", "probe_score": 0.013517764396965504, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 747, "end": 755, "key": "prwp:001312:33:1:4", "source": "camp2", "luna_reason": "Named risk-factor dataset underlying the reported obesity prevalence indicator.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "---|\n||Sentinel-5P<br> <br>|Sentinel-5P<br> <br>|Sentinel-5P<br> <br>|Google Traffic|Google Traffic|\n||CAMS-3<br>|<br>Aerosol<br>Prediction<br>|NO2<br>Prediction<br>|<br>CAMS-3<br>|<br>Prediction<br>|\n|N <br>|<br>362<br>|<br>434<br>|<br>406<br>|<br>34<br>|<br>93<br>|\n|<br>min<br>|<br>11<br>|<br>13<br>|<br>14<br>|<br>14<br>|<br>21<br>|\n|<br>p10<br>|<br>22<br>|<br>25<br>|<br>25<br>|<br>23<br>|<br>23<br>|\n|<br>p25<br>|<br>35<br>|<br>31<br>|<br>31<br>|<br>31<br>|<br>26<br>|\n|<br>p50<br>|<br>55<br>|<br>43<br>|<br>44<br>|<br>84<br>|<br>36<br>|\n|<br>p75<br>|<br>87<br>|<br>70<br>|<br>70<br>|<br>125<", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000489", "page": 15, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Google Traffic", "probe_tag": "drop", "probe_score": 0.03810717910528183, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 70, "end": 84, "key": "prwp:000489:15:1:4", "source": "camp2", "luna_reason": "Standalone table header naming a traffic data source.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": "br>**Location**<br>India (state of Andhra Pradesh)<br>US<br>Australia<br>US<br>**Sample restrictions/**<br>**Mother characteristics**<br>Sample restricted to households  in rural<br>areas in both periods<br>**Sample**|**Data source**<br>YLS<br>NLSY<br>HILDA<br>ECLS-K<br>**Years**<br>2007 & 2009-2010<br>biannually from 1986-1998<br>2,007<br>fall 1998, spring 1999, fall 1999, spring<br>2000, spring 2002, spring 2004<br>**Sample size**<br>3,725<br>16,650 child-year observations from 6283<br>mothers; sample size for FE ranges from<br>4,159 for child FE to 7919 for sibling FE<br>907 (IV), 430 (mother FE)<br>18,990 person-years for 6,330 indivdiuals<br>**Location**<br>India (state of Andhra Pradesh)<br>US<br>Australia<br>US<br>**Sample restrictions/**<br>**Mother characteristics**<br>Sample restricted to households  in rural<br>areas in both periods<br>**Sample**|**Data source**<br>YLS<br>NLSY<br>HILDA<br>ECLS-K<br>**Years**<br>2007 & 2009-2010<br>biannually from 1986-1998<br>2,007<br>fall 1998,", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001080", "page": 25, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "YLS", "probe_tag": "drop", "probe_score": 0.012573227286338806, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 237, "end": 240, "key": "prwp:001080:25:3:0", "source": "camp2", "luna_reason": "Survey name appears as a standalone table cell under Data source.", "drop_reason": "table_artifact", "specificity": "named"}, {"text": "HILDA", "probe_tag": "drop", "probe_score": 0.012573227286338806, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 252, "end": 257, "key": "prwp:001080:25:3:2", "source": "camp2", "luna_reason": "Named survey listed as the study's data source.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "M. Regulatory substance- quality of supply index for the Philippines and comparators, 2015\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Colombia|Peru|Philippines|Vietnam|International<br>benchmark|\n|---|---|---|---|---|---|\n|**Quality Regulation**<br>|100%|100%|92%|71%|75%|\n|<br>**Quality of Service Standards**|100%|100%|100%|75%|82%|\n|<br>Requirement to meet quality of service standards<br>|||||100%|\n|Specific quality of service standards are formally<br>written and publicly available for- quality of the<br>product, quality of the service and customer<br>service|||||97%|\n|Performance on quality of service standards is<br>public<br>|||||71%|\n|Fines for failing to meet quality of service<br>standards<br>|||||59%|\n|**Quality of Service Enforcement**|100%|100%|83%|67%|68%|\n|<br>Requirement to report technical data on a<br>periodic basis|||||100%|\n|<br>Regulator specifies how to collect technical<br>performance data|||||71%|\n|<br>Regulator reviews or validates technical<br>performance data|||||47%|\n|<br>Automated information management systems<br>are required to measure the quality or reliability<br>of the power supply|||||71%|\n|Measurements of the quality or reliability of<br>power supply are made public|||", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001786", "page": 69, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "performance data", "probe_tag": "drop", "probe_score": 0.007020060438662767, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 883, "end": 899, "key": "prwp:001786:69:0:1", "source": "camp2", "luna_reason": "Standalone table row fragment, not an independently used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "sup>9</sup> . This figure is almost double that of host country nationals (12%), implying a\nlarge gap in economic vulnerability. Compared to 2023, poverty rates have decreased substantially (from\n36% <sup>10</sup> ), suggesting an overall improvement in the economic well-being of Ukrainian refugees over time.\n\n\n**<u>REFUGEE VERSUS HOST POVERTY RATES BY COUNTRY</u>**\n\n\nUkrainian refugees (2024) Host country nationals (2023)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Hungary Moldova Poland Romania Slovakia Estonia Latvia Lithuania Region\n\n\nNote: Poverty rates for all countries apart from the Republic of Moldova are based on a calculation that follows Eurostat’s at-risk-of-poverty (AROP)\nmethodology with the at-risk-of-poverty threshold set at 50% of the national median disposable income after social transfers. Refugee disposable\nincome has been computed based on survey data. For the Republic of Moldova, the poverty threshold was taken to be the 4Q23 absolute poverty line\nreported by the National Bureau of Statistics of Moldova.\n\n\nSource: Survey data, <u>[Eurostat,](https://ec.europa.eu/eurostat)</u> <u>[National Bureau of Statistics of Moldova, SAG estimates](https://statistica.gov.md/en)</u>\n\n\n7. The MSNA, which ran in 7 countries: Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and Slovakia\n8. Equivalized as per <u>[Eurostat methodology. Essentially income per person, but with household members beyond the first one](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Equivalised_income)</u>\nassigned weights less than", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9577, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 872, "end": 883, "key": "sample:jad_paddy_docs:000010:3:1:0", "source": "gold", "luna_reason": "Survey data underlies the computed refugee disposable-income measure.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "\nand accommodation type. All interviews were conducted face to face. As a probabilistic selection of\nrespondents could not be ensured, the primary goal was to collect a diverse sample that would reflect the\npopulation’s composition as closely as possible.\n\n\nFor the regional analysis, weights were applied based on the most up-to-date estimates of the number of\nrefugees staying in each country. This allowed calculated indicators to more accurately represent the broader\nrefugee population across the region.\n\n\nAppropriate measures were implemented to ensure the protection of personal data and to guarantee\nconfidentiality in all data collection and processing activities. Consent was requested and recorded for all\nselected participants, providing clear information on the purpose, and expected use of the data.\n\n\nWith the exception of Republic of Moldova, the poverty line for each country was defined as 50% of the median\n<u>[equivalized disposable income (after social transfers) as reported by](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Equivalised_disposable_income)</u> <u>[Eurostat for 2023. This figure was indexed](https://ec.europa.eu/eurostat)</u>\ntowards 2024 using national annual wage inflation data for the third quarter of 2024. As the Republic of\nMoldova does not currently run the SILC survey, the absolute poverty line as reported by the country’s National\nBureau of Statistics was used instead. Host poverty rates were based on the same poverty threshold. With the\nexcept of Republic of Moldova, these were equal to the at-risk-of-poverty (AROP) rate reported by Eurostat. On\n\n\n**14**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "national annual wage inflation data", "probe_tag": "keep", "probe_score": 0.9279, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1215, "end": 1250, "key": "sample:jad_paddy_docs:000010:13:1:0", "source": "gold", "luna_reason": null}, {"text": "SILC survey", "probe_tag": "keep", "probe_score": 0.9283, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1336, "end": 1347, "key": "sample:jad_paddy_docs:000010:13:1:1", "source": "gold", "luna_reason": null}]}
 {"text": ".\nRegionally, the Ukraine refugee NEET rate tends to\nincrease with age, as it becomes more affected by\nunemployment, which is high for the 15 – 24 cohort\n(at 17%).\n\n\n\nOther\n\n\nNo longer\n\nemployed\n\n\nConstruction\n\n\nEducation\n\n\nAdministrative\n\nand\nsupport\n\nservice\nactivities\n\n\n\n16 Likely to be a bit overstated, as the survey did not inquire about activities of 15-year-olds outside of school enrollment. Also,\nsome respondents were not asked about distance learning in Moldova\n\n17 [Reference indicators were taken from the OECD dataset for 2022 with the exception of Moldova, where 2023](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm) <u>[data reported by](https://statistica.gov.md/en/youth-neet-in-the-republic-of-moldova-for-the-second-9430_60713.html)</u>\n<u>[the national statistics office](https://statistica.gov.md/en/youth-neet-in-the-republic-of-moldova-for-the-second-9430_60713.html)</u> was used\n\n\n**8**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "OECD dataset", "probe_tag": "keep", "probe_score": 0.9945, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 521, "end": 533, "key": "sample:jad_paddy_docs:000000:7:1:0", "source": "gold", "luna_reason": "OECD dataset supplied reference indicators used in the analysis.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": ",\npharmacists (0.01%), and psychologists\n(0.09%), compared to the following shares\nfor Polish citizens: 0.26%, 0.19%, and 0.18%,\nrespectively.\n\n\n\n**One of the most effective forms**\n**of support offered to refugees**\n**and other immigrants in terms of**\n**employment and earnings to be found**\n**in the literature is language training.**\nFoged et al. (2024) analysed labour market\noutcomes of language training, placement\nin strong labour markets, active labour\nmarket policies, cutting welfare benefits,\nand placement in co-ethnic networks that\nwere directed at refugees in Denmark.\nThanks to unusually detailed Danish data,\nthey could follow individual refugees who\narrived in Denmark between 1987 and\n2008, for at least 10 years, and in most\ncases for 15 years. They found intensive\nlanguage training introduced in 1999 to be\nthe most effective of all policies, accounting\nfor a 5-6 pp. increase in the probability of\nemployment and a USD 3,000 increase\nin annual earnings (2015 figures). While\nlocating refugees in strong labour markets\nalso had considerable positive effects,\nthe report found only some evidence that\nActive Labour Market Policies (ALMPs)\nfocused on matching refugees with deficit\noccupations improved their employment\nprospects and no evidence of positive\neffects of cutting benefits or placing\nrefugees in co-ethnic networks. Heller\nand Mumma (2023) exploited randomized\nenrolment lotteries for a publicly-funded", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 15, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "Danish data", "probe_tag": "keep", "probe_score": 0.9788, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 613, "end": 624, "key": "sample:jad_paddy_docs:000001:15:4:0", "source": "gold", "luna_reason": "Detailed Danish data supports employment and earnings findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>REGIONAL REFUGEE EMPLOYMENT RATE BY LEVEL OF</u>**\n\n**LOCAL LANGUAGE KNOWLEDGE (2024)**\n\n\nEmployment rate Share of the refugee population (rhs)\n\n\n\n80%\n\n\n60%\n\n\n40%\n\n\n20%\n\n\n0%\n\n\n\n<u>35%</u>\n\n\n\nDoes not\nunderstand\n\n\n\nBeginner Intermediate Advanced Fluent\n\n\n\nSource: Survey data\n\n\nThe 2024 survey introduced a new question on local language proficiency, reinforcing previous findings of a\nstrong correlation between language skills and employment. Respondents with at least an intermediate level of\nlocal language proficiency reported nearly twice the employment rate compared to those with no knowledge\n(9% of respondents). Even Ukrainians with only a basic understanding—limited to a few words or phrases (28%\nof the sample)—experienced a notable increase in employment compared to those with no local language\nskills <sup>16</sup> [^16: The data also demonstrates that the employment rate of refugees fluent in the local language is lower than for those with\nan intermediate or advanced knowledge. The reason for this is that the former group is heavily concentrated in lower age\nbrackets, with almost 30% being 15-19 years old] .\n\n\nFinally, unlike for the host population, refugee employment rates were found to be practically the same for all\neducation levels above technical or vocational <sup>17</sup>, implying that local employment markets may not be valuing\nadvanced degrees. Possible explanations include impediments to foreign qualifications recognition and other\nbarriers that are preventing placement into high-skilled jobs (such as language, a mismatch between\nqualifications and local demand, etc.).\n\n\n**Wages also improved but remain significantly below host levels**\n\n\nDespite a 28% increase in the regional weighted average wage of refugees in 2024, this figure still stands 30%\nlower than that of the local population. This means that, on average, Ukrainians earned roughly two-thirds of\nwhat their hosts did", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 11, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Survey data", "probe_tag": "keep", "probe_score": 0.999, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 376, "end": 387, "key": "sample:jad_paddy_docs:000010:11:0:0", "source": "gold", "luna_reason": null}, {"text": "2024 survey", "probe_tag": "keep", "probe_score": 0.9953, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 394, "end": 405, "key": "sample:jad_paddy_docs:000010:11:0:1", "source": "gold", "luna_reason": "Survey findings support reported employment and language-proficiency relationships.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>SHARE OF POPULATION PAYING FOR RENTED HOUSING: HOSTS VS REFUGEES</u>**\n\n\nShare of hosts living in rented housing (2023) Share of refugees fully paying for rent (2024) Share of refugees partially paying for rent (2024)\n\n\n100%\n\n\n80%\n\n\n60%\n\n\n40%\n\n\n20%\n\n\n0%\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\nSource: Eurostat, survey data, SAG estimates\n\n\n**<u>HOUSING COST AS A SHARE OF HOUSEHOLD DISPOSABLE INCOME</u>**\n\n\nRefugees (2024) Hosts (2022)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\nSource: Eurostat, survey data, SAG estimates\n\n\n**<u>REFUGEE POVERTY RATES WITH AND WITHOUT CORRECTION FOR EXCESSIVE HOUSING COSTS</u>**\n\n\nRefugees (2024) Refugees with housing expense correction (2024) Hosts (2023)\n\n\n\n65%\n\n\n\n40%\n\n\n\n52%\n\n\n\n\n\n\n\n\n\n\n\n31%\n\n\n\n\n\n46%\n43%\n37%\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Hungary Moldova Poland Romania Slovakia Estonia Latvia Lithuania Region\n\n\nSource: Eurostat, survey data, SAG estimates\n\n\n**6**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9968, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 476, "end": 487, "key": "sample:jad_paddy_docs:000010:5:0:0", "source": "gold", "luna_reason": null}]}
-{"text": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**Republic of Moldova: the case for housing costs corrections in income-based poverty metrics**\n\n\nData from the Republic of Moldova highlights the limitations of poverty metrics that rely solely on disposable\nincome, as they fail to account for vulnerability related to asset ownership. Based on income alone, the 2024\npoverty rate suggests that Ukrainian refugees are able to attain a higher standard of living than their hosts, with\nonly 10% living in poverty compared to 32% of Moldovans. This apparent disparity is largely driven by the\nsizeable financial support that Ukrainians received from humanitarian organizations in 2024, which amounted\nto 44% of their total household income. While the above comparison could suggest that the provided aid is\nexcessive, such an interpretation overlooks an important factor – namely that only 5% of Moldovans incur rental\nexpenses compare to 41% of refugees. In fact, including utilities, housing costs were estimated to consume 46%\nof refugees’ disposable income (inclusive of humanitarian aid), whereas they account for just 14% for Moldovan\nhouseholds. In essence, these findings indicate that refugees are using the entirety of their aid to cover\naccommodation needs. Adjusting disposable income at the household level to reflect these additional housing\nexpenses raises the poverty rate for refugees to 43%, surpassing that of Moldovans.\n\n\n**Poverty is associated with tangibly inferior living conditions, worse healthcare coverage,**\n**more frequently children being out of school, and having to skip meals**\n\n\nRefugee households with members living in poverty were found to more often not report feeling safe when\nwalking alone in their neighborhood after dark (18% vs 10% for those not at risk), to significantly more frequently\nlive in collective housing (27% vs 8%), and to feel under pressure to leave their accommodation (29% vs 11%", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data from the Republic of Moldova", "probe_tag": "keep", "probe_score": 0.943, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 206, "end": 239, "key": "sample:jad_paddy_docs:000010:6:0:0", "source": "gold", "luna_reason": null}]}
-{"text": ". <sup>11</sup> [^11: According to the social security data until 30th September 2023.]\nWhile public data does not distinguish\nbetween refugees entering these sectors\nand pre-2022 Ukrainian workers changing\njobs, it is largely consistent with the MSNA\nPoland 2023 survey, in which the most\nrefugees are employed in manufacturing\n(14%), accommodation and food service\n(12%), and trade and repair (6%).\n\n\nUkrainian refugee households in Poland\n\nto the MSNA Poland 2023 survey, 20% of\nUkrainian refugee households earn less\nthan 3 000 PLN, 41% earn between 3 000\nand 6 000 PLN, and 12% earn more than\n6 000 PLN, while 27% of respondents\npreferred not to answer. That said, the\nstandard of living of Ukrainian refugees\nmay be significantly lower than that of\nnative residents, even at similar incomes,\ndue to their lack of housing, which in\nPoland is usually occupant-owned.\n\n\n\n**Inflow of Ukrainian refugees into**\n**Poland**\nThe beginning of the full-scale war in\nUkraine in February 2022 resulted in large\nflows of refugees, reaching more than\n6 million globally. <sup>3</sup> [^3: As of December 2023, according to UNHCR, based on governmental sources <u>[Situation Ukraine Refugee Situation (unhcr.org)](https://data.unhcr.org/en/situations/ukraine)</u>] Much of this exodus\nhappened through the Polish border.\nAs of October 2023, almost 1 million\nUkrainian refugees were living in Poland <sup>4</sup> [^4: According to the active PESEL UKR database.]\n(Chapter 1). In the past decade, Poland\nexperienced large labour migration from\nUkraine. The number of workers with\nUkrainian citizenship that registered for\nsocial security (this data does not include\nthose working in the shadow economy\nor some minor cases that do not require\nregistration) grew from just 33 thousand interm", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "social security data", "probe_tag": "keep", "probe_score": 0.9995, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 39, "end": 59, "key": "sample:jad_paddy_docs:000007:3:1:0", "source": "gold", "luna_reason": "Existing social security data are cited as the source for labor-market claims.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "MSNA Poland 2023 survey", "probe_tag": "keep", "probe_score": 0.9955, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 450, "end": 473, "key": "sample:jad_paddy_docs:000007:3:1:1", "source": "gold", "luna_reason": null}, {"text": "PESEL UKR database", "probe_tag": "keep", "probe_score": 0.9866, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1432, "end": 1450, "key": "sample:jad_paddy_docs:000007:3:1:2", "source": "gold", "luna_reason": null}]}
-{"text": "-union-statistics-on-income-and-living-conditions)</u>\n<u>[survey, which the OECD uses as the basis for host country poverty](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)</u>\nassessments\n\n2. Results for the Czech Republic not individually presented due to\nsampling limitations\n\n3. Accommodation rent support has been calculated as the difference\nbetween the actual equivalized accommodation expense and the\nmedian equivalized market rent in the region\n\n\n\n8 A household is defined to fall below the poverty line if its members fall below the poverty line on individual basis (the\nequivalized income of all household members is the same)\n\n\n\n9 Its magnitude can be computed as the difference between the median equivalized market rent in the region and the actual\nequivalized accommodation expense\n\n\n\n10 Those that are below the poverty line\n\n\n\n**5**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 4, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "union-statistics-on-income-and-living-conditions", "probe_tag": "keep", "probe_score": 0.9359, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1, "end": 49, "key": "sample:jad_paddy_docs:000000:4:2:0", "source": "gold", "luna_reason": null}]}
-{"text": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n\n**<u>SHARE OF YOUNG UKRAINIANS (AGED 15 TO 24) WHO ARE NOT ENGAGED IN EMPLOYMENT, EDUCATION, OR TRAINING</u>**\n**(NEET) BY COUNTRY, %** <sup>**1,2,3**</sup>\n\n\nHost country Refugees, excluding online education Refugees\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Hungary Moldova Poland Romania Slovakia Region\n\n\n\n1. Data reported by the national statistics service was used as a\nreference for Moldova\n\n2. With the exception of Poland and the Czech Republic, the reliability\nof data by country is hindered by a relatively low number of\nobservations\n\n[3. Host country data is based on indicators reported by the OECD for](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm)\n[2022](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm)\n\n\n**<u>UKRAINE REFUGEE YOUTH ACTIVITY BY AGE</u>**\n\n\n\n**The gender divide: female – led households are**\n**more economically vulnerable than their male –**\n**led counterparts**\nThe share of households that are composed of\nfemale only adults with or without children\nconstitute 65% of the total sample across the\nregion. Compared to households with male only\nadults, the vast majority of which are without\nchildren, they are 51% more likely to find themselves\nbelow the poverty line.\n\n\n**<u>DISTRIBUTION OF HOUSEHOLDS BY GENDER OF</u>**\n**ADULTS, %**\n\n\n\nNEET\n\n\n15", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 8, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data reported by the national statistics service", "probe_tag": "keep", "probe_score": 0.9647, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 432, "end": 480, "key": "sample:jad_paddy_docs:000000:8:0:0", "source": "gold", "luna_reason": null}]}
-{"text": ", and Zenou, 2010;\nÅslund and Rooth, 2007), and Switzerland\n(Müller, Pannatier, and Viarengo, 2022),\nas well as the previously described crosscountry study. This could in principle stem\nfrom scarring on an individual level from\nweak initial opportunities, or persistently\nweak local labour market combined with\nimperfect geographic mobility. The effects\nare hard to disentangle, while Åslund and\nRooth (2007) find some indication that both\nphenomena are at play, Godøy (2017) finds\nevidence only for persistently weak local\nlabour markets.\n\n\n##### Migrants and refugees dispersed away from ethnic enclaves experience weaker labour market inclusion outcomes, and vice versa.\n\nCo-nationals can provide important\ninformation to refugees about employment\nopportunities. In Germany, Battisti, Peri,\nand Romiti (2022) found that immigrants\ninitially located in places with more conationals, as well as well as refugees and\nrepatriated ethnic Germans dispersed to\nsuch places, are more likely to be employed\nin the first 3 years. It was found, however,\nthat these groups had lower probability of\ninvesting in human capital. In Swiss data,\nMartén, Hainmueller, and Hangartner\n(2019) found that refugees dispersed to\nlocations with more co-nationals are more\nlikely to find work, especially in the first 3\nyears. In Danish data, Damm (2014) found that\nhigher skill levels of non-Western immigrant\nmen in an area raises employment probability\nof refugee men, while higher employment\nrates of their co-national men raises their\nearnings. Also in Danish data, Damm (2009)\nfound that larger size of ethnic network in an\narea increases earnings of refugees.\nIn Swedish data, Edin, Fredriksson,\nand Aslund (2003) found that refugees\ndispersed to areas with more co-nationals\nexperience higher earnings.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nKingdom,", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Swiss data", "probe_tag": "keep", "probe_score": 0.9927, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1120, "end": 1130, "key": "sample:jad_paddy_docs:000007:12:2:0", "source": "gold", "luna_reason": null}, {"text": "Danish data", "probe_tag": "keep", "probe_score": 0.9708, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1307, "end": 1318, "key": "sample:jad_paddy_docs:000007:12:2:1", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Box 2.** Labour productivity of refugees in relation to the rest of population\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nTo gauge the labour productivity of Ukrainian refugees in relation to the rest of the population we **Chart 14.** Distribution of workers (refugees from Ukraine vs. natives and other immigrants) by average earnings in a poviat\nperformed back-of-the-envelope calculations. Unfortunately, publicly available data for the refugee and _Persons registered for social security on 30.09.2023_\ngeneral populations is gathered differently and for different time periods. Assuming that such results\n\nUkrainian refugees\n\nare broadly correct – educational attainment and geographical distribution imply higher earnings (a\nproxy for labour productivity) of refugees than the general population, while their employer firm sizes, 10%\n\n\n9%\n\n\n\nUkrainian refugees\n\n\n\n10%\n\n\n\n9%\n\n\n\n\n|Col1|Col2|Col3|Col4|Warszaw|a|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|||Nearly**10% of re**<br>work in Warsaw|**  fugees**|||||\n|||||||||\n||||Wrocław|||||\n|||||||||\n|||||Kraków||||\n|||Łodź|Poznań||||R² = 0,20|\n|||Szczecin<br>||Gdańsk||||\n||Poznański|Bydgoszcz||~~Katowice~~||||\n|||||Łęczy", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "publicly available data", "probe_tag": "keep", "probe_score": 0.9864, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 522, "end": 545, "key": "sample:jad_paddy_docs:000007:16:0:0", "source": "gold", "luna_reason": "Existing data supports calculations comparing refugee and general-population labour productivity.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nRefugees from Ukraine are not yet\nutilising their full potential in the Polish\nlabour market. In May 2022, 46% of\narriving refugees declared that they had\nno knowledge of the Polish language\n(NBP, 2023). Over time, this percentage\nimproved, with data from November 2022\nshowing a result of 21%, though this still\nrepresents a large group of people who\ndo not know the local language <sup>24</sup> [^24: Due to possible differences in methodologies data from this surveys should not be directly compared], placing\nthem at risk of limiting possible jobs to\nthose below their educational level. Nearly\n40% of Refugees from Ukraine insured\nat ZUS on 30th June 2023 in Poland were\nemployed in elementary occupations <sup>25</sup> [^25: Elementary occupations include: Cleaners and helpers; Agricultural, forestry and fishery labourers; Labourers in mining, construction, manufacturing\nand transport; Food preparation assistants; Street and related sales and services workers; Refuse workers and other elementary workers.],\n\n\n\nwhile for all employed persons in Q2 2023\nthis percentage was only 5%. Furthermore,\nthe Deloitte Ukraine Refugee Pulse report\nindicates that 50% of respondents point\nto language barriers as an obstacle to\naccessing services to meet basic needs\n(Deloitte, 2023). Meanwhile, in the MSNA\nPoland 2023 survey, when asked about\nencountered barriers for accessing the\nlabour market, 34% of respondents\npointed to lack of language knowledge.\n\n\nSmooth inclusion of refugees on labour\nmarket thus far was enabled by proper\npolicies. In response to the war escalation\n\n\n\nin Ukraine and the influx of refugees into\nthe EU, prompt actions were taken both at\nEU and national level.\n\n\nRefugees from Ukraine in the European\nUnion are covered by the Temporary\nProtection Directive TPD, which was\nactivated on 4th March 2022 (European\nCouncil, 2022). The regulation aims to\nsupport EU Member States’ asylum\nschemes and to ensure harmonised\nrights for the incoming", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 11, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data from November 2022", "probe_tag": "keep", "probe_score": 0.9875, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 322, "end": 345, "key": "sample:jad_paddy_docs:000007:11:0:0", "source": "gold", "luna_reason": null}, {"text": "Deloitte Ukraine Refugee Pulse report", "probe_tag": "keep", "probe_score": 0.9841, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1185, "end": 1222, "key": "sample:jad_paddy_docs:000007:11:0:1", "source": "gold", "luna_reason": null}, {"text": "MSNA\nPoland 2023 survey", "probe_tag": "keep", "probe_score": 0.9876, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1377, "end": 1400, "key": "sample:jad_paddy_docs:000007:11:0:2", "source": "gold", "luna_reason": null}]}
 {"text": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n# Health analysis\n\n### **Health remains a** **priority need**\n\nAccess to health services has remained a priority\nneed and is ranked among the top three priorities\nby 33% of households, second only to employment\nand livelihoods support. The identification of health\nas a priority is consistent with 2023, where 34% of\nhouseholds ranked health among their top three\nneeds.\n\n\nVariations exist across countries, health care was\nthe top priority need for respondents in half the\ncountries (Bulgaria, Hungary, Moldova, Romania,\nand Latvia). In 2024, health care became a top\npriority for 49% of households in Romania, a shift\nfrom 38% in 2023, potentially indicating barriers and\nchanges in the level of access.\n\n\n\n(2023 N=9,466, 2024 N=7,140)\n\n- Not included in 2023 survey\n\n\n\n**<u>TOP 10 PRIORITY NEEDS (OUT OF THOSE WHO REPORTED)</u>**\n\n\n2023 2024\n\n\n\nEmployment,\n\nlivelihoods\n\n\nHealthcare\n\nservices\n\n\nAccommodation\n\n\nLanguage course\n\n\nEducation for\n\nchildren\n\n\nMedicines\n\n\nFood\n\n\nTrainings,\neducation adults\n\n\nLegal status*\n\n\nRegistration,\nlegal assistance\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n                                   - Not included in 2023 survey\n\nRegionally, women and men prioritized health care\nnearly equally with respectively 34% and 32%\nidentifying it as a priority need. For women, health was the second highest priority after employment\ncompared to men who prioritized it third after\nemployment and accommodation.\n\n\n\n**<u>TOP 10 PRIORITY NEEDS (OUT OF THOSE WHO REPORTED), BY COUNTRY</u>**\n\n\nTop 1 Top 2 Top 3 priority\n\n\n\n|Col1|Regional|Bulgaria|Czechia|Estonia|Hungary|Latvia|Lithuania|Moldova|Poland|Romania|Slovakia|\n|---|---|---|---|---|---|---|", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2023 survey", "probe_tag": "keep", "probe_score": 0.9978, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 829, "end": 840, "key": "sample:jad_paddy_docs:000004:9:0:0", "source": "gold", "luna_reason": null}]}
+{"text": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n# Executive summary\n\nThe war in Ukraine, now in its third year, continues\nto have devastating effects on the Ukrainian\npopulation, triggering one of the largest\ndisplacement crises in Europe since World War II. As\nof December 2024, over 6.2 million Ukrainian\nrefugees have been recorded across Europe, the\nmajority of whom are women, children, and older\npersons. The European Union extended the\nTemporary Protection Directive until March 2026,\ngranting Ukrainian refugees access to essential\nhealth services, education, and other critical\nsupport. The Republic of Moldova followed this\nmodel and also introduced Temporary Protection for\nUkrainian refugees.\n\n\nIn 2024, to assess the health and mental health\nsituation of Ukrainian refugees, their access to\nservices, and the barriers they face across\ncountries, Regional Refugee Response Plan (RRP)\nhealth and mental health and psychosocial support\n(MHPSS) partners conducted a regional analysis of\nthe Socio-Economic Insights Survey (SEIS) data from\n10 refugee-hosting countries: Bulgaria, Czechia,\nEstonia, Hungary, Latvia, Lithuania, Poland, Republic\nof Moldova, Romania, and Slovakia. The analysis\nincludes a comparison with key indicators collected\nin 2023.\n\n\nKey finding from the regional analysis include:\n\n\n\n\n\n\n\n\n\n\n\n\n\n**3**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Socio-Economic Insights Survey", "probe_tag": "keep", "probe_score": 0.9776, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1024, "end": 1054, "key": "sample:jad_paddy_docs:000004:2:0:0", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 15. Ukrainian refugees wages median net wage by age group**\n\n\nMonthly net wage (PLN) Percengate of all workers total economy average\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 16. Median net wages of Ukrainian refugees median net wage by sector**\n\n\nin PLN Percentage of total economy average\n\n\n\n126%\n\n\n\n\n\n\n\n\n\n\n\n15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64\n\n\nUkrainian refugees All workers\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey and GUS data.\n\n\n\n**The Ukrainian refugee groups to earn**\n**the highest wages compared to the**\n**wages in the economy as a whole are**\n**the younger age groups.** Ukrainian\nrefugee incomes from employment are\nhighest in the 25–34 and 35–44 age\ngroups. However, relative to the economy\nas a whole, the wages of Ukrainian\nrefugees are the highest in the youngest\nage groups and decrease with age. This\ncan be explained by three facts. First,\nwages in the youngest age groups are\nmost compressed, because they diverge\nwith time and accumulated professional\nexperience. Second, younger persons have\nless experience and so lose least from\nmigration. Third, younger persons often\nfind it easier to learn the language of the\nhost country.\n\n\n\n**The earnings of Ukrainian refugees**\n**differ across sectors in nominal**\n**terms and as a percentage of the**\n**economy as a whole – only education**\n**ranked lowest on both measures.**\nUkrainian refugees earn the highest\nwages in manufacturing, health, and\naccommodation and food service activities,\nwhile the lowest in education, other\nservices, and construction. A comparison\nto median earnings in these sectors in the\neconomy as a whole (after re", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9906, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 604, "end": 621, "key": "sample:jad_paddy_docs:000001:10:0:0", "source": "gold", "luna_reason": "Named survey cited as the basis for wage analysis and reported findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "GUS data", "probe_tag": "keep", "probe_score": 0.9429, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 626, "end": 634, "key": "sample:jad_paddy_docs:000001:10:0:1", "source": "gold", "luna_reason": null}]}
+{"text": "/data2.unhcr.org/en/situations/ukraine](https://data2.unhcr.org/en/situations/ukraine)</u>\n\n\n14\n\n\n\n**Source:** Deloitte own elaboration based on the results of the MSNA Poland 2023 survey\n\n\n\n15", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 7, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "MSNA Poland 2023 survey", "probe_tag": "keep", "probe_score": 0.9996, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 164, "end": 187, "key": "sample:jad_paddy_docs:000007:7:3:0", "source": "gold", "luna_reason": null}]}
 {"text": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n\n**<u>TOP 5 REFUGEE EMPLOYMENT SECTORS SPLIT BY</u>**\n**EMPLOYEE BACKGROUND (2024)**\n\n\n\n**<u>TOP EMPLOYMENT BARRIERS FOR EMPLOYED REFUGEES</u>**\n**(2024)**\n\n\n\nEmployed in the same\nsector in Ukraine\n\n\nManufacturing\n\n\nHospitality\n\n\nConstruction\n\n\nWholesale\n\n\nIT\n\n\n\nLack of local language\n\nknowledge\n\nCannot find a job with\n\ndecent pay\n\nFew jobs for my skills or\n\nexperience\n\nLack of jobs with a suitable\n\nschedule\n\nDegree or skills recognition\n\nissues\n\n\nSource: Survey data\n\n\n\n17%\n\n\n15%\n\n\n\n35%\n\n\n\n5%\n\n\n2%\n\n\n4%\n\n\n\nEmployed in a different\nsector in Ukraine\n\n\n16%\n\n\n9%\n\n\n5%\n\n\n\n24%\n\n\n\n\n\n\n\n\n\n6%\n\n\n\n4%\n\n\n\n1%\n\n\n\nNote: Percentages are based on the distribution of relevant responses\nin the survey\n\n\nSource: Survey data\n\n\nMoreover, in the latest survey round, nearly 35% of employed refugees identified inadequate pay, a lack of\npositions that match their skill set, and challenges in having their qualifications recognized as barriers to\nemployment. All of these answers also suggest a mismatch between qualifications and job placement.\nConsistent with the findings on having to shift to jobs outside of previous employment backgrounds, working\nwomen reported the above employment barriers more frequently than men, supporting the hypothesis that\nthey may be facing underemployment more often.\n\n# **Methodology**\n\nThe approach to data collection in each of the countries included in the report differed depending on the\navailability of sampling frames and information on the distribution of the refugee population by geographic area\nand accommodation type. All interviews were conducted face to face. As a probabilistic selection of\nrespondents could not be ensured, the primary goal was to collect a diverse sample that would reflect the\npopulation’s composition as closely as possible.\n\n\nFor the regional analysis,", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Survey data", "probe_tag": "keep", "probe_score": 0.9579, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 568, "end": 579, "key": "sample:jad_paddy_docs:000010:13:0:0", "source": "gold", "luna_reason": null}]}
+{"text": " enough money to\nmeet their needs, the refugees were nearly\nequally split (around 0.5% more reported\nno difficulties), with an additional 8% not\nknowing or refusing to answer. According to\nthe National Bank of Poland survey carried\nout in November 2022, 28% of refugees\nsaid they spend less than half of their\nincome on daily expenses, most spend\nbetween 50% and 80%, and 19% spend 80100% of their income.\n\n\n###### Currently between 225 and 350 thousand of refugees from Ukraine are working in Poland. The lower bound is the number from social security, while the higher bound is the product of employment rate from the surveys and working age population with PESEL numbers.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Box 1.** Inflow of savings from Ukraine\n\n\n\n**Chart 13.** Income structure of Ukrainian refugee households\n\n\n**5%** **1%**\n\n\n\nWork (regular-, temporary-,and self-employment in Poland,\nremote employment in Ukraine\n\n\nRemittances from friends/relatives\n\n\nPolish government benefits (Family 500+, cash benefits,\ndisability grants)\n\n\nUkrainian government benefits (pensions, disability grants,\nparental benefits)\n\n\nOther (humanitarian organizations, other sources)\n\n\n\n**Source:** Deloitte elaboration based on the MSNA Poland 2023. The work category includes regular employment, temporary work, self-employment\nand remote work in Ukraine.\n\n\n31 <u>[Cudzoziemcy w polskim systemie ubezpieczeń społecznych (zus.pl)](https://www.zus.pl/documents/10182/2322024/Cudzoziemcy+w+polskim+systemie+ubezpiecze%C5%84+spo%C5%82ecznych_2022.pdf/)</", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "National Bank of Poland survey", "probe_tag": "keep", "probe_score": 0.9996, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 193, "end": 223, "key": "sample:jad_paddy_docs:000007:14:2:0", "source": "gold", "luna_reason": null}, {"text": "surveys and working age population with PESEL numbers", "probe_tag": "keep", "probe_score": 0.9248, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 620, "end": 673, "key": "sample:jad_paddy_docs:000007:14:2:1", "source": "gold", "luna_reason": null}, {"text": "MSNA Poland 2023", "probe_tag": "keep", "probe_score": 0.9021, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1263, "end": 1279, "key": "sample:jad_paddy_docs:000007:14:2:2", "source": "gold", "luna_reason": null}]}
+{"text": " data. Based on the MultiSector Needs Assessment Poland 2023\nsurvey conducted in July-August 2023, we\ncalculate that 80% of the income of refugee\nhouseholds is derived from employment,\nwith an additional 5% coming from\nremittances and 2% from Ukrainian pension\nbenefits. In economic terms, refugees\nfrom Ukraine in Poland are not receivers\nof social services and charity, but primarily\nconsumers, employees, and entrepreneurs.\n\n\nIn Chapter 3, we estimate the economic\nimpact of refugees from Ukraine in Poland\nin general equilibrium Deloitte D.Climate\nmodel. This is the gold standard of\neconomic modelling on the macro-level,\nwhich comprehensively accounts for the\nsupply side of the economy including\nlabour supply and productivity, and the\ndemand side including consumption\nas well as taxation. Unfortunately, such\nmacroeconomic models cannot account for\nhow exactly refugees and other migrants\nenable native workers to specialise in\nbetter paid professions (occupational\nupgrading), or how firms allow for new\nskills by adapting different production\ntechnologies. As such, our estimates\nshould be treated as a conservative lower\nbound of the effect.\n\n\n\nFurthermore, in Chapter 4, we move\nbeyond theoretical modelling, to examine\nempirical studies on how immigrants\nand refugees impact not just output, but\nlabour productivity as well. This effect\ncomes not from traditional supply-demand\nanalysis, but from increased specialisation.\nImmigrants enable occupational upgrading\nof residents, supply new skills to firms,\nenter household works services that allow\nhighly productive native women to increase\nlabour supply, and exhibit high rates of\nentrepreneurship.", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "MultiSector Needs Assessment Poland 2023\nsurvey", "probe_tag": "keep", "probe_score": 0.9999, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 20, "end": 67, "key": "sample:jad_paddy_docs:000007:5:1:0", "source": "gold", "luna_reason": null}]}
+{"text": "-union-statistics-on-income-and-living-conditions)</u>\n<u>[survey, which the OECD uses as the basis for host country poverty](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)</u>\nassessments\n\n2. Results for the Czech Republic not individually presented due to\nsampling limitations\n\n3. Accommodation rent support has been calculated as the difference\nbetween the actual equivalized accommodation expense and the\nmedian equivalized market rent in the region\n\n\n\n8 A household is defined to fall below the poverty line if its members fall below the poverty line on individual basis (the\nequivalized income of all household members is the same)\n\n\n\n9 Its magnitude can be computed as the difference between the median equivalized market rent in the region and the actual\nequivalized accommodation expense\n\n\n\n10 Those that are below the poverty line\n\n\n\n**5**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 4, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "union-statistics-on-income-and-living-conditions", "probe_tag": "keep", "probe_score": 0.9359, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1, "end": 49, "key": "sample:jad_paddy_docs:000000:4:2:0", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**The only reliable timeseries of the**\n**number of Ukrainians in Poland over**\n**the past decade is social insurance**\n**data on insured Ukrainian nationals,**\n**though it accounts only for workers.**\nThe focus on workers rather than on\nthe entire group does not change much\nin the data from before February 2022,\nas the previous influx consisted mainly\nof Ukrainians seeking employment in\nPoland. However, the actual number\nof employed Ukrainian nationals must\nhave been higher. First, certain types\nof legal work often undertaken by\ntemporary employees do not require\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 4. Age and gender structure of Ukrainian refugees**\n\n\n\n**Most of the refugees from Ukraine**\n**currently living in Poland are women**\n**and children, though over half of**\n**the total population is of working**\n**age.** The best population data available\nis the regularly updated active PESEL\ndatabase. <sup>4</sup> [^4: Available in the repository maintained by the government <u>https://dane.gov.pl/pl/dataset/2715</u> as well as UNHCR data portal <u>https://app.powerbi.com/</u>\n<u>view?r=eyJrIjoiODhkOGZiMzctZTliMi00NzA5LTgyM2QtZGZhM2IwZjBiZDk2IiwidCI6ImU1YzM3OTgxLTY2NjQtNDEzNC04YTBjLTY1NDNkMmFmODBiZSIsImMiOjh9</u>] According to the registry, 61.5%\nof the registered are women and 38.5%\nare men. The database also includes the\nage of PESEL UKR holders, which indicates\nthat over half (57.4%), i.e. more than\n560 thousand people, are of working age\n(18-65). While the male and female shares\nof people below 18 years of age (20% and\n19%, respectively) and 66+ (1%", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on insured Ukrainian nationals", "probe_tag": "keep", "probe_score": 0.9623, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 198, "end": 233, "key": "sample:jad_paddy_docs:000001:4:0:0", "source": "gold", "luna_reason": null}, {"text": "PESEL\ndatabase", "probe_tag": "keep", "probe_score": 0.9643, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1020, "end": 1034, "key": "sample:jad_paddy_docs:000001:4:0:1", "source": "gold", "luna_reason": null}]}
 {"text": ", to account\nfor spending of savings from Ukraine, data\nfrom the National Bank of Ukraine on\ncash withdrawals and retail transactions\nfrom Ukrainian bank cards in Poland was\nused <sup>55</sup> and then calibrated to data for\nprivate consumption in Poland. Additionally,\nthe same data was used to calibrate the\nnegative shock to investment in Eastern\nEurope.\n\n\n\nFor productivity two options were tested.\nFirstly, neutral impact: no shock to\nproductivity. Secondly, lower productivity of\nworkers from Ukraine negatively impacting\ntotal labour productivity. These shocks were\ncalibrated to match the difference in data\nbetween refugees income from labour in\nUNHCR survey and average wage in Poland\nfrom Statistics Poland weighted by refugees\nshare in total workforce.\n\n\nAs one period in the model is set to one\nyear and refugees started coming to Poland\nby the end of February 2022 it was assumed\nthat their impact on economy started being\nfelt starting from II quarter of the year.\nAs such shocks were set so that ¾ of shocks\nwere calibrated to data from 2022 and ¼ to\ndata for 2023 <sup>56</sup> .\n\n\n\n51  Computational General Equilibrium.\n52  Global Trade Analysis Project, <u>[GTAP Models: Current GTAP Model (purdue.edu).](https://www.gtap.agecon.purdue.edu/models/current.asp)</u>\n53  Region combined from: Russia, Belarus, Ukraine, Moldova, Czechia, Slovakia, Hungary, Romania, and Bulgaria.\n54  All shocks are percent deviations.\n55 <u>[Oversight of financial market infrastructures (bank.gov.ua)](https://bank.gov.ua/en/payments/oversite)</u>\n56  E.g. for total increase in number of workers of 350 thousand around 262.5 thou. was set to have happened in 2022 while rest in 2023.", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 21, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data\nfrom the National Bank of Ukraine", "probe_tag": "keep", "probe_score": 0.9987, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 51, "end": 89, "key": "sample:jad_paddy_docs:000007:21:1:0", "source": "gold", "luna_reason": null}, {"text": "data for\nprivate consumption in Poland", "probe_tag": "keep", "probe_score": 0.9774, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 216, "end": 254, "key": "sample:jad_paddy_docs:000007:21:1:1", "source": "gold", "luna_reason": null}, {"text": "UNHCR survey", "probe_tag": "keep", "probe_score": 0.9653, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 655, "end": 667, "key": "sample:jad_paddy_docs:000007:21:1:2", "source": "gold", "luna_reason": null}, {"text": "data from 2022", "probe_tag": "keep", "probe_score": 0.9704, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1043, "end": 1057, "key": "sample:jad_paddy_docs:000007:21:1:3", "source": "gold", "luna_reason": null}]}
 {"text": " have relatively better labour\nmarket situations. In countries with lower\nunemployment, refugees fare better in\nthe labour market. Since women make\nup the majority of refugees of working\nage, the situation of women on the labour\nmarket is especially important. As such,\nfemale unemployment rates explain 36%\nof the variation in refugees from Ukraine\nemployment rates in studies from 11 EU\nMember States <sup>22</sup> [^22: After excluding Germany and Switzerland as outliers. 23  Due to possible differences in methodologies data from this surveys should not be directly compared]\n\n\n**Chart 10.** Female unemployment and refugees from Ukraine employment in Europe\n\n\n70%\n\n\n\n**Chart 11.** Education attainment of Poles and Ukrainians\n\n\n**Eurostat** Poland LFS 2022\n\n\n\n**UNHCR**\n\n**(2023)**\n\n\n**NBP**\n**(2022)**\n\n\n**Ukrstat**\n\n\n\n11%\n\n\n56%\n\n\n48%\n\n\n46%\n\n\n\n30%\n\n\n\nRefugees from Ukraine VII-VIII 2023\n\n\nRefugees from Ukraine XI 2022\n\n\nPre-2022 migrants from Ukraine XI 2022\n\n\nUkraine LFS 2020\n\n\n\n29%\n\n\n20%\n\n\n17%\n\n\n29%\n\n\n\n60%\n\n\n14%\n\n\n33%\n\n\n37%\n\n\n\n37%\n\n\n\n60%\n\n\n50%\n\n\n40%\n\n\n30%\n\n\n20%\n\n\n10%\n\n\n0%\n\n\n\n\n|PL XI<br>PL VII-VIII|2022<br>2023 U|K**|Col4|Col5|\n|---|---|---|---|---|\n||~~CZ~~<br> <br>|LT<br>|SE||\n|||DK<br>NL||EE|\n||||FR|**R = 0,36**|\n|||IE<br>|||\n||DE<br>|~~H*~~||~~IT~~|\n||||||\n\n\n\n2% 4% 6%\n\n**Female unemployment rate**\n\n\n\n34%\n\n\n\n\n\n\n\n\n\n\n\nThe", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Poland LFS 2022", "probe_tag": "keep", "probe_score": 0.9924, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 747, "end": 762, "key": "sample:jad_paddy_docs:000007:10:1:0", "source": "gold", "luna_reason": "Named Polish labor force survey cited as the source for charted education data.", "usage_type": "evidential", "specificity": "named"}, {"text": "NBP", "probe_tag": "keep", "probe_score": 0.9496, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 792, "end": 795, "key": "sample:jad_paddy_docs:000007:10:1:1", "source": "gold", "luna_reason": null}, {"text": "Ukrstat", "probe_tag": "keep", "probe_score": 0.9496, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 813, "end": 820, "key": "sample:jad_paddy_docs:000007:10:1:2", "source": "gold", "luna_reason": null}]}
-{"text": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>HOUSEHOLD INCOME DISTRIBUTION BY SOURCE AND POVERTY CATEGORY</u>**\n\n\n\nEmployment Family support Social\nprotection\n(host country)\n\n\n\nOld age\npension\n(Ukraine)\n\n\n12%\n\n\n67%\n\n\n\nSocial\nprotection\n(Ukraine)\n\n\n35%\n\n\n\nHumanitarian\ncash\n\n\n8%\n\n\n\n13%\n\n\n\n23%\n\n\n\n6%\n\n\n\nOther\n\n\n5%\n\n\n3%\n\n\n\n3%\n\n\n5%\n\n\n\nBelow the poverty line\n\n\nBelow the poverty line after housing\n\ncost correction\n\n\nAbove the poverty line after housing\n\ncost correction\n\n\nSource: Survey data, SAG estimates\n\n\n\n26%\n\n\n\n88%\n\n\n\n**Higher employment earnings were the main driver behind the drop in poverty rates from**\n**2023**\n\n\nThe mean monthly equivalized household income <sup>12</sup> [^12: Household disposable income adjusted for size, as per Eurostat’s methodology] of Ukrainian refugees across the seven countries surveyed\nin both rounds increased by 38% from last year, to an equivalent of EUR 763. This increase was much higher\nthan the 4% rise in the regional poverty threshold over the same time.\n\n\nApproximately 90% of the increase in refugee household income can be attributed to higher employment\nearnings, driven by a combination of rising employment rates and wage growth. A significantly smaller, though\nstill notable, contribution came from increased financial support from families in Ukraine, although this finding\nmay partially be an artifact of adjustments to the survey questionnaire <sup>13</sup> .\n\n\n**<u>WEIGHTED AVERAGE MONTHLY EQUIVALIZED INCOME EVOLUTION, EUR</u>**\n\n\n800\n\n\n600\n\n\n400\n\n\n200\n\n\n\n0\n\n\n\nFamily\nsupport\n\n\n\nHost country\n\nsocial\nprotection\n\n\n\nUkraine\n\nsocial\nprotection\n\n(inc.\npensions)\n\n\n\nHumanitarian\n\ncash\n\n\n\nEquivalized\n\n\n\nEmployment\n\nincome\n\n\n\nOther Equivalized\n\n\n\nincome\n\n\n\n2024\n\n\n\nincome\n\n\n\n2023\n\n\n\nNote: Only includes data from the 7 countries surveyed in both rounds (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and\nSlovakia)\n\n\nSource", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 8, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Survey data", "probe_tag": "keep", "probe_score": 0.9981, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 544, "end": 555, "key": "sample:jad_paddy_docs:000010:8:0:0", "source": "gold", "luna_reason": null}, {"text": "data from the 7 countries surveyed in both rounds", "probe_tag": "keep", "probe_score": 0.9846, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1824, "end": 1873, "key": "sample:jad_paddy_docs:000010:8:0:1", "source": "gold", "luna_reason": null}]}
-{"text": "**\n**policymakers.** According to a previous\nresearch, usually about a third of migrants\nholding a university degree work in jobs\nrequiring only high-school diplomas, versus\n10% of natives (Tani, 2020). Migrants may\nlack language fluency or country-specific\nknowledge (e.g. of the law or business\ncontacts) and find it difficult to prove the\nprofessional experience or educational\ncredentials gained in their home country.\nThey also face regulatory barriers to\nentering some professions, e.g., in the\npublic sector or regulated specialist\noccupations. Ensuring that migrants`\nand refugees` skills are fully utilized to\nthe benefit of both the individuals and\nhost-country economies is a central policy\nchallenge for the countries facing largescale immigration.\n\n\n**In Poland, non-EU27 citizens are twice**\n**as likely to be over-qualified (for their**\n**job) as Polish citizens.** In its Labour\nForce Survey (LFS), Eurostat defines overqualification rate as the share of persons\nwith tertiary education (bachelor’s degree\nand higher) who are employed in the ISCO\n(International Standard Classification of\nOccupations) 4-9 occupational groups <sup>25</sup> [^25: This is the same classification as quoted from GUS and ZUS in the previous chapters. Codes 4-9 refer to clerical support workers; service and sales workers; skilled\nagricultural, forestry and fishery workers; craft and related trades workers; plant and machine operators and assemblers; elementary occupations.] .\nWhile the LFS is unlikely to cover all\nUkrainian refugees and migrants from\nother nationalities in Poland, there was a\nvisible increase in over-qualification rates\nfor non-EU27 citizens between 2022 and\n2023 that is not observed for Polish\ncitizens.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 18. Over-qualification rates by citizenship**\n\n48%\n\n\nNon-EU27 Citizenship Polish Citizenship\n\n\n\nSource: Deloitte own elaboration based on Eurostat\n(Labour Force Survey) data.\n\n\n**Occupational downgrading is**\n**widespread among Ukrainian refugees**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Labour\nForce Survey", "probe_tag": "confusion", "probe_score": 0.8815752267837524, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 888, "end": 907, "key": "jad_paddy_docs:000001:13:1:0", "source": "camp2", "luna_reason": "Eurostat survey defines the rate and supplies chart data.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": ", it has\ndeclined by 2.6 million. This trend is set to\ncontinue. According to the latest Eurostat\nprojections, without migration, the\npopulation (counting all nationalities) aged\n20-64 years would decrease by 4.8 million\nby 2050. <sup>20</sup> [^20: Eurostat data, <u>[https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-](https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-4aca-a51f-15c98be37466)</u>\n**Source:** Eurostat <u>[Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/lfsq_pganws__custom_8677828/bookmark/table?lang=en&bookmarkId=06047812-2bde-4cf8-a627-7d63d65f17db)</u> <u>[4aca-a51f-15c98be37466](https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-4aca-a51f-15c98be37466)</u>]\n\n\n© UNHCR / Anna Liminowicz\n\n\n\n19  Statistics Poland data, <u>[https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n<u>[temporary-stay-from-poland-between-2004-2020,8,14.html](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n20  Eurostat data, <u>[https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-](https://ec.", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 8, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Eurostat data", "probe_tag": "keep", "probe_score": 0.9976, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 250, "end": 263, "key": "sample:jad_paddy_docs:000007:8:1:0", "source": "gold", "luna_reason": null}, {"text": "Statistics Poland data", "probe_tag": "confusion", "probe_score": 0.7274, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 965, "end": 987, "key": "sample:jad_paddy_docs:000007:8:1:1", "source": "gold", "luna_reason": null}, {"text": "Eurostat data", "probe_tag": "confusion", "probe_score": 0.7274, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1542, "end": 1555, "key": "sample:jad_paddy_docs:000007:8:1:2", "source": "gold", "luna_reason": null}]}
+{"text": "## **HELPING HANDS** THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n#### An inter-agency exploration of socio-economic data April 2024", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 11, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "socio-economic data", "probe_tag": "confusion", "probe_score": 0.5559, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 164, "end": 183, "key": "sample:jad_paddy_docs:000000:11:0:0", "source": "gold", "luna_reason": "Generic data phrase in a title, with no attributed finding or demonstrated use.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": " shock\nto the total factor productivity growth. This\nyields GDP higher by 1.5-2.6% by 2030,\nsignificantly higher than our long-term\nestimate – the higher result is likely due to\nthe increase in TFP that we do not include\nin our modelling. Fourth, Monitor Deloitte\n(2022) provided an early wide estimate of\nthe economic impact of Ukrainian refugees.\nThis would translate into 0.9-2.4% higher\nGDP, also due to the possibility of a positive\nproductivity shock. We review the relevant\nliterature on the impacts of immigration on\nproductivity in Chapter 4.\n\n\n\nrefugees, we have adjusted all the results\nproportionally to a 1.4-2.2% employment\ngrowth. First, Gradzewicz, Jabłon\nowski, Sasiela, and Żółkiewski (2021)\nuse the NBP CGE model to estimate the\neconomic impact of pre-2022 Ukrainian\nmigrants over the 2015-2018 period,\ntreating their inflow as a positive unskilled\nlabour shock. If the Ukrainian refugee\ninflow had the same characteristics, it\nwould yield a 0.5-0.8% higher GDP – the\nlower bound of our estimate. Second,\nStrzelecki, Growiec, and Wyszyński (2022)\nperform a growth accounting exercise to\ngauge the economic impact of the pre-2022\nUkrainian migrants over the 2014-2018\nperiod, accounting for hours and worker\ncharacteristics to arrive at a productivityadjusted labour supply. If Ukrainian\nrefugees had the same characteristics, they\n\n\n© UNHCR / Anna Liminowicz\n\n\n\nAs such **4 scenarios** were calculated with options corresponding to different mixes\nof low and high estimation for employment and productivity while keeping stable\nimpact on consumption: high or low employment level, similar (baseline) or lower\n(conservative) productivity. In the conservative productivity scenario,\nwe assumed approximately 10% lower refugee productivity estimated based\non incomes reported in MSNA Poland 2023 and data from Statistics Poland.\n\n\n**Table 2", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "MSNA Poland 2023", "probe_tag": "keep", "probe_score": 0.9387843608856201, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1795, "end": 1811, "key": "jad_paddy_docs:000007:17:1:0", "source": "camp2", "luna_reason": "Named survey data informs the estimated refugee productivity assumption.", "usage_type": "evidential", "specificity": "named"}, {"text": "data from Statistics Poland", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1816, "end": 1843, "key": "jad_paddy_docs:000007:17:1:1", "source": "camp2", "luna_reason": "Statistics Poland data informs the estimated 10% lower refugee productivity.", "usage_type": "evidential", "specificity": "named"}]}
 {"text": "%\n\n\n\n\n\n\n\n62%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\nNote: For comparability, employment rates for host countries have been recalculated assuming a similar gender distribution to that of refugees\n\n\nSource: ILO, survey data\n\n\n14. The employment rate is defined as the number of employed or self-employed individuals of working age (15-64) as a share of\nthe total number of people in this age group\n15. The labor force is defined as the number of people that are either employed or unemployed\n\n\n**10**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "ILO, survey data", "probe_tag": "confusion", "probe_score": 0.8690335750579834, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 278, "end": 294, "key": "jad_paddy_docs:000010:9:1:0", "source": "camp2", "luna_reason": "ILO survey data is cited as the source for employment-rate figures.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " workers in the\neconomy, but also accounts for increased\nproductivity brought about by more\nspecialization. Considering all aspects, the\noverall impact of the refugees has been\npredominantly positive, and it moved the\nPolish economy to a higher growth path.\nRefugees contribute to the economy\nslightly more than their employment\nshare – they increase the labour supply\nas both workers and entrepreneurs and\nexpand demand as consumers. The rise\nin productivity due to more specialization\nacross the labour force further boosts\nthe economy. The impact of refugees\nis lowered by a temporary decrease in\nthe capital-to-labour ratio (companies\nneed time to invest in equipment and\nmachines to match the rise in the number\nof workers), as well as an increase in\ncompetition on the labour market.\n\n\n**The figures are higher than those in**\n**the previous Deloitte (2024) report,**\n**which – due to scant data available**\n**at the time – did not account for the**\n**positive impact on labour productivity.**\nIn the earlier report, the overall positive\nimpact of refugees was reduced based on\nconservative assumptions, in the absence\nof available/clear data on the increased\ncompetition in the labour market. The\n\n\n\nmodel notably considered lower wages\nand higher unemployment among native\nworkers. However, recent data indicates\nthat these concerns did not materialize.\nInstead, Polish workers have moved on to\nbetter paid occupations, and the economy\nhas benefited from a larger pool of talent,\nenabling deeper specialization and\nincreased productivity growth.\n\n##### Remaining challenges\n\n\n**Despite significant progress in**\n**integrating refugees into the labour**\n**market, several challenges persist.**\nRefugees are half as likely to have an\nemployment contract as Polish citizens\nand few of them achieve high incomes.\nAlthough refugees have been moving on\nto more desirable professions at a faster\nrate than other groups in the economy,\ntheir jobs continue to be disproportionately\nskewed towards elementary occupations.\nThese issues are most evident among\nthose with", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 2, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "recent data", "probe_tag": "confusion", "probe_score": 0.4682, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1299, "end": 1310, "key": "sample:jad_paddy_docs:000001:2:3:0", "source": "gold", "luna_reason": null}]}
-{"text": " 15,902\n\n\n**7. Szczecin** 14,318\n\n\n**8. Poznanski** 14,028\n\n\n**9. Pruszkowski** 12,206\n\n\n\n\n\n\n\n18-59 female and male\n\n\n\n\n\n60+ female and male\n\ntwo 18-59 or 60+ females\n\nother households\n\n\n\n\n\n\n\n18-59 female with one or\nmore 60+ individuals\n\n\n\ntwo 18-59\n\nfemales\n\n\n\n0.3% 7.4%\n\n\n\n\n\n**10. Katowice** 11,591\n\n\n\nNote that poviat-level population does not include Ukrainian refugees, who were added to calculate their appropriate shares.\n\nSource: Deloitte own elaboration based on the PESEL database as of September 2024 and GUS population data as of mid-2024.\n\n#### **1.3 Households income sources**\n\n\n\n18-59 female\nand male\n\n\nother\nhouseholds\n\n\n\n\n\nNote: Some groups that constituted less than 2% of households have been omitted.\n\nSource: Deloitte own elaboration based on SEIS (May-June 2024) UNHCR (2024) survey.\n\n\n\n**The majority of refugees settled in**\n**major cities, especially Warsaw and**\n**Wroclaw, and their vicinities.** Eight most\npopulous poviats in Poland <sup>5</sup> comprising\n16% of the host population, are also the\ntop eight poviats in terms of the number\nof Ukrainian refugees, 29% of whom\nreside there. This shows that Ukrainian\nrefugees are more concentrated in the\nlargest cities than the host population,\nas they migrated to the most attractive\n\n\n5 Seven cities and Poznański poviat.\n\n\n10\n\n\n\n11\n\n\n\nlabour markets, where they have better\nchances of supporting themselves.\nUkrainian refugees make up the largest\nshares of the population in the city of\nWroclaw (7.4%), Przemysl, a city on the\nUkrainian border (6.5%), and in Pruszkowski\npoviat", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "PESEL database", "probe_tag": "keep", "probe_score": 0.9914, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 477, "end": 491, "key": "sample:jad_paddy_docs:000001:5:1:0", "source": "gold", "luna_reason": null}, {"text": "GUS population data", "probe_tag": "keep", "probe_score": 0.9517, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 517, "end": 536, "key": "sample:jad_paddy_docs:000001:5:1:1", "source": "gold", "luna_reason": null}, {"text": "SEIS", "probe_tag": "confusion", "probe_score": 0.4326, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 766, "end": 770, "key": "sample:jad_paddy_docs:000001:5:1:2", "source": "gold", "luna_reason": null}, {"text": "UNHCR (2024) survey", "probe_tag": "keep", "probe_score": 0.9423, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 787, "end": 806, "key": "sample:jad_paddy_docs:000001:5:1:3", "source": "gold", "luna_reason": null}]}
-{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## Executive summary\n\n\n##### Progress in market integration\n\n**Ukrainian refugees have been**\n**increasingly successful in terms of**\n**labour market integration.** The large\ninflux of refugees since February 2022,\nhas further increased and changed the\ndemographics of the already significant\nUkrainian migrant population in Poland.\nRefugees from Ukraine are primarily\nwomen and children, with over 67% of\nfemale-headed households. Poland was\nquick to open its labour market to refugees\nfrom Ukraine, who – despite difficulties\n\n- surprisingly promptly began their\neconomic integration and soon supported\nthemselves primarily from employment.\nIn the past year, refugees’ employment\nrate grew from 61% to 69%, with the\nmedian net wage rising from PLN 3,100 to\nPLN 4,000 and narrowing the gap to the\nmedian net wage in the entire economy.\n**As Ukrainian refugees entered the**\n**labour market, the economy adapted,**\n**resulting in more specialization and**\n**higher productivity.** In a simplistic\nsupply-demand framework, the influx\nof Ukrainian refugees would have had\na negative impact on Polish workers\nemployment or caused a decline in real\nwages. However, this has not occurred.\nFirst, Polish citizens employment rates\nhave grown, and unemployment rates\nhave fallen. Second, poviats in which the\nemployment share of Ukrainian refugees\nhas grown by 1 pp. saw 0.5 pp. higher\nemployment rates among Polish citizens,\nand 0.3 pp. lower unemployment rates.\nThird, there is no evidence of lowered\nwages, in fact the limited available data\nindicates that a higher share of Ukrainian\nrefugees in a poviat may have caused local\nwages to rise. Such findings are in line with\nacademic literature, which documents\na positive impact of migrants on native\nworkers. With foreigners entering the\n\n\n04\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n*", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "limited available data", "probe_tag": "confusion", "probe_score": 0.8446, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1588, "end": 1610, "key": "sample:jad_paddy_docs:000001:2:0:0", "source": "gold", "luna_reason": null}]}
-{"text": " stronger increase in\nlabour productivity than was assumed. As\na result, the positive impact of Ukrainian\nrefugees on the economy is greater than\npreviously expected.\n\n\n\n**As Ukrainian refugees entered the**\n**labour market, the economy adapted,**\n**resulting in more specialization and**\n**higher productivity.** In a simplistic\nsupply-demand framework, the influx\nof Ukrainian refugees should have\ncaused some Polish workers to become\nunemployed or leave the labour force, or\nreal wages to fall. This has not happened.\nFirst, among Polish citizens employment\nrates have grown, and unemployment\nrates have fallen. Second, poviats in which\nemployment share of Ukrainian refugees\nhas grown by 1 pp., saw 0.5 pp. higher\nemployment rates among Polish citizens,\nand 0.3 pp. lower unemployment rates.\n\n\n\nThird, there is no evidence of lowered\nwages, in fact the limited available data\nsuggests that Ukrainian refugees may have\ncaused higher wage growth in poviats\nwhich they have moved to. These are\ncommon findings well documented in\nacademic literature, that as immigrants\nenter the labour market, native workers\nspecialize in complementary, higher\nvalue tasks, which we see empirically in\nPolish workers moving to more attractive\noccupational groups. This can be seen in\nthe data, as Polish citizens are moving to\nbetter paid occupations. It constitutes a\npositive shock to productivity which is what\ncounterbalances labour market pressures. <sup>17</sup> [^17: For the literature review, underlying empirical evidence, and model calibration refer to the appendix on modelling strategy.]\n\n\n\nSource: Deloitte D.Climate estimates. For details see\nthe Online Technical Appendix.\n\n\n**The main impact of Ukrainian refugees**\n**is expanding the economy and putting**\n**it on a higher growth path.** According\nto the Deloitte D.Climate model, economic\nimpact of Ukrainian refugees amounted\nto a higher real GDP by 1.5% in 2022, as\nthey initially entered the labour market.\nWith more", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 11, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "limited available data", "probe_tag": "confusion", "probe_score": 0.0747, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 857, "end": 879, "key": "sample:jad_paddy_docs:000001:11:2:0", "source": "gold", "luna_reason": null}]}
+{"text": "-and-</u>\n<u>salaries-by-occupations-for-october-2022,4,8.html</u>\n\n\nGUS (2024b). Education in the school year 2023/2024 (preliminary data),\nStatistical Office in Gdańsk, <u>https://stat.gov.pl/en/topics/education/education/</u>\n<u>education-in-the-school-year-20232024-preliminary-data,13,2.html</u>\n\n\nHeller, B. H., & Mumma, K. S. (2023). Immigrant integration in the United States:\nthe role of adult English language training. American Economic Journal: Economic\nPolicy, 15(3), 407-437.\n\n\nJaumotte, M. F., Koloskova, K., & Saxena, M. S. C. (2016). Impact of migration on\nincome levels in advanced economies. International Monetary Fund.\n\n\nKleiner, M. M., & Krueger, A. B. (2013). Analyzing the Extent and Influence of\nOccupational Licensing on the Labor Market. Journal of Labor Economics, 31(2),\nS173–S202. <u>https://doi.org/10.1086/669060</u>\n\n\n46\n\n\n\nLessem, R., & Sanders, C. (2020). Immigrant wage growth in the United States:\nThe role of occupational upgrading. International Economic Review, 61(2),\n941-972.\n\n\nLewandowski, P., Górny, A., Krząkała, M., & Palczyńska, M. (2025). The Role of Job\nTask Degradation in Shaping Return Intentions: Evidence from Ukrainian War\nRefugees in Poland. IBS working paper, 01/2025. <u>https", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 23, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Education in the school year 2023/2024", "probe_tag": "confusion", "probe_score": 0.2256, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 82, "end": 120, "key": "sample:jad_paddy_docs:000001:23:2:0", "source": "gold", "luna_reason": null}]}
 {"text": " net wage of\na Ukrainian refugee (estimated based on\nthe SEIS UNHCR survey in chapter 2) from\n80% to 98% of the median in the economy\nas a whole (or from 80% to 93% according\nto Ukrainian refugee’s median in the NBP’s\n2024 survey), almost closing the gap to the\neconomy as a whole in these terms. It is in\nfact higher than the PLN 500 median net\nwage premium of the pre-war Ukrainian\nmigrants over Ukrainian refugees in the\nNBP (2024) survey, even though 68% of the\nformer and only 28% of the latter said they\nhad a high level of fluency in Polish.\n\n\n31\n\n\n\nprofessions (physicians, dentists, nurses,\nand midwives) have opened to migrants\nand refugees to reduce shortages, and\nwhile the shares for all of them stand at\njust 0.9% compared to 1.9% for Polish\ncitizens, the gap is actually very narrow for\nphysicians and dentists, who constitute\n0.7% of Ukrainian refugees and 0.8% of\nPolish citizens. In legal professions (legal\ncounsels, barristers, notaries, and bailiffs),\nthe gap remains wide, although in addition\nto occupational licensing, the likely causes\nmay be the differences between the Polish\nand Ukrainian legal systems as well as\nnew entrants’ struggles with attracting\nclients due to advertising restrictions. In\neffect, just 0.02% of Ukrainian refugees\nwork in legal professions, compared to\n0.4% of Polish citizens. There are also\nhigh contrasts across the remaining\nregulated professions, which employ\n0.8% of Ukrainian refugees and 3.3% of\nPolish citizens. These are construction\nengineers (0.02% Ukrainian refugees),\npharmacists (0.01%), and psychologists\n(0.09%), compared to the following shares\nfor Polish citizens: 0.26%, 0.19%, and 0.18%,\nrespectively.\n\n\n\n**One of the", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 15, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9287, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 57, "end": 74, "key": "sample:jad_paddy_docs:000001:15:3:0", "source": "gold", "luna_reason": "Survey data estimates refugee wages and supports the reported comparison.", "usage_type": "evidential", "specificity": "named"}, {"text": "NBP’s\n2024 survey", "probe_tag": "confusion", "probe_score": 0.533, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 212, "end": 229, "key": "sample:jad_paddy_docs:000001:15:3:1", "source": "gold", "luna_reason": null}, {"text": "NBP (2024) survey", "probe_tag": "confusion", "probe_score": 0.0598, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 424, "end": 441, "key": "sample:jad_paddy_docs:000001:15:3:2", "source": "gold", "luna_reason": null}]}
-{"text": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n# Recommendations\n\n\n\nHost countries and communities have made\ncommendable and continuous efforts to support\nrefugees in accessing essential health and MHPSS\nservices. While most respondents reported\nadequate access, barriers to services changed and\nincreased for some refugees. These changes do not\ntake the same form for all refugees, and\nintersectional factors related to gender, age,\ndisability, and chronic illness continue to impact the\nexperiences and needs of refugees from Ukraine in\nthis regard. The recommendations below highlight\nkey priorities and actions for governments and RRP\npartners to address these challenges and enhance\nrefugees’ access to care in host countries.\n\n\nThese actions aim to support governments and\nlocal communities in strengthening health and\nMHPSS systems in areas impacted by refugee\narrivals and advancing the integration of refugees\ninto national systems. Achieving these goals will\nrequire long-term planning and sustained funding\ncommitments.\n\n\n\n\n\n\n\n9. <u>[Integration of migrant and refugee data in health information systems in Europe: advancing evidence, policy and practice](https://doi.org/10.1016/j.lanepe.2023.100744)</u>\n\n\n**28**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "migrant and refugee data", "probe_tag": "confusion", "probe_score": 0.74, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1084, "end": 1108, "key": "sample:jad_paddy_docs:000004:27:0:0", "source": "gold", "luna_reason": null}]}
-{"text": ".**\nUkrainian refugees earn the highest\nwages in manufacturing, health, and\naccommodation and food service activities,\nwhile the lowest in education, other\nservices, and construction. A comparison\nto median earnings in these sectors in the\neconomy as a whole (after recalculation\nfrom gross to net earnings) changes that\norder, with Ukrainian refugees employed in\naccommodation and food service activities,\nand construction earning more than\n100% of all workers median, and education,\nhealth services, and transportation and\nstorage on the lowest ranks. Earnings\n\n\n\nrelative to the total economy would be\nlower, if gross wages were compared,\nbecause Ukrainian refugees are less\nlikely to have employment contracts and\npay social contributions on their entire\nearnings. <sup>16</sup> Ukrainian refugees employed\nin education have the lowest median\nnet wages when compared to other\nsectors. This is likely due to occupational\nregulations that prevent persons with nonEU citizenship from working as teachers in\npublic schools, which is further discussed\nin chapter 4.\n\n\n\n4,198 4,216\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey and GUS data.\n\n\n© UNHCR / Anna Liminowicz\n\n\n\n16 As refugees more often than average in the Polish economy work based on civil law contracts or self-employment, they may not be covered by employee\nprotections denoted in the labour code. Furthermore, if they pay lower pension contributions, they will receive lower pensions in the future, as Poland has a defined\ncontribution system. It also lowers their sick leave benefits.\n\n\n20\n\n\n\n21", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9874, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1124, "end": 1141, "key": "sample:jad_paddy_docs:000001:10:1:0", "source": "gold", "luna_reason": null}, {"text": "GUS data", "probe_tag": "confusion", "probe_score": 0.8815, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1146, "end": 1154, "key": "sample:jad_paddy_docs:000001:10:1:1", "source": "gold", "luna_reason": null}]}
+{"text": " workers in the\neconomy, but also accounts for increased\nproductivity brought about by more\nspecialization. Considering all aspects, the\noverall impact of the refugees has been\npredominantly positive, and it moved the\nPolish economy to a higher growth path.\nRefugees contribute to the economy\nslightly more than their employment\nshare – they increase the labour supply\nas both workers and entrepreneurs and\nexpand demand as consumers. The rise\nin productivity due to more specialization\nacross the labour force further boosts\nthe economy. The impact of refugees\nis lowered by a temporary decrease in\nthe capital-to-labour ratio (companies\nneed time to invest in equipment and\nmachines to match the rise in the number\nof workers), as well as an increase in\ncompetition on the labour market.\n\n\n**The figures are higher than those in**\n**the previous Deloitte (2024) report,**\n**which – due to scant data available**\n**at the time – did not account for the**\n**positive impact on labour productivity.**\nIn the earlier report, the overall positive\nimpact of refugees was reduced based on\nconservative assumptions, in the absence\nof available/clear data on the increased\ncompetition in the labour market. The\n\n\n\nmodel notably considered lower wages\nand higher unemployment among native\nworkers. However, recent data indicates\nthat these concerns did not materialize.\nInstead, Polish workers have moved on to\nbetter paid occupations, and the economy\nhas benefited from a larger pool of talent,\nenabling deeper specialization and\nincreased productivity growth.\n\n##### Remaining challenges\n\n\n**Despite significant progress in**\n**integrating refugees into the labour**\n**market, several challenges persist.**\nRefugees are half as likely to have an\nemployment contract as Polish citizens\nand few of them achieve high incomes.\nAlthough refugees have been moving on\nto more desirable professions at a faster\nrate than other groups in the economy,\ntheir jobs continue to be disproportionately\nskewed towards elementary occupations.\nThese issues are most evident among\nthose with", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 2, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "recent data", "probe_tag": "confusion", "probe_score": 0.4682, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1299, "end": 1310, "key": "sample:jad_paddy_docs:000001:2:3:0", "source": "gold", "luna_reason": null}]}
+{"text": " additionally a positive\nimpact on labour productivity that cannot\nbe accounted for using the available data.\nThese effects could stem from the growth\nin specialisation due to additional workers\nwith different skillsets appearing on the\nlabour market, e.g., occupational upgrading\nof native workers.\n\n\n\n**Immigrants could possess complementary skills that**\n**make native workers more productive as they specialise.**\nThese skills do not even need to be advanced to be\ncomplementary. Natives are likely to deal better with\ncommunications-intensive tasks and have better networking, all\nof which may be better paid and not easily transferable between\ncountries. OECD (2016) gives an example of a native carpenter,\nwho employs an immigrant to do his previous manual tasks\nand himself focuses on marketing and business development.\nSuch occupational upgrading has been first shown in a seminal\npaper by Peri and Sparber (2009) in the USA data, but has been\nquickly extended to other countries. From this perspective\nFoged and Peri (2016) look at refugees in Denmark in the 19912008 period. They find that inflow of low-skill refugees caused\nless educated native workers to pursue less manual-intensive\ntasks - improving their wages, employment, and occupational\nmobility. These effects are causal, as the authors exploit the\nrefugee dispersal system, which is orthogonal to economic\nopportunities.\n\n\n**Immigrants could enter childcare, elderly care, and**\n**housekeeping services, allowing highly educated and**\n**productive native women to increase their labour supply.**\nA caveat in the case of refugees from Ukraine is that this could\nmean working below their qualifications or in the informal\nsector, making the overall effect for productivity unclear.\nNevertheless, as availability of care and housework services\nincreases, it becomes easier for women mainly to combine\nfamily and professional lives and increase labour supply.\nSuch effects may be stronger for countries with less accessible\nchildcare. Furtado (2015) reviews this literature, finding evidence\nfrom Australia, Hong", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "USA data", "probe_tag": "confusion", "probe_score": 0.8086, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 931, "end": 939, "key": "sample:jad_paddy_docs:000007:20:1:0", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nTo account for refugees impact on\neconomy shocks for economy were\ncalibrated according to existing data.\nAs the refugees started coming to Poland\nby the end of February and in March\n2022 it was assumed that their impact\non the economy should be seen starting\nfrom the second quarter of 2022. As such\ntheir primary impact on yearly data was\ndivided as between 2022 and 2023 setting\n¾ of it in 2022 and ¼ in 2023. The total\nnumber of refugees was set according to\nthe newest data from the PESEL registry\n(Chart 3. in Chapter 1). Their employment\nwas calibrated to match data presented\nin Chapter 2. Changes in population and\n\n\n\nlabour supply in Poland were offset by\nequivalent changes for Eastern Europe\nregion <sup>41</sup> [^41: Aggregate region in model consisting of Ukraine, Russia, Belarus, Moldova, Czechia, Slovakia, Hungary, Romania and Bulgaria.] . It was also assumed that refugees\nshould have higher spending needs which\nmeans a lower saving rate than natives.\nMoreover, data shows that it is partially\nfinanced by savings they have in Ukrainian\nbanks which was calibrated as them having\nnegative saving rate while being offset\nby lowering investment levels in Eastern\nEurope <sup>42</sup> [^42: In other words it was assumed that money that would be spent e.g. through credit action for investments in Eastern Europe were spent for\nconsumption in Poland.] . Lastly, their productivity may\ndiffer from productivity of natives (Box 2)\nwhich also was taken into account.\nIn total there were three major sources\nof uncertainty: total level of employment,\nproductivity, and impact on consumption.\n\n\n\nwould increase GDP by 0.9-1.3% – the mid\nto higher bound of our estimate.\nThird, Urban (2022) uses an Oxford\nEconomics model to estimate the impact of\nUkrainian refugees on the potential GDP by\n2030", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "yearly data", "probe_tag": "confusion", "probe_score": 0.8706, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 476, "end": 487, "key": "sample:jad_paddy_docs:000007:17:0:0", "source": "gold", "luna_reason": null}, {"text": "PESEL registry", "probe_tag": "keep", "probe_score": 0.9697, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 639, "end": 653, "key": "sample:jad_paddy_docs:000007:17:0:1", "source": "gold", "luna_reason": null}]}
+{"text": ". The complete questionnaires, along with the\nconsolidated anonymized dataset, are available in\nthe <u>[UNHCR Microdata Library.](https://microdata.unhcr.org/index.php/catalog/?page=1&from=2023&to=2024&region%5B%5D=3&ps=100)</u>\n\n\n# Limitations\n\nThis analysis has several limitations that should be\nconsidered when interpreting the findings. First, due\nto sampling constraints (lack of complete sampling\nframe) and the non-probabilistic selection of\nrespondents, the results may not fully represent the\nentire Ukrainian refugee population. Additionally,\nthe choice of sampling locations may have\nintroduced a bias toward more vulnerable segments\nof the population. Variations in sampling\napproaches and data collection periods across\ncountries can also affect comparability.\n\n\nThe findings on disability, chronic illness, and\nvaccination are based on self-reports and were not\nverified against medical records, which may impact\ntheir accuracy.\n\n\nA high non-response rate was observed for\nsensitive questions related to mental health,\npsychosocial well-being, protection, income and\nexpenditure which could affect the completeness of\nthe data. Additionally, the survey results for certain\nindicators, such as infant and young child feeding\nand SRH barriers, should be interpreted with\ncaution due to the small sample size or low\nresponse rates. As a result, some indicators could\nnot be further analyzed to assess how factors such\nas gender, age, disability, or place of residence\nimpact access to health and MHPSS services.\n\n\nIt is also important to note that there were slight\ndifferences in the questionnaire across countries\nand years, such as adjustments to answer options.\nTherefore, the regional trend analysis was limited to\nquestions that were consistently used across all\nparticipating countries and years to ensure\ncomparability. Furthermore, certain indicators were\nexcluded from the regional analysis due to\ninsufficient sample size or the unavailability of data\nacross all countries.\n\n\n\n7. <u>[", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "consolidated anonymized dataset", "probe_tag": "confusion", "probe_score": 0.1552, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 46, "end": 77, "key": "sample:jad_paddy_docs:000004:6:1:0", "source": "gold", "luna_reason": null}]}
 {"text": "’s\nRegulated Professions Database. This can\nbe a problem, as occupational licensing is\ncited in the literature among the reasons\nfor occupational downgrading of migrants.\nCassidy and Dacass (2021) found that in the\nUnited States, immigrants were significantly\nless likely to have a license than similar\n\n\n\n**Chart 21. Share of regulated professions by citizenship and legal status, Q2 2024**\n\n\n\n**The educational premium seems**\n**to be lower for Ukrainian refugees**\n**compared to the general workforce**\n**in Poland.** According to the SEIS survey,\nUkrainian refugees with master’s and\nPhD degrees earn a 22% higher median\nnet wage than those with only secondary\neducation. This appears to be a small\ngain, even accounting for the fact that,\ngenerally, the differences between median\nwages are less pronounced than between\naverage wages (which are pulled higher\nby top incomes) and that our method of\nwage estimation based on SEIS household\nincomes <sup>26</sup> [^26: As described in chapter 2, SEIS measures incomes on the household level. Using it to estimate individual wages likely underrepresents lowest and highest incomes.\nDetails are available in the Online Technical Appendix.] flattens the distribution.\nAccording to the most recent estimate in\nOctober 2022, in the economy as a whole,\nthe average gross wage of master’s and\nPhD degree holders was 84% higher than\nthose with only secondary education. <sup>27</sup> [^27: Note that the GUS (2024) data for the host population is not exactly comparable, as it does not include microenterprises, it covers an earlier period and focuses on\ngross and average wages.]\n\n\n\n**Most Ukrainian refugees work in**\n**a different sector than previously**\n**in Ukraine, which also points to**\n**occupational downgrading.** The SEIS\nsurvey indicates that 34% of Ukrainian\nrefugees currently employed in Poland\nwork in the same sector", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "SEIS survey", "probe_tag": "keep", "probe_score": 0.9814, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 538, "end": 549, "key": "sample:jad_paddy_docs:000001:14:2:0", "source": "gold", "luna_reason": "SEIS survey supports attributed wage and employment-sector findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "SEIS household\nincomes", "probe_tag": "confusion", "probe_score": 0.8237, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 928, "end": 950, "key": "sample:jad_paddy_docs:000001:14:2:1", "source": "gold", "luna_reason": null}]}
-{"text": " by\n1.4 pp. (PLN 6,000-8,000), 0.6 pp.\n(PLN 8,000-10,000), and 0.3 pp. (above\nPLN 10,000) (see Chart 30).\n\n\n\nThird, cross-section regression analysis\nshows that poviats with a higher number of\nUkrainian refugees saw a greater increase\nin wages, which was caused by larger\nshare of refugees in local employment.\nDue to limitations in the wage dataset,\nour calculations incorporated yearly data.\nCross-section models were estimated using\na data sample for all 380 poviats in 2023.\nThe share of Ukrainian refugees among\nall employed, temporarily employed, and\nself-employed persons insured at ZUS in a\ngiven poviat was averaged across quarters\nto construct a yearly variable. The wage\nvariable is the GUS data series on gross\nmonthly wages and salaries <sup>30</sup> [^30: Unfortunately, GUS data for these time periods and poviat level include the enterprise sector (firms that employ 10 or more persons) and public sector, which is\nmost of the labour market, but not the total economy.], and taken\nas nominal change in 2023 from 2022.\nThe ordinary least squares cross-section\nmodel shows that in 2023, a 1 percentage\npoint increase in the employment share of\nUkrainian refugees was associated with an\nincrease in wages of PLN 66. Given that in a\nmean poviat gross wage growth amounted\nto PLN 757 and the gross wage in the\nprevious year was PLN 5,803, wages have\ngrown by 13.1% in nominal terms (including\ninflation), of which 0.7 percentage points\nwere associated with Ukrainian refugees\n(considering the fact that the employment\nshare of the Ukrainian refugees in a mean\npoviat was 0.61%).\n\n\nInstrumental variables regressions were\nperformed with the Two Stage Least\nSquares technique. In the first stage, it\nadjusts for the non-random distribution\nof Ukrainian refugees across poviats,\nand in the second stage, it calculates\nthe models. These results can be\ninterpreted causally. The", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 20, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "wage dataset", "probe_tag": "keep", "probe_score": 0.9753, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 337, "end": 349, "key": "sample:jad_paddy_docs:000001:20:2:0", "source": "gold", "luna_reason": "Existing wage data informed calculations using yearly observations.", "usage_type": "declaration", "specificity": "vague"}, {"text": "yearly data", "probe_tag": "keep", "probe_score": 0.9971, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 381, "end": 392, "key": "sample:jad_paddy_docs:000001:20:2:1", "source": "gold", "luna_reason": null}, {"text": "GUS data series", "probe_tag": "confusion", "probe_score": 0.8794, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 698, "end": 713, "key": "sample:jad_paddy_docs:000001:20:2:2", "source": "gold", "luna_reason": null}, {"text": "GUS data", "probe_tag": "keep", "probe_score": 0.9712, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 785, "end": 793, "key": "sample:jad_paddy_docs:000001:20:2:3", "source": "gold", "luna_reason": null}]}
-{"text": " overall.\nThese connections are important to bear in mind when designing government, development, and humanitarian\nsupport programs.\n\n\nEmployment continues to be closely associated with lower poverty rates, though ultimately, it’s the size of\nincome that is generated by working household members that makes the biggest difference. Considering that\nthe share of working-age refugees that are employed is nearing host population levels after rising further in\n2024, attention should now turn to wages. Data on the latter, which was derived from household level\nindicators, demonstrates that refugees on average make two-thirds of what the local population does per hour\nof work. Low wage premiums for higher education levels and the fact that some 60% of current refugee\nemployees have a background in an entirely different sector of the economy, suggest the presence of\nunderemployment and skills mismatching. This assertion is corroborated by nearly 35% of employed refugees\nin the region reporting few available jobs with adequate pay, lack of positions that match their skills, or issues\nwith getting their qualifications recognized. Moreover, almost the same percentage indicate lack of local\nlanguage knowledge to be a problem, a well-acknowledged barrier to skilled employment.\n\n\n**Based on the above findings it is recommended that:**\n\n\n- Governments, development and humanitarian actors take into account poverty levels when designing their\nsupport programs for Ukrainian refugees. The quality of day to day life, safety, and level of access to key\nservices are directly tied to household income.\n\n- Poverty measures account for differences in housing costs between refugees and host populations.\n\n- A special focus is placed on supporting refugee employment at their skill level, including transition from\ncurrent low-level jobs. The difference between refugee and local population wages could be an important\nmetric to monitor on an ongoing basis\n\n\n1. Compared to the <u>[2023 MSNA data](https://data.unhcr.org/en/documents/details/108068)</u>\n2.", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 2, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household level\nindicators", "probe_tag": "confusion", "probe_score": 0.1331, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 544, "end": 570, "key": "sample:jad_paddy_docs:000010:2:1:0", "source": "gold", "luna_reason": null}, {"text": "2023 MSNA data", "probe_tag": "confusion", "probe_score": 0.6904, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1982, "end": 1996, "key": "sample:jad_paddy_docs:000010:2:1:1", "source": "gold", "luna_reason": "Named 2023 MSNA dataset used as a comparison source.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " circular migration, with Ukrainians\ncoming to Poland for half of the year,\nthen returning to Ukraine for another six\nmonths, and coming back to Poland. The\ndata on employers’ declarations do not\nreveal the actual number of Ukrainian\ncitizens who followed this system – a single\nperson could hold several declarations,\nbecause with every change of employer\nor promotion at the same employer they\nhad to ask for a new declaration. What is\nmore, with stays shorter than one year,\n\n\n\nthose people fell outside the definitions\nof population used by Statistics Poland\n(Główny Urząd Statystyczny, GUS,\nPoland’s statistical office). The National\nBank of Poland estimated that between\n2014 and 2018, there were approximately\none to two million Ukrainian workers\nin Poland at a time (Strzelecki, Growiec\nand Wyszyński, 2022). According to the\n2021 Polish National Census, one year\nbefore the outbreak of the full-scale war\nin Ukraine there were about one million\nUkrainian citizens residing in Poland,\nalmost all of them on a temporary basis.\n\n\n\nAfter the full-scale Russian invasion of\nUkraine, Poland experienced a massive\ninflux of refugees – with more than\n27 million border crossings from Ukraine\nand more than 1.9 million applications for\nprotection submitted by April 7, 2025 <sup>1</sup> . Not\nall of those people stayed in Poland. Many\n\n\n\nof them later returned to Ukraine or moved\nto other countries. By February 14, 2025,\nPESEL UKR <sup>2</sup> [^2: PESEL UKR is a version of Polish national ID number for Ukrainian citizens in connection with the armed conflict in the territory of that country.] holders who remained\nin Poland stood at less than 1 million,\nwhile the border movement balance\nbetween Poland and Ukraine was slightly\nbelow 2 million.\n\n\n\n1 UNHCR data, <u>https://data2.unhcr.org/en/situations/ukraine</u>\n\n2 PESEL UKR is a version of Polish national ID number for Ukrainian citizens in connection with the armed conflict in", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on employers’ declarations", "probe_tag": "confusion", "probe_score": 0.2361, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 157, "end": 188, "key": "sample:jad_paddy_docs:000001:3:1:0", "source": "gold", "luna_reason": null}, {"text": "2021 Polish National Census", "probe_tag": "confusion", "probe_score": 0.6833, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 834, "end": 861, "key": "sample:jad_paddy_docs:000001:3:1:1", "source": "gold", "luna_reason": null}, {"text": "UNHCR data", "probe_tag": "keep", "probe_score": 0.9905, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1757, "end": 1767, "key": "sample:jad_paddy_docs:000001:3:1:2", "source": "gold", "luna_reason": null}]}
-{"text": " SRH\nservices and one in five did not trust local\nhealthcare providers, in addition to facing language\nbarriers.\n\n\nWomen with a disability reported more barriers with\n11% across the region (N=29) compared to those\nwithout disability (5%).\n\n\nAn in-depth assessment is needed to better\nunderstand sexual and reproductive health (SRH)\nneeds, the role of SRH access barriers in decisions\nto visit Ukraine, and how these barriers vary among\nwomen of different age groups, pregnant and\nbreastfeeding women, and women with disabilities.\n\n\n**Support services for survivors of gender-based**\n**violence**\nServices for survivors of gender-based violence\nencompass a range of functions, including safety\nand security, legal assistance, healthcare, mental\nhealth and psychosocial support. A critical\ncomponent is access to clinical management of\nrape to ensure timely medical treatment and care.\nAs this service is provided by the health care sector,\nas part of SRH, it is included in this analysis.\n\n\nThe SEIS identified gaps in awareness about on\navailable GBV services. In 2024, 38% of\nrespondents were unaware of health services\nproviding support to GBV survivors in their area,\nwhile 58% were unaware of available psychosocial\nsupport services. Respondents were less aware of\nhealth services in rural areas (45%) compared to\nurban areas (37%). Key barriers to accessing\nGBV-related services in general included lack of\nawareness (58%), language and cultural barriers\n(53%) and stigma/ shame (46%). This indicates that\nadditional coordinated efforts between the health,\nprotection and GBV working groups and partners\nare required to enable access to all lifesaving\nGBV-related services including clinical management\nof rape.\n\n\n**17**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 16, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "SEIS", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 994, "end": 998, "key": "sample:jad_paddy_docs:000004:16:1:0", "source": "gold", "luna_reason": null}]}
-{"text": " of workers – mostly made up\nof the youngest refugees who might not\nhave worked back in Ukraine. Employment\nin one’s pre-displacement sector appears\nto boost the median net wage by about\n6%, when compared to those who switch\nfields – a back-of-the-envelope calculation\nputs their median net earnings at 89% of\nthe overall median. However, this likely\noverstates the true effect of staying in the\nsame sector, since the higher-paid groups\n(for example, the majority of IT specialists)\n\n\n\nwere more likely to remain in their original\nindustry.\n\n\n**Highly skilled Ukrainian refugees**\n**are likely to suffer from significant**\n**downgrading.** With the median wages\nof Ukrainian refugees estimated at 84%\n(SEIS survey) or 80% (NBP 2024 survey)\nof the national median (see chapter 2),\nthe difference for average wages may be\neven larger. This is because medians are\ninsensitive to high earners who typically\ninflate average earnings. Such high earners\nmay suffer significant downgrading\nconsidering the unfavourable occupational\nstructure of Ukrainian refugees. There are\nmany reasons to this, from occupational\nlicensing to a high level of language fluency\nrequired by high-skill jobs. <sup>28</sup> [^28: Lessem and Sanders (2020) modelled immigrant wage growth in the United States, finding that in a counterfactual model eliminating barriers to occupational entry\nwould lead to only small earnings increase for the average immigrant, but a substantial increase for the most highly skilled.]\n\n\n\nUkrainian\n\nrefugees\n\n\n\n\n\n\n\n\n\n\n\n\n\nPre-war\nUkrainians\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nOther\nforeigners\n\n\n\nPolish\ncitizens\n\n\n\nDrivers (truck, bus)\n\n\nTeachers\n\n\nMedical professions\n(physician, dentist, nurse, midwife)\n\n\nLegal professions\n(legal counsel, barrister, notary, bailiff)\n\n\nTaxi drivers\n\n\nOthers\n\n\nSource: Deloitte own elaboration based on ZUS data\non June 30th 2024.\n\n\n\n26 As described in chapter 2, SEIS measures incomes on the household level. Using it to estimate individual wages likely underrepresents lowest and highest incomes.\nDetails are available in the Online Technical Appendix.\n\n27 Note that the GUS (2024) data for", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "SEIS survey", "probe_tag": "confusion", "probe_score": 0.5162, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 703, "end": 714, "key": "sample:jad_paddy_docs:000001:14:3:0", "source": "gold", "luna_reason": null}, {"text": "NBP 2024 survey", "probe_tag": "confusion", "probe_score": 0.8219, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 724, "end": 739, "key": "sample:jad_paddy_docs:000001:14:3:1", "source": "gold", "luna_reason": null}, {"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.9997, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1825, "end": 1833, "key": "sample:jad_paddy_docs:000001:14:3:2", "source": "gold", "luna_reason": null}, {"text": "SEIS", "probe_tag": "drop", "probe_score": 0.0004, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1886, "end": 1890, "key": "sample:jad_paddy_docs:000001:14:3:3", "source": "gold", "luna_reason": null}]}
-{"text": ">dropouts and learning outcomes, a few different scenarios were considered.</mark>\n\n<mark>43.</mark> **<mark>It was assumed that those households in the bottom quintiles (the poorest 40 percent) would be the</mark>**\n**<mark>most affected by the pandemic.</mark>** <mark>According to the</mark> <mark>Uganda National Household Survey (UNHS) 2016/17, these</mark>\n<mark>households account for 54 and 24 percent of the total children and youth currently enrolled in public primary and</mark>\n\n\nPage 18 of 43\n\n\nOfficial Use", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 22, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Uganda National Household Survey", "probe_tag": "keep", "probe_score": 0.9868, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 301, "end": 333, "key": "sample:jdc_operational:000034:22:2:0", "source": "gold", "luna_reason": "Named survey supports enrollment figures for poorer households.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# Non-technical summary\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nSwift legal action facilitated labour market\nintegration of refugees. After the beginning\nof the full-scale war on 26th February\n2022, the European Union activated the\nTemporary Protection Directive on 4th\nMarch 2022, and the Polish parliament\npassed a special act to facilitate refugee\nintegration on 12th March 2022. Ukrainian\nrefugees in Poland were granted instant\naccess to the job market, health care, and\neducation. The authorities granted people\nescaping Ukraine legal residency for a\nperiod of eighteen months and enabled\nthem to access digital services and basic\nadministrative systems like PESEL.\nThus, the policies that have previously\nhampered job market integration of\nrefugees in other contexts, such as\ntemporary labour market bans (Fasani,\nFrattini, & Minale, 2021) and forced\ndispersals (Fasani, Frattini, & Minale, 2022),\nhave been avoided.\n\n\nThe high employment rate of refugees\nin Poland covers not only employees,\nbut also entrepreneurs. Five percent of\nUkrainian refugees registered for social\nsecurity have set up a business or work as\nfreelancers. Similar results can be gleaned\nfrom the Multi-Sector Needs Assessment\nPoland 2023 survey results, which show\nthat slightly more than 5% of respondent\nhouseholds receive income from selfemployment or similar activities.\n\n\n\nAll broad sectors of the economy saw an\nincrease in the number of workers with\nUkrainian citizenship and social insurance\nsince 2021, apart from storage and\ntransportation. The number increased\nthe most in manufacturing (almost by\n34 thousand), accommodation and food\n(more than 18 thousand), and wholesale\nand retail trade (more than 18 thousand). <sup>11</sup>\nWhile public data does not distinguish\nbetween refugees entering these sectors\nand pre-2022 Ukrainian workers changing\njobs, it is largely consistent with the MSNA\nPoland 2023 survey, in which the most\nrefugees are employed", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Multi-Sector Needs Assessment\nPoland 2023 survey", "probe_tag": "confusion", "probe_score": 0.886, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1290, "end": 1338, "key": "sample:jad_paddy_docs:000007:3:0:0", "source": "gold", "luna_reason": null}, {"text": "public data", "probe_tag": "keep", "probe_score": 0.9754, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1841, "end": 1852, "key": "sample:jad_paddy_docs:000007:3:0:1", "source": "gold", "luna_reason": null}, {"text": "MSNA\nPoland 2023 survey", "probe_tag": "confusion", "probe_score": 0.8983, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1994, "end": 2017, "key": "sample:jad_paddy_docs:000007:3:0:2", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **2.** Situation of refugees from Ukraine on the labour market in Poland\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 7.** Unemployment rate\n\n\n12%\n\n\n10%\n\n\n8%\n\n\n6%\n\n\n4%\n\n\n2%\n\n\n0%\n\n\n**Source:** Harmonized data, Eurostat, <u>[Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/une_rt_m/default/table?lang=en)</u>\n\n\n##### Refugees from Ukraine fit well into the needs of the Polish labour market.\n\nUkrainians arrived on a labour market that\nstructurally needs more workers, as the\ndomestic population is ageing rapidly, while\nthe economy is growing. High levels of\neducation, cultural proximity and previous\nconnections to Poland helped refugees\nadapt to the labour market. Furthermore,\nPoland made an important and strategic\npolicy decision by promptly opening\nthe labour market and supporting their\ninclusion.\n\n\n16\n\n\n\n17\n\n\n\n**Chart 6.** Working age population with Polish citizenship (20-64 years old)\n\n\n\n25\n\n\n24\n\n\n23\n\n\n22\n\n\n21\n\n\n20\n\n\n\n\n\n\n\n\n\n\n\nThe number of people of working age\nin Poland is shrinking and is expected\nto keep declining. Although substantial\nmigrations from Poland after EU accession\nin 2004 <sup>19</sup> [^19: Statistics Poland data, <u>[https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n<u>[temporary-stay-from-poland-between-2004-2020,8,14.html](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>] distort population data, the\ndomestic", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 8, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Harmonized data", "probe_tag": "keep", "probe_score": 0.993, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 309, "end": 324, "key": "sample:jad_paddy_docs:000007:8:0:0", "source": "gold", "luna_reason": null}, {"text": "Statistics Poland data", "probe_tag": "keep", "probe_score": 0.9929, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1275, "end": 1297, "key": "sample:jad_paddy_docs:000007:8:0:1", "source": "gold", "luna_reason": null}, {"text": "population data", "probe_tag": "confusion", "probe_score": 0.6838, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1857, "end": 1872, "key": "sample:jad_paddy_docs:000007:8:0:2", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nImportantly, most of the income of\nUkrainian nationals living in Poland, both\nrefugees and pre-2022 migrants, comes\nfrom their work. Our calculations based\non the UNHCR MSNA Poland 2023 survey\nresults show that 80% of refugee income\ncomes from employment, with other\nsources on average playing a much lesser\nrole. The income brackets presented in the\nsurvey show that 20% of households earn\nless than 3000 PLN, 41% earn between\n3,000 and 6,000 PLN and 12% earn more\nthan 6,000 PLN, while 27% of respondents\npreferred not to answer. Meanwhile, in the\nNBP (2023) survey conducted in November\n2022 the net income of refugees oscillated\nbetween 2,000 and 3,000 PLN, while the\nnet income of pre-2022 migrants was\ncloser to between 3,000 and 4,000 PLN.\nIn the case of Ukrainians that were out\nof work, the monthly income was more\nvaried, especially because there were fewer\nprevious migrants in this situation.\nThe median income for non-employed prewar immigrants was around 2,500 PLN <sup>32</sup> .\nAmong refugees from Ukraine remaining\nout of work at the time of the survey, the\nmedian income equaled around 600 PLN.\n\n\nThe standard of living of refugees from\nUkraine may be significantly lower than\nnatives, even at similar incomes due to\ntheir lack of housing capital. 87% of the\npopulation in Poland resided in owneroccupied housing in 2021 and 2022,\naccording to Eurostat. As most refugees\nfrom Ukraine do not possess housing of\ntheir own in Poland, they need to rent in a\nrelatively tight market, especially when they\nreside in large metropolitan areas that offer\nthe most opportunities. Initially, in the first\nmonth after the outbreak of the full-scale\nwar in Ukraine, the number of renting\noffers in the OLX and Otodom portals\ndropped by approximately 60%, though it\nlater", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR MSNA Poland 2023 survey", "probe_tag": "keep", "probe_score": 0.9899, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 239, "end": 268, "key": "sample:jad_paddy_docs:000007:14:0:0", "source": "gold", "luna_reason": "Survey results support calculations and income-distribution findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "NBP (2023) survey", "probe_tag": "confusion", "probe_score": 0.8845, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 626, "end": 643, "key": "sample:jad_paddy_docs:000007:14:0:1", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **1.** Inflow of refugees from Ukraine into Poland\n\n##### Even before the 2022 full-scale war in Ukraine the number of Ukrainians in Poland was substantial and growing, although their precise number is difficult to measure.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 1.** Ukrainian workers with social insurance.\n\n\nRate of change (right axis) Number (left axis)\n\n\n\n**Source:** Deloitte own elaboration based on ZUS data.\n\n\n\n1000\n\n\n750\n\n\n500\n\n\n250\n\n\n0\n\n\n\n\n\n\n\n120%\n\n\n100%\n\n\n80%\n\n\n60%\n\n\n40%\n\n\n20%\n\n\n0%\n\n\n-20%\n\n\n\n\n\n\n\n\n\nA steady inflow of migrants could be\nobserved in the last decade since 2014,\nwhen armed conflict erupted in Eastern\nUkraine. As the Ukrainian economy\nsuffered and its currency lost value, many\nUkrainians came to Poland looking for\nwork. Most of them came on a guest\nworker basis, enabled by a law from 2011,\nthat allowed Ukrainians and five other\nnations to work in Poland for 6 months\nduring a year without a work permit, based\non employers' declaration. This was a\ncircular migration, in which they returned to\nUkraine once the 6 month period expired.\nIn effect most stayed in Poland for less\nthan twelve months and therefore were\nnot included in the resident population or\nother national population estimates.\nA National Bank of Poland research paper\nestimates that between 2014 and 2018,\nbetween one and two million Ukrainian\nworkers arrived in the country (Strzelecki,\nGrowiec and Wyszyński, 2022).\nHard data on the number of Ukrainian\nworkers in Poland before 2022 are limited\n\n\n12\n\n\n\nand might understate their presence.\nThe only hard data on these flows is the\nnumber of Ukrainian workers with social\ninsurance, which nevertheless understates\nthe numbers, as certain kinds of legal\nwork often undertaken by temporary\nemployees did not require it, and some\nUkrainians worked in the shadow economy.\nThe", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.9775, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 530, "end": 538, "key": "sample:jad_paddy_docs:000007:6:0:0", "source": "gold", "luna_reason": null}, {"text": "hard data", "probe_tag": "confusion", "probe_score": 0.7393, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1671, "end": 1680, "key": "sample:jad_paddy_docs:000007:6:0:1", "source": "gold", "luna_reason": null}]}
+{"text": " larger share of data being collected from more\nvulnerable households.\n\n\nThere was also a notably high non-response rate regarding questions related to income and expenditure,\nwhich likely resulted in non-response bias. The income module of the SEIS was also materially different from\nthe one employed by the EU SILC and the Republic of Moldova’s Household Budget Survey, which may limit\ncomparability of this data to that of host populations.\n\n\nIt is also important to highlight that there were slight differences in the questionnaire across countries. Not all\nquestions were consistently included in all country-level surveys, and some answer options were individually\nadjusted.\n\n\nLastly, the survey was conducted during the summer months, coinciding with both host country and Ukraine\nschool holidays. This period often sees many households temporarily visiting Ukraine, which impacted the\naccessibility of households and posed challenges in meeting targets, particularly in certain countries and\ngeographic locations.\n\n\n**15**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Household Budget Survey", "probe_tag": "drop", "probe_score": 0.0183, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 347, "end": 370, "key": "sample:jad_paddy_docs:000010:14:1:0", "source": "gold", "luna_reason": null}]}
+{"text": "\neducational attainment from November 2022\nsurvey) to 19% (July-August 2023) higher\n\nearnings than the general population. <sup>36</sup>\n\n\nPoviat-level geographical distribution of\nUkrainian refugees is more concentrated in\nhigh productivity agglomerations, implying\n7% higher earnings than for other workers\nregistered for social security. <sup>37</sup>\n\n\nThere is no publicly available hard data on the\nsectoral distribution of Ukrainian refugees,\nwhich we proxy by the growth in employees\nwith Ukrainian citizenship registered for social\nsecurity since the outbreak of the full-scale\nwar in Ukraine (unfortunately this to some\nextent will be Ukrainian workers previously\npresent in Poland who changed jobs) – this\nimperfect proxy implies 7% lower earnings\nthan general workers. <sup>38</sup>\n\n\n\nSmaller firm sizes of employers\nof Ukrainian refugees imply their\n8% lower productivity (and thus earnings)\nfrom the general population. <sup>39</sup>\n\n\nMost of all, occupational distribution of\nUkrainian refugee workers from ZUS implies\n21% lower earnings from the general\npopulation when measured by nine large\noccupational groups and 23% lower by\ndetailed occupations. <sup>40</sup>\n\n\n\n5000 6000 7000 8000 9000 10000 11000 12000\n\n\n**Average monthly gross earnings in enterprise sector in poviat of employment in 2022**\n\n\nNatives and other immigrants\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n36  Note that these percentages are only indicative, as Ukrainian refugee educational attainment is assumed on the basis of November 2022 NBP\n(2023) survey for 18+ age group and July-August 2023 UNHCR (2023) survey for 15+ age group, while the general population is taken from the 2022\nLabour Force Survey for 15-74 (broadest available) age group, and earnings by educational attainment are taken from the GUS (2022) “Structure of\nwages and salaries by occupations in October 2020”.\n37  Note that the numbers of Ukrainian refugees and all workers", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "NBP\n(2023) survey", "probe_tag": "confusion", "probe_score": 0.0869, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1504, "end": 1521, "key": "sample:jad_paddy_docs:000007:16:2:0", "source": "gold", "luna_reason": "Survey data underpin assumed Ukrainian refugee educational attainment.", "usage_type": "evidential", "specificity": "named"}, {"text": "UNHCR (2023) survey", "probe_tag": "drop", "probe_score": 0.002, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1561, "end": 1580, "key": "sample:jad_paddy_docs:000007:16:2:1", "source": "gold", "luna_reason": null}, {"text": "2022\nLabour Force Survey", "probe_tag": "confusion", "probe_score": 0.5191, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1647, "end": 1671, "key": "sample:jad_paddy_docs:000007:16:2:2", "source": "gold", "luna_reason": "Survey data provide the general-population basis for comparative earnings analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "529 refugees within the region (Arua district is about 50\nkm from Koboko and connected to South Sudan by the KYM road, Adjumani district is about 30 km from\nMoyo and connected to DRC border at Oraba by KYM road). It is a gravel road with poor geometry in a few\nplaces; passes through low-lying areas and seasonal swamps; and constrained to provide all-weather\nconnectivity. It has narrow, damaged and non-functional cross-drainage structures and the transport\nsituation worsens during rainy season when some of the rivers and their tributaries flood and cut off access.\nThis road corridor connects DRC and South Sudan through Uganda and is an alternate route to reach the\n\n\n32 UNRA Diagnostic Study funded by the World Bank – DFID multi-donor trust fund\n33 The host and refugee population of Koboko district are 258,000 and 5,423 (2 percent of the host population) respectively, the host\nand refugee population of Yumbe district are 663,600 and 232,109 (35 percent of host population) respectively, and the host and\nrefugee population of Obongi district, which is a new district carved out of Moyo district, are 48,300 and 122,645 (254 percent of\n[host population) respectively – Source: https://data2.unhcr.org/en/country/uga](https://data2.unhcr.org/en/country/uga)\n34 Bidibidi resettlement concentration Zone 2, Lobule and Palorinya settlements are about 9 km, 6 km and 18 km away respectively\nfrom the KYM road and there are access roads to reach the settlements from the KYM road corridor.\n[35 https://data2.unhcr.org/en/documents/download/74603](https://data2.unhcr.org/en/documents/download/746", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 18, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "UNRA Diagnostic Study", "probe_tag": "keep", "probe_score": 0.9167993068695068, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 677, "end": 698, "key": "jdc_operational:000050:18:2:0", "source": "camp2", "luna_reason": "Named diagnostic study cited as an existing external assessment.", "usage_type": "declaration", "specificity": "named"}]}
 {"text": " specified package of benefits to all</mark>\n<mark>members of a society with the end goal of providing financial risk protection, improving access to health</mark>\n<mark>services and health outcomes</mark> .” <sup>9</sup> Financed from the Lebanon Syria Multi-Donor Trust Fund, the project\naims to strengthen and improve access to PHC services, especially for the low-income host communities\ncrowded out by the increased demand for PHC services from refugees. The project strengthens the\ncapacity of 75 MoPH network centers, expands the package of services provided, and subsidizes the cost\nof care to 150,000 poor Lebanese enrolled in the NPTP (see Box 2). However, strengthening the capacity\nof the network clinics also extends benefits to low-income non-subsidized Lebanese and displaced\nSyrians covered by the international community. The latest MoPH data show that improving the\ncapacity of the network centers through the EPHRP is having a positive impact on access to services for\nhost communities and displaced Syrians alike. While before the project access to PHC services was\nrelatively low, especially for host communities in areas with high concentration of displaced Syrians, it\nincreased steadily after the start of the project for both poor Lebanese (28 percent) and displaced\nSyrians (47 percent). <sup>10</sup> The project demonstrates that strengthening the integrated PHC model benefits\nboth communities.\n\n\n9 WHO, SDGs, 2016.\n10 Ministry of Public Health data, 2017.\n\n\nPage 13 of 54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 15, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "MoPH data", "probe_tag": "keep", "probe_score": 0.9351112246513367, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 850, "end": 859, "key": "jdc_operational:000032:15:1:0", "source": "camp2", "luna_reason": "Ministry of Public Health data support reported access improvements.", "usage_type": "evidential", "specificity": "named"}, {"text": "Ministry of Public Health data", "probe_tag": "keep", "probe_score": 0.92680424451828, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1448, "end": 1478, "key": "jdc_operational:000032:15:1:1", "source": "camp2", "luna_reason": "Ministry data support reported access increases for Lebanese and displaced Syrians.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "are a significant predictor of students sitting final primary school exams but that this is not\nsignificantly different from zero when looking directly at performance on standardised tests.\nAlthough point estimates on electricity access in the classroom suggest that this may improve\nperformance, these are weakly determined, and not significant at typical levels. Teacher\nperformance appears to be a statistically and economically important predictor of both test scores\nand primary school test completion, with increases in teacher absence overwhelmingly appearing to\nnegatively influence student performance. Pedagogical training in particular appears to be an\nimportant determinant of test scores, representing nearly a 1 standard deviation increase in the test\nscore distribution. These results from teacher training are supported by findings from Public\nExpenditure Tracking Survey (PETS) test score analysis (Moser, 2012). In these tests, student\nperformance responded positively to teacher training, specifically whether or not the teacher had\ncompleted a high-school diploma. The PASEC scores analysis also provides evidence in favour of\nthe effectiveness of school management committees and (weak) evidence that reductions in student/\ntextbook ratios may increase performance. In those schools where APEs meet more regularly,\nstudent performance appears to be higher by around 0.1-0.2 of a test-score standard deviation.\nReducing the number of students per French book in a classroom does seem to increase likelihood\nof passing to final exams, however similar results are not seen when reducing students per book\nratios in mathematics classes nor on the test scores. Given that the textbooks are unlikely to be\nuseless in improving learning; this potentially highlights the need for a quality-oriented intervention\nto go further than simply distributing textbooks and contemplate, for example, implementation\nmechanism promoting appropriate use of the material.\n\nRationale of the project\n\nAs illustrated above, despite recent efforts to reform the education sector, the “business as usual”\napproach has not resulted in sufficient improvements in student retention or learning outcomes. The\nproject will therefore support the government to leverage its economic growth to improve human\ndevelopment indicators by identifying", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000020", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Public\nExpenditure Tracking Survey", "probe_tag": "keep", "probe_score": 0.959823727607727, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 853, "end": 887, "key": "jdc_operational:000020:5:0:0", "source": "camp2", "luna_reason": "Survey findings are cited as evidence in test score analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "43. **_DLIs 1 - 4 on the institutional performance of and service delivery by the 22 MLGs have evolved_**\n**_to incentivize further institutional improvements_** **.** Given the high attainment of performance measures in\nthe current phase by all participating municipal LGs, the same thematic areas have been retained under the\nAF but the indicators have been revised and strengthened to incentivize further improvement <sup>41</sup> [^41: The AF will retain the same seven thematic areas: i) linkages between municipal physical plan, five-year development plan and\nannual budget, ii) own source revenue generation, iii) procurement, iv) financial management, v) program execution and\nimplementation (budget execution), vi) monitoring, enhanced accountability, transparency and communication and vii)\nenvironmental and social sustainability. Service delivery will be measured through i) quantitative outputs against plans, and ii) value\nfor the money audits as well as iii) review of operational and maintenance performance, which an added parameter.] . For example,\nAnnual Program Assessments results showed that most MLGs scored above 90 percent in the last years\nassessment of environmental and procurement indicators. The bar for such indicators has therefore been\nraised throughout. Several new indicators have also been introduced, to ensure that municipalities play their\nroles in promoting LED, including: (i) addition of Municipal Commercial Officer as a minimum condition\nin year 2 and incentives for LGs that prioritize investments through a participatory process that includes\nprivate sector representatives; (ii) organization of regular forums to hear concerns of the private sector and\ntake action on them; (iii) creation of a One Stop Center providing registration, tax education, investor\naftercare and grievance desk services; and implementation of enterprise support activities through their\ncommercial office.\n\n44. **_DLIs 5 - 6 on the support to MoLHUD to develop the necessary systems for urban development_**\n**_and management have also been strengthened and improved to focus on key results_** **", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Annual Program Assessments results", "probe_tag": "keep", "probe_score": 0.9273189902305603, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1067, "end": 1101, "key": "jdc_operational:000062:24:0:0", "source": "camp2", "luna_reason": "Past assessments provide scores showing most MLGs exceeded 90 percent.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " **The SEZs, which will enjoy trade preference to the EU, are already well established and**\n**serviced.** They have idle capacity (vacant land and capacity potential in existing factories). For example,\nin Al Mafraq, a 23 km <sup>2</sup> zone adjacent to Al Zaatari camp, only 10 percent of the land is occupied.\n\n\n12. **Jordan has a weak business environment.** In parallel with investment promotion efforts to target\nthe new opportunities described earlier, substantial reform of the business environment is required. With\nregard to Doing Business Indicators, Jordan ranks 113th globally, out of 189 countries, in 2016 (down from\n107 last year). Moreover, the business environment is reputed to be unpredictable as policy changes can\noccur with neither consultation nor notice. Implementation of regulations is also an issue—it is often\narbitrary and unpredictable. Syrian investors and other restricted nationalities (such as Iraqi and Yemeni)\nface a different treatment with regard to business entry, such as solvency requirements in the form of large\nbank deposits to obtain an investor status (JOD 250,000). In addition to addressing the business\nenvironment, other important areas that will require significant improvement as part of the implementation\nof the Compact include: (a) access to finance, which has been identified as one of the most important\nobstacles to firms operations by the recent Enterprise Survey (2013–2014); (b) incubation type support for\nsome industries—provision of rentable factory space; (c) transportation and child care (core issues for\nwomen’s employment); (d) trade facilitation; and (e) skills development. Not all of these are covered by\nthe PforR. Skills development and vocational training, as well as access to finance, are supported by other\ndonors and other programs.\n\n\n13. **Another core goal of this Bank-supported Program is", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Doing Business Indicators", "probe_tag": "keep", "probe_score": 0.9489250779151917, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 536, "end": 561, "key": "jdc_operational:000045:11:1:0", "source": "camp2", "luna_reason": "Indicators support Jordan’s stated global business-environment ranking.", "usage_type": "evidential", "specificity": "named"}, {"text": "Enterprise Survey", "probe_tag": "keep", "probe_score": 0.9000961184501648, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1407, "end": 1424, "key": "jdc_operational:000045:11:1:1", "source": "camp2", "luna_reason": "Enterprise Survey data identify access to finance as a major obstacle.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "/files/documents/UNACNorthern%20Uganda%20and%20West%20Nile%20Humanitarian%20and%20Development%20Report%20-January-February%202018.pdf)_\n_[%20Development%20Report%20-January-February%202018.pdf, p. 2.](http://ug.one.un.org/sites/default/files/documents/UNACNorthern%20Uganda%20and%20West%20Nile%20Humanitarian%20and%20Development%20Report%20-January-February%202018.pdf)_\n_19_ South Sudan Regional Refugee Response Plan, UNHCR, 2018\n20 Informing the Refugee Policy Response in Uganda: Results from the Uganda Refugee and Host Communities 2018 Household\nSurvey. Washington DC, World Bank, 2019.\n21 Uganda’s Education Response Plan for Refugees and Host Communities. Ministry of Education and Sports, 2018\n\n\nPage 10 of 80", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 14, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Uganda Refugee and Host Communities 2018 Household\nSurvey", "probe_tag": "keep", "probe_score": 0.9129970669746399, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 501, "end": 558, "key": "jdc_operational:000050:14:3:0", "source": "camp2", "luna_reason": "Bibliographic entry listing a survey, without demonstrated data use in the passage.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": " under the context of a fixed exchange rate regime that has been in effect\nfor a couple of decades and which has become a central pillar of the Lebanese economy. Poverty\nrates are relatively high, at 27.4 percent based on the latest household survey of 2011/12, and are\nestimated to have increased to 32 percent in 2017. Furthermore, a notable share of youth is employed\nin a growing informal sector which provides limited social protection and growth. For example,\ninformality affects six in 10 young workers in Lebanon with young women more likely to be affected\nthan men. <sup>2</sup> [^2: ILO: Towards Decent Work in Lebanon: Issues and Challenges in Light of the Syrian Crisis, 2015; ILO Work for Youth Country Brief: Lebanon, 2016.]\n\n3. **The economy is highly dependent on external financing, which undermines its ability to**\n**invest in infrastructure.** Funding the economy's substantial financing needs is highly dependent on\nforeign inflows, mainly from donor aid and remittances, that are intermediated via a banking sector\nwhose balance sheet is over three times of GDP. Banque du Liban (BdL), the country's central bank,\nensures that banks keep attracting foreign deposits to fund gross financing needs of the public and\nprivate sectors, thereby financing the sizable twin (fiscal and current account) deficits. To attract\nforeign deposits, BdL offers certificate of deposits and various subsidized refinancing schemes.\nLebanon's currency peg is sustained in good part by these foreign currency inflows. To meet\nGovernment needs, BdL is the residual buyer of Government debt in the primary and secondary\nmarkets. The result is a banking-sovereign feedback loop with amplification effects that generate\nsystemic macro-financial risks. The ensuing high interest rates reflect the risk premia that need to be\npaid in such a context to maintain the attractiveness of Lebanese assets and generate capital inflows.\n\n\n1 This indicator is ranked out of 183 countries in 2010 and 190 in 2019.\n2 ILO:", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000010", "page": 2, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household survey", "probe_tag": "confusion", "probe_score": 0.8538918495178223, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 233, "end": 249, "key": "jdc_operational:000010:2:1:0", "source": "camp2", "luna_reason": "2011/12 household survey provides the cited 27.4 percent poverty estimate", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nChad - Refugees and Host Communities Support Project (P164748)\n\n\n**<mark>ANNEX 2: GEO-SPATIAL ANALYSIS</mark>**\n\n\n1. A major obstacle to effective targeting of development projects in many developing\ncountries is the lack of existing datasets. One option to overcome this obstacle is remote sensing.\nFor this project, preliminary work has been done to determine the host population around selected\ncamps using remote sensing imaging analysis. To generate population estimates, the analysis uses\nworld population census data and statistical modeling based on the relationship between\npopulations and physical socioeconomic characteristics such as land uses, dwelling units and\nimage pixel characteristics.\n\n2. The figure shows the population layer within 25 km of selected camps, and the table shows\npopulation estimates at 50 km, 25 km, 15 km, 10 km and 5 km from the camps. Since village\nboundary information for Chad is not available in world population data, satellite imagery and\nestimates of average village size from the most recent census will be used to approximate the\nnumber of host villages around each camp.\n\n\n**Population Layer within 25 km of Selected Camps in the East, South, and Lake Chad**\n\n**Regions**\n\n\nSource: World Bank Geospatial Operations Support Team (GOST).\n\n\nPage 77", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 81, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "world population census data", "probe_tag": "confusion", "probe_score": 0.8737138509750366, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 514, "end": 542, "key": "jdc_operational:000035:81:0:0", "source": "camp2", "luna_reason": "Census data are used in modeling to generate population estimates.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "world population data", "probe_tag": "keep", "probe_score": 0.9360651969909668, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 958, "end": 979, "key": "jdc_operational:000035:81:0:1", "source": "camp2", "luna_reason": "Existing population data are cited as insufficient, motivating substitute spatial estimates.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\nelderly people who are more exposed to these alternatives by spending more time at home. Recently,\nthese traditional sources of lighting have started to be replaced by lamps and flashlights powered by\ndry-cell batteries. This change is also taking place in Chad where the results of the most recent survey of\nhouseholds indicate that 84 percent of the non-electrified households in Chad rely on dry-cell\nbattery-powered flashlights. On average, rural households in Chad pay CFAF 2,518 per month on lighting\nalternatives and about CFAF 1,467 per month to charge their mobile device outside of their house . These\ncosts incurred by households, nevertheless, include taxes and other transfer payments (for example, drycell battery flashlights and their components are sold by local shops from which the seller derives a\nmargin) that need to be excluded from the economic analysis. For the analysis, it is assumed that about\n35 percent of the current expenditure are taxes and other transfer payments. Furthermore, as the current\nmain alternative is portable (drycell- battery flashlights), it is conservatively assumed that not all the\ncurrent costs of current alternatives will be avoided, and that 30 percent of the current expenditure will\nbe incurred anyway as some current alternatives will be used complementarily to the SHS by households.\n\n6. **Nonresidential customers.** Nonresidential customers (and some better-off households) rely\nmostly on diesel self-generators to get electricity and some also rely on SSSs. The cost of self-generation\nis assumed to be US¢35 per kWh including taxes, duties, and transfer payments. <sup>59</sup> [^59: It is noted that this is a regional estimate as for Chad, such data are not available.] For the economic\nanalysis, these costs are adjusted to net off the taxes, duties, and transfer payments in a similar way as\nthe adjustment described for households above.\n\n7. **WTP.** While the avoided", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 83, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "survey of\nhouseholds", "probe_tag": "confusion", "probe_score": 0.8559368848800659, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 366, "end": 386, "key": "jdc_operational:000051:83:0:0", "source": "camp2", "luna_reason": "Survey findings attribute the 84 percent household reliance figure.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\nimplementing AEP (for instance, War Child Canada, Save the Children and other), Office of the Prime Minister,\nDistrict Local Government including the Education Office (DEO) and UNHCR to deliver the project activities. The\nproject will support capacity building and knowledge exchange in this area for the MoES staff and will regularly\nshare information with the Education Response Plan Secretariat.\n\n80. Component 3, subcomponent 3.1. will be led by Teachers Instructors Education and Training (TIET)\nDepartment and co-led by Secondary Education Department with support of ICT unit of the Ministry.\nSubcomponent 3.2. will be led by Policy and Planning Department with support from the technical MoES units. A\ncomponent coordinator within the PCU will be responsible for coordinating/facilitating the technical specialists\nworking together from the NCDC, TIET, UNEB and DES to deliver the component activities.\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n\n81. The monitoring systems which will be used for the PDO and to measure the intermediate and high-level\nindicators are as follows:\n\n\n\n(a) The Education Management Information System (EMIS) is being strengthen and will be able to generate\n\n\n\ndata to respond to the indicators. The EMIS data is collected through periodic school census.\n(b) For PBCs, third party assessments will be done to verify the achievement of the indicators and\n\n\n\nsatisfactory completion of large procurements.\n(c) Independent surveys will be done periodically to measure the results of the project. Data will be\n\n\n\ncollected in response to specific indicators.\n(d) Assessments will be carried out in the following areas: (i) to measure the impact of the lower secondary\n\n\n\neducation expansion approaches implemented under the Project (i.e. school designs, optimized\nstructure of the school subjects, ICT assisted teaching, streamlined teacher training and support) on\nimproving access in", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 35, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "periodic school census", "probe_tag": "confusion", "probe_score": 0.11476772278547287, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1357, "end": 1379, "key": "jdc_operational:000018:35:0:0", "source": "camp2", "luna_reason": "Sentence describes collecting EMIS data through a recurring census.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": " uniform data standards and\nclassification. Some of these key databases are; the maternal and neonatal registry, cancer registry,\ncommunicable disease surveillance registry, primary health care information system, and hospital\nutilization and billing system (visa billing system).\n\nThe aim of this component is to design a database that will allow for interoperability and serve as a\nmain repository of health sector data ready for analysis and dissemination. The database will not\nonly link the key MoPH databases, but will also pull relevant data from other sources such as CAS\nhousehold surveys (including Demographic and Health survey), NHA, and national hospital\nmorbidity and mortality reporting.\n\nThis component will work on the following activities:\n\n➢❨¢ Develop key performance indicators for assessing the performance of the health sector\nincluding disease burden, efficiency and equity of the health sector, PHC and hospital key\nperformance indicators, health economics indicators, as well as setting a plan to extract and monitor\nthe progress in the health and health-related Sustainable Development Goals indicators\n➢❨¢ Design an ICT system for ensuring interoperability of the existing databases including\nunification of patient identification numbers to facilitate statistical analyses for evidence based\ndecision making in the implementation of the national health sector plan\n\n\nPage 4 of 7", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000046", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "communicable disease surveillance registry", "probe_tag": "confusion", "probe_score": 0.345010370016098, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 130, "end": 172, "key": "jdc_operational:000046:3:1:0", "source": "camp2", "luna_reason": "Registry is listed as an existing system, but its data are not shown informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "descriptive"}, {"text": "CAS\nhousehold surveys", "probe_tag": "keep", "probe_score": 0.9010677933692932, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 576, "end": 597, "key": "jdc_operational:000046:3:1:1", "source": "camp2", "luna_reason": "Future database integration plans to pull survey data; no completed analytical use is shown.", "drop_reason": "promissory", "specificity": "named"}, {"text": "Demographic and Health survey", "probe_tag": "confusion", "probe_score": 0.4907922148704529, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 609, "end": 638, "key": "jdc_operational:000046:3:1:2", "source": "camp2", "luna_reason": "Existing survey data will be integrated for health-sector analysis and dissemination.", "usage_type": "declaration", "specificity": "named"}, {"text": "NHA", "probe_tag": "confusion", "probe_score": 0.24544283747673035, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 641, "end": 644, "key": "jdc_operational:000046:3:1:3", "source": "camp2", "luna_reason": "Future database integration plans to pull NHA data; no completed use is shown.", "drop_reason": "promissory", "specificity": "vague"}, {"text": "national hospital\nmorbidity and mortality reporting", "probe_tag": "confusion", "probe_score": 0.8718696236610413, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 650, "end": 701, "key": "jdc_operational:000046:3:1:4", "source": "camp2", "luna_reason": "Existing hospital reporting data will be integrated for health-sector analysis.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "Based on the above, the technical design of the Program will contribute to the overall goal of**\n**efficiently producing results and reaching the Program’s objectives** . The Program technical design\nreflects international good practice in the overall urban sector and specifically in technical standards and\ntypology of Program activities. Furthermore, the design ensures, to the extent possible, that the incentives\nare in place for Program stakeholders to effectively contribute to the Program’s success. Therefore, the\nProgram is assessed to be **technically sound** .\n\n**Program expenditure framework and assessment**\n\n28. **The GoU has a well-developed budget classification system** to track government expenditures\nunder the Program and the new PBS (from OBT) will further improve the program reporting facilities,\ncombined with roll-out of IFMS to all the participating MLGs. In terms of the **intergovernmental fiscal**\n**transfers**, the MTEF clearly outlines the respective grants, classified in recurrent and development grant\ntransfers. For FY 2017/18, the total grants to LGs constituted about 2.8 trillion UGSH, of which the DDEG\n\n\n54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 61, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "IFMS", "probe_tag": "confusion", "probe_score": 0.12090394645929337, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 849, "end": 853, "key": "jdc_operational:000006:61:2:0", "source": "camp2", "luna_reason": "Names a financial management system without showing use of its data.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": " in Jamjang and Maban do not plan to\n\n\n23 For example, the International Organization for Migration (IOM) staff note reports that the Marial Bai Agreement helps cattle-keeper and\nfarming communities in Western Bahr el Ghazal and Warrap States prevent, manage, and resolve conflicts that had repeatedly occurred during\nthe January–April dry season through IOM-supported dialogues and sensitization exercises that provide a safe space for these communities to\ndiscuss challenges and identify local solutions.\n24 South Sudan: Refugee and Asylum Seeker Population, UNHCR, January 31, 2022. https://data2.unhcr.org/en/country/ssd.\n25 Refugees in South Sudan – by months, UNHCR, January 31, 2022. https://data2.unhcr.org/en/country/ssd.\n\n\nPage 11 of 73", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 16, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Refugees in South Sudan – by months", "probe_tag": "confusion", "probe_score": 0.6965494751930237, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 629, "end": 664, "key": "jdc_operational:000028:16:2:0", "source": "camp2", "luna_reason": "Named UNHCR refugee population resource cited as an existing data source.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "Network coverage is another serious constraint to higher adoption of mobile broadband, with sharp**\n**regional disparities.** While more than 95 percent of the population is covered by mobile telephony networks (2G),\n\n\n23 World Bank Group. 2017. “Global Findex Database”, World Bank Group, 2017\nhttps://globalfindex.worldbank.org/sites/globalfindex/files/2018-04/2017%20Findex%20full%20report_0.pdf\n24 NITA-U (National Information Technology Authority of Uganda). 2018. National Information Technology Survey 2017/18 Report. NITA\nUganda, March 2018.\n25 NITA-U (National Information Technology Authority of Uganda). 2018. National Information Technology Survey 2017/18 Report. NITA\nUganda, March 2018.\n26 Economic Policy Research Centre. 2019. “Women’s Economic Empowerment in Uganda: Inequalities and Implications” Policy Brief No.\n110, Economic Policy Research Centre, November 2019. Kampala: Economic Policy Research Centre. Available at: https://eprcug.org/allpublications/614-women-s-economic-empowerment-in-uganda-inequalities-and-implications\n27 The State of ICT in Uganda. Research ICT Africa, 2019. “The State of ICT in Uganda.” https://researchictafrica.net/publication/the-stateof-ict-in-uganda\n28 ITU.\n29 The State of ICT in Uganda. Research ICT Africa, 2019. “The State of ICT in Uganda.” https://researchictafrica.net/publication/the-stateof-ict-in-uganda\n30 The State of ICT in Uganda. Research ICT Africa,2019. “The State of ICT in Uganda.” https://researchictafrica.net/publication/the", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 16, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Global Findex Database", "probe_tag": "confusion", "probe_score": 0.6842935085296631, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 247, "end": 269, "key": "jdc_operational:000023:16:2:0", "source": "camp2", "luna_reason": "Bibliographic reference entry without shown data use in the passage", "drop_reason": "ref_list", "specificity": "named"}, {"text": "National Information Technology Survey 2017/18 Report", "probe_tag": "confusion", "probe_score": 0.8558894991874695, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 470, "end": 523, "key": "jdc_operational:000023:16:2:1", "source": "camp2", "luna_reason": "Bibliographic reference entry without shown data use.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": " 640 heritage buildings which were damaged by the blast are of residential use.\nAmong these buildings, UNESCO interventions have focused on securing the most severely damaged buildings\nusing international and DGA standards <sup>95</sup>, with a lot of 14 heritage buildings in Rmeil, Saifi and Medawer. <sup>96</sup>\nHowever, most of the affected historic residential units did not receive any attention, and those damaged\nbuildings that have been addressed require further complex technical interventions to ensure their habitability.\n\n\n89 World Bank Group; European Union; United Nations. (2020). _Beirut Rapid Damage and Needs Assessment_ . Washington, DC.: World Bank Group.\n\n90 The 87,552 damaged residential building represented about 51 percent of the 171,887 housing units assessed\n91 Port surrounding areas include Marfaa, Medawar, Saifeh, and Remeil\n\n92 Combined low-income apartment buildings and low-income, single-family housing asset typologies.\n\n93 RDNA\n94 Buildings with less than 10 percent of physical damage.\n95 Prior the PoB explosion, many heritage buildings were object of inappropriate interventions using concrete and other non-compatible materials,\nwhich have weakened the historical structural fabrics.\n96 Other damaged buildings were stabilized by other organizations, including Aliph (12), Association for Protecting Natural Sites and Old Buildings in\nLebanon (APSAD) (5), Beirut Built Heritage Rescue (BBHR) (12), private contractors ‘on pro-bono’ basis and others.\n\n\nPage 52 of 66", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 57, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "RDNA", "probe_tag": "confusion", "probe_score": 0.23069915175437927, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 964, "end": 968, "key": "jdc_operational:000012:57:2:0", "source": "camp2", "luna_reason": "Standalone acronym fragment does not itself identify a usable data resource.", "drop_reason": "ref_list", "specificity": "vague"}]}
-{"text": "**The World Bank**\nLebanon: Grain emergency response project (P178866)\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Cumulative amount of wheat procured<br>through the project and delivered in the<br>ports of Beirut and Tripoli|The indicator will measure<br>the amount of wheat (tons,<br>gross weight) imported to<br>Lebanon and delivered in<br>the ports of Beirut and<br>Tripoli. The indicator will be<br>measured based on data<br>collected regularly and<br>reported by the Ministry of<br>Economy and Trade.|The indicator<br>will be<br>measured<br>monthly and<br>at the end of<br>the project<br>implementati<br>on period,<br>and will<br>reflect<br>cumulative<br>wheat import<br>procured<br>with project<br>financing sinc<br>e the start of<br>the project.<br>||||\n|Vulnerable beneficiaries with access to<br>affordable bread.|The data will be collected<br>from using random<br>sampling and surveying<br>(biweekly) using UNHCR and<br>WFP beneficiary lists.||||", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 40, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "WFP beneficiary lists", "probe_tag": "confusion", "probe_score": 0.6864109039306641, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1167, "end": 1188, "key": "jdc_operational:000019:40:0:0", "source": "camp2", "luna_reason": "Existing WFP beneficiary lists are used to draw the survey sample.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "000\npeople with food supplies and some 30,000 households had been assisted with Emergency Flood Rapid\nResponse Kits. Humanitarian efforts continue in priority locations and additional response teams have been\ndeployed to flood-affected areas to further expand relief efforts. Increased flood response is enabled by\ndonor contributions, including US$15 million from United Nations Central Emergency Response Fund and\nUS$9.8 million from the South Sudan Humanitarian Fund. <sup>123</sup> [^123: UNOCHA. 2019. “South Sudan Flooding Update Nr. 4.” November 29, 2019.] To respond to the short-and longer-term needs\nexacerbated by the floods, UNDP in coordination with other disaster relief organizations is gathering hazard\nand exposure data to produce a comprehensive hazard risk profile for South Sudan. <sup>124</sup> [^124: According to personal communication with UNDP.]\n\n\n5. **The proposed project DRM activities complement humanitarian response efforts by aiming to**\n**reduce disaster vulnerability and enhancing existing coping capacities of affected communities.** Where\npossible, the ECRP will seek to build peoples’ and communities’ resilience on the basis of existing capacities\nand coping mechanisms in a way that promotes self-reliance and helps better manage shocks. The project\nwill ensure that all interventions further develop preparedness and coping strategies and disaster adaptation\nprocesses that exist at the community level and also determine and respond to the risk perceptions and\nknowledge of safety systems among communities in the event of a disaster.\n\n\n6. **DRM activities are developed in alignment with the subproject cycle.**\n\n\n(a) As part of the county and community diagnostics, a hazard screening will be performed based\n\non available flood and drought hazard data.\n\n\n(b) If hazard-prone communities choose to implement disaster risk reduction measures (as per the\n\nproject’s open menu approach), BDC and other community representatives are first engaged in\n\n\n119 UNEP. 2018. _South Sudan First State of the Environment and Outlook Report_ .\n120 UNOCHA. 2020. “South", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 91, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "hazard\nand exposure data", "probe_tag": "confusion", "probe_score": 0.11241526901721954, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 712, "end": 736, "key": "jdc_operational:000049:91:1:0", "source": "camp2", "luna_reason": "Data are being gathered to produce a future hazard risk profile.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "flood and drought hazard data", "probe_tag": "confusion", "probe_score": 0.4548339545726776, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1767, "end": 1796, "key": "jdc_operational:000049:91:1:1", "source": "camp2", "luna_reason": "Existing hazard data used as the basis for community hazard screening.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nUganda Digital Acceleration Program (P171305)\n\n\n(see Annex 3). Universal access funds available through the Rural Communications Development Fund\n(RCDF) could possibly be repurposed for this. The mobilization of private sector investment could be\nmade on the basis of competitive tenders to increase the accessibility, quality and affordability of\nInternet services.\n\n\n**Figure 7: Mobile telecommunications coverage maps (3G)**\n\n\n_Source: GSMA_\n**Figure 8. New players, technologies, and business models to crack the internet challenge**\n\n\n<u>Subcomponent 1.3: Digital inclusion, especially for host communities and refugees</u>\n\n  - Development and deployment of digital solutions to facilitate hosting communities in their interactions\n\nand integration efforts of refugees including for instance the establishment of local networks with\nhotspots and integrated digital datacenters, pre-purchasing internet bandwidth, providing subsidies for\nuser’s equipment and installing community power charging stations. These solutions will cater for the\n\n\nJul 22, 2019 Page 18 of 28", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000063", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Mobile telecommunications coverage maps", "probe_tag": "confusion", "probe_score": 0.09906323999166489, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 400, "end": 439, "key": "jdc_operational:000063:17:0:0", "source": "camp2", "luna_reason": "Figure caption naming a visual artifact, not an analyzed data resource", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
-{"text": " communicate with\ntheir families and host communities. As such, the Uganda Digital Acceleration Project (UDAP) will be laying\nan important foundation needed to enable digital services delivery from key development actors serving\nrefugees and RHDs. COVID-19 pressures have further highlighted the impact of this digital divide on\nrefugees. The need for information on fluctuating market prices, accessing mobile learning platforms, and\nsupporting MSMEs with information, finance and learning support have all increased within refugee\nsettlements which have seen periodic lock downs.\n\n\n**12.** **The growing amount of e-waste also presents challenges to the ICT sector.** A survey conducted by\nUNEP in 2017 <sup>45</sup> [^45: UNEP] demonstrate that the amount and flow of e-waste is rising fast with the estimated stock\nof e-waste at 1,900 MT. It has an estimated annual growth of 25,000 tons. A recent study has projected\nthat between 2018 and 2022, there will be an average of 4,500 tons per year of e-waste generated from\ncommunications end user equipment only (phones, televisions, computers and radios). <sup>46</sup> [^46: UNEP]\n\n**13.** **Uganda has put in place the legal, policy, strategic and technical foundations for cybersecurity**\n**resilience and is optimizing them, while shifting focus to next-stage good practices in governance,**\n**capacity building and steady-state sustainability.** With an increasing number of digital platforms\nand services being rolled out by Uganda’s public and private sectors and investments made into\nnetworks and applications, Uganda has prioritized the strengthening of its cybersecurity, information\nsecurity and data protection frameworks. In 2018, cyber-attacks cost the Ugandan economy an\nestimated US$52 million, up from US$42 million in 2017 and US$35 million in 2016. The most\naffected sectors are the Government sector,", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000033", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey conducted by\nUNEP in 2017", "probe_tag": "confusion", "probe_score": 0.4686, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 672, "end": 704, "key": "sample:jdc_operational:000033:7:1:0", "source": "gold", "luna_reason": "UNEP survey data support reported e-waste stock and growth findings.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " about half of\nall mobile subscribers in Uganda using mobile internet services. The penetration rate of mobile broadband was 23%\ncompared to 1% only for fixed-line internet access by June 2018. <sup>28</sup> High prices hamper efforts to increase the\npenetration rate of broadband access. According to ITU, the cost of a basic mobile broadband services (1GB of mobile\ndata) was at 16.61% of GNI per capita in 2017 <sup>29</sup>, in contrast with the UN Broadband Commission’s target of 2%,\nmaking it prohibitively expensive for many Ugandans. In the second quarter of 2018, Uganda had the 17 <sup>th</sup> cheapest\n1GB mobile broadband product on the market in Africa <sup>30</sup>, making data cheaper than in South Africa or Lesotho for\nexample. Based on a survey by Research ICT Africa in 2018 <sup>31</sup>, internet use among individuals earning more than USD\n1,000 per month is very high but drops significantly in lower income brackets. Only 11% of people earning less than\nUSD 100 per month and around two-third of people earning between USD 100-1,000 per month reported using the\ninternet. Affordability of mobile devices also appears to be a key barrier to entry: 89% of respondents of the NITA-U\nsurvey who do not own a mobile phone, cite the cost of the mobile device as the main barrier <sup>32</sup> . Data also suggest <sup>33</sup>\nthat the recent introduction of social media and mobile money taxes in Uganda has disincentivized internet use, with\na drop of 30% in estimated internet users registered between March and September 2018 after their introduction\n(see risks section below). Furthermore, the lack of electricity and adequate", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000063", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey by Research ICT Africa", "probe_tag": "keep", "probe_score": 0.9410707950592041, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 759, "end": 788, "key": "jdc_operational:000063:4:1:0", "source": "camp2", "luna_reason": "Research ICT Africa survey supports reported internet-use findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "NITA-U\nsurvey", "probe_tag": "confusion", "probe_score": 0.8139608502388, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1200, "end": 1213, "key": "jdc_operational:000063:4:1:1", "source": "camp2", "luna_reason": "NITA-U survey supports the reported 89% barrier finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "br>Review of the online<br>publications.<br>• <br>Approved Bid Evaluation<br>Reports recommending<br>contract award.<br>• <br>Signed contracts submitted to<br>IDA.<br> <br> <br>|\n|Result 1.3.<br>Construction progress:<br>A. 30% completion:<br>foundation level<br>complete, floor slab<br>and walls have<br>reached window level;<br>B. 70% completion: all<br>facilities roofed;<br>C. 90% completion<br>(i.e. substantial<br>completion): all<br>facilities plastered,<br>painted, windows and<br>doors fitted, water &|<br> <br>• <br>No. of schools where the buildings are<br>30%, 70%, 90% and 100% completed<br>respectively.<br>• <br>Supervision reports are published online<br>by district, by school, and by contractor.<br>• <br>Construction progress reports by the<br>MoES.<br>• <br>Publish the List of completed schools<br>with completed civil works online, and<br>publish the certificate online.<br>• <br>Verify that District and headteachers<br>have certified school completion for all<br>completed schools submitted for funding<br>and publish the certified information<br>online.|• <br>Reports of site visits by<br>construction supervisory staff.<br>• <br>A third-party verification of<br>construction progress of all<br>schools.<br>• <br>Certification of school<br>completion from District", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 48, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "List of completed schools", "probe_tag": "confusion", "probe_score": 0.1411934494972229, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 790, "end": 815, "key": "jdc_operational:000018:48:2:0", "source": "camp2", "luna_reason": "Imperative requires future publication of a project completion list.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": " rural areas and\nwork in the agricultural sector, which accounts for 70 percent <sup>6</sup> [^6: World Bank Data.] of total employment (75 percent of all women in\nthe labor force) and around a quarter of the country’s gross domestic product (GDP). <sup>7</sup> [^7: World Bank. 2020. _Uganda Economic Update_, _Strengthening Social Protection to Reduce Vulnerability and Promote Inclusive Growth_,\n2020. World Bank.] This renders a significant\nportion of the workforce vulnerable to climate change and weather shocks and demonstrates the need for\neconomic diversification and alternative sources of employment in higher productivity industries.\n\n2. **The Coronavirus Disease 2019 (COVID-19) pandemic is putting Uganda’s growth trajectory at risk,**\n**exacerbating structural constraints and increasing pressure on the poor and vulnerable, including people living**\n**in Refugee Hosting Districts (RHDs).** Uganda’s real GDP grew at 2.9 percent in FY20, less than half the 6.8 percent\nrecorded in FY19, <sup>8</sup> [^8: World Bank. 2020. _Uganda Economic Update, 1_ 6 _th Edition, December 2020:_ Investing in Uganda’s Youth. December 2020.] due in large part to the effects of the COVID-19 pandemic. As of February 2021, there have\nbeen almost 40,000 cases of COVID-19 in the country. The expected revenue loss from COVID-19 measures is\nestimated at 0.18 percent of GDP in FY20 while tax revenues, more broadly, are expected to fall to 11.6 percent\nof GDP for FY20—1 percentage point less than FY19. Economic activity stalled during the latter part of the fiscal\nyear due to a domestic lockdown that lasted over four months, border closures, and the spillover effects of\ndisruption in global demand and supply chains. This resulted in a sharp contraction in public investment and\ndeceleration in private consumption. The", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "World Bank Data", "probe_tag": "confusion", "probe_score": 0.8944699168205261, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 98, "end": 113, "key": "jdc_operational:000023:13:1:0", "source": "camp2", "luna_reason": "World Bank Data sources the attributed 70 percent employment statistic.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\ndevelopment (ECD) services. <sup>14</sup> As a result, South Sudan ranked 172 out of 174 in the Human Capital Index (HCI) in 2020,\nwith HCI at 0.31, meaning that a child born today will only reach 31 percent of its full potential. <sup>15</sup>\n\n6. **Restrictive gender and social norms significantly limit socioeconomic opportunities for women and girls and**\n**increase the risk of gender-based violence (GBV).** South Sudan ranks in the bottom fourth of countries for the life-course\ngender gap and women's empowerment of the Human Development Index. <sup>16</sup> A highly patriarchal structure and social\nnorm in the country often exclude women from decision-making processes and limit their income-generating\nopportunities, and stark gender disparities exist in education and access to employment and livelihood opportunities,\nsuch that women in South Sudan are less likely than men to be employed as waged and salaried workers, despite high\nparticipation in agricultural activities. Further, girls are often excluded from socioeconomic opportunities based on\nharmful gender norms, which dictate that girl assume domestic and caretaking responsibilities, with the expectation that\nthey marry early. This in turn contributes to an intergenerational cycle of poverty and low education levels among\nwomen. GBV also continues to be one of the most critical threats to the protection and well-being of women and girls,\nwith close to 65 percent having experienced physical and/or sexual violence in their lifetime in conflict-affected\nlocations. <sup>17</sup> Key factors that influence GBV include normalization of violence, whether related to conflict or\nintercommunal strife; breakdown of rule of law; and increases in opportunistic crime (largely due to high levels of\npoverty).", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Human Capital Index", "probe_tag": "confusion", "probe_score": 0.8952804803848267, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 189, "end": 208, "key": "jdc_operational:000057:14:0:0", "source": "camp2", "luna_reason": "Index provides South Sudan’s ranking and HCI value.", "usage_type": "evidential", "specificity": "named"}, {"text": "Human Development Index", "probe_tag": "keep", "probe_score": 0.9527044296264648, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 622, "end": 645, "key": "jdc_operational:000057:14:0:1", "source": "camp2", "luna_reason": "Index cited as basis for South Sudan’s gender-gap ranking.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " operating in Lebanon.\n\n45. Detailed description of implementation arrangements, including the functioning of the\ncitizen engagement in subproject identification and monitoring, will be given in the Project\nOperational Manual (OM), which will be prepared and updated as required by CDR, and\napproved by the Bank. The OM will be completed within thirty days of Project effectiveness.\n\n\n**B.** **Results Monitoring and Verification**\n\n\n46. Monitoring and evaluation (M&E) arrangements will be supported under Component 3:\nProject Implementation Support (see detailed Results Framework in Annex 1). The Project will\ntrack inputs, outputs and results through the following modalities:\n\n\n  - On a routine basis, the Project will track expenditures and other fiduciary data relevant to\n\nproject implementation. This will be carried out by the PMU via semi-annual progress\nreports and financial statements and annual financial audits by independent auditors\ncontracted under the Project. CDR will report on this data semi-annually to the World\nBank, the LSCTF and any potential donor partners.\n\n\n  - On a half yearly basis, the Project will track key activities and outputs implemented at the\n\nunion/municipal level — for example, the number of community infrastructure\n\n\n13", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "fiduciary data", "probe_tag": "confusion", "probe_score": 0.19368015229701996, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 753, "end": 767, "key": "jdc_operational:000003:23:1:0", "source": "camp2", "luna_reason": "Routine project fiduciary tracking and reporting is administrative bookkeeping, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|\n|**4.**Municipal** r**oads built<br>or rehabilitated with<br>related infrastructure<br>using urban LDG|√|3|Km<br>Targets|53.02|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Annually|Municipal reports|Participating<", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 36, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "Municipal reports", "probe_tag": "drop", "probe_score": 0.0016635797219350934, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1379, "end": 1396, "key": "jdc_operational:000062:36:4:0", "source": "camp2", "luna_reason": "Table cell naming municipal reports, not an independently used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "br>Partner<br>|\n|Number of beneficiary households<br>receiving cash transfer for participating in<br>the behavioral change communication<br>training|The number of beneficiary<br>households that participate<br>in behavioral change<br>communication training<br>activities to receive their<br>cash transfer.|This<br>indicator<br>will be<br>measured,<br>at a<br>minimum,<br>on a<br>quarterly<br>basis<br>|SNSOP<br>Management<br>Information<br>System<br>|Attendance data<br>collected during each<br>training session<br>|Implementing Partner<br>|\n|Number of beneficiary households<br>receiving Direct Income Support|The number of total<br>beneficiary HHs that are<br>selected to participate in DIS<br>under sub-component 1.2,<br>in accordance with the<br>Project Operations Manual,|<br>This<br>indicator<br>will be<br>measured,<br>at a<br>minimum,|Registration<br>and payment<br>data from<br>the SNSOP<br>MIS<br>|Beneficiary data will be<br>collected during<br>registration and<br>updated over the<br>course of project<br>implementation.|Selected Implementing<br>Partner<br>|\n\n\nPage 56 of 74", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 60, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Attendance data", "probe_tag": "drop", "probe_score": 0.00925491377711296, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 450, "end": 465, "key": "jdc_operational:000057:60:1:0", "source": "camp2", "luna_reason": "Attendance data will be collected during project training sessions.", "drop_reason": "production", "specificity": "vague"}, {"text": "Beneficiary data", "probe_tag": "confusion", "probe_score": 0.09937722235918045, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 907, "end": 923, "key": "jdc_operational:000057:60:1:1", "source": "camp2", "luna_reason": "Data will be collected and updated during project implementation.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Uganda Support to<br>Municipal Infrastructure<br>Development Program<br>Additional Financing<br>(P163515)<br>Financing: US360 million<br>WHR: US50 million|Enhance institutional performance of program<br>local governments for urban service delivery.<br>This includes planning, land tenure security,<br>and small-scale infrastructure investments<br>within refugee-hosting urban centers and their<br>wider districts. It will support eight refugee-<br>hosting districts. The focus is secondary cities.|1. Collaboration with the Ministry of Land<br>and Urban Development for the adequate<br>inclusion of common-user facilities the<br>cross-sectoral fiscal plans for local<br>development (only the framework has been<br>developed).<br>2. Complementary infrastructure<br>investments in RHDs (for example, USMID<br>roads, lighting, and markets in RHDs can be<br>supplemented by GROW business<br>infrastructure)<br>3. Both focus on strengthening district level<br>implementation and management of<br>infrastructure needs in RHDs.|\n|---|---|---|\n|**GBV and Violence Against**<br>**Children Prevention and**<br>**Response Services in**<br>**Uganda’s Refugee-Hosting**<br>**Districts Report**<br> <br>**Financing:**US$0.5 million <br>|To mitigate GBV and prevent violence against<br>children through engagement", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 75, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Districts Report", "probe_tag": "drop", "probe_score": 0.039743680506944656, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1300, "end": 1316, "key": "jdc_operational:000025:75:0:0", "source": "camp2", "luna_reason": "Standalone table fragment, not a data source or data-use statement.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "PIT Project Implementation Team\nPO Production officers\nPOM Program Operations Manual\nPPDA Public Procurement and Disposal of Public Assets\nPPP Private-Public Partnership\nPPSD Project Procurement Strategy for Development\nPSC Project Steering Committee\nPSFU Private Sector Foundation Uganda\nPTC Project Technical Committee\nRHD Refugee-Hosting District\nSOPs Standard Operating Procedures\nSORT <mark>Systematic Operations Risk-rating Tool</mark>\nSTEP Systematic Tracking of Exchanges in Procurement\nUBOS Uganda Bureau of Statistics\nUGGDS Uganda Green Growth Development Strategy\nUIA Uganda Investment Authority\nUIRI Uganda Industrial Research Institute\nUNHCR United Nations High Commissioner for Refugees\nUNHS Uganda National Household Survey\nUEW Unsafe Environment for Women\nUWEP Uganda Women Entrepreneurship Program\nVSLAs Village Savings and Loans Associations\nWEE Women’s Economic Empowerment\nWHR Window for Host Communities and Refugees", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Uganda National Household Survey", "probe_tag": "drop", "probe_score": 0.01937042735517025, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 706, "end": 738, "key": "jdc_operational:000025:3:0:0", "source": "camp2", "luna_reason": "Survey is only defined in a glossary, with no data use or finding.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n\n|Col1|Col2|Col3|Col4|(about 590,000) and<br>50% of students<br>enrolled in private<br>schools (about 322,000)<br>and students enrolled<br>in new schools. The<br>training of the teachers<br>will be done gradually:<br>25% trained in Y2, 50%<br>by Y3, 75% by Y4 and<br>100% by Y5. Students<br>from the new schools<br>are included as well.|Col6|\n|---|---|---|---|---|---|\n|Students benefiting from direct<br>interventions to enhance learning -<br>Female||Same as for<br>the core<br>indicator<br> <br>|Same as for<br>the core<br>indicator<br>|<br>Same as for the core<br>indicator<br>|Same as for the core<br>indicator<br>|\n|Enrolment at public lower secondary<br>schools in targeted districts, girls|The indicator will measure<br>the number of female<br>students who will annually<br>enroll in public school in the<br>targeted districts (2017 is<br>the baseline year).<br>|<br>Measuremen<br>t will be<br>taken at<br>project<br>midterm and<br>end of<br>project.<br>|<br>EMIS<br>|Headcount<br>|MoES<br>|\n|Enrolment at", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 56, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "EMIS", "probe_tag": "drop", "probe_score": 0.022800931707024574, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1042, "end": 1046, "key": "jdc_operational:000018:56:0:0", "source": "camp2", "luna_reason": "Standalone table cell naming EMIS, with no shown use of its data.", "drop_reason": "table_artifact", "specificity": "named"}, {"text": "MoES", "probe_tag": "drop", "probe_score": 0.022800931707024574, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1065, "end": 1069, "key": "jdc_operational:000018:56:0:1", "source": "camp2", "luna_reason": "Agency name appears as a source cell within an indicator table.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": ">psycho-social support.|Defn: Emergency response<br>preparedness and psycho-<br>scial support refer to<br>strategic measures put in<br>place (by national COVID<br>taskforce) to manage the<br>spread and mitigate against<br>negative impacts of COVID-<br>19.<br> <br>Train or orient head<br>teachers of grant-supported<br>schools on the above<br>measures to help guide their<br>response at school level;|<br>once<br>|Training<br>reports<br>|Data collection through<br>monitoring of training<br>and review of<br>attendance registers<br>|MoES through<br>Directorate of Basic and<br>Secondary Education<br>|\n\n\nPage 34 of 43\n\n\nOfficial Use", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "attendance registers", "probe_tag": "drop", "probe_score": 0.014660093933343887, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 508, "end": 528, "key": "jdc_operational:000034:38:1:0", "source": "camp2", "luna_reason": "Routine attendance records reviewed for project training monitoring.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
+{"text": "**The World Bank**\nCHAD Improving Learning Outcomes Project (P175803)\n\n\nof parents of children aged 7-14 years report that the school management committee includes parent members; and\nonly one fifth report participating in meetings of the committee. The majority (62 percent) receive report cards, but only\n26 percent report discussing their child’s progress with a teacher. <sup>27</sup> [^27: Data for this and the following two paragraphs are taken from MICS 2019.]\n\n\n18. **Children enter school poorly prepared for learning** **and are taught in a language** **they do not speak.** Many\nchildren start Grade One after years of debilitating health episodes and inadequate cognitive stimulation. Roughly 40\npercent of children under five years old are either moderately or severely stunted. Only one percent of children aged\n36-59 months attend a pre-school program, while only 2 percent of Grade One students have attended a pre-school in\nthe previous year. Also, the existing preschool program dates from 1994 and is no longer relevant, and there are no\nstandards regulating this sub-sector. Further, almost all children are taught in a language they cannot speak.\n\n\n19. **Education budgets are inadequate, and financial mechanisms can be strengthened** . Public spending on\neducation was the equivalent of 2 percent of GDP and education expenditures constituted only 11 percent of total\ngovernment expenditures in 2018, <sup>28</sup> [^28: Chad Public Expenditure Analysis 2019: Fiscal Space for Productive Social Sectors Expenditure, June 2019, pp. 55 ff.] well below those recommended by the Global Partnership for Education, 5 percent\nand 20 percent respectively. They are also low by regional standards. Over the past fifteen years, Chad’s public\nexpenditures on education as a percentage of GDP have on average been 0.8 percentage points lower than the Sahelian\naverage. <sup>29</sup> Education expenditures are fragile and susceptible to shocks. In", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MICS 2019", "probe_tag": "keep", "probe_score": 0.9788, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 457, "end": 466, "key": "sample:jdc_operational:000009:12:0:0", "source": "gold", "luna_reason": "Named MICS 2019 data source supports the reported education findings.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": ", communities, and societies as a whole. Several benefits from educating girls should be highlighted here\n(see Wodon et al., 2019, for details):\n\n\n\n<u>(2%)</u>\n\n\n\n\n    - **Child marriage and early childbearing:** The prevalence of child marriage (32.5 percent among girls aged\n18-22 according to the latest Demographic and Health Survey) and early childbearing (26.0 percent)\nremain high in Uganda. Girls from rural areas and disadvantaged socio-economic backgrounds tend to\nhave worse outcomes. Keeping girls in secondary school until they graduate is one of the best ways to end\nchild marriage and early childbearing. Each additional year of secondary education is associated with a\nsubstantial reduction in the risks of child marriage and early childbearing and universal secondary\neducation for girls could virtually eliminate child marriage and thereby also reduce the prevalence of early\nchildbearing by half (because about half of all instances of early childbearing appear to be due to child\nmarriage).\n\n    - **Fertility and population growth:** Women who have children earlier (including when they are still children\nthemselves) tend to have more children over their lifetime. By reducing the risks of child marriage and\nearly childbearing, as well as providing agency for women, universal secondary education could reduce\nfertility rates by more than a third (36 percent) in Uganda. This, in turn, would reduce population growth,\naccelerate the demographic transition, and potentially generate a large demographic dividend which\ncould help in raising standards of living and reducing poverty. For example, levels of human capital wealth\nper capita would increase.\n\n    - **Women’s health:** Finally, analysis suggests that universal secondary education for girls would increase\nwomen’s health knowledge and their ability to seek care, improve their psychological well-being, and\nreduce the risk of intimate partner violence from partners, and reduce risks associated with having\nchildren at an early age.\n\n7. **Education for children", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 95, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Demographic and Health Survey", "probe_tag": "keep", "probe_score": 0.9614960551261902, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 307, "end": 336, "key": "jdc_operational:000018:95:1:0", "source": "camp2", "luna_reason": "Survey data support the reported child-marriage prevalence figure.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\nthrough out-of-pocket payments. This poses major challenges in terms of the equity, the efficiency and the\nsustainability of the country’s health financing architecture.\n\n15. **Health facilities have low readiness levels to deliver quality health services** . The number of health facilities\nin Chad is low and more than 3,000 facilities are needed to reach WHO target of two facilities per 10,000\ninhabitants. Further, according to the most recent SARA survey, one in three health facilities had access to\nelectricity and two in three had access to improved water sources. The availability of essential medical\nequipment (scales, thermometers, stethoscopes, etc.) and laboratory capacity were also substandard\n(WHO, 2019). In terms of health professionals, in 2017 there were less than 10,000 professionals in all Chad.\nShortages are particularly acute for doctors and specialized health professionals (0.38 per 10,000\npopulation), and there are important disparities in the distribution of health professionals between\nprovinces.\n\n16. **The coverage of essential health services is low** . The above-mentioned constraints, together with the\nsignificant geographic barriers enhanced by the poor transport infrastructure, lead to the low coverage of\nessential health services such as reproductive, maternal, neonatal and child health services and nutrition.\nIn 2017, one in four children under five received all required vaccines. According to the DHS 2014/2015,\nonly 25 percent of women attended at least four antenatal care visits and less than 30 percent delivered at\na health facility. These coverage rates reflect a low demand for health services and great difficulties\ndelivering health services through outreach.\n\n17. **Weakness in core capacities to enforce International Health Regulation (IHR) can increase the risk of**\n**emergencies** . Chad signed on to the International Health Regulations (RSI,", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SARA survey", "probe_tag": "keep", "probe_score": 0.9431947469711304, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 538, "end": 549, "key": "jdc_operational:000039:14:0:0", "source": "camp2", "luna_reason": "Existing SARA survey supports a concrete health-facility access finding.", "usage_type": "evidential", "specificity": "named"}, {"text": "DHS 2014/2015", "probe_tag": "keep", "probe_score": 0.9315034747123718, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1537, "end": 1550, "key": "jdc_operational:000039:14:0:1", "source": "camp2", "luna_reason": "DHS survey supports antenatal-care and facility-delivery coverage findings.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": ". Besides assisting these communities with inclusive improved all-season access to opportunities,\nservices and markets, the Project will generate employment opportunities.\n\n\n7. **Uganda is the land “bridge” for the rest of the Great Lakes region** <sup>**6**</sup> [^6: Consists of Burundi, Democratic Republic of Congo, Kenya, Malawi, Rwanda, Tanzania and Uganda] **, connecting its landlocked neighbors**\n**to the coastal countries.** Regional integration is indispensable for Uganda and provides great opportunity\nto foster trade with its neighbors. Uganda is ranked 102 in the Logistics Performance Index 2018 and\ninfrastructure and tracking and tracing are the two areas it is ranked very low with a ranking of 124 and 123\nrespectively <sup>7</sup> [^7: https://openknowledge.worldbank.org/bitstream/handle/10986/29971/LPI2018.pdf] . The efficiency of the transit traffic performance in the major road corridors is critical for\nsupporting and sustaining competitive international trade in the sub-region as well as supporting the\nrefugee settlements and host communities through the facilitation of logistics services from the various\nhumanitarian agencies. Inefficiencies in logistics systems can have dire consequences especially during\nemergency situations like the spread of a pandemic (e.g. COVID-19) when uninterrupted flow of essential\ngoods like food and medical supplies is imperative.\n\n8. **Uganda has a longstanding history of hosting refugees, since 1942 and is currently hosting the largest**\n**number of refugees in Africa and the third largest number in the world.** By the end of February 2020, there\nwere 1.4 million refugees and asylum seekers in Uganda and their numbers have been increasing since\nOctober 2018. South Sudanese (62 percent) make up the largest refugee population followed by refugees\nfrom the Democratic Republic of Congo (DRC) (29 percent), Burundi (3.4 percent), Somalia (2.8 percent) and\nothers", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Logistics Performance Index 2018", "probe_tag": "keep", "probe_score": 0.9400362372398376, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 581, "end": 613, "key": "jdc_operational:000050:12:1:0", "source": "camp2", "luna_reason": "Named index cited as evidence for Uganda’s logistics ranking and performance weaknesses.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " profession and to effectively manage teachers in improving teacher classroom practices.\nWith renewed political commitment, along with the directives outlined in the National Human\nResource Development Strategy (NHRDS) (2016–2025), the MOE is working toward formalizing and\nimplementing the NTPSF. The overall aim of the NTPSF is to tackle the low status, social prestige, and\nquality of the professional performance of Jordanian teaching staff, and to expand preservice training.\n\n\n13 According to MOE data for the 2015‐2016 academic year, enrollment is similar for girls and boys.\n14 Latest (2012) EGRA and EGMA scores for Jordan.\n15 PISA 2015\n\n4", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 11, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "MOE data", "probe_tag": "confusion", "probe_score": 0.6974576115608215, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 499, "end": 507, "key": "jdc_operational:000041:11:2:0", "source": "camp2", "luna_reason": "MOE data supports the enrollment comparison for 2015–2016.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "43 \nthe Customs \nGolden List  \nfollow expedited clearance including lowered \nguarantees, green channel streaming, cursory \ndocument review, and minimal to no physical \ninspections \n  \nDepartment of \ncustom services  \nAutomated \nsystem for \ncustoms data \ndatabase \n \na print from the \ncustoms IT system \n(automated system \nfor customs data) to \nverify the number \nof entries by those \ncompanies and \nwhat, if any, \nexaminations \noccurred.  \nAB will confirm the \ncounting and \nperform random \nchecks as needed \nand issue its report \nwithin 2 months \nfollowing PMU \nnotification.  \nMOPIC will submit \nrelated \ndocumentation \nconfirming \nachievement of \nresults along with \nthe AB report. \nDLI 5 \nNumber of \ninvestments \nbenefitting \nfrom \ninvestment \nfacilitation by \nthe JIC  \nDLR 5.1: Removing the minimum capital \nrequirements for foreign investments (Prior \nResult) \nDLR 5.2: Number of investments benefiting \nfrom investment facilitation by JIC = 530 \n(cumulative).  \n \nThis includes the following:  \n(a) Basic communication/investor inquiries \n(b) Site visits facilitated \n(c) Secured investment commitment \nYes \nThe JIC’s CRM \ndatabase \nAB \nAt the end of each \nCY, the JIC will \nprovide to the PMU \nits CRM database. \nAB will review and \nconfirm the \ncounting and \nperform random \nchecks of the \nfacilitated \ninvestments as \nneeded. The AB", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 51, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "JIC’s CRM \ndatabase", "probe_tag": "confusion", "probe_score": 0.5221622586250305, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1120, "end": 1139, "key": "jdc_operational:000045:51:0:0", "source": "camp2", "luna_reason": "Database provision and review are planned future verification activities.", "drop_reason": "promissory", "specificity": "named"}, {"text": "CRM database", "probe_tag": "confusion", "probe_score": 0.10118318349123001, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1207, "end": 1219, "key": "jdc_operational:000045:51:0:1", "source": "camp2", "luna_reason": "Future database submission for DLI verification is planned monitoring machinery.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": " part of the Government’s COVID-19 response.** In response to the\ndanger posed by the pandemic to Ugandan students, the Government announced the closure of all schools from\nMarch 20, 2020 for a period of 30 days in a bid to avoid the possible rapid spread of new infections of COVID-19.\nThe closure of schools remains in place and it is not clear when this could be lifted. This has impacted more than\n67,516 schools affecting more than 15 million students and over 400,000 teachers.\n\n\n**<u>Table 1. Enrollment by education level (public and private, and refugees)</u>**\n\n|Level of education|# of Schools|# of Students|# of Teachers|\n|---|---|---|---|\n|Pre-primary|28,208|2,050,403|90,742|\n|Primary|36,314|10,777,846|315,787|\n|Lower Secondary|2,994|1,779,550|114,859|\n|**Total **|**67,516 **|**14,607,799 **|**406,529 **|\n\n\n\nSources: Report on the Master List of schools in Uganda (MEIU) Uganda Bureau of Statistics (UBOS) 2019\n\n13. **The COVID-19 outbreak and school closures are expected to have a wide range of impacts on students,**\n**teachers and households.** Prolonged school closures are expected to lead to a loss in learning. Households will\nface increasing economic difficulties with rising unemployment and income losses. This could impact the\nlikelihood of children staying in school and transitioning to the next level of education once the schools reopen,\nincreasing the number of out-of-school children. Parents’ ability to contribute to educational inputs may also be\nmore limited", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Master List of schools in Uganda", "probe_tag": "confusion", "probe_score": 0.7999981045722961, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 848, "end": 880, "key": "jdc_operational:000034:12:1:0", "source": "camp2", "luna_reason": "Named source cited for enrollment table figures.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "sup>12</sup> The percentage of women in leadership roles was highest\nin Western Bahr el Ghazal state (30.3 percent) and lowest in Warrap State (4.9 percent). <sup>13</sup> In addition,\nthere are limited income generating opportunities for women. When women do generate income,\n\n\n7 World Bank 2021.\n8 UNDP (United Nations Development Programme). 2020. _Human Development Report_ .\n9 World Bank 2021.\n10 HDI’s life-course gender gap compiles 12 indicators that analyze gender gaps in choices and opportunities across the life-span including\neducation, labor and work, political representation, time use, and social protection. HDI’s women’s empowerment dashboard compiles 13\nwoman-specific empowerment indicators in three categories: reproductive health and family planning, violence against women and girls, and\nsocioeconomic empowerment.\n11 UNDP. 2018. _Human Development Indices and Indicators: 2018 Statistical Update - South Sudan._\n12 Kenwill International Limited. 2015 _. Fortifying Equality and Economic Diversification (FEED): Improved Livelihoods in South Sudan._ Gender\nAssessment Report, World Vision.\n13 Kenwill International Limited 2015 _._\n\n\nPage 9 of 73", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "women’s empowerment dashboard", "probe_tag": "confusion", "probe_score": 0.6299849152565002, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 631, "end": 660, "key": "jdc_operational:000028:14:2:0", "source": "camp2", "luna_reason": "Dashboard is named, but its data are not shown informing analysis or a finding.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "**The World Bank**\nStrengthening Lebanon’s Covid-19 Response (P178587)\n\n\n79 **. The World Bank will support various efforts to actively engage with citizens to collect feedback on the NDVP and**\n**project performance, through social media surveys, the TPM mechanism, and through the use of Iterative**\n**Beneficiary Monitoring (IBM).** In February 2021, the World Bank team administered a Facebook survey to assess\nbeliefs and attitudes towards COVID-19 vaccination. Responses from more than 15,000 participants showed that\nonly 28 percent of them intended to take the vaccine when it becomes available, and 48 percent were still unsure\nat the time of the survey. Moreover, as part of the TPM mechanism, feedback from vaccine recipients and health\nproviders was collected and shared regularly with the MoPH, the National Vaccination Committee, and the Vaccine\nExecutive Committee for corrective action as needed. Additionally, performance score cards were produced and\nshared with vaccination sites to monitor performance and identify challenges. An IBM approach is also being\nplanned as an iterative feedback loop that collects information directly from beneficiaries and identifies challenges\nat the local level that can be addressed by project teams. In addition to improving project efficiency, this approach\nincreases beneficiary engagement and satisfaction by creating positive, self-reinforcing cycles of improvement.\nFindings will be used to improve the communication campaign and citizen engagement. Through the IBM as well\nas social media surveys, engagement with community, especially in remote areas, will ensure the inclusion of their\nongoing feedback in the rollout and implementation of the COVID-19 vaccination campaign to strengthen targeting\naccuracy and increase uptake. To ensure citizen engagement, the project will: (a) target messages to areas where\nvulnerable groups, including refugees and IDPs, reside to inform them about safety measures and benefits; (b)\ntailor messages to the elderly and those with medical risks including their target family members and health care", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 39, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "social media surveys", "probe_tag": "confusion", "probe_score": 0.6578184962272644, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 246, "key": "jdc_operational:000000:39:0:0", "source": "camp2", "luna_reason": "Future project-supported surveys are planned to collect feedback.", "drop_reason": "production", "specificity": "vague"}, {"text": "social media surveys", "probe_tag": "confusion", "probe_score": 0.6606130003929138, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 246, "key": "jdc_operational:000000:39:0:2", "source": "camp2", "luna_reason": "Future project feedback surveys are planned, not cited as existing data used.", "drop_reason": "promissory", "specificity": "vague"}, {"text": "Facebook survey", "probe_tag": "keep", "probe_score": 0.9451995491981506, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 389, "end": 404, "key": "jdc_operational:000000:39:0:1", "source": "camp2", "luna_reason": "Past survey produced vaccination-attitude findings from over 15,000 participants.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Enrolment at lower secondary education<br>for refugees|The project will finance<br>construction of about<br>15,000 new places in lower<br>secondary schools in the<br>refugee hosting areas. The<br>target is set based on the<br>assumption that the current<br>proportion in enrollment<br>between refugees and hosts<br>is maintained (33% to 67%).<br>However, the overall<br>enrolment will depend on<br>the refuges influx and<br>internal migration during<br>the project life, which is<br>beyond the project control.<br>Enrolment in private and<br>public schools is counted as<br>reliable disagregated<br>baseline data is not<br>available.<br>AEP enrolment is not<br>included and measured<br>under a dedicated indicator.|Midterm and<br>end of<br>project|EMIS|Enrollment data by<br>refugee settlement and<br>hosting communities.|MOES|\n|---|---|---|---|---|---|\n|Enrolment at lower secondary education<br>for host communities|<br>The project will finance<br>construction of about<br>15,000 new places in lower<br>secondary schools in the<br>refugee hosting areas. The<br>target is set based on the<br>assumption that the current<br>proportion in enrollment|Data will be<br>reported at<br>midterm and<br>end of<br>project.<br>|Baseline", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 57, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Enrollment data", "probe_tag": "confusion", "probe_score": 0.12864945828914642, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 842, "end": 857, "key": "jdc_operational:000018:57:0:0", "source": "camp2", "luna_reason": "Standalone table cell, not an independently used data source", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\nwill develop detailed checklists to ensure consistent and compliant Project procurement.\n\n   - The PIU will also develop a contract management system to ensure that all contracts under the\nProject are effectively and efficiently managed. This will include the tracking of key contract\nmilestones and performance indicators as well as capturing all procurement and contract records.\n\n\n**Table A2.3. Procurement risk analysis and mitigation**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Risk Description|Description of Mitigation|Risk owner|\n|---|---|---|\n|**(i) Operational context:**  volatile political<br>situation<br>and<br>weak<br>macro‐economic<br>projection; current constraint in making<br>payments to another party outside of country<br>due to foreign exchange shortages.|Direct payments to suppliers at the request<br>of the Government.|Borrower|\n|**(ii) Fiduciary risk:**    corruption and bribery<br>concerns with regards to internal controls<br>within the Ministry and broader context of the<br>country;  South  Sudan  is  ranked  the  second<br>most corrupt country in the world on<br>transparency corruption perception index.|Project to be implemented with the support<br>of  UN  Agencies  as  the  main  suppliers  of<br>goods and services. In addition, direct<br>payments are proposed.|Borrower|\n|**(iii)Lack of complaints and resolution of**<br>**disputes system:**  the Government does not<br>have ", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 59, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "transparency corruption perception index", "probe_tag": "confusion", "probe_score": 0.16599568724632263, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1158, "end": 1198, "key": "jdc_operational:000038:59:0:0", "source": "camp2", "luna_reason": "Index ranking is cited as evidence of South Sudan’s corruption risk.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " percent. More than 70 percent of school-age children are not receiving education. <sup>37</sup> [^37: UNESCO, et. al. 2018. _Global Initiative on Out of School Children, South Sudan Country Study._] The country\nhas the lowest road density in Africa with less than 2 percent of the primary network paved, constraining access to the\nschools and health facilities that do exist. <sup>38</sup> [^38: World Bank 2018.] The situation would likely worsen if the number of returnees (both from within\nand outside the country) increased to areas where humanitarian assistance is limited, as the impacts of COVID-19 become\nmore widespread, and in areas where continuing violence triggers short-term, localized displacement.\n\n\n13. **Local institutions—both local governments and community institutions—are mandated to play an integral role**\n**in providing services.** Under the Transitional Constitution of South Sudan 2011 as well as the Local Government Act (LGA)\n2009, the Government is organized into three tiers **—** at the national, state, and local levels. The local government, in turn,\n\n\n30 Ibid.\n31 IOM 2021; and United Nations Mission in South Sudan (UNMISS) (August 2019) ( _Mimeo_ ).\n32 IDMC (International Displacement Monitoring Center 2021. 2019 figures from UNOCHA Humanitarian Needs Overview, p.13 and IOM DTM, p.4\n33 IOM “Draft Population Movement Analysis October 2019.”\n34 IOM DTM. The movements of the remaining 7 percent of returnees could not be clearly determined.\n35 IOM DTM. Some displaced have moved to settle more permanently in urban centers (as in Wau or Malakal) or may remain in cities because they are unable to return\nto their villages due to security concerns, or the occupation of their land and houses by other groups (for example, Bor or Bentiu).\n36 UNOCHA Humanitarian Needs Overview (2018).\n37 UNESCO, et.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000027", "page": 6, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "UNOCHA Humanitarian Needs Overview", "probe_tag": "confusion", "probe_score": 0.8923570513725281, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1267, "end": 1301, "key": "jdc_operational:000027:6:2:0", "source": "camp2", "luna_reason": "Named humanitarian overview cited as source for 2019 figures.", "usage_type": "evidential", "specificity": "named"}, {"text": "IOM DTM", "probe_tag": "keep", "probe_score": 0.9492936730384827, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1312, "end": 1319, "key": "jdc_operational:000027:6:2:1", "source": "camp2", "luna_reason": "Named IOM displacement data source cited for reported 2019 figures.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": ", is the very low share of\nhouseholds that have access to means of communication, thus making it difficult to reach large sections of the\ncountry using new technologies. In order to ensure continuity in the teaching and learning process, multiple\neducation delivery modalities will need to be used to reach the maximum number of students. These modalities\ninclude paper-based resources (printed materials, books, etc.), mobile phones, radio/audio interaction;\nvideo/television; and online teaching and learning platforms. This sub-component will mainly target vulnerable\nhouseholds using data from the recent household survey.\n\n\n**_Sub-Component 1.2: Teacher training to prepare and deliver educational content through a multi-modal_**\n**_distance learning system (US$0.7 million)._**\n\n\n14. Sub-component 1.2 will support training of approximately 5,000 teachers, particularly female teachers, in\nonline and distance learning methodologies to ensure teachers can effectively play a key role in supporting\nremote teaching and learning programs. Teachers will be trained to design formative questions, tests, or\nexercises to closely monitor students’ learning processes. Teachers will also engage with parents and design\nsimple audio clips for parents who may not have gone to school to support them in home schooling, be on call\nfor interaction with learners and parents, or hosting online-or phone-based group learning conversations. To\nachieve this, the proposed Project will support: (i) technical assistance for teacher training programs to adapt the\ncurrent curriculum to distance learning strategies; (ii) a platform for all teachers (WhatsApp for instance) to\nengage among themselves, or with the administration, students, and parents; and (iii) printing and distribution\n(including digital) of guidance materials for teachers on the management of daily home-based learning practices.\n\n\nAugust 14, 2020 Page 7 of 13", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000031", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household survey", "probe_tag": "confusion", "probe_score": 0.757037341594696, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 609, "end": 625, "key": "jdc_operational:000031:6:1:0", "source": "camp2", "luna_reason": "Existing household survey data are used to target vulnerable households.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "from Decision Review Decision Note)**|\n|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|\n|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Project Financing Data", "probe_tag": "confusion", "probe_score": 0.11081644147634506, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 863, "end": 885, "key": "jdc_operational:000003:6:1:0", "source": "camp2", "luna_reason": "Standalone table header, not a substantive data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "<br>|\n|<br>N’Djamena<br>|<br>51.0<br>|<br>43.8<br>|<br>49.6|\n\n\n2. The gap in electricity access is also visible when looking at quintiles of wealth, although it only\nbecomes sizable for the highest quintile. From all male-headed households in the top quintile, 40.9\npercent have access to electricity while the same figure is 29.79 percent for female-headed households.\n\n\n\n\n\n\n|Location|Male (%)|Female (%)|All (%)|\n|---|---|---|---|\n|<br>Poorest|<br>0.01|<br>0.03|<br>0.01|\n\n\n\n43 The data on the distribution of household heads were updated by a survey on ability and willingness of households to pay for\nelectricity services, completed in 2021. Details are provided in annex 6.\n\n\nPage 71 of 87", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 76, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data on the distribution of household heads", "probe_tag": "confusion", "probe_score": 0.5760777592658997, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 484, "end": 527, "key": "jdc_operational:000051:76:2:0", "source": "camp2", "luna_reason": "Survey data updated the household-head distribution used in the analysis.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "survey on ability and willingness of households", "probe_tag": "keep", "probe_score": 0.9391711354255676, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 546, "end": 593, "key": "jdc_operational:000051:76:2:1", "source": "camp2", "luna_reason": "Completed survey updated household-head distribution data used in analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " in volume and\nhave an 18-month maturity so as to be available over the COVID-19 period only and so as not to distort the market\nfor loan capital. All participants along the chain will still maintain positive margins, even if reduced ones. Burden\nsharing means costs are reduced or absorbed, or revenues (margins) are compressed while staying moderately\npositive and different stakeholders assume their respective shares. Those financial intermediaries benefiting from\nthese credit lines will determine how to provide the COVID-19 support to their clients so as not to disrupt their\n\n\n47 Surveys will be conducted in person or over the phone and could be substituted by surveys conducted by UBOS.\n48 The objective is to develop an actional M&E system that is used as instrument to monitor and improve project effectiveness along\nimplementation rather than just a system for ex-post accountability.\n\n\nPage 31 of 92", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 36, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "surveys conducted by UBOS", "probe_tag": "confusion", "probe_score": 0.7967768311500549, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 670, "end": 695, "key": "jdc_operational:000021:36:2:0", "source": "camp2", "luna_reason": "Future surveys are planned data production by UBOS.", "drop_reason": "production", "specificity": "named"}]}
+{"text": "openknowledge.worldbank.org/handle/10986/34401 License: CC BY 3.0 IGO\n14 The referenced study uses a definition of CCIs based on the World Intellectual Property Organization (WIPO) copyright definition: Visual arts,\nMusic, Performing arts, Cinema, Photography, Television and Radio, Videogames, Books and Press, Advertising and Communication and\nSoftware.\n15 IOF. “The Contribution of Cultural and Creative Industries to the Lebanese Economy - Executive Summary.” Accessed December 20, 2021.\nhttp://www.institutdesfinances.gov.lb/publication/the-contribution-of-cultural-and-creative-industries-to-the-lebanese-economy-executivesummary/.\n16 World Bank Group; European Union; United Nations. 2020. Beirut Rapid Damage and Needs Assessment. World Bank, Washington, DC. ©\nWorld Bank. https://openknowledge.worldbank.org/handle/10986/34401 License: CC BY 3.0 IGO\n17 Socio-economic vulnerability: The project will prioritize the poorest and the most vulnerable households affected by the blast (e.g. lowincome, FHH, refugees), based on a socioeconomic field survey. The vulnerability criteria considers social (i.e. presence of elderly, female\nheaded households, people with disabilities, refugees, building located in an area of higher social vulnerability) and economic vulnerability (i.e.\nhousehold receiving rental support, presence of CCI, level of income).\n18 World Bank Group; European Union; United Nations. (2020). _Beirut Rapid Damage and Needs Assessment_ . Washington, DC.: World Bank\nGroup.\n\n19 The terms \"housing\", \"units\", \"apartments\" are used equally throughout the document to refer to the individual residential unit. The term\n\"building\" refers to the urban infrastructure that", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 13, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "socioeconomic field survey", "probe_tag": "confusion", "probe_score": 0.16337135434150696, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1033, "end": 1059, "key": "jdc_operational:000012:13:2:0", "source": "camp2", "luna_reason": "Existing survey data informs planned vulnerability-based household prioritization.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " the integrated data platform. Data from each implementing agency will be\naggregated with the data of others and used as the basis of quarterly progress reports.\n\n82. **Data generation and reporting** . The data to track the key performance indicators come from (a) project-specific\nsurveys and questionnaires, (b) project service providers (women’s entrepreneurship platform managers, trainers, PFIs,\nfacility managers); (c) local governments; (d) consultant reports; and (e) supervising engineers’ reports on construction\nprogress. The MGLSD PIT is responsible for preparing the quarterly financial and progress report, consolidating\ninformation from each and from the integrated data platform. It will submit the submit quarterly project progress reports\nto the World Bank, the PTC, the PSC, and to other the stakeholders within 45 days of the end of each quarter. The\ngovernment and World Bank will prepare a comprehensive midterm review of the project implementation and results in\n2024/25, during which the target values will be reviewed and any required adjustments to project design agreed.\n\n83. **Capacity building for M&E** . The project will provide support to strengthen capacity for M&E of the MGLSD and of\nthe national and subnational PITs. Specifically, the project will finance consultants who will work with the MGLSD to\nprepare a detailed M&E and reporting system plan, provide on-the-job and other training for M&E specialists (at both\nthe MGLSD and other implementing agencies), and provide other capacity support required to establish and operate an\neffective M&E system. The project will also finance follow-on training and workshops with M&E specialists to ensure that\nnormal staff turnover does not disrupt the M&E effort.\n\n**C. Sustainability**\n\n\n84. **The project aims to support female entrepreneurs grow and transform their micro and small enterprises to**\n**larger more profitable firms", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 36, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "integrated data platform", "probe_tag": "confusion", "probe_score": 0.3854335844516754, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 5, "end": 29, "key": "jdc_operational:000025:36:1:0", "source": "camp2", "luna_reason": "Platform data are consolidated and used for quarterly progress reporting.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "project-specific\nsurveys and questionnaires", "probe_tag": "confusion", "probe_score": 0.2756115198135376, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 266, "end": 309, "key": "jdc_operational:000025:36:1:1", "source": "camp2", "luna_reason": "Project-specific surveys are planned M&E data sources, not existing external data.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nChad Rural Mobility and Connectivity Project (P164747)\n\n\n**Figure 2: Theory of Change**\n\n\n\nPage 18 of 76", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Chad Rural Mobility and Connectivity Project", "probe_tag": "confusion", "probe_score": 0.06444920599460602, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 63, "key": "jdc_operational:000048:21:0:0", "source": "camp2", "luna_reason": "Project title names an operation, not an existing data resource or data use.", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n1. To inform the design of the project subcomponent aiming to electrify households through SHSs,\na survey on ability and willingness of Chad rural households to pay for electricity services was conducted\nin the first half of 2021. Due to time and budget limitations, as well as security constraints, the survey was\nimplemented in the rural areas of three Chadian provinces that were selected with the objective of\nobtaining representative data that can be extrapolated to the rest of the rural areas of the country. The\npoverty incidence, together with homogeneity/differences between provinces, played a key role in the\nstratification of the sample. Table 6.1. summarizes information on the three selected provinces and\nsample size, while figure 6.1. shows a Chad map with the names of provinces.\n\n|Province|Poverty Incidence (%)|Sample Size|\n|---|---|---|\n|<br>Guéra <br>|<br>60.0 <br>|<br>248 <br>|\n|<br>Kanem <br>|<br>27.7 <br>|<br>241 <br>|\n|<br>Logone Occidental <br>|<br>43.5 <br>|<br>239 <br>|\n|<br>Total|<br> <br>|<br>728|\n\n\n\n2. Select results of the survey by province and the average for the three provinces are summarized\nin Table 6.2.\n\n\nPage 84 of 87", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 89, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "survey by province", "probe_tag": "confusion", "probe_score": 0.7453206777572632, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1127, "end": 1145, "key": "jdc_operational:000051:89:0:0", "source": "camp2", "luna_reason": "Survey results by province are presented as evidence in Table 6.2.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " The sub-component will\nsupport the implementation of the overall project by PSFU. The sub-component will support regular auditing,\nfinancial reporting, all safeguards assessments and monitoring and evaluation. Establishment of a web platform\nto enable the project to reach all beneficiaries (particularly refugees and host communities) and be accessible\nfrom all locations in Uganda. Monitoring and evaluation (M&E) activities undertaken as part of this component\nwill focus on data collection, survey implementation, and evaluating the economic impact of the program through\na structured impact evaluation at the conclusion of the project. The monitoring component of the M&E approach\nwill require data collection across different dimensions of the project: (a) performance tracking data (for example,\nsales, employment, wages, transactions); (b) activity tracking data reflecting the theory of change; (c) key results\ndata (for example, value of private investment in manufacturing firms, formal employment in manufacturing\nfirms); and (d) tracking of key risks (for example, project implementation performance, NPL ratio of banks, and\nportfolio at risk [PAR] of MFIs). The evaluation component will build on the data collected under the monitoring\ncomponent but additionally focus on implementing a structured impact evaluation process to measure the impact\nand attribution of the program.\n\n\n**C. Project Beneficiaries**\n\n\n52. The project targets direct beneficiaries, 140,000 MSMEs and 120,000 refugees, of these at least 40,000\nare expected to be women-led microenterprises. The project will seek to have a focus on the manufacturing\nand/or exporting supply chains. Other larger-size firms will also benefit from project interventions, for instance\nindirectly benefiting from the receivables financing under sub-component 1.3. The program will also focus on\neconomic opportunities <sup>42</sup> for RHDs by seeking to catalyze investments that enhance economic activity as well as\n\n\n40 This group of firms will typically include", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 29, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "performance tracking data", "probe_tag": "confusion", "probe_score": 0.07655828446149826, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 764, "end": 789, "key": "jdc_operational:000021:29:1:0", "source": "camp2", "luna_reason": "Data are to be collected for project monitoring, so they are project-produced.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "key results\ndata", "probe_tag": "confusion", "probe_score": 0.09124857187271118, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 909, "end": 925, "key": "jdc_operational:000021:29:1:2", "source": "camp2", "luna_reason": "Project monitoring data collection is planned, not existing data use.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "/Abdeh<br>area – Akkar,<br>North Lebanon|89,100|20,315|\n|Union of Municipalities of Al<br>Shafat|11|Halba area –<br>Akkar, North<br>Lebanon|84,800|13,810|\n|Total|166**||1,095,729|250,373|\n\n\n*Number of Syrians registered with UNHCR in a given union as of March 31, 2014. Source: _UNHCR/CDR_\n** Given the limitations of the current available funding envelope, a number of municipalities in the targeted unions\nmay not initially benefit from Project interventions.\n\n\n**A.** **Project Components**\n\n\n24. The Project consists of three components: (i) Emergency Response; (ii) Rehabilitation of\nCritical Infrastructure; and (iii) Project Implementation Support.\n\n25. **_Component 1: Emergency Response (US$ 3.5 million)._** This component will finance the\nprovision of high priority municipal services (Subcomponent 1A) and initiatives that promote\nsocial interaction and collaboration (Subcomponent 1B) in the eleven participating unions of\nmunicipalities. Allocation of resources among the participating unions of municipalities will be\nrelated to the number of Syrians hosted, considering the number of Syrian refugees as a proxy of\nthe additional stress on local communities. Initiatives will be selected in consultation with\nmunicipalities and communities, with a decentralized approach to decision-making. These\ninitiatives will provide non-exclusionary benefits addressing some of the most immediate service\nneeds in the unions most affected by the crisis and will be aimed at: (i) improving safety and\nmobility; (ii) mitigating the increasing health and environmental risks associated with the\ndeterioration of water, waste, and sanitation services; and (iii) increasing collaboration and\ninteraction amongst the communities.\n\n26. _Subcomponent 1A_ _Service Delivery_ will focus", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 17, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Number of Syrians registered with UNHCR", "probe_tag": "confusion", "probe_score": 0.5861893892288208, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 191, "end": 230, "key": "jdc_operational:000003:17:1:0", "source": "camp2", "luna_reason": "UNHCR registration figures support refugee-hosting-based resource allocation.", "usage_type": "evidential", "specificity": "named"}]}
 {"text": "## **Annex 5: Fiduciary Systems Assessment – Addendum**\n\n1. **As part of the USMID additional financing Program preparation and in accordance with**\n**OP/BP 9.0, a fiduciary assessment was carried out that evaluated the Program Procurement,**\n**Financial Management, Governance and Anti-corruption systems.** The assessment determined that\nexisting systems can provide reasonable assurance that the Program expenditures will be used appropriately\nto achieve their intended purpose with due attention to the principles of economy, efficiency, effectiveness\nand transparency. There is sufficient evidence under the current original USMID financing, as documented\nin the five years of independent Annual Performance Assessments and audits, that funds have been used as\nintended.\n\n2. **The Fiduciary Systems Assessment has identified the various implementation and Program**\n**risks and their potential impact on the ability of the Program to attain its development objective.** As\ndiscussed in detail below, the Program Implementation framework is characterized by the following main\nrisks: (i) low staffing levels, (ii) limited staff knowledge about systems and lack of full systems availability\nwhere one MC - Mubende is not on IFMS, (iii) Poor internet connectivity, (iv) An environment of low\nlevels of compliance to laws and regulations with weak enforcement regimes, (v) Planning and budgeting\nfigures are not consistently adhered to with mismatch between annual budgeted funds and annual\nassessment results resulting in releases that have not been appropriated, (vi) weak contract management,\n(vii) Low bidder participation and poor quality bids, (viii) Poor record keeping, and (ix) Weak cash flow\nmanagement. The gaps in the functioning of monitoring and oversight systems like internal audit and\nprocurement audits regarding capacity and limited coverage of MCs also pose additional risks. Based on\nthe above analysis of the risks, the overall fiduciary risk of the operation is rated as Substantial.\n\n3. **Key design features of", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 71, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "independent Annual Performance Assessments and audits", "probe_tag": "drop", "probe_score": 0.044023506343364716, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 682, "end": 735, "key": "jdc_operational:000006:71:0:0", "source": "camp2", "luna_reason": "Existing assessments and audits provide evidence that funds were used as intended.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n\n|Col1|Col2|Col3|Col4|(about 590,000) and<br>50% of students<br>enrolled in private<br>schools (about 322,000)<br>and students enrolled<br>in new schools. The<br>training of the teachers<br>will be done gradually:<br>25% trained in Y2, 50%<br>by Y3, 75% by Y4 and<br>100% by Y5. Students<br>from the new schools<br>are included as well.|Col6|\n|---|---|---|---|---|---|\n|Students benefiting from direct<br>interventions to enhance learning -<br>Female||Same as for<br>the core<br>indicator<br> <br>|Same as for<br>the core<br>indicator<br>|<br>Same as for the core<br>indicator<br>|Same as for the core<br>indicator<br>|\n|Enrolment at public lower secondary<br>schools in targeted districts, girls|The indicator will measure<br>the number of female<br>students who will annually<br>enroll in public school in the<br>targeted districts (2017 is<br>the baseline year).<br>|<br>Measuremen<br>t will be<br>taken at<br>project<br>midterm and<br>end of<br>project.<br>|<br>EMIS<br>|Headcount<br>|MoES<br>|\n|Enrolment at", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 56, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "EMIS", "probe_tag": "drop", "probe_score": 0.022800931707024574, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1042, "end": 1046, "key": "jdc_operational:000018:56:0:0", "source": "camp2", "luna_reason": "Standalone table cell naming EMIS, with no shown use of its data.", "drop_reason": "table_artifact", "specificity": "named"}, {"text": "MoES", "probe_tag": "drop", "probe_score": 0.022800931707024574, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1065, "end": 1069, "key": "jdc_operational:000018:56:0:1", "source": "camp2", "luna_reason": "Agency name appears as a source cell within an indicator table.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|include realization of local<br>hazard protection measures<br>(e.g. levees) and climate<br>change adaptation (e.g.<br>flood-proof/heat-resistant<br>buildings).|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Percentage of county government officials<br>trained.|<br>Percentage of county<br>government officials trained<br>in areas described in the<br>PAD.|Biannual<br>|UNOPS/IOM<br>|Regular monitoring<br>|UNOPS/IOM<br>|\n|Percentage of grievances appropriately<br>responded to within the pre-determined<br>timeframe.||Quarterly<br>|Project MIS<br>|Regular monitoring<br>|UNOPS<br>|\n|Percentage of counties for which the<br>required information is uploaded to the<br>MIS in a timely manner to monitor results.<br>|<br>Geo-referenced data on<br>subproject progress<br>uploaded in the MIS in a<br>timely manner for project<br>management to monitor<br>results.|Quarterly<br>|Project MIS<br>|Regular monitoring<br>|UNOPS<br>|\n\n\nPage 56 of 94", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 61, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Geo-referenced data", "probe_tag": "drop", "probe_score": 0.03658657148480415, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 837, "end": 856, "key": "jdc_operational:000049:61:0:0", "source": "camp2", "luna_reason": "Span is a data phrase embedded within a monitoring table.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nUganda Digital Acceleration Project – GovNet (P171305)\n\n\nto the national development priorities and institutional mandates to ensure that the different activities are fully\nsupported. Institutional strengthening of NITA-U has already taken place during implementation of RCIP-5 and the\nuse of alternative delivery models involving partnerships with the private sector and NGOs to complement\ngovernment efforts will also be applied under this project. Despite these mitigation measures, the residual\nstakeholder risk remains substantial for the time being.\n\n**100.** **Refugee protection is an ‘other’ risk that is rated as Moderate.** The WB, in consultation with UNHCR, has\nconfirmed that Uganda’s protection framework is adequate for accessing funding under the IDA19 WHR. Uganda\nis adopting comprehensive humanitarian and development programs aimed at mitigating protection risks faced\nby refugees, including the managed arrival of refugees despite COVID-19 border closures. However, there is a\nmoderate risk that Uganda’s asylum space and refugee policies could become more restrictive in response to the\nstrain on services and the natural environment, continuing refugee population growth, and COVID-19-related and\npolitical pressure. Additional refugee-specific risks include the high proportion of women and girls and other\nvulnerable people within the refugee population, which poses specific protection challenges, including GBV;\nchallenges to the ongoing allocation of land to refugees; and administrative and informal barriers for refugees to\naccess productive employment, finance, and market opportunities. Another protection risk that this project will\nmanage relates to ensuring the ongoing adequacy and management of refugee registration data. Over the three\nyears, the WB has undertaken analytical studies in Uganda across refugees and RHDs such as on GBV,\ndeforestation and environmental management, and socioeconomic status informing refugee policy. The findings\nof these are being operationalized through WHR-financed projects including this one. These risks are then being\nmanaged jointly through effective in-country coordination mechanisms which include the", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 48, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "refugee registration data", "probe_tag": "drop", "probe_score": 0.03967767581343651, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1751, "end": 1776, "key": "jdc_operational:000023:48:0:0", "source": "camp2", "luna_reason": "Mentions managing registration data but shows no substantive analytical or decision use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\nbuses, motorbikes, cars, and trucks (modes used by refugees/hosts and for trade)\n(iii) Time of closure of Project road corridor in a year for movement of trucks (days)\n(iv) Percentage increase in trade volumes using the Project road (dis-aggregated by refugees, hosts)\n\n(b) enhance the capacity of UNRA to manage environmental, social and road safety risks\n\n(v) Fully operational Environmental and Social Management System in place\n(vi) Crash data entered into system, publicly reported, and used in decision making (yes/no)\n(vii) Annual Number of fatalities or serious injuries involving construction vehicles or at construction\n\nsites\n\n\n**B. Project Components**\n\n\n43. The project will have the following components as detailed below.\n\n\n44. **Component 1: Road Upgrading Works (Total US$145.8 million; IDA: US$125.8 million equivalent, GoU:**\n**US$20 million).**\n\n\n1(a) Upgrading - to bituminous paved road standard - and widening of about 105 km of KobokoYumbe-Moyo road corridor.\n1(b) Carrying out supervision of civil works under part 1(a) of the Project.\n1(c) Carrying out environmental and social risks management (including implementation of action\nplans to address among others gender-based violence, sexual exploitation and abuse, violence\nagainst children and HIV/AIDS), monitoring and evaluation, third party integrated performance\naudits and road user satisfaction surveys.\n1(d) Preparation of Project’s environmental and social risk management documents as well as\ndetailed engineering designs of civil works and carrying out land acquisition, and resettlement\nand rehabilitation associated with upgrading works under Part 1(a) and maintenance of the road\ncorridor for five years post-construction.\n\n45. This", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Crash data", "probe_tag": "drop", "probe_score": 0.044629987329244614, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 535, "end": 545, "key": "jdc_operational:000050:25:0:0", "source": "camp2", "luna_reason": "Planned monitoring indicator for future crash-data entry and reporting", "drop_reason": "promissory", "specificity": "vague"}, {"text": "road user satisfaction surveys", "probe_tag": "drop", "probe_score": 0.046286437660455704, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1453, "end": 1483, "key": "jdc_operational:000050:25:0:1", "source": "camp2", "luna_reason": "Project will carry out future road user satisfaction surveys.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": " enrolment, teacher training,<br>socio‐emotional learning program, school maintenance,<br>student assessment, etc.|MOE (OpenEMIS)|Third Party|The verification agency will check<br>the number of Syrian refugee<br>children enrolled in target schools<br>and will conduct site visits and spot<br>checks in a sample of randomly<br>selected schools to verify<br>enrollment numbers.|\n|**DLR#2**Number of additional<br>children enrolled in public and<br>private KG2|<br> <br> <br>Number of students enrolled in public or freely provided<br>private KG2. Data should be reported disaggregated by type of<br>school, directorate, gender, and nationality.|MOE (OpenEMIS)|Third Party|Enrollment data and disaggregation<br>is provided to the verification<br>agency. The verification agency will<br>conduct site visits and spot checks<br>in a sample of randomly selected<br>schools to verify enrollment<br>numbers. The sampling framework<br>should be acceptable to the WB.|\n|**DLR#3.1**Comprehensive and<br>harmonized quality assurance", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 43, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Enrollment data", "probe_tag": "drop", "probe_score": 0.0021, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 670, "end": 685, "key": "sample:jdc_operational:000041:43:1:0", "source": "gold", "luna_reason": "Enrollment data appears in planned DLR verification machinery, not substantive analysis.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n\n\n\n\n\n\n\n\n|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|<br>beneficiaries <br>|||||||FAO<br>|\n|Percent of which are<br>female||Number|0.00|55.00|Quarterly<br>|M&E System<br>|MAFS/WFP/FAO<br>|\n|<br> <br>Description:|<br> <br>Description:|<br> <br>Description:|<br> <br>Description:|<br> <br>Description:|<br> <br>Description:|<br> <br>Description:|<br> <br>Description:|\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|**Name:**Amount of general<br>food  rations availed to<br>beneficiaries||Metric<br>ton|0.00|15000.00|Monthly<br>|Progress reports<br>|MAFS/WFP<br>|\n|<br>Description:|", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 37, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "South Sudan Emergency Food and Nutrition Security Project", "probe_tag": "drop", "probe_score": 0.04795027896761894, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 76, "key": "jdc_operational:000038:37:0:0", "source": "camp2", "luna_reason": "Project title identifies an operation, not an existing data resource or data use.", "drop_reason": "ref_list", "specificity": "named"}]}
 {"text": "gating the Impact of COVID-19 with a Focus on the Manufacturing and Exporting**\n**Sectors Driving Economic Transformation, including Refugee and Host Districts (IDA US$79 million and US$5**\n**million from the IDA-19 Window for Host Communities and Refugees, WHR).** The objective of this component is\nto ease liquidity constraints on MSMEs, including women led and refugee MSMEs. For the reasons discussed\nabove, the component will seek to prioritize the manufacturing and exporting sectors driving economic\ntransformation, with the vision of connecting lower income regions, like RHDs with more viable and sustainable\nmarkets. This component will operate three different windows designed to assist MSMEs to better manage the\nCOVID crisis by easing the cost of finance and the availability of liquidity by working with Participating Financial\nInstitutions (PFIs) to reach the MSMEs. PFIs will be required to provide gender-disaggregated data on eligible\nMSMEs in order to address the lack of data on women-led firms as well as data on refugee or host community\nstatus to ensure that intersectional issues of exclusion are sufficiently addressed.\n\n38. **Window 1.1** will support loans that have been restructured under the Bank of Uganda COVID-19 response\napproach, primarily in the manufacturing and exporting sectors by covering part of the added financial cost due\nto the restructuring. The window will be available to qualifying MSMEs who received an extension of the\namortization period on their loans, to reduce the MSMEs incremental cost or debt servicing liability. The cost for\nthis rebate will be shared with PFIs to ensure that PFIs participate in burden sharing through lower margins than\nusual. <sup>38</sup> The window will focus on MSMEs in the manufacturing and exports sectors, and strongly encourage the\ninclusion of women-led firms. The window can also be used by Microfinance Institutions (MFIs) or Savings and", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 25, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "gender-disaggregated data on eligible\nMSMEs", "probe_tag": "confusion", "probe_score": 0.6084432601928711, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 916, "end": 959, "key": "jdc_operational:000021:25:1:0", "source": "camp2", "luna_reason": "PFIs will provide this data prospectively; it is planned data production.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "data on refugee or host community\nstatus", "probe_tag": "drop", "probe_score": 0.01904595084488392, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1027, "end": 1067, "key": "jdc_operational:000021:25:1:1", "source": "camp2", "luna_reason": "PFIs are required to provide this data as a planned collection activity.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "|UNRA<br>|UNRA and M&E reports<br>|Monitoring and<br>evaluation consultants,<br>UNRA<br>|\n|Annual number of fatalities or serious<br>injuries involving construction vehicles or<br>at construction sites<br>|Effectiveness of the traffic<br>management plan<br>implemented and<br>occupational health and<br>safety monitoring program<br>under the civil works|Semi-<br>annually<br>|M&E reports,<br>UNRA<br>reports<br>|Police data<br>|Monitoring and<br>evaluation consultants,<br>UNRA<br>|\n\n\n**ME PDO Table SPACE**\n\n\n\n\n\n\n\n\n\n\n\nPage 55 of 80", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 59, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Police data", "probe_tag": "drop", "probe_score": 0.044583193957805634, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 412, "end": 423, "key": "jdc_operational:000050:59:1:0", "source": "camp2", "luna_reason": "Police data is identified as the source for tracking construction-related fatalities.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nChad - Refugees and Host Communities Support Project (P164748)\n\n\n\n**<u>Population Estimates Around Camps using Remote Sensing</u>**\n\n\n\n\n\n\n\n\n\n\n\n|Region|Camp|Population Estimates|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|**Region**|**Camp**|50 km<br>radius|25 km<br>radius|15 km<br>radius|10 km<br>radius|5 km<br>radius|\n|**Ouaddai**|Farchana|254,334|66,256|25,553|14,145|6,735|\n|**Ouaddai**|Gaga|199,981|45,497|17,444|8,780|3,988|\n|**Ouaddai**|Treguine|217,488|54,023|24,491|17,686|6,561|\n|**Ouaddai**|Bredjing|237,726|59,905|25,704|17,049|7,359|\n|**Logone Orientale**|Amboko|186,483|56,194|28,610|18,716|5,381|\n|**Logone Orientale**|Dosseye|272,782|66,296|26,105|13,034|5,523|\n|**Logone Orientale**|Gondje|187,843|61,168|29,041|11,399|3,411|\n|**Lac Chad**|Dar Es Salam", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 82, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Population Estimates Around Camps using Remote Sensing", "probe_tag": "drop", "probe_score": 0.040210574865341187, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 90, "end": 144, "key": "jdc_operational:000035:82:0:0", "source": "camp2", "luna_reason": "Standalone table heading introducing population estimates by camp and radius.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
-{"text": ") business development services in the long term through\ncollaboration with ILO and UNHCR. This support will also include activities aimed at strengthening\nwomen’s technical skills and will be implemented in cooperation with organizations addressing other\nconstraints (in particular food nutrition and hygiene) of vulnerable households. The training would\ninclude awareness-raising of risks from climate change and benefits of climate change adaptation.\n17. **_Component 2: Poultry value chain input support for improved food and nutrition security and_**\n**_increased incomes (US$ 1.0 million):_** This activity would finance the distribution of egg-laying chicken\nand feed and provision of agro-technical advice to refugees in order to tackle food and nutrition\ninsecurity and contribute to improved livelihoods. The activity would also support a limited value\nchain development, providing opportunities for the poultry producers to sell the surplus products\nthat the family does not require for consumption.\n18. **_Component 3: Supervision and monitoring_** **_(US$ 0.5 million):_** This component would finance overall\nproject management, monitoring and implementation, including the following aspects: (a) project\nmanagement and coordination among different actors and stakeholders; (b) monitoring and\nevaluation, including periodic beneficiary satisfaction survey (at inception, mid-term and project\nconclusion) including ethnicity and gender disaggregated data; (c) project environmental and social\nsafeguards; (d) project fiduciary administration, internal controls and audit, and (e) citizen\nengagement mechanism **.**\n\n\n**Environmental and Social Standards Relevance**\n\n\n**E. Relevant Standards**\n\n\nSep 02, 2021 Page 8 of 10", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000036", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "periodic beneficiary satisfaction survey", "probe_tag": "confusion", "probe_score": 0.0517096109688282, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1329, "end": 1369, "key": "jdc_operational:000036:7:1:0", "source": "camp2", "luna_reason": "Planned periodic survey is project monitoring data to be generated.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "ethnicity and gender disaggregated data", "probe_tag": "drop", "probe_score": 0.04785730689764023, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1428, "end": 1467, "key": "jdc_operational:000036:7:1:1", "source": "camp2", "luna_reason": "Data will be collected through planned periodic beneficiary satisfaction surveys.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": " emergency procedures while deferring exact projects/roads selection\nand associated safeguards to implementation;\n\n2. Agree on the first‐year road works program to speed up implementation;\n\n3. Include the purchase of necessary equipment which can be implemented quickly; and\n\n4. Introduce retroactive financing to support timely project implementation and initiate\nprocurement activities and required studies.\n\n  - **Deliver good quality infrastructure and asset management practices:**\n\n1. Prepare procurement strategy and packages to ensure a wider participation of local contractors\n(hence, broader benefits in different areas/communities) while maintaining well qualified\ncontractors to guarantee proper rehabilitation works in accordance with existing Lebanon’s high\nroad rehabilitation design standards;\n\n2. Introduce proper and objective road prioritization measures through the visual survey of the\nnetwork’s condition and safety, which will also later inform the creation of a new and integrated\nroad asset management system for Lebanon;\n\n3. Introduce road safety and climate resilient improvements to improve existing road design and\nconstruction standards and practices in Lebanon; and\n\n4. Introduce routine maintenance contracts as an important and efficient asset preservation\nmeasure (including possibly the piloting of performance‐based contracts).\n\n  - **Create significant number of short‐term jobs for Lebanese and Syrians:**\n\n      - Select road sections with required civil works such as drainage and slope stabilization structures\nto increase the labor content of contracts;\n\n\nPage 22 of 90", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 25, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "visual survey", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 886, "end": 899, "key": "sample:jdc_operational:000008:25:1:0", "source": "gold", "luna_reason": "Proposed survey activity, not an existing dataset used for an attributed finding.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "3\n\n\n**2. Project development objective** (see Annex 1)\n\nThe objective of the project is to enhance the quality of education and to increase enrollment in\nprimary schools.\n\n\n**3. Key performance indicators:** (see Annex 1)\n\nThe key performance indicator is an increased number of students enrolled in grades 1-9, especially\namong girls.\n\n\nB. **STRATEGIC CONTEXT**\n\n\n**1. Sector-related Country Assistance Strategy (CAS) goal supported by the project** (see Annex 1)\n\n\n**Document number:** P 7403 DJI **Date of latest CAS discussion:** (scheduled for) 12/19/00\n\nThe CAS has been prepared in the context of the country's economic difficulties and deepening\npoverty. Despite Djibouti's relatively high nominal per capita income (US$790 versus an average of\nUS$510 for Sub-Saharan Africa, and US$100 for Ethiopia), Djibouti has one of the poorest social\nindicators in the world (poverty, illiteracy, maternal and infant mortality, and morbidity), according to\nthe UNDP Human Development Index, ranking 157th among 174 countries.\n\n\nThe Republic of Djibouti has very few natural resources and the economy is mainly dependent on the\nport, external financial assistance, the French military and associated services. However, with the\n\ndecreased amount of external assistance, and deepening structural problems, the country has suffered\neconomic stagnation over the past decade and a half. As a result, per capita Gross Domestic Product\n(GDP) declined by 50% in real terms since 1985. The switch of Ethiopia's transit traffic from Assab in\nEritrea to Djibouti in mid-1998 and the consequent four-fold increase in port traffic has opened new,\nas yet not fully exploited, opportunities for investment and growth. Djibouti's open economic policies\nand relative stability, characterized by a liberal trade policy and exchange system, which operates free\n\nof capital or", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000093", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNDP Human Development Index", "probe_tag": "keep", "probe_score": 0.9622568488121033, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 959, "end": 987, "key": "refugee_pads:000093:6:0:0", "source": "camp2", "luna_reason": "Index cited as evidence for Djibouti's social-indicator ranking.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "The World Bank\nMauritania Water and Sanitation Sectoral Project (P167328)\n\n\n\n8. **Access to water and sanitation**\n**is relatively high, especially in urban**\n\npopulation had access to basic\n\nshould be noted that these figures are\nfor nationals only, and do not include\nrefugees. According to a 2016\ninventory of piped systems, solar pumping is used by 80 percent of the water posts and 50 percent of the smallscale water systems ( _alimentation en eau potable_, AEP) and mini-AEPs.\n\n\n9. **The development of sanitation lags water supply** . In 2015, 63 percent of the urban population, and 20\npercent of the rural population had access to an improved sanitation facility (either individually or shared with\nother households) <sup>9</sup> [^9: UNICEF/WHO, Joint Monitoring Program – 2015 Estimates Updated in 2017.] . Open defecation is prevalent in rural areas, where it is practiced by 61 percent of the\npopulation. While there has been some improvement in terms of access to sanitation in institutions and public\nlocations, only 35 percent of schools and 61 percent of health centers have onsite sanitation facilities.\n\n\n10. **Water supply and sanitation services for refugees are managed by UNHCR and partner non-governmental**\n**organizations (NGO)** . The M’Bera refugee camp is equipped with five boreholes from which water is pumped into\ntwo separate piped systems supplying 12 stand posts. Although the systems are operational, they were\nconstructed in haste, with frequent turnover among contractors, leading to a jumbled system. Consequently,\nthere are many technical issues, such as lack of pressure, which hinder the quality of service and leads to some\nresidents not receiving reliable water supply, particularly at the tail end of the distribution network. As for\nsanitation, the camp has been equipped with double ventilated improved pit (VIP) latrines <sup>10</sup> combined with a\nshower, but the current ratio of four", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000106", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2016\ninventory of piped systems", "probe_tag": "keep", "probe_score": 0.9398746490478516, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 295, "end": 326, "key": "refugee_pads:000106:13:0:0", "source": "camp2", "luna_reason": "Existing inventory supports concrete pumping-use percentages.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "Joint Monitoring Program", "probe_tag": "keep", "probe_score": 0.9571872353553772, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 756, "end": 780, "key": "refugee_pads:000106:13:0:1", "source": "camp2", "luna_reason": "Named source for reported sanitation access figures", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "children, **l6** and child (under 5) mortality due to perinatal period conditions increased substantially in\n2002 to become the leading cause of death for children under 5 and the second leading cause of death\noverall). Per capita food consumption has declined by a quarter since 1998. The incidence o f Post\nTraumatic Stress Disorder (PTSD) has risen significantly and affects women and children in particular.\nNevertheless Palestine society remains fairly cohesive and families for the most part remain functional.\nThis situation together with the responses of the Palestine Authority i s described in more detail in _Twenty_\n_Seven Months, Intifada, Closures and Palestine Economic Crisis,_ May 2003, and ‘in _Palestine: The_\n_Current Socio-Economic Crisis and the Ministry of_ _Social Affairs,_ December, 2002, Report # 25262-02).\n\n\nThe coping capacity of poor households has been strained to the limit. Families have used a variety of\nstrategies to cope with a sharp decline in income.” Initially, many made up for lost income by drawing\non their savings (24 percent), assistance from family and friends (15 percent), cultivating land (10\npercent), or selling property (8 percent). B y November 2001, the number of families reporting income\nwas not enough for their needs had increased to 68 percent, and 17 percent were reducing their expenses,\n\n15 percent were relying on assistance from family and friends, and only 13 percent were able to draw\nfrom their savings. In terms of food, 82 percent of families rely on their own income for their food needs,\nwhile 11 percent rely on family and friends and 7 percent rely on relief assistance. Of those relying on\nrelief assistance for food, the majority were in Gaza. The surveys help illuminate the effectiveness of the\nrelief programs in reaching the poor. Households identified as Hardship Cases receive 56 percent of all\nfood assistance, and those below the poverty line receive another 26 percent", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "surveys", "probe_tag": "keep", "probe_score": 0.9045634865760803, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1725, "end": 1732, "key": "refugee_pads:000047:25:0:0", "source": "camp2", "luna_reason": "Surveys support concrete findings about relief-program reach among poor households.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": " of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an age when they think they can help around the household.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000062", "page": 38, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Household Survey", "probe_tag": "keep", "probe_score": 0.9659751057624817, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 166, "end": 182, "key": "refugee_pads:000062:38:2:0", "source": "camp2", "luna_reason": "Survey data support a concrete finding about girls’ schooling and parental decisions.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": " mean annualized, district‐specific population growth rate\nderived from the 1998 and 2017 Pakistan censuses. <sup>69</sup> It is assumed that the project benefits will\nmaterialize from the second year over the period FY21–24 and that the magnitude of impacts is expected\nto depend on the type of intervention that a facility receives: service utilization of facilities that will be\nimproved within their current level of care is assumed to increase by 30 percent between FY20 and FY24,\nan annualized increase of 6.8 percent. For facilities being upgraded from BHU to RHC, a fourfold increase\nis assumed in utilization over the project cycle, or 41 percent annually—a conservative estimate, as the\ncatchment area of RHCs is typically 10 times that of BHUs.\n\n\n10. **The project is estimated to save the lives of 168 mothers and children under five** (table 1.3) **.** The\nincrease in service utilization is translated into deaths averted using published empirical studies; mortality\nrates for Balochistan were taken from the 2012 and 2017–18 PDHS. <sup>70</sup> Effect sizes for the impacts of an\nadditional skilled birth on maternal and neonatal mortality rates come from Graham, Bell, and Bullough\n(2001) <sup>71</sup> and Bhutta et al. (2014), <sup>72</sup> respectively. The effect size used to estimate the impact of measles\nvaccination on mortality of children under five is based on McGovern and Canning (2015). <sup>73</sup> Because their\neffect size is for full child vaccination, an adjustment factor of 0.89 is applied to the share of children with\n\n\n69 Pakistan Bureau of Statistics. _Population Census 2017_ . http://www.pbs.gov.pk/content/block‐wise‐provisional‐", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000085", "page": 43, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Pakistan censuses", "probe_tag": "keep", "probe_score": 0.9549088478088379, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 90, "end": 107, "key": "refugee_pads:000085:43:1:0", "source": "camp2", "luna_reason": "Censuses provide population data used to derive district-specific growth rates.", "usage_type": "evidential", "specificity": "named"}, {"text": "PDHS", "probe_tag": "keep", "probe_score": 0.9752954840660095, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1040, "end": 1044, "key": "refugee_pads:000085:43:1:1", "source": "camp2", "luna_reason": "PDHS mortality rates are used to estimate deaths averted.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " economic recovery, which started in 2018. Chad entered into\nrecession in 2020 as the economy contracted by 0.9 percent. Both the fiscal and current account balances\ndeteriorated substantially, and difficulties in financing the fiscal deficit may have led to further domestic\narrears’ buildup. The pandemic has highlighted Chad’s oil dependence and vulnerability to multiple and\noften concurrent shocks. The passing of the Chad President in April 2021 deepened the slowdown in\neconomic activity in the second quarter of 2021, as the new authorities shifted public resources from\ncritical investments toward the political transition and security-related spending to curb sociopolitical\ntensions. Economic growth is projected to gradually rise, due to the recovery in global oil markets,\ninternational trade, and economic activity in agriculture and industry. Chad experienced another year of\nrecession, as the economy contracted by 1.2 percent in 2021 (-4.1 percent in per capita terms), after the\n2020 growth contraction of 1.6 percent, due to political and security developments and a two-month\nsuspension of oil production in Esso plants, accounting for one-fourth of the total oil production in Chad.\n\n3. **Security risks originating in neighboring countries have persistently destabilized the regional**\n**economy and created a situation of acute humanitarian needs and large refugee inflows into Chad.** Over\nthe past 25 years, the number of refugees in Chad continued to grow, and many refugees have been in\nthe country for more than a decade. By December 2021, the United Nations High Commissioner for\nRefugees (UNHCR) data indicated that Chad was hosting 560,000 refugees and asylum seekers, accounting\nfor more than 3 percent of the population in the country. <sup>3</sup> [^3: UNHCR data as of December 31, 2021. _[https://data2.unhcr.org/en/country/tcd,](https://data2.unhcr.org/en/country/tcd)_ accessed on January 21, 2022.]", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000193", "page": 15, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "UNHCR data", "probe_tag": "keep", "probe_score": 0.9270403385162354, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1787, "end": 1797, "key": "refugee_pads:000193:15:1:0", "source": "camp2", "luna_reason": "UNHCR data support the reported refugee and asylum-seeker count.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the adverse effects of the situation on\nthe students. The keeping of photographic archives was begun during this mission.\n\n\nThe impacts considered will not be due solely to the project but also to the prevailing situation, which is\ncharacterized by significant degradation of the existing facilities. Since a particular aim of the project is\nto increase the capacity of schools, the main environmental measure to be included in the project will be\nto construct or rehabilitate the sanitary facilities of these schools, and to design a system of upkeep and\nmaintenance that will ensure the appropriate functioning of the schools.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 65, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "photographic archives", "probe_tag": "confusion", "probe_score": 0.21480418741703033, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 363, "end": 384, "key": "refugee_pads:000041:65:1:0", "source": "camp2", "luna_reason": "Archives were begun during the mission, indicating newly produced documentation.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "second cycle of activities. The Mid Term Review will take into account the results of the\nevaluations and readjust the project activities accordingly.\n\n\n38. **The process evaluation will use several sources of data.** The MIS and regular\nmonitoring reports will produce information on whether the key elements of the safety nets\nsystem (targeting mechanism, payment, MIS) have been adequately developed. The process\nevaluation will include interviews with local implementing partners, such as payment agencies\nand NGOs in charge of the accompanying measures, to identify bottlenecks and recommend\nsolutions. A small qualitative beneficiary assessment might be carried out to complete the\nprocess evaluation to assess the satisfaction of direct beneficiaries with payment procedures,\naccompanying measures and with the benefits they will have received.\n\n\n39. **Targeting assessment.** The project targeting approach will be refined as the project starts\nimplementation and on the basis of specific studies supported by the ASP MDTF. The result of\nthe targeting assessment will support the preparation of the manuals. The proposed approach is\nas follows: Beneficiary households will be selected combining community, geographical, and\npoverty approaches; and will include a census of all village households in select areas,\ncategorical targeting (households with children under the age of 12 or with pregnant women) and\na simple PMT exercise. Data will be collected for all pre-selected households, following a list of\nvariables and based on the experience of other targeting techniques, namely the HE A. This will\nallow the calculation of a PMT score to be used to confirm preselected households, reduce\npotential inclusion errors and make the final selection. The community will then discuss the list\nand validate it if in agreement. Comparison of the poverty ranking of the actual beneficiaries\nwith the national survey poverty criteria at different levels will provide the basis for estimating\nthe extent of any inclusion and exclusion errors (ECOSIT 2011 is the most recent national\nhousehold survey, but a new one is expected to be conducted in 2016).\n\n\n40. **", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000028", "page": 59, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "census of all village households", "probe_tag": "confusion", "probe_score": 0.7668625116348267, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1271, "end": 1303, "key": "refugee_pads:000028:59:0:0", "source": "camp2", "luna_reason": "Planned census activity for future beneficiary targeting, not existing data use.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "national\nhousehold survey", "probe_tag": "confusion", "probe_score": 0.5708417296409607, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 2076, "end": 2101, "key": "refugee_pads:000028:59:0:2", "source": "camp2", "luna_reason": "Existing survey underpins poverty comparison and estimates inclusion and exclusion errors.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " laws and regulations on social safeguards and\nland acquisition. The RPF provides clear guidance on minimizing land acquisition and related\nphysical or economic displacement; compensating project-affected persons; rehabilitating\nlivelihoods; addressing grievances; and implementing other aspects of the RPF. If resettlement\ndoes occur in any of the activities, subproject-specific Resettlement Actions Plans (RAPs) or\nAbbreviated Resettlement Action Plans (ARAPs) will be prepared by the CFS following the\nguidelines set out in the RFP. The resettlement process is meant to be inclusive, to encompass\nvulnerable groups such as refugees, and to guarantee that they receive equitable treatment. The\nRPF and RAPs/ARAPs will be reviewed and cleared by the Bank and the Government and\ndisclosed publicly on the World Bank website and in-country.\n\n\n83. **Gender inclusion and SGBV** **_._** Gender issues are critical to the implementation of the Chad\nRefugees and Host Communities Support Project, since refugee women and children are especially\nvulnerable to sexual and gender-based violence. The project will be sensitive to the need to: (a)\nprotect women and children protection from SGBV; (b) increase women’s economic opportunities;\n(c) provide appropriate services to women; (d) establish gender-disaggregated baseline data in\norder to measure the gender impact of the project; and (e) mainstream gender-sensitive approaches\nin all project activities. Moreover, the project will sensitize key stakeholders and contractors on\nthe prevention of SGBV by including specific clauses in bidding documents and contracts. In\naddition, a social and gender assessment is being conducted to examine household dynamics in\n\n\nPage 34", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000112", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "gender-disaggregated baseline data", "probe_tag": "confusion", "probe_score": 0.12031161785125732, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1290, "end": 1324, "key": "refugee_pads:000112:38:1:0", "source": "camp2", "luna_reason": "Project will establish baseline data, indicating planned data production.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": " the ones with the worst indicators.\n\n\nGuinea already benefits from a Multi-Sectoral AIDS Project (MAP) which became effective in\nMarch 2003. The country also received financing from the Global Fund to address the HIViAIDS\nepidemic in 2003. Therefore, the present operation would not invest in this area. HIV/AIDS indicators are\nmonitored by the MAP. And, although those indicators would be looked at during each annual review o f\nthe Five-Year Plan, the present operation would not be held accountable for those indicators.\n\n\n**3.** **Project Components**\n\n\nIt was agreed that the Bank’s comparative advantages would be channeled into activities around the\nfollowing two components:\n\n\n9 **Component I: Strengthening Health Care Services** **_(US$18.99_** **million)**\n\n\nThis component would help strengthen health posts, health centers and hospitals in the 18\nselected prefectures to give quality services to at least one million pregnant women and 933,000\nchildren less than one year o f age. The package o f health services that would be reinforced are\nthose for prenatal care, normal and emergency delivery for women, and those o f the integrated\nmanagement o f childhood diseases, as well as control o f communicable diseases (TB, malaria).\n\n_o_ Sub-component A       - Quality o f care. Investments would be made in particular to: (i)\nreinforce the chain of care for at-risk deliveries, starting with early identification by\nvillage traditional birth attendants (TBAs); (ii) improve the norms and adherence to the\nnorms for basic as well as emergency birth delivery in public and private health centers;\n(iii) improve emergency birth delivery care at the higher levels o f the network, namely in\n‘Centres de SantC AmCliorCs”, private clinics (including NGOs) and prefectoral hospitals;\n\n\n5", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000092", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "HIV/AIDS indicators", "probe_tag": "confusion", "probe_score": 0.23320886492729187, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 305, "end": 324, "key": "refugee_pads:000092:10:1:0", "source": "camp2", "luna_reason": "Indicators are only described as monitored, with no cited finding or analytical use.", "drop_reason": "system_registry", "specificity": "vague"}]}
-{"text": "**233.** In a series of micro-simulations on existing SWF beneficiary and survey data from **2008,** the\nPMT targeting accuracy in increasing the coverage of the poor was compared to the previous Score Card\ntargeting method used by SWF. The SWF **2008** survey included income level information as well as\nPMT/Score Card indicator data, allowing comparison of actual income reported with the PMT and Score\nCard scores for each applicant.\n\n\nThe simulations showed that using the Score Card targeting method would extend coverage to\nonly **8.4** percent of the population and reach only 10.8 percent of the lowest HBS decile (Le., the\npoorest 10 percent).\nBy applying the PMT weights, the coverage for Group A remained approximately the same **(9**\npercent), but reach was extended to cover **26.9** percent of the poorest 10 percent.\nBy including Group A&B data in the simulation, **35** percent of the Yemeni population would be\ncovered and the program would reach _77.5_ percent of the poorest 10 percent.\nIn considering budget allocation to the extreme poor, the Score Card method was found to reach\napproximately 19 percent of the poorest, while the PMT Group A method reached approximately\n**50** percent of the poorest.\n\n\nThese results suggest higher targeting errors (inclusion and exclusion errors) under the Score\nCard targeting method, leading to the recommendation that SWF use the PMT method to increase the\ntargeting accuracy of the program to include poor and vulnerable households.\n\n**_Process of beneficiary selection and enrollment_** - **_reaching out to the poor_**\n\n\n**235.** Reaching the ultra-poor is a challenge: they are often widely dispersed in small settlements, have\nno means of communication with authorities and lack basic skills (i-e., literacy", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 78, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SWF beneficiary and survey data", "probe_tag": "confusion", "probe_score": 0.8420286774635315, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 54, "end": 85, "key": "refugee_pads:000080:78:0:0", "source": "camp2", "luna_reason": "Existing SWF survey and beneficiary data support targeting simulations and findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "SWF **2008** survey", "probe_tag": "keep", "probe_score": 0.9380082488059998, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 241, "end": 260, "key": "refugee_pads:000080:78:0:1", "source": "camp2", "luna_reason": "Existing survey data informed targeting simulations and accuracy comparisons.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nENHANCING CONNECTIVITY AND RESILIENCE IN THE FAR NORTH OF CAMEROON FOR INCLUSIVENESS\nPROJECT (P178207)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|passability during the rainy<br>season.|Col3|Col4|passable road within<br>five kilometers of the<br>MDK road section|Col6|\n|---|---|---|---|---|---|\n|Number of refugees and host<br>communities population with access<br>to an all-weather passable road within<br>five kilometers of the MDK road<br>section.|<br>Number of refugees and<br>people in host communities<br>with access to an all-season<br>road. Climate change<br>impacts are expected to<br>affect road passability<br>during the rainy season.|Yearly<br>|Surveys<br>UNHCR data<br>|The methodology will<br>consist on using survey<br>to calculate the number<br>of refugees and host<br>communities<br>population<br>located within a 5km-<br>buffer zone of each<br>road section<br>rehabilitated and<br>maintained with<br>climate<br>resilience features.<br>|Project Implementation<br>Unit<br>|\n|Share of women with improved<br>access to an all-weather passable<br>road within five kilometers of the<br>MDK road section.|This sub-indicator measures<br>the percentage of women<br>with improved access to an<br>all-weather passable road<br>within five kilometers of the<br>MDK", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000003", "page": 62, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR data", "probe_tag": "confusion", "probe_score": 0.6173585057258606, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 664, "end": 674, "key": "refugee_pads:000003:62:0:0", "source": "camp2", "luna_reason": "UNHCR data is identified as the source for calculating refugee and host-community access.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": " in schools without any WASH facilities available to them, 0.3 million without\navailable water, and another 0.3 million without access to a sanitation facility. <sup>12</sup> [^12: Ministry of Education. 2020. _WASH in Schools Situation Analysis_ . Unpublished draft.] There are about 130,000 children living\nwith disabilities in formal public schools, requiring special consideration for access to WASH facilities. Poor access to\nWASH, and specifically to menstrual hygiene management (MHM) services, has been identified as one of the significant\nbarriers preventing girls from attending and completing school. <sup>13</sup> [^13: Alexander, Kelly T., et al. 2014. “Water, Sanitation and Hygiene Conditions in Kenyan Rural Schools: Are Schools Meeting the Needs of\nMenstruating Girls?” _Water_ 6 (5): 1453–1466. https://doi.org/10.3390/w6051453.] A sampling of healthcare facilities (HCFs) indicated a\n\n\n[6 United Nations High Commissioner for Refugees (UNHCR) (July 2023) https://www.unhcr.org/ke/wp-content/uploads/sites/2/2023/08/Kenya-](https://www.unhcr.org/ke/wp-content/uploads/sites/2/2023/08/Kenya-Statistics-Package-31-July-2023-DIMA.pdf)\n<u>[Statistics-Package-31-July-2023-DIMA.pdf.](https://www.unhcr.org/ke/wp-content/uploads/sites/2/2023/08/Kenya-Statistics-Package-31-July-2023-DIMA.pdf)</u>\n7 For a map, see https://data2.unhcr.org/en/country/ken.\n8 Socioeconomic Hubs for Integrated Refugee Inclusion in Kenya.\n9 UN University Institute for Water, Environment and Health (2022) Water Security in Africa: A Preliminary Assessment, Issue 13\nhttps://inweh.unu.edu/water-security-in-africa-a-preliminary-assessment/\n[10 Kenya Population and Housing Census", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000190", "page": 13, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Kenya Population and Housing Census", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1635, "end": 1670, "key": "refugee_pads:000190:13:2:0", "source": "camp2", "luna_reason": "Named population census cited as an existing data source.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "\n(42). The two Hodhs together make up 50 percent of the needs. Following this initial list, a feasibility study was\nconducted as part of project preparation to verify parameters such as population size and technical feasibility\nand from this basis, the final list of infrastructures per region was determined.\n\n3. As for urban and semi-urban centers, SNDE expressed its specific needs of infrastructure rehabilitation\ninvestments which cover 19 semi-urban centers (localities of more than 5,000 inhabitants), formerly managed\nby ONSER but which were transferred to SNDE, following the multiple failures of ONSER management. Seven\nof these centers will benefit from the project through rehabilitation and expansion, after which they will be\ndelegated to private operators.\n\n4. The activities related to sanitation were developed based on the needs expressed by the DA, in\nconsultation with the Ministries of Health and Education. According to the data presented by DA, 1,746 of the\n2,283 schools surveyed do not currently have latrines (256 in Assaba, 303 in Gorgol, 193 in Guidimakha, 500 in\nHodh Ech Echargui and 494 in Hodh El Gharbi). With regard to health centers, the DA indicated the latrine\nrequirements for 25 centers in Assaba, none in Gorgol, 20 in Guidimakha, 86 in Hodh Ech Echargui and 53 in\nHodh El Gharbi.\n\n5. The selection of water and sanitation activities in the M’Bera refugee camp is based on assessments of the\nexisting facilities. A diagnostic report of water and sanitation infrastructure, commissioned by UNHCR,\nprovided useful background information on the profile of the camp, its infrastructure and the surrounding\ncommunities. In addition, a World Bank team visited the refugee camp in March 2019 and in November 2019\nfor field assessments as part of project preparation. Both the report and the field visits helped to inform the\ndesign of the water and sanitation interventions in the", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000106", "page": 52, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data presented by DA", "probe_tag": "confusion", "probe_score": 0.3634602725505829, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 946, "end": 966, "key": "refugee_pads:000106:52:1:0", "source": "camp2", "luna_reason": "DA-presented data supports the concrete finding on schools lacking latrines.", "usage_type": "evidential", "specificity": "named"}, {"text": "diagnostic report of water and sanitation infrastructure", "probe_tag": "confusion", "probe_score": 0.6706436276435852, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1455, "end": 1511, "key": "refugee_pads:000106:52:1:1", "source": "camp2", "luna_reason": "Existing UNHCR-commissioned report informed intervention design.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the adverse effects of the situation on\nthe students. The keeping of photographic archives was begun during this mission.\n\n\nThe impacts considered will not be due solely to the project but also to the prevailing situation, which is\ncharacterized by significant degradation of the existing facilities. Since a particular aim of the project is\nto increase the capacity of schools, the main environmental measure to be included in the project will be\nto construct or rehabilitate the sanitary facilities of these schools, and to design a system of upkeep and\nmaintenance that will ensure the appropriate functioning of the schools.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 65, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "photographic archives", "probe_tag": "confusion", "probe_score": 0.21480418741703033, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 363, "end": 384, "key": "refugee_pads:000147:65:1:0", "source": "camp2", "luna_reason": "Archives were begun during the mission, indicating newly produced project documentation.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\ncomprehensive framework is required to ensure that the various efforts on the ground are integrated and support the\nsame long-term goal of the city’s development. As such, rehabilitating the coastal (blast) zone for the urban population\nprovides a great opportunity to recover not only the physical condition of the infrastructure and residential assets,\nbut also to envision the regeneration of the waterfront neighborhoods as part of an integrated port-city development\napproach that considers social inclusion, sustainability, and local economic development. However, actions towards\nthis vision have not yet begun and the government does not have a clear ownership or capacity to kickstart this phase\nof the recovery.\n\n**11.** **The lack of coordinated policies and support systems for property owners and occupants has rendered housing**\n**conditions contingent on the owners’ ability or willingness to pay for necessary works.** <sup>**28**</sup> Low and middle-income\nhouseholds are under the greatest distress, and consequently in most need of financial and physical support for heavy\nrehabilitation and rental costs. Precarious tenure and the threat of evictions by property owners are of great concern\nin Beirut, particularly for the most vulnerable groups. A multisectoral needs assessment of two of the most blastaffected neighborhoods, Karantina and Mar Mikhael, highlights the precarious tenure conditions for many of those\nmost affected, with up to 57.2 percent of respondents without an official lease agreement and 3.2 percent of\nrespondents had lost these documents in the blast. <sup>29</sup> <sup>30</sup> Beyond the physical damage of the blast, housing speculation\nis threatening the preservation of the cultural and social identity of the central areas of Beirut.\n\n**12.** **The lack of effective coordination between entities in", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "multisectoral needs assessment", "probe_tag": "confusion", "probe_score": 0.6942591071128845, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1377, "end": 1407, "key": "refugee_pads:000034:15:0:0", "source": "camp2", "luna_reason": "Existing assessment supports concrete findings on tenure conditions and lease documentation.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "**PAD DATA SHEET**\n\n\n_Lebanon_\n\n\n_Lebanon Municipal Services Emergency Project (P149724)_\n\n\n**PROJECT APPRAISAL DOCUMENT**\n\n\n_MIDDLE EAST AND NORTH AFRICA_\n\n\n_MNSSU_\n\n\nReport No.: PAD1018\n\n|Basic Information|Col2|Col3|\n|---|---|---|\n|Project ID|EA Category|Team Leader|\n|P149724|B - Partial Assessment|Chantal Reliquet|\n|Lending Instrument|Fragile and/or Capacity Constraints [ X ]|Fragile and/or Capacity Constraints [ X ]|\n|Investment Project Financing|- Fragile within a non fragile<br>country<br>|- Fragile within a non fragile<br>country<br>|\n||Financial Intermediaries [  ]|Financial Intermediaries [  ]|\n||Series of Projects [  ]|Series of Projects [  ]|\n|Project Implementation Start Date|Project Implementation End Date|Project Implementation End Date|\n|20-June-2014|30-June-2017|30-June-2017|\n|Expected Effectiveness Date<br>Expected Closing Date|Expected Effectiveness Date<br>Expected Closing Date|Expected Effectiveness Date<br>Expected Closing Date|\n|1-July-2014<br>30-Dec-2017|1-July-2014<br>30-Dec-2017|1-July-2014<br>30-Dec-2017|\n|Joint IFC<br> <br>|Joint IFC<br> <br>|Joint IFC<br> <br>|\n|No<br> <br>|No<br> <br>|No<br> <br>|\n|Sector Manager<br>Sector Director<br>Country Director<br>Regional Vice President|Sector Manager", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PAD DATA SHEET", "probe_tag": "drop", "probe_score": 0.04990347847342491, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 2, "end": 16, "key": "jdc_operational:000003:5:0:0", "source": "camp2", "luna_reason": "Standalone document/table heading, not a cited or used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " Procurement Documents:** The World Bank’s Standard Procurement Documents (SPDs) shall be used for\nprocurement of goods, works, and non-consulting services under Open International Competitive Procedures. National\nBidding documents as set forth in the Public Procurement and Disposal Act, 2003 may be used under Open National\ncompetitive as well as for the Request for Quotation method subject to the inclusion of the universal eligibility and ES\nprovisions. Selection of consultant firms shall use the World Bank’s SPDs, in line with procedures described in the\nProcurement Regulations.\n\n\n37. In accordance with paragraph 5.3 of the Procurement Regulations, the request for bids/request for proposals\ndocument shall require that Bidders/Proposers submitting Bids/Proposals to present a signed acceptance at the time of\nbidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the World Bank’s\nAnti-Corruption Guidelines, including without limitation the World Bank’s right to sanction and the World Bank’s\ninspection and audit rights.\n\n\n38. **Record keeping and management.** All records pertaining to award of tenders, including bid notification, register\npertaining to sale and receipt of bids, bid opening minutes, bid evaluation reports and all correspondence pertaining to\nbid evaluation, communication sent to/with the World Bank in the process, bid securities, and approval of\ninvitation/evaluation of bids will be retained by the respective agencies in electronic or hard copy and uploaded in STEP.\n\n\n40 (a) open advertising of the procurement opportunity at the national level; (b) the procurement is open to eligible firms from any country; (c) the\nrequest for bids/request for proposals document shall require that Bidders/Proposers submitting Bids/Proposals present a signed acceptance at the\ntime of bidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the World Bank’s Anti-Corruption\nGuidelines,", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 70, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "register\npertaining to sale and receipt of bids", "probe_tag": "drop", "probe_score": 0.023, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1196, "end": 1243, "key": "sample:jdc_operational:000025:70:1:0", "source": "gold", "luna_reason": "Procurement bid register retained for recordkeeping, not substantive data analysis.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "|\n|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|\n|Fiscal Year|2015|2016|2017||||||||||||||\n|Annual|9.00|6.00|3.00||||||||||||||\n|Cumulative|9.00|15.00|18.00||||||||||||||\n|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Institutional Data", "probe_tag": "drop", "probe_score": 0.036259736865758896, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 877, "end": 895, "key": "jdc_operational:000007:6:1:0", "source": "camp2", "luna_reason": "Standalone table header, not an actual cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "Institutional Data", "probe_tag": "drop", "probe_score": 0.011391296982765198, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 877, "end": 895, "key": "jdc_operational:000007:6:1:2", "source": "camp2", "luna_reason": "Standalone table header, not a cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Uganda Support to<br>Municipal Infrastructure<br>Development Program<br>Additional Financing<br>(P163515)<br>Financing: US360 million<br>WHR: US50 million|Enhance institutional performance of program<br>local governments for urban service delivery.<br>This includes planning, land tenure security,<br>and small-scale infrastructure investments<br>within refugee-hosting urban centers and their<br>wider districts. It will support eight refugee-<br>hosting districts. The focus is secondary cities.|1. Collaboration with the Ministry of Land<br>and Urban Development for the adequate<br>inclusion of common-user facilities the<br>cross-sectoral fiscal plans for local<br>development (only the framework has been<br>developed).<br>2. Complementary infrastructure<br>investments in RHDs (for example, USMID<br>roads, lighting, and markets in RHDs can be<br>supplemented by GROW business<br>infrastructure)<br>3. Both focus on strengthening district level<br>implementation and management of<br>infrastructure needs in RHDs.|\n|---|---|---|\n|**GBV and Violence Against**<br>**Children Prevention and**<br>**Response Services in**<br>**Uganda’s Refugee-Hosting**<br>**Districts Report**<br> <br>**Financing:**US$0.5 million <br>|To mitigate GBV and prevent violence against<br>children through engagement", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 75, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Districts Report", "probe_tag": "drop", "probe_score": 0.039743680506944656, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1300, "end": 1316, "key": "jdc_operational:000025:75:0:0", "source": "camp2", "luna_reason": "Standalone table fragment, not a data source or data-use statement.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " among small scale farmers**|** Enhanced production and income generation among small scale farmers**|\n|Description|The number of small-scale farmers supported to improve production|\n|Frequency|Annual|\n|Data source|Project progress report, Ministry of Agriculture|\n|Methodology for Data<br>Collection|Biannual review, number of trainings and grants provided|\n|Responsibility for Data<br>Collection <br>|MoHAIS <br>|\n\n\n\n**<u>Monitoring & Evaluation Plan: Intermediate Results Indicators by Components</u>**\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: Intermediate Result Indicators|Col2|\n|---|---|\n|**Number of legislative reforms instituted in support of policy objectives**|**Number of legislative reforms instituted in support of policy objectives**|\n|Description|The indicator will measure the number of legal and policy reforms identified for amendment to support implementation<br>of the Refugee Policy by addressing inconsistencies in existing laws that prevent refugees and former refugees from<br>accessing basic services and regularizing their immigration status.|\n|Frequency|Biannual|\n|Data source|Project progress report, cabinet memos|\n|Methodology for Data<br>Collection|Data collected through minutes of the interministerial committee (MORHCSA) meetings, Parliamentary committee<br>reports|\n|Responsibility for Data<br>Collection <br>|MoHAIS <br>|\n|**Stakeholder consultations convened and priority measures identified**|**Stakeholder consultations convened and priority measures identified**|\n|Description|Number of high-level consultations held with relevant government ministries and civil society organizations to deliberate<br>on measures identified for legislative and regulatory reform, implementation performance, roles and responsibilities of|\n\n\nPage 35", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000187", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Project progress report", "probe_tag": "keep", "probe_score": 0.9178452491760254, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 215, "end": 238, "key": "refugee_pads:000187:38:1:0", "source": "camp2", "luna_reason": "Data-source citation identifies the progress report underlying the monitoring indicator.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000102", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household expenditure survey data", "probe_tag": "keep", "probe_score": 0.9571933746337891, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 565, "end": 598, "key": "refugee_pads:000102:38:1:0", "source": "camp2", "luna_reason": "Survey data supports enrollment-rate comparisons across expenditure quintiles.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "survey data", "probe_tag": "keep", "probe_score": 0.9347544312477112, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 870, "end": 881, "key": "refugee_pads:000102:38:1:1", "source": "camp2", "luna_reason": "Existing survey data supports enrollment-gap findings and clarifies education-level separation.", "usage_type": "evidential", "specificity": "vague"}, {"text": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9652993679046631, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1978, "end": 2008, "key": "refugee_pads:000102:38:1:2", "source": "camp2", "luna_reason": "Existing household survey data supports a concrete finding about girls leaving school.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000022", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "household\nexpenditure survey data", "probe_tag": "keep", "probe_score": 0.9439554214477539, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1661, "end": 1694, "key": "refugee_pads:000022:19:0:0", "source": "camp2", "luna_reason": "Survey data supports a concrete enrollment-rate comparison from 1996.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " Food Programme (WFP), the United Nations Children’s Fund (UNICEF), the\nFood and Agriculture Organization, the Islamic Development Bank, the United States Agency for Development, and the\nNorwegian Refugee Council) which were mainly focused on providing food to vulnerable populations. At present, the\nscale and funding of SSN programs remains inadequate to protect most poor and vulnerable groups. According to the\nlatest available data, only 32.7 percent of the poorest 20 percent of households are covered by any SSN program. In\naddition, the Government’s share of spending in SSN is quite limited, as Djibouti only spends 0.18 percent of its GDP on\n\n\n10 Hallegatte et al, “Shockwaves: Managing the Impacts of Climate Change on Poverty”, World Bank, 2016.\n11 Wooden et al, “ _Impact of Weather Shocks on MENA Households_ ”, World Bank, 2014.\n12 _Djibouti’s First NDC_, August 2015, p2.\n\n\nPage 8 of 44", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000063", "page": 12, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "latest available data", "probe_tag": "keep", "probe_score": 0.913141667842865, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 415, "end": 436, "key": "refugee_pads:000063:12:2:0", "source": "camp2", "luna_reason": "Available data supports the reported SSN coverage figure.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "**The World Bank**\nSudan Basic Education Emergency Support Project (P172812)\n\n\n19. The current economic analysis presents estimates of the efficiency gains in basic education to 2021, based on\nenrollment estimates employing UN population projections, average values from recent years for intake into\nGrade 1 of basic education (from the School Census) relative to population, and recent trends in promotion\nand retention in each grade of basic school. The analysis employs the same projections as the current\nEducation Sector Strategic Plan (ESSP) including for the GDP growth (IMF/World Bank), share of domestic\nresources spent on education (a 0.5 p.p. annual increase from 9.8 percent in 2017/18).\n\n\n20. _Gains from improved Internal Efficiency_ . The project objective is to sustain enrollment in public schools\nmeaning that the enrollment in target schools is to increase at the rate of the population growth – 2.5 percent\nper annum: from 5.40 million pupils to 5.54 million in 2021. The analysis is built on the assumption that survival\nand repetition rates will remain unchanged.\n\n21. We compare inefficient government spending under the expected scenario and a scenario, under which there\nis no increase in the student enrollment. The following formula is used to estimate inefficient spending:\n\n\n\n𝟖\n\n\n\n𝒙 <sup><u>𝒊</u></sup> ∗𝑮𝒙𝒊\n\n\n\n𝒙\n\n𝑰𝒏𝒆𝒇𝒇𝒊𝒄𝒊𝒆𝒏𝒕 𝑺𝒑𝒆𝒏𝒅𝒊𝒏𝒈 = ∑( <sup>𝑫𝒊</sup>\n\n\n\n𝑮𝒊\n\n\n\n𝒙 ) ∗𝑺 <sup>𝒙</sup>,\n\n\n\n𝒙𝒊\n\n\n\n𝒊=𝟏\n\n\n\nwhere 𝑫𝒊𝒙 is the dropout rates in grade 𝒊 in year 𝒙 in target schools; 𝑮𝒙𝒊 is the number of pupils enrolled in\n\ngrade 𝒊 in year 𝒙 ; 𝑺 <sup>𝒙</sup> is the projected government spending per pupil in year 𝒙 .\n\n22. According to the", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000024", "page": 43, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UN population projections", "probe_tag": "keep", "probe_score": 0.9506517648696899, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 224, "end": 249, "key": "refugee_pads:000024:43:0:0", "source": "camp2", "luna_reason": "UN projections underpin enrollment estimates in the economic analysis", "usage_type": "evidential", "specificity": "named"}, {"text": "School Census", "probe_tag": "keep", "probe_score": 0.9061861634254456, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 337, "end": 350, "key": "refugee_pads:000024:43:0:1", "source": "camp2", "luna_reason": "School Census data inform enrollment estimates used in efficiency analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "The World Bank\nMauritania Water and Sanitation Sectoral Project (P167328)\n\n\n8. The consumer surplus is equal to the increase of water consumption multiplied by the difference of\nthe water price paid before and after the project and by the price elasticity (0.5).\n\n\n**Table 4.4: Consumption and Water Prices with and without Project**\n\n\n\n\n\n|Col1|Without project|Col3|With project|Col5|\n|---|---|---|---|---|\n|**Current/ future source of supply**|**Consumption**<br>**(lpcd)**|**Cost**<br>**(MRU/m3) **|**Consumption**<br>**(lpcd)**|**Cost**<br>**(MRU/**<br>**m3) **|\n|Distant sources/ stand posts (small water systems)|3|159|15|50|\n|Distant sources/ connection (regular watersources)|3|159|20|25|\n|Neighbor/ own connection|Neighbor/ own connection|Neighbor/ own connection|Neighbor/ own connection|Neighbor/ own connection|\n|-7 SNDE centers|8.9|40|20|25|\n|Kiffa|16|40|30|25|\n\n\n_Source: ONSER surveys, SNDE and World Bank estimates._\n\n\n\n\n\n\n\n9. **Sensitivity Analysis** . A range of scenarios has been developed to test the sensitivity of the EIRR to the\nmain elements of the economic cash-flows. The variables tested were: (i) investment costs; (ii) operating\ncosts; and (iii) water demand. The outcome of the scenarios is given in", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000106", "page": 60, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "ONSER surveys", "probe_tag": "keep", "probe_score": 0.9015008807182312, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 885, "end": 898, "key": "refugee_pads:000106:60:0:0", "source": "camp2", "luna_reason": "Named surveys cited as the source for tabled consumption and water-price estimates.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " their own<br>indicators but also on the geographical location where<br>they live<br>- <br>The Social Registry will have the capacity to refer<br>beneficiaries affected by climate change to existing social<br>programs|\n|**Component 4:**<br>**Integration of**<br>**refugee and host**<br>**communities into**<br>**national social**<br>**protection systems**<br>**(US$ 20 million)**<br> <br>Cash transfers<br>Productive inclusion<br>Sensitization<br>on<br>climate<br>change<br>adaptation<br>and<br>mitigation, including links<br>between<br>nutrition<br>and<br>climate change<br>- <br>Reduces the pressure of refugees on resources from host<br>communities<br>- <br>Livelihood diversification (alternative to agriculture)<br>- <br>Reduce reliance on deforestation as a livelihood<br>- <br>Beneficiaries will receive extension services on crops that<br>are more adapted to changing climatic conditions<br>- <br>Behavior change interventions with information on timing<br>of rainy and lean seasons or which kinds of crops to<br>diversify out of or into; (ii) savings interventions to<br>generate a buffer to absorb climate shocks, enable<br>investments in adaptation or adjustment of livelihood<br>portfolios; (iii) skills training and coaching to support<br>diversification of livelihoods|**Component 4:**<br>**Integration of**<br>**refugee and host**", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 88, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "Social Registry", "probe_tag": "confusion", "probe_score": 0.2966858744621277, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 95, "end": 110, "key": "refugee_pads:000130:88:4:0", "source": "camp2", "luna_reason": "Names a registry without showing its data being used.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": "**The World Bank**\nStrengthening Institutions for Refugee Administration Project (P165542)\n\n\n\n\n\n\n\n\n\n|Women employed in CCAR and CARs|Measures combined share<br>of CCAR and CAR employees<br>that are women|Annually|CCAR/CAR<br>HR records|Reports from HR data<br>bases of CCAR and CAR|CCAR and CAR|\n|---|---|---|---|---|---|\n|Host communities with functioning<br>complaints handling mechanisms|This indicator measures the<br>proportion of refugee<br>communities countrywide<br>that have established local<br>level complaint handling<br>mechanisms.|Semi-<br>Annual<br>|Refugee<br>hosting<br>communities<br>|Review of the list<br>describing the host<br>communities and the<br>nature of their<br>Grievance Redress<br>Mechanism<br>|CCAR<br>|\n|Women employed in professional<br>positions in the Operations Support Unit<br>to support project implementation|Measures proportion of<br>professional women<br>employees in the OSU.<br>Targets are cumulative.|Annual<br>|Payroll of the<br>OSU<br>|Review of payroll data<br>and head count of<br>professional women<br>employees<br>|OSU<br>|\n|Quarterly progress reports submitted<br>within 15 days after the end of the<br>reporting cycle<br>|Measures submission of<br>progress reports on a<br>quarterly basis. Each year, at<br>least four reports expected.|<br>Quarterly<", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000009", "page": 32, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "HR data", "probe_tag": "confusion", "probe_score": 0.5466874837875366, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 249, "end": 256, "key": "refugee_pads:000009:32:0:1", "source": "camp2", "luna_reason": "HR data supports the reported share of women employed in CCAR and CARs.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "payroll data", "probe_tag": "confusion", "probe_score": 0.23358580470085144, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 992, "end": 1004, "key": "refugee_pads:000009:32:0:2", "source": "camp2", "luna_reason": "Routine payroll records used for project staffing headcount, not substantive external data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
+{"text": "its Public Expenditure\nTracking Survey (PETS)\n\nscorecard inproves each\nsemester\n\n\n\n**Project Components /** **Inputs:** **(budget for** each Project reports: (from Components to\nSub-components: component) Outputs)\n\n\n\n1. Community Driven - US$ 28.0 million (IDA $25.0 <sup>- M&E data</sup> - Cormnunities emnpowered\n\n\n\n**Program** (CDP) million) - Quarterly progress reports; and responsible for\nimplementing sub-projects;\n\n                                                  - Implemnenting partners <sup>are</sup>\ncomnpetent to support\n**2.** Pilot and Special\n\n\n\n**Programs in** Newly cormmunities;\n\n                                                - Implementing partners\n**Accessible** **Areas**\n\n                - US$ 2.0 mnillion (ODA <sup>$1.75</sup> participate in capacity building\n\n\n\n**(a)** **Rural Public Works** million) activities;\n\n                - US$ 2.0 million (IDA <sup>$1.75</sup>                - Operations Manual and\n\n\n\n**(b)** **Shelter** Program **for** million) annexed Handbooks for Direct\n\nFinancing to Communities <sup>and</sup>\n**Vulnerable** **Groups**\n\n               - US$ 10.0 million (IDA <sup>$6.5</sup>                - NaCSA and IDA Public Works are thorough,\n\n\n\n3. **Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**In", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000096", "page": 32, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Public Expenditure\nTracking Survey", "probe_tag": "confusion", "probe_score": 0.8166483640670776, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 4, "end": 38, "key": "refugee_pads:000096:32:0:0", "source": "camp2", "luna_reason": "Named expenditure-tracking survey is referenced as an existing data resource.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " 2017 and was reconfirmed under IDA19 in September 2020, with the\napproval of the Additional Financing to the Refugees and Host Communities Support Project (P164748).\n\n6. **The World Bank, following consultations with UNHCR, confirms that the protection framework**\n**for refugees is adequate in Chad** **(UNHCR update of August 8, 2021).** It has an adequate institutional and\nmonitoring framework to ensure the implementation of the refugee protection framework, <sup>5</sup> [^5: See annex 2 for details.] including (a)\na dedicated agency, National Commission for Reception and Reintegration of Refugee and Returnees\n( _Commission Nationale d'Accueil de Réinsertion des Réfugies,_ CNARR) set up within the GoC to manage\nrefugee protection; (b) an action plan to implement a Comprehensive Refugee Response Framework; (c)\na ministerial-level high committee integrating representatives of all sectors contributing to the refugee\nagenda; and (d) the Asylum Law enacted in December 2020. In 2020–2021, a reduction of food assistance\nin some refugee camps and the COVID-19 restrictions temporarily heightened protection risks and access\nto socioeconomic services but these have since been reduced or mitigated.\n\n7. **In terms of gender equality, Chad ranks 147 out of 153 countries for the Global Gender Gap**\n**Index and 187 out of 189 for the Gender Inequality Index with significantly worsening trends in the past**\n**few years.** <sup>6</sup> [^6: Human Development Report: _[http://hdr.undp.org/sites/default/files/hdr2020.pdf](http://hdr.undp.org/sites/default/files/hdr2020.pdf)_] Women are disadvantaged for productive activities due to limited agency, access to resources,\nand employment opportunities as well as high fertility rates that can exacerbate these challenges. In\naddition, female-headed households are on average", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000193", "page": 16, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Gender Inequality Index", "probe_tag": "confusion", "probe_score": 0.7192186117172241, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1342, "end": 1365, "key": "refugee_pads:000193:16:1:0", "source": "camp2", "luna_reason": "Named index cited for Chad's gender inequality ranking, sourced to the Human Development Report.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " économique et sociale – PRES_ ), underpinned by a dedicated\nSolidarity Fund at the Central Bank of Western African States – FORCE-COVID-19. The main objectives of PRES are to\nupgrade the health system and mitigate the economic fallout, while providing targeted support to vulnerable\nhouseholds and firms. In particular, it allowed the GoS to pay for the electricity bills of the most vulnerable\nhouseholds of Senegal (975,000) between May and June 2020 – for a total cost of US$34 million. In addition, the GoS\nissued on September 5, 2020, a new version of its Priority Action Plan - Adjusted and Accelerated (PAP 2A). The PAP\n2A, spanning 2021-23, seeks to ensure that the economy is on track to meet the objectives of the National\n\n[25] Enquête Harmonisée sur les Conditions de Vie des Ménages (EHCVM) 2018/19.\n\n[26] Between 2005 and 2015 poverty reduction in several countries in SSA exceeded 1 p.p. per year: Tanzania (-2.6 p.p.); Rwanda (-1.5 p.p.) and Ghana (-1.3\np.p.). Over the same period, Senegal reduced poverty at an annual rate of 0.43 p. p. and only by 0.65 p.p. per year between 2011 and 2018. Source: World\nBank staff calculations using _[PovCalNet](http://iresearch.worldbank.org/PovcalNet/povOnDemand.aspx)_ 2020 harmonized surveys and Macro Poverty Outlook Fall 2019 for the evolution between 2011 and 2018.\n\n[27] Sub-Saharan Africa is 0.894.\n\n[28] UNDP, 2020. Human Development Report, Senegal. http://hdr.undp.org/sites/default/files/Country-Profile", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000116", "page": 11, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "PovCalNet", "probe_tag": "confusion", "probe_score": 0.7439053654670715, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1156, "end": 1165, "key": "refugee_pads:000116:11:2:0", "source": "camp2", "luna_reason": "PovCalNet harmonized surveys underpin World Bank staff poverty calculations.", "usage_type": "evidential", "specificity": "named"}, {"text": "2020 harmonized surveys", "probe_tag": "confusion", "probe_score": 0.5870317220687866, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1227, "end": 1250, "key": "refugee_pads:000116:11:2:1", "source": "camp2", "luna_reason": "Harmonized surveys are cited as sources for World Bank poverty calculations.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000093", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Household Expenditure Survey", "probe_tag": "confusion", "probe_score": 0.8797882199287415, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1906, "end": 1934, "key": "refugee_pads:000093:9:0:0", "source": "camp2", "luna_reason": "Recent survey supports a concrete population-distribution finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "**Annex 10: IBRD Map 39860 showing Local Governments included under LGDP**\n\n\n                       - 81", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000166", "page": 95, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "IBRD Map 39860", "probe_tag": "confusion", "probe_score": 0.6364783644676208, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 12, "end": 26, "key": "refugee_pads:000166:95:0:0", "source": "camp2", "luna_reason": "Named IBRD map presents the included local governments under LGDP.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "No**|**Investment name**|**Scope**|**Budget**<br>**(million EUR)**|\n|C-1|Extension of Kayseri<br>Wastewater<br>Treatment Plant|• <br>Extension of existing WWTP (2nd phase) and installation of solar sludge<br>drying facility; replacement of existing belt filters with decanter units.|25|\n\n\n\n**.Konya Municipality**\n\n\n22. **Konya context.** The refugee population in Konya consists mainly of Syrians and Afghans. In 2018, Konya province\nhad a total population of about 2,205,609 <sup>52</sup> [^52: As per the address-based census for 2018] people out of which 109,124 (or 4.95 percent of the total population)\nwere SuTP’s <sup>53</sup> [^53: Calculations based on PID for Konya and projected estimates for the year 2020.] . There are no refugee camps in Konya <sup>54</sup> [^54: UNHCR Turkey: Syrian Refugee Camps and Provincial Breakdown of Syrian Refugees Registered in South East Turkey (January 2020):\n_[https://data2.unhcr.org/en/documents/details/73300](https://data2.unhcr.org/en/documents/details/73300)_, accessed on January 15, 2020], refugees are mainly living in the central districts of Konya.\nSince 2014, water supply and sanitation services for the metropolitan municipality of Konya are provided by Konya\nWater and Sewerage Administration General Directorate (KOSKİ). Due to high seasonal variations in the availability\nof water resources and the high NRW (57 percent) <sup>55</sup> [^55: According to PID for Konya], KOSKİ has developed the following investment project for\nAkşehir district.\n\n\n23. **Konya Sub-Project.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000125", "page": 67, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "address-based census for 2018", "probe_tag": "keep", "probe_score": 0.9427332282066345, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 508, "end": 537, "key": "refugee_pads:000125:67:1:0", "source": "camp2", "luna_reason": "Existing census provides the cited 2018 population figure.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "PID for Konya", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 663, "end": 676, "key": "refugee_pads:000125:67:1:2", "source": "camp2", "luna_reason": "PID data underlies calculated refugee population estimates.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "- **_Reducing pesticides_** . Farmers currently rely on application of chemical pesticides, with little\n\nknowledge about their handling and management. The project will control the use of pesticides\non rational basis according to IPM tactics and practices on farm. This component aims to\n**reduce pesticides application by about 40-50 percent** of their current use in targeted crops\n(FAO 2015).\n\n109. **Activities** _._ IPM activities will be implemented through the FFS methodology, which is a\nproven methodology based on a participatory approach to train and empower farmers on the use of\nIPM techniques and on the proper handling and disposal of pesticides. Similar participatory approaches\nwill be used to train farmers on alternative methods and practices for sustainable fertilizer use in the\nproject area. Baseline surveys and regular farm visits will be conducted to monitor the use of\nagrochemicals by targeted farmers as well as the sales of these chemicals in the project area.\n\n110. **Steps** _._ The component is based on four steps:\n\n(a) Assessing current agricultural practices and developing GAP-IPM program. Review previous\n\nsurveys, undertake chemical analysis of soil and water, and identify essential practices to\naddress existing gaps (that is, activities, target farmers, and crops).\n(b) Train professionals and facilitators in GAP-IPM practices. Train field technical staff from\n\nMoA, other stakeholders, and facilitators on extension and FFS methods to promote the\npractices identified above.\n(c) Implement the GAP-IPM program at the farm. Identify the FFS curriculum and agricultural\n\ninputs needed and establish and run the FFS based on crops and target areas.\n(d) Evaluate and monitor for sustainability. Provide the monitoring, review, and follow-up\n\nstrategy for sustainability of the project outcomes.\n\n\n111. Given that the FAO has been implementing a Regional Integrated Pest Management Program\nin the Near East since 2004 that covers ten countries (including Lebanon)", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000036", "page": 38, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Baseline surveys", "probe_tag": "confusion", "probe_score": 0.06484626233577728, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 814, "end": 830, "key": "refugee_pads:000036:38:0:0", "source": "camp2", "luna_reason": "Future baseline surveys will be conducted by the project.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": " an increase by 600,000 from\nthe previous year. <sup>10</sup> [^10: United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA). 2022. _South Sudan Humanitarian Needs Overview 2022._\n11Integrated Food Security Phase Classification (IPC) -the severity and magnitude of food insecurity\nclassifying units of analysis in five distinct phases: (1) Minimal/None, (2) Stressed, (3) Crisis, (4) Emergency, (5) Catastrophe/Famine] In the current IPC analysis period of February to March 2022, an estimated 6.83 million people (55.3\npercent of the population) are facing Crisis (IPC Phase 3) or worse acute food insecurity, of which 2.37 million people are\nfacing Emergency (IPC Phase 4) acute food insecurity. An estimated 55,000 people are classified in Catastrophe (IPC Phase\n5) acute food insecurity. It is expected that food insecurity levels will remain elevated due to the impact of severe flooding\nand drought on livelihoods, conflict, and persistent macroeconomic challenges. The percentage of the population that\nhas experienced crisis (IPC3 <sup>11</sup> ) or emergency (IPC4) conditions has increased significantly over the last few years (Figure\n1). <mark>In addition, an estimated 2 million people, including 1.3 million children under the age of five, and 676,000</mark>\n<mark>pregnant and lactating women, are expected to be acutely malnourished in 2022.</mark> <sup>12</sup> [^12: OCHA- South Sudan Humanitarian Needs Overview 2022 (February 2022)]\n\n\n5 Climate induced natural disasters have increased in recent years in terms of intensity, frequency, and complexity, such that in 2017,\nSouth Sudan ranked among the five worst-performing countries in the world in tackling the impact of climate change, according to the\nClimate Change Vulnerability Index.\n6 World Bank. 2021", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000153", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Climate Change Vulnerability Index", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1744, "end": 1778, "key": "refugee_pads:000153:12:1:0", "source": "camp2", "luna_reason": "Index supports the stated ranking of South Sudan's climate-change performance.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\nindicated that they struggled to make ends meet. <sup>12</sup> [^12: Federation of Small and Medium Sized Enterprises in Uganda (August 2021).] Of those MSMEs in Kampala, 45 percent reported closing their\nbusiness as a direct consequence of the pandemic. They were facing both demand (willingness to spend) and\nsupply (labor force disruptions) constraints. Socioeconomically depressed districts, such as those hosting refugees,\nare expected to be even further negatively impacted. The poorest quintiles and vulnerable communities, including\nrefugees, are already showing significant income reductions and increased food insecurity.\n\n\n**B. Sectoral and Institutional Context**\n\n\n10. **COVID-19 remains a significant threat to emerging economic transformation in Uganda and**\n**puts prospects of new jobs in danger.** Data from the June 2020 <sup>13</sup> [^13: Uganda Bureau of Statistics June 2020 conducted with the support of the World Bank.] Uganda Bureau of Statistics (UBOS) high\nfrequency phone survey on the impact of the COVID-19 pandemic show that the following sectors lost the highest\nnumber of workers: services 43 percent, commerce 43 percent, and transport 39 percent. It is expected that the\nhardest-hit firms will be exporters to international markets, manufacturing companies, and start-ups. The\nfloriculture industry, for example, which employs over 10,000 people, is still facing severe disruptions in its supply\nchains and cancellation of orders. Restarting or continuing economic transformation will require the provision of\nnew loans and products in the market, leaner and more efficient firms and rapid adaptation to new market\nconditions, and the capacity to identify new markets and sources of demand, particularly for new and exporting\nfirms. This is consistent with the World Bank Group’s economic response including the <mark>Green, Resilient, and</mark>\n<mark>Inclusive Development (</mark>", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000073", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data from the June 2020", "probe_tag": "confusion", "probe_score": 0.6015898585319519, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 911, "end": 934, "key": "refugee_pads:000073:16:0:0", "source": "camp2", "luna_reason": "Bare date-only qualifier cannot inherit the cited survey's source or finding.", "drop_reason": "ref_list", "specificity": "vague"}, {"text": "high\nfrequency phone survey", "probe_tag": "confusion", "probe_score": 0.7738115191459656, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1075, "end": 1102, "key": "refugee_pads:000073:16:0:1", "source": "camp2", "luna_reason": "UBOS June 2020 phone survey provides sectoral worker-loss findings.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nIntegrated Cash Transfer and Human Capital Project (P166220)\n\n\nindicating forecasts and discrepancies relative to the actual budget; and (v) a comprehensive\nlist of all fixed assets.\n\nThe IFRs should be produced by SEAS every quarter and sent to the World Bank within 45 days from the end of\neach quarter. PFS should be produced annually. The PFS should include (i) a cash flow statement; (ii) a closing\nstatement of financial position; (iii) a statement of ongoing commitments; (iv) an analysis of payments and\nwithdrawals from the project’s account; (v) a statement of cash receipts and payments by category and\ncomponent; (vi) reconciliation statement for the balance of the project’s DA; (vii) statement of cash payments\nmade using SOE basis; and (viii) the yearly inventory of fixed assets acquired under the project.\n\n_Flow of funds:_ payments will be instructed by three signatures: The Secretary General of SEAS, the Director of the\nExternal Financing Department at the Ministry of Finance and the Director of the Debt Department at the Ministry\nof Budget.\n\nFunds will be transferred from the World Bank based on withdrawal applications submitted by SEAS. The funds\nwill be channeled from the World Bank through a segregated DA in US$ opened in a commercial bank in Djibouti\nacceptable for the World Bank. Advances from the IDA account will be disbursed to the DA to be used for the\nproject expenditures.\n\n_Internal control:_ For purpose of the project, SEAS will prepare a POM which will define the roles, functions and\nresponsibilities for the implementing agency. The POM will contain a separate financial management chapter\ndetailing the financial management and accounting procedures and will include internal controls procedures. The\nmanual will be prepared no later than one month following effectiveness.\n\n_Additional Control Arrangements_\n\nThe project will be financing expenditures covering works, goods, consultants’ services, non-consultant services,\nsoft conditional", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000063", "page": 44, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "yearly inventory of fixed assets", "probe_tag": "confusion", "probe_score": 0.21519474685192108, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 781, "end": 813, "key": "refugee_pads:000063:44:0:0", "source": "camp2", "luna_reason": "Routine project fixed-assets inventory for financial reporting.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "br>delivery, including private-sector service providers [Number].|\n|Frequency|Annually.|\n|Data source|Annual reports on DPI implementation by MODEE and public- and private-sector relying parties.|\n|Methodology for Data<br>Collection|Indicator values will be collected from the administrative data of MODEE and public- and private-sector relying parties<br>on the use of transactional digital services that incorporate trusted, people-centric DPI, and cross-checked by the IVA<br>through spot surveys.|\n|Responsibility for Data<br>Collection|MODEE.|\n|||\n|**Improving trusted, people-centric data sharing**|**Improving trusted, people-centric data sharing**|\n|Description|Availability of trusted, people-centric data sharing [Yes/No].|\n|Frequency|Annually|\n|Data source|(a) Annual reports on DPI implementation from MODEE, sectoral ministries, and the private sector, (b) MODEE’s<br>software documentation and testing reports, and (c) Third-party assessment reports.|\n|Methodology for Data<br>Collection|Indicator values will be collected from (a) DPI implementation reportsreleased by MODEE, sectoral ministries, and the<br>private sector, (b) MODEE’ssoftware documentation, and testing reports, and (c) Official reports submitted by third-<br>party assessment bodies recruited to carry out the Privacy Impact Assessments. All indicator values will be cross-<br>checked by the IVA.|\n|Responsibility for Data<br>Collection|MODEE.|\n|||\n|**Enhanced management of medical records**|**Enhanced management of medical records**|\n|Description|Promoting digital transformation in health servcie delivery by scaling up", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 48, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "administrative data of MODEE", "probe_tag": "confusion", "probe_score": 0.6366053819656372, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 277, "end": 305, "key": "refugee_pads:000181:48:1:0", "source": "camp2", "luna_reason": "Data will be collected for indicator measurement.", "drop_reason": "production", "specificity": "named"}]}
 {"text": "|4,513<br>5,028|28,601<br>104,972|\n\n\n2. **The economic activity slow down caused by COVID-19 has affected Uganda’s ability to generate**\n**jobs for those living in vulnerable situations, including refugees and host communities.** Despite the\nconcerted efforts to integrate refugees within the ecosystems of their host communities, refugeehosting districts (RHDs) remain less developed areas. Low levels of disposable incomes have resulted\nin low demand and limited access to labor markets, leaving those residents with some access to land\nwith no alternative but to live off subsistence agriculture and humanitarian aid. These areas were less\ndeveloped even before the inflow of refugees and remain decoupled from resilient and viable supply\nchains in the economy. For example, the average value of assets among all households (both refugee\nand host) in the district of Arua <sup>64</sup> is 560,000 Ugandan shillings (US$ 144), which is only 10 percent of\ncomparable asset values in the Kampala region.\n\n\n62 Uganda Comprehensive Refugee Response Portal ( _[https://data2.unhcr.org/en/country/uga](https://data2.unhcr.org/en/country/uga)_ ) 31 October 2021\n63 Calculation based on district-level firm data from Census of Business Establishments (COBE), and refugee and host\ncommunity household data from the Refugee and Host Community Household Survey\n64 Arua was until recent sub-divisions of the district considered a refugee hosting district.\n\n\nPage 71 of 92", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000073", "page": 76, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Census of Business Establishments", "probe_tag": "keep", "probe_score": 0.919272780418396, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1211, "end": 1244, "key": "refugee_pads:000073:76:3:0", "source": "camp2", "luna_reason": "Named census data underpin a district-level calculation.", "usage_type": "evidential", "specificity": "named"}, {"text": "refugee and host\ncommunity household data", "probe_tag": "confusion", "probe_score": 0.8897304534912109, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1257, "end": 1298, "key": "refugee_pads:000073:76:3:1", "source": "camp2", "luna_reason": "Household data from a named survey supports a district-level economic calculation.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "\nactivities which cover the running and human resources costs for CCI. <sup>27</sup> [^27: Data collected during technical sessions held virtually between World Bank task team and UNESCO team between October and December\n2021.] As a result, the livelihoods of these cultural\nworkers have been affected and there has been a decline in cultural production. Emergency support to CCI is urgently\nrequired to sustain the livelihoods of cultural actors and help reverse their exodus to recover and retain the vibrancy\nand creative identity of the affected neighborhoods.\n\n**9.** **The humanitarian phase has subsided, but recovery has not occurred proportional to the human and financial**\n**resources that were invested.** Commendable efforts have been put in place by different institutions (e.g.,\nGovernorate/Municipality; Forward Emergency Room, FER; Directorate General of Antiquities, DGA; and Public\nCorporation for Housing, PCH) to collaborate, support, and organize and the Civil Society responded extraordinarily in\nthe emergency phase. While domestic and national organizations have provided support to the housing and cultural\nsectors in the last year, severely damaged residential buildings have largely been left out of the rehabilitation process.\nIn addition, the multifaceted political, economic, and social challenges, coupled with market failures, have resulted in\nthe inability to address most vulnerable households and cultural entities to recover without support from the\ninternational community.\n\n**10.** **The lack of coordination has led to a fragmented response, reducing the overall effectiveness of interventions.**\nInstitutions were empowered to procure help directly from international organizations, but data sharing was not\nincentivized, so there was no systematic tracking of interventions. With no central body to coordinate, the recovery\nprocess was marred with a duplication of efforts and a piecemeal response. As such, the impact of the recovery effort\ndoes not equal the amount of resources, both human and financial that have been put into the various activities.\nMoreover, there has been no ownership", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Data collected during technical sessions", "probe_tag": "confusion", "probe_score": 0.3672219514846802, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 91, "end": 131, "key": "refugee_pads:000034:14:1:0", "source": "camp2", "luna_reason": "The span describes data collection rather than showing substantive reuse of existing data.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "required for local government involvement, and arrangements for maintenance, monitoring and\nevaluation (M&E). Social capital enhancing activities would be a mandatory part of all sub-projects, and\nwould be tailored to support activities chosen by the communities.\n\nSupport to Decentralized Government Structures. Most local administrations are beginning\nto operate again with a limited number of staff and other inputs. District and chiefdom authorities are\nvery weak, however, and lack the financial and human resources needed to address their concerns and\npnorities effectively. NGOs have demonstrated their ability to implement successful community-based\nsocial and economic projects and have played a key role in shelter reconstruction activities. With the\ngradual strengthening of local government capacity, partnerships between community groups and local\nauthorities are expected to increase. Upon completion of initial training, district and chiefdom authorities\nwould be required to demonstrate that they have used the training by showing that there have been some\nimprovements in their community. For instance, at the end of each training session, district authorities\nwould be required to develop a simple action plan that specifies some activities that NSAP or other\npartners could support. District and chiefdom authorities would also gain experience in implementing,\nsupporting or overseeing community development activities.\n\nHealth. The unfavorable health indicators in Sierra Leone can be attributed to several factors.\nHigh fertility, female genital mutilation and the presence of HIV/AIDS increase morbidity and mortality\nrisks for women and children. Many risk factors that have contributed to HIV/AIDS epidemics in other\nAfrican countries have long been present in Sierra Leone, and the protracted conflict has created the\nconditions for explosive growth in HIV/AIDS infection rates. The Centers for Disease Control carried\nout a survey in 2002 which found the HIV prevalence among adults (aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000050", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "survey in 2002", "probe_tag": "confusion", "probe_score": 0.7887161374092102, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1950, "end": 1964, "key": "refugee_pads:000050:10:0:0", "source": "camp2", "luna_reason": "Past survey is attributed to CDC and reports HIV prevalence findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " of Expenditures (SOE) and the Special\nAccount (SA), would be audited quarterly internally and annually by an independent auditor, in\naccordance with internationally accepted standards. In addition, the auditor would carry out field spot\ncheck audits to ascertain compliance with contractual requirements. Compliance with conditional cash\ntransfers would be monitored by an independent external consultant (paragraph _C.3)._\n\n\n**4.** **Social**\n\nOpportunities, constraints, impacts, and risks arising. out of the socio-cultural and political context.\n\nThe impact of closure and incursions in the West Bank and Gaza has been extensively documented. On\nthe rise are poverty, unemployment, school drop out rates; on the decline or deteriorating are household\nincomes, living conditions, school attendance rates, at-large nutritional status and in particular of children\n0-5 years of age.13\n\nThe so called “newly poor”, those who are just above the poverty line before the outbreak of the second\nIntifada, in the third quarter of 2000, have been assisted by various interventions. To date, it has been\nmuch more difficult to find ways to assist the very poor, or first decile, whose coping mechanisms are\nessentially exhausted. The proposed project i s designed to support children (0-18 years old) in the first\ndecile. Although the SHC has targeted the first decile for more than 20 years, the program i s very small\ntoday in relation to need and requires new instruments to address the present situation and to shift\nMOSA’s overall strategy from one of coping to one of social springboard. Therefore, the project will\nsupport MOSA in reshaping its social assistance strategy and to improve effectiveness and efficiency of\n\n\n~\n\n**l3** PCBS quarterly household surveys, Palestinian Living Conditions quarterly surveys, IUCN, University of Geneva, Living\n\nStandards quarterly surveys, Nutrition Study, Johns Hopkins University, _2002,_ Nutrition Survey, PCBS and", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "PCBS quarterly household surveys", "probe_tag": "confusion", "probe_score": 0.7826956510543823, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1732, "end": 1764, "key": "refugee_pads:000047:20:1:0", "source": "camp2", "luna_reason": "Named household surveys cited as evidence for documented social conditions", "usage_type": "evidential", "specificity": "named"}, {"text": "Palestinian Living Conditions quarterly surveys", "probe_tag": "keep", "probe_score": 0.9613426923751831, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1766, "end": 1813, "key": "refugee_pads:000047:20:1:1", "source": "camp2", "luna_reason": "Named existing survey cited among sources documenting social conditions.", "usage_type": "declaration", "specificity": "named"}, {"text": "Living\n\nStandards quarterly surveys", "probe_tag": "confusion", "probe_score": 0.7496303915977478, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1843, "end": 1878, "key": "refugee_pads:000047:20:1:2", "source": "camp2", "luna_reason": "Existing survey source listed among evidence documenting social conditions.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": " survey within\nthe duration of the ASPIRE MPA to seek feedback on benefits and services provided by the program. A\ncitizen engagement strategy will be developed to maintain continuous engagement and communication\nwith beneficiaries and citizens overall and contribute to building trust and a social contract. In addition,\nongoing citizens’ feedback will be considered when implementing the activities of the MPA phases, and\nPENRA will publish the results of the beneficiary surveys on its website, as a key results indicator for citizen\nengagement.\n\n\nPage 38 of 74", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000133", "page": 41, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "beneficiary surveys", "probe_tag": "confusion", "probe_score": 0.5372411012649536, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 462, "end": 481, "key": "refugee_pads:000133:41:2:0", "source": "camp2", "luna_reason": "Planned beneficiary surveys are future project feedback activities.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": ", and geographical classifications. The only\nexpenditure of bodies controlled by the central government not reflected therein is that of the 10 public universities, whose\nexpenditures in 2020 were equivalent to approximately 5.4 percent of the total budget expenditures. In-year budget\nreports are published in the monthly General Government Finance Bulletin within four weeks of the end of the month.\nThey have become more informative as in-year internal reports show a breakdown by economic, administrative,\nprogrammatic, and functional classifications. However, they only cover payments and no commitments.\n\n\n**12.** **Annual financial statements cover revenues, expenditures, financial assets, liabilities, guarantees, long-term**\n**obligations, and cash balances comparable with the approved budget** . The Ministry of Finance is required by law to\n“submit to the Audit Bureau the final account of each fiscal year within not more than six months as of the date of year\nending.” The latest annual financial statements for the year ending December 31, 2022, were submitted to the Audit Bureau\nwithout delay. Consistent standards have been applied. The final accounts are published on the MOF’s website. The\ngovernment's consolidated financial statements are prepared according to International Public Sector Accounting\nStandards (IPSAS), and the Jordan Audit Bureau issues an audit opinion. There is a clear Audit Bureau opinion confirming\nthat cash based IPSAS were applied.\n\n\n**13. The MOF keeps a record of expenditure arrears reported by line ministries (including those ministries included in the**\n**Program), in conformity with the new Organic Budget law.** Despite GFMIS having a commitment control module, it is not\nutilized. The implementing agencies use Excel sheets to record commitments and follow up on payments. To enhance\ncommitment controls, an electronic system should be used by the implementing agencies to record and report on\ncommitments and be financially linked to the GFMIS. Until the latter is achieved, annual reports concerning commitments\nand arrears", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 74, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "record of expenditure arrears", "probe_tag": "confusion", "probe_score": 0.3434138298034668, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1504, "end": 1533, "key": "refugee_pads:000181:74:1:0", "source": "camp2", "luna_reason": "Routine financial recordkeeping, with no substantive data use shown.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\nto learning, (b) instruct in a way that deepens student understanding and encourages critical thinking, (c)\nfoster socioemotional skills that encourage students to succeed both inside and outside the classroom,\nand (d) use inclusive teaching practices that help all students to learn. A communication campaign will be\nconducted by ANACEC to inform and consult with teachers and managers about the rollout of the\nassessment of the quality of teaching in classrooms.\n\n29. This subcomponent (part B: US$2.7 million ELP) will also finance the development and\nimplementation of in-service teacher training in the pedagogical capacity for ECE teachers and educators\nin line with the Early Learning and Development Standards for Children (0–7), with the focus on new\nteachers, educators, and teaching assistants to expand ECEC provision. The training will focus on the ECE\ncurriculum and support play-based teaching and learning. This subcomponent will support an in-depth\nperiodic quality assessment in a nationally representative sample of ECEC service providers to better\nunderstand the quality of ECEC service delivery in the country. <sup>28</sup> [^28: The quality assessment survey will build on tools such as TEACH ECE that focuses on measuring teaching quality in the classroom\nand the Measuring Early Learning and Quality Outcomes that focuses on children’s learning and development outcomes and the\nquality of early learning environments.] The standard package of support for ECEC\nwill include the provision of indoor and outdoor teaching and learning and play materials. <sup>29</sup> [^29: Including in Ukrainian language such as Romanian-Ukrainian learning materials developed by UNICEF.] The quality\nassessment survey will also collect information about the quality of ECEC facilities against climate change\nand related disaster risks, particularly extreme heat, droughts, and floods. The data collected through the\nproject will provide the MoER with valuable information that can be used to plan and enhance the climate\nresilience of the ECEC infrastructure through rehabilitation and expansion efforts", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "quality assessment survey", "probe_tag": "confusion", "probe_score": 0.5301714539527893, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1225, "end": 1250, "key": "refugee_pads:000185:21:0:0", "source": "camp2", "luna_reason": "Survey is planned and will collect project data.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "quality\nassessment survey", "probe_tag": "confusion", "probe_score": 0.5509300827980042, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1769, "end": 1794, "key": "refugee_pads:000185:21:0:1", "source": "camp2", "luna_reason": "Survey will collect new information through the project.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "data collected through the\nproject", "probe_tag": "confusion", "probe_score": 0.24485400319099426, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1966, "end": 2000, "key": "refugee_pads:000185:21:0:2", "source": "camp2", "luna_reason": "Project will collect the data for future planning.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "and financial audits. A PIU will be set up prior to effectiveness to carry out implementation,\nproject management and administration, supervision of activities, and coordination with\ninternational and national partners and stakeholders, including line ministries and local\nauthorities, as well as M&E, and communication. The PIU will be supported with technical\nassistance from the World Bank.\n\n32. _Project Management_ will include activities that will cover operating costs related to the\nfiduciary management of the project to ensure the coordination, implementation, and\nmanagement of the International Development Association (IDA) financing. From those working\nin the PIU, only the staffing and project-related operational costs for the financial management\nofficer, internal auditor, procurement specialist, procurement assistant and accountant will be\nsupported through the IDA grant.\n\n33. _Sensitization and Communication_ activities will build on preceding communications\nactivities that the Government and MINUSMA will have been implementing, and will continue\nthroughout the project life cycle. Communication activities will not be limited to disseminating\ninformation but will provide a voice to the project beneficiaries and thus enable bottom-up\ncommunication approaches through community meetings and beneficiary outreach.\n\n34. _Results Monitoring and Evaluation_ . Overall responsibility for M&E will rest with the PIU,\ncomplemented by close World Bank supervision. A results framework and monitoring matrix to\ntrack inputs, outputs, and outcomes has been developed for the project with intermediate and key\nperformance indicators (Annex 1). The PIU will be supported by the coordination mechanisms as\noutlined in the Peace Agreement with regards to monitoring, implementation and performance of\nthe overall DDR program. Beneficiaries and project implementation progress and effectiveness\nwill be monitored through a well-functioning Reinsertion MIS. This system will support the\nM&E activities through several databases to: (i) monitor an ex-combatant from cantonment to\nreinsertion, (ii) follow the implementing partners providing reinsertion support, and (iii) monitor\nfinancial management. Monitoring of", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000148", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Reinsertion MIS", "probe_tag": "confusion", "probe_score": 0.2108319103717804, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1951, "end": 1966, "key": "refugee_pads:000148:19:0:0", "source": "camp2", "luna_reason": "Planned project monitoring system, with no cited data used for analysis.", "drop_reason": "promissory", "specificity": "named"}]}
-{"text": "**The World Bank**\nCameroon COVID-19 Preparedness and Response Project (P174108)\n\n\n90. **A grievance redress mechanism (GRM)** will be designed to allow affected stakeholders to raise\ngrievances and seek redress when they perceive that a negative impact has arisen from the project\ninterventions. The GRM will be designed in consultation with relevant government and non-government\nstakeholders and will build on the SEP. It will establish accessible processes to submit complaints as well as\nclear procedures from investigation to resolution and feedback. The GRM will include the provision for\nappeal if aggrieved parties are dissatisfied with the outcome. A communication campaign will be\nimplemented aiming at raising awareness and informing stakeholders on how to use the GRM and\nstipulating the investigation and resolution sequential process, timeline and procedures.\n\n91. **Large volumes of personal data, personally identifiable information and sensitive data are likely to**\n**be collected and used in connection with the management of the COVID-19 outbreak under circumstances**\n**where measures to ensure the legitimate, appropriate and proportionate use and processing of that data**\n**may not feature in national law or data governance regulations, or be routinely collected and managed**\n**in health information systems** . In order to guard against abuse of that data, the Project will incorporate\nbest international practices for dealing with such data in such circumstances. Such measures may include,\nby way of example, data minimization (collecting only data that is necessary for the purpose); data accuracy\n(correct or erase data that are not necessary or are inaccurate), use limitations (data are only used for\nlegitimate and related purposes), data retention (retain data only for as long as they are necessary),\ninforming data subjects of use and processing of data, and allowing data subjects the opportunity to correct\ninformation about them, etc. In practical terms, operations will ensure that these principles apply through\nassessments of existing", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000169", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "personal data", "probe_tag": "drop", "probe_score": 0.04315655678510666, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 899, "end": 912, "key": "refugee_pads:000169:36:0:0", "source": "camp2", "luna_reason": "Data are described as likely to be collected and used by the project.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000165", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.027876049280166626, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 240, "key": "refugee_pads:000165:31:0:0", "source": "camp2", "luna_reason": "Names monitoring data without showing its figures informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.11965898424386978, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 412, "end": 437, "key": "refugee_pads:000165:31:0:1", "source": "camp2", "luna_reason": "Named administrative data source listed for verifying program indicators.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MOE reports", "probe_tag": "drop", "probe_score": 0.034246839582920074, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 385, "end": 396, "key": "refugee_pads:000147:30:0:0", "source": "camp2", "luna_reason": "Logframe verification report mechanism, not an existing report used as evidence.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "iii. **Data Validation and Verification:** Data validation and verification will be\ndone internally by MoPH. Internal verification will be aligned with the system\nused by the MoPH and will take place at two levels: (i) at the district level\n(Caza), the Caza Coordinator verifies a sample of 5 percent of all claims made\nthrough a combination of telephone and/or home visits (the sample is generated\nmonthly by the HIS and sent through the Coordinator tasked with this activity;\nand (ii) at the central level, a random sample of 2 percent of claims validated at\nthe district level is then re-validated by the central team at MoPH. Also at the\ncentral level, the MoPH will conduct trend and pattern analysis of the claims\nbeing processed to identify outlying data as an established anti-fraud tool.\n\n**b)** **Developing reporting mechanisms which will include:** (i) monthly reports from\n\nimplementing partners to PMU; (ii) quarterly reports from PMU to the Bank; and (iii) an\nAnnual Project Implementation Report, consolidating progress in the project\nimplementation by each of the institutions involved, based on administrative data, survey\ndata, beneficiary assessments and independent evaluations.\n\n\n_Evaluation_\n\n50. Evaluation will comprise mainly of an independent project evaluation, beneficiary\nassessment and evaluation by the Bank. The aim is to determine the relevance and fulfillment of\nobjectives, development effectiveness and sustainability. **_Independent Evaluation_** **:** The\nindependent project evaluation will be contracted by the MoPH, using the Word Bank\nprocurement processes and with Terms of Reference (TORs) acceptable to the Bank. The\npurpose of the independent evaluation will be to: (i) verify project’s progress towards\nachievement of the development objective; (ii) ensure the correct use of funds on a six monthly\nbasis; (iii) verify the services received by project beneficiaries through independently checking a\nsample", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 54, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "survey\ndata", "probe_tag": "drop", "probe_score": 0.041761837899684906, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1134, "end": 1145, "key": "refugee_pads:000020:54:0:1", "source": "camp2", "luna_reason": "Survey data is an existing basis for consolidating project implementation progress.", "usage_type": "declaration", "specificity": "vague"}]}
-{"text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 62, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "1999 data", "probe_tag": "drop", "probe_score": 0.02271115779876709, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 688, "end": 697, "key": "refugee_pads:000147:62:2:0", "source": "camp2", "luna_reason": "Generic data qualifier provides no attributed finding or analytical use.", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9823695421218872, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 758, "end": 796, "key": "refugee_pads:000147:62:2:1", "source": "camp2", "luna_reason": "Named database cited as the source for the presented economic data table.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000104", "page": 29, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "M&E data", "probe_tag": "drop", "probe_score": 0.02301034703850746, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 530, "end": 538, "key": "refugee_pads:000104:29:2:0", "source": "camp2", "luna_reason": "Fragment embedded in a project output-indicator table.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": " the IFRs on a yearly basis. The annual reports will be submitted to\nthe World Bank within six months from the closure of each fiscal year and the limited review opinion will be\nsubmitted to the World Bank along with the yearly audit report.\n\nSEAS will ensure that the recruitment of the external auditor will be done six months after project effectiveness\nin order for the auditor to start the field work early enough to deliver the audit report and management letter\nwithin the deadlines.\n\n_Technical audit of the project:_ technical audits will be carried out at mid-term and at the end of the project for the\nactivities related to the cash transfers and the sub-projects. SEAS will enter into a contract with a technical auditor\nwith ToR acceptable to the World Bank. The technical auditor will verify that all activities related to the cash\ntransfers and sub-projects are carried out as per the terms and conditions set in the POM.\n\n_Flow of information_ : SEAS will be responsible for preparing periodic reports on project implementation progress\nand on both physical and financial achievements. These reports will be based on project activity progress (by\ncomponent and expenditure category), including technical and physical information reported on a quarterly\nbasis. SEAS will maintain the project bookkeeping and will produce annual PFSs and quarterly IFRs.\n\n\nPage 41 of 44", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 45, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "project activity progress", "probe_tag": "drop", "probe_score": 0.03156767785549164, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1133, "end": 1158, "key": "refugee_pads:000154:45:1:0", "source": "camp2", "luna_reason": "Future project reporting based on planned monitoring progress", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": "PF); (vii) monitoring and evaluation arrangements; (viii) communications\narrangements; and (ix) the composition and terms of reference (ToR) of the project steering committee, a role which is\nexpected to be assumed by the existing PNSF Steering Committee. This committee is chaired by the Secretary of State\nfor Social Affairs and composed of representatives from various relevant stakeholders. The project steering committee\nis expected to approve the project’s annual work plans and budgets and ensure coordination with technical ministries\nand other donors.\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n58. The results monitoring framework assesses progress towards the PDO through key indicators, focusing on\nproviding targeted cash transfers to poor households and supporting access to community-level interventions that\nimprove human capital. In addition, intermediate indicators will be used to monitor the progress of each component over\nthe life of the project. The SEAS will collect data for the activities they will implement. SEAS will be responsible for\naggregating results data and preparing periodic reports on results as specified in the Financing Agreement (FA).\nMonitoring will occur at each stage of project implementation to identify arising problems and issues and to promptly\nconsider and adopt corrective measures.\n\n59. The project will conduct a mid-term review and several evaluations to gauge progress towards the PDO, to assess\nthe impact of the project on the beneficiaries, the quality of the works carried out, as well as overall project efficiency.\nFor component 1, these evaluations will include a process evaluation and a targeting assessment to evaluate the accuracy\nof safety net targeting procedures. For component 3, evaluations will include technical audits of infrastructures built (at\nmid-term and end of project) and audits of adherence to environmental and social safeguards (at mid-term and end of\nproject). Beneficiary satisfaction surveys will also be conducted.\n\n\nPage 20 of 44", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000063", "page": 24, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "results data", "probe_tag": "drop", "probe_score": 0.04223040118813515, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1091, "end": 1103, "key": "refugee_pads:000063:24:1:0", "source": "camp2", "luna_reason": "Planned project monitoring data aggregation and periodic reporting, not existing external data use.", "drop_reason": "promissory", "specificity": "vague"}, {"text": "Beneficiary satisfaction surveys", "probe_tag": "confusion", "probe_score": 0.15671026706695557, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1963, "end": 1995, "key": "refugee_pads:000063:24:1:1", "source": "camp2", "luna_reason": "Surveys are planned to be conducted by the project.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nAdvancing Sustainability in Performance, Infrastructure, and Reliability of the Energy Sector in the West Bank\nand Gaza (P170928)\n\n\ncapacity needs, the first phase will facilitate the creation of a community of practitioners (CoP) among the\nsector institutions (PENRA, PETL, DISCO, and PERC) to enable (a) alignment of PETL’s transmission master\nplan, DISCO’s distribution master plans, and demand projections from LGUs; (b) development and\nharmonization of the transmission code, distribution grid code including for utility-scale solar, and\ninterconnection standards for imports; (c) strategic prioritization of T&D investment needs for financing\nthrough tariffs, PA budget, and donor support; and (d) a cohesive approach to technical coordination with\nIEC. This community will create long-term capacity and coordination within the sector institutions that\nwill also inform future phases.\n\n\n30. **Service delivery, under Pillar 2, is the keystone of the electricity sector as it focuses on customer**\n**management and responsiveness.** Under ESPIP, DISCOs have started implementing a harmonized\nrevenue protection program (RPP) that targets the largest customers. ASPIRE Phase 1 will begin the\nprocess of enhancing metering, billing, and collection for a broader group of customers, which includes\nthe next tier of largest customers and potentially public sector consumers. This will involve installation of\nsmart meters. More importantly, Phase 1 will seek to identify citizen engagement, communication, and\nother approaches to improve the ability of DISCOs to install the meters, to ensure timely payments, to\nreduce nonpayment, and to improve monitoring of financial flows for each DISCO and the entire sector.\n\n\n31. **Private sector engagement, under Pillar 3, is a longer-term goal that requires longer-term**\n**planning, sustained effort, and innovative solutions.** Building on lessons learned from ESPIP and demand\nestimation", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000132", "page": 23, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "demand projections from LGUs", "probe_tag": "drop", "probe_score": 0.0207193773239851, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 410, "end": 438, "key": "refugee_pads:000132:23:0:0", "source": "camp2", "luna_reason": "Existing local-government demand projections inform sector planning alignment.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "هدفة التراكمية**|**القيم المستهدفة التراكمية**|**القيم المستهدفة التراكمية**|**المعيار**<br>**2013**<br>|** وحدة**<br>**القياس**|**الجوهر**|اسم المؤشر|\n|** الجهة المسؤولة**<br>**عن جمع البيانات**|** مصدر**<br>**البيانات/من**<br>** هجةجمع**<br>**البيانات**|**التكرارية**|**17**<br>**-**<br>**2016**<br> <br>** (السنة**<br>**)الثالثة**|**16**<br>**-**<br>**2015**<br> <br>** (السنة**<br>**)الثانية**|**15**<br>**-**<br>**2014**<br> <br> <br>** (السنة**<br>**)الولى**|**15**<br>**-**<br>**2014**<br> <br> <br>** (السنة**<br>**)", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000066", "page": 42, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "البيانات", "probe_tag": "drop", "probe_score": 0.003757212543860078, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 185, "end": 193, "key": "refugee_pads:000066:42:2:0", "source": "camp2", "luna_reason": "Standalone table header identifying data collection responsibility, not data use.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Col1|Project Operations Manual,<br>and have received cash<br>transfers, at least for one<br>payment cycle.|minimum<br>on a<br>quarterly<br>basis|Information<br>System (MIS)|course of project<br>implementation.<br>Payment data will be<br>liked to and updated in<br>the MIS.|Col6|\n|---|---|---|---|---|---|\n|Number of beneficiaries receiving cash for<br>performing labor intensive public works<br>who are female|<br>Number of total<br>beneficiaries that directly<br>receive cash transfer for<br>working on LIPW under sub-<br>component 1.1 on behalf of<br>beneficiary HH, of which are<br>female|This<br>indicator<br>will be<br>measured<br>at a<br>minimum<br>on a<br>quarterly<br>basis<br>|Registration<br>and payment<br>data in the<br>SNSOP MIS<br>|Beneficiary data is<br>collected during<br>registration and<br>updated over the<br>course of the project.<br>Payment data will also<br>be periodically updated<br>in the MIS<br>|Selected Implementing<br>Partner<br>|\n|Number of beneficiary households<br>receiving cash transfer for participating in<br>the behavioral change communication<br>training|The number of beneficiary<br>households that participate<br>in behavioral change", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000153", "page": 60, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Payment data", "probe_tag": "drop", "probe_score": 0.023877780884504318, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 314, "end": 326, "key": "refugee_pads:000153:60:0:0", "source": "camp2", "luna_reason": "Future project payment-data updating is planned monitoring activity.", "drop_reason": "promissory", "specificity": "vague"}, {"text": "SNSOP MIS", "probe_tag": "confusion", "probe_score": 0.14305520057678223, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 833, "end": 842, "key": "refugee_pads:000153:60:0:1", "source": "camp2", "luna_reason": "Named MIS provides registration and payment data for the indicator.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "br> <br>|People provided with access to safely<br>managed water supply services -<br>Female<br> <br> <br> <br> <br>|\n|Time spent by women and girls on water<br>fetching daily decreased|Time spent on fetching is<br>estimated as time (in<br>minutes) spent on walking<br>to the water source,<br>queuing to collect water,<br>collecting water and walking<br>back to the household<br>premises. When water is not<br>piped to the home the<br>burden of fetching it falls<br>disproportionately on<br>women and children,<br>especially girls. Therefore,<br>when water is obtained by<br>water-fetching, 'the<br>availability of an acceptable<br>quantity and quality of<br>water for health,|<br> <br>Twice at the<br>project's<br>start to<br>determine<br>and confirm<br>baseline<br>value of the<br>indicator (in<br>minutes) and<br>then at the<br>operational/<br>project<br>completion<br>stage, to<br>track<br>decrease in<br>the time<br>required|Baseline and<br>endline<br>surveys.<br>|Indicator value at the<br>baseline will be<br>measured for all the<br>project zones (for the<br>sample of households<br>in each village<br>representative of the<br>population of target<br>zones) through a<br>baseline survey. The<br>value will be reported", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000162", "page": 53, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "baseline survey", "probe_tag": "drop", "probe_score": 0.013732190243899822, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1177, "end": 1192, "key": "refugee_pads:000162:53:1:0", "source": "camp2", "luna_reason": "Future baseline survey will measure project indicators; data collection has not yet occurred.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "**\n\n**o grupos de personas que se han**\n**visto forzados a huir de sus casas**\n\n**o lugares de residencia habitual,**\n**especialmente como resultado de**\n\n**o con el fin de evitar un conflicto**\n**armado, situaciones de violencia**\n**generalizada, violaciones de derechos**\n**humanos o desastres naturales o**\n**provocados por la mano del hombre,**\n**y que no han traspasado frontera**\n\n\n\n**de las estadísticas de ACNUR,**\n**esta categoría de población sólo**\n**incluye a los desplazados internos**\n**por conflictos a los que la Agencia**\n**extiende su protección y/o asistencia.**\n**La población desplazada también**\n**incluye a personas en situación**\n\n\n**Refugiados retornados son ex**\n**refugiados que han regresado a su**\n**país de origen espontáneamente**\n\n**o de manera organizada pero que**\n**no se han integrado plenamente**\n**todavía. Este retorno sólo tendría**\n**lugar normalmente en condiciones**\n**de seguridad y dignidad. A efectos**\n**de este informe, se incluyen**\n**exclusivamente los refugiados que**\n**retornaron entre enero y diciembre**\n**de 2012. Sin embargo, en la práctica,", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001451", "page": 36, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "estadísticas de ACNUR", "probe_tag": "keep", "probe_score": 0.9225529432296753, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 398, "end": 419, "key": "reliefweb:001451:36:1:0", "source": "camp2", "luna_reason": "UNHCR statistics support the stated population-category definition.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "A November Winterisation study among vulnerable Syrian refugees found that education levels slightly\ncontributed to the ability to generate income:\n\n- 17% of those with no education were able to generate an income\n\n- 28% of those with primary education levels\n\n- 24% of those with for secondary education or higher\n\n- However, those with higher levels of education were more likely to have permanent employment\n\n- 20% of those with secondary education had permanent employment\n\n- 10% of those with primary education\n\n- 13% with no education\n\n_South_\n\nA Swiss Solidar assessment in Nabatieh and Jezzine Districts in Southern Lebanon in August among around\n700 individuals showed that those employed in Lebanon were doing similar work to that in Syria, although\nthere was a shift away from skilled work such as metalwork and carpentry towards more menial casual labour.\n\n_North and Bekaa_\n\nThe EMMA assessment in April 2013 on construction showed that the construction market can better support\nthe income needs of skilled workers compared to unskilled workers: from 30 to 60% of the overall income\nneeds for unskilled construction workers and60-100% of the needs for skilled workers.\n\n\n_Beirut_\n\nA small-scale assessment by Amel in February 2014 in Beirut and Tyre found that women face challenges in\nsecuring higher incomes, related to a lack of capital, lack of equipment, and difficulty in obtaining a loan. Very\nfew of them would launch a business independently and prefer to work collectively, in order to diminish risks\nand be able to rely on the others.\n\n<u>Palestinian refugees</u>\n\n\nA 2011 labour force survey among Palestinian refugees living in camps and gatherings showed that the\nPalestinian workforce is poorly educated, young and lacking in skills. Most are engaged in low-status jobs\nconcentrated in commerce and construction.\n\n\n25", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000441", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Swiss Solidar assessment", "probe_tag": "keep", "probe_score": 0.9194372296333313, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 553, "end": 577, "key": "reliefweb:000441:24:0:0", "source": "camp2", "luna_reason": "Assessment reports employment and occupational shifts among surveyed individuals.", "usage_type": "evidential", "specificity": "named"}, {"text": "2011 labour force survey", "probe_tag": "keep", "probe_score": 0.9254007339477539, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1593, "end": 1617, "key": "reliefweb:000441:24:0:2", "source": "camp2", "luna_reason": "Existing survey provides findings about Palestinian refugees’ workforce characteristics.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "........................................................................................ 21\n\n\n5. CONCLUSION ...................................................................................................................... 23\n\n\n**Figures & Tables**\n\n\nFigure 1. Displacement as of 8 July 2015……………………………………………………………………………………………..5\n\n\nFigure 2. Displacement as of 30 September 2015………………………………………………………………………………..5\n\n\nFigure 3. Family tracing and reunification data, per quarter, 2015……………………………………………………….6\n\n\nFigure 4. Types of GBV reported in the South Sudan GBV IMS, per quarter, 2015…………………………………8\n\n\nFigure 5. Incidents of grave violations reported to", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000601", "page": 1, "chunk": 6, "split": "holdout_annotate", "spans": [{"text": "GBV IMS", "probe_tag": "keep", "probe_score": 0.9576, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 561, "end": 568, "key": "sample:reliefweb:000601:1:6:1", "source": "gold", "luna_reason": "GBV IMS data are presented in a figure showing reported GBV types.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "psychological or emotional abuse were the most commonly reported types of GBV incidents, accounting\nfor **36 percent** and **34 percent** of incidents, respectively.\n\nSexual abuse remains a risk with devastating consequences on women and girls. However, it remains\nunderreported because of the stigma associated with it. Rape and sexual assault constitute a 17 percent\nof all reported incidents according to GBVIMS report for Q2 2022.\n\nHome remains not a safe space for survivors of GBV. According to the GBVIMS report covering the\nsecond quarter of 2022, 27 percent of the GBV incidents reported took place in the perpetrators home,\nwhile 56 percent of incidents took place in the client’s home. These high percentages are linked to the\nhigh percentage of intimate partner violence incidents reported in the same quarter, with 57 percent of\nthe cases and marking a 2 percent increase compared to the first quarter of 2022.\n\n\n**_Intimate Partner Violence_**\n\n\nIntimate partner violence reporting continued to increase in 2022, with 2 percent increase compared to\nthe first quarter of 2022, accounting for **57 percent** in the second quarter of 2022, according to the\nGBVIMS. Data extracted from the GBVIMS indicate that both adults and children are subjected to intimate\npartner violence, with **7 percent** of female children reporting being subjected to intimate partner violence\nas well in the context of early marriage. According to KAFA internal reports <sup>5</sup> [^5: 2022. KAFA Internal reports on urgent cases of GBV in need for legal assistance. Accessed at: https://kafa.org.lb/en.] on urgent cases of women\nand girls’ reporting different incidents of gender-based violence in Bekaa, Beirut and Mount Lebanon and\nthe South, the majority of cases requesting legal assistance are cases of intimate partner violence. Women\nand girls are requesting legal protection, prosecution of the perpetrator/ intimate partner, safe shelter\nand childcare and the procedures weren’t put in action due to the", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001273", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "GBVIMS report", "probe_tag": "keep", "probe_score": 0.9708601236343384, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 408, "end": 421, "key": "reliefweb:001273:2:0:0", "source": "camp2", "luna_reason": "GBVIMS report supports the cited 17 percent incident finding.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " employment. Proof of legal identity\nis also the basis for exercising rights, such as property ownership, and nationality. For governments and businesses, ID\nsystems can serve as a platform for more effective and efficient service delivery by enabling the unique identification and\nverification of persons. Importantly, ID systems can promote greater inclusion by de-risking and reducing the costs of\n\n\n8 UNHCR's Ethiopia Update on the Total Number of Refugees and Asylum Seekers as of August 31, 2023.\n9 In Tigray, new internal displacement data has been reported, including 1,021,798 IDPs (250,468 households) in 643 sites across six zones (excluding\n20 _woredas_ /districts hard to reach due to security or environmental factors).\n10 IOM. 2023. Ethiopia National Displacement Report 16 - Site Assessment Round 33 and Village Assessment Survey Round 16: Nov 2022 - Jun 2023.\nhttps://reliefweb.int/report/ethiopia/ethiopia-national-displacement-report-16-site-assessment-round-33-and-village-assessment-survey-round16-november-2022-june-2023.\n11 Foundational ID systems are primarily created to provide credentials to the general population as proof of identity for a wide variety of public and\nprivate sector transactions. Common types of foundational ID systems include civil registries, national ID systems, and population registers.\n\n\nPage 2 of 39", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000005", "page": 12, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "internal displacement data", "probe_tag": "confusion", "probe_score": 0.2249027043581009, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 520, "end": 546, "key": "refugee_pads:000005:12:2:0", "source": "camp2", "luna_reason": "Reported displacement data supports concrete IDP and household counts.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nSudan Basic Education Emergency Support Project (P172812)\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Student enrollment in targeted schools|The enrollment will be<br>monitored through the<br>annual school census|Annual<br>|Annual<br>School<br>Census<br>|Census of schools key<br>data collected yearly<br>|Ministry of Education<br>and PCU<br>|\n|Girls enrolment in targeted schools<br>|Number of girls enrolled in<br>targeted schools|Annual<br>|Annual<br>School<br>Census<br>|Census of school key<br>data collected annually<br>|Ministry of Education<br>and PCU<br>|\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000024", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Census of school key", "probe_tag": "confusion", "probe_score": 0.13345079123973846, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 730, "end": 750, "key": "refugee_pads:000024:33:0:2", "source": "camp2", "luna_reason": "Fragment inside a monitoring table methodology field; not an independent data mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " (DLI 3).|\n|Data source/ Agency|Annual reports on the usage of digital services from MODEE, sectoral ministries, and the private sector.|\n|Verification Entity|KACE.|\n|Procedure|Indicator values will be collected from MODEE’s administrative data on the usage of transactional digital<br>services that use trusted, people-centric DPI and cross-checked by the IVA through spot surveys.|\n\n\n\n\n\n\n\n|DLI 2: Number of individuals adopting people-centric digital identity|Col2|\n|---|---|\n|Formula|The DLI will disburse US$3 for each unique individual activating people-centric digital identity, up to a total<br>3.5 million individuals, in the limit of US$10.5 million. Moreover, it will disburse the following additional<br>amounts:<br>• <br>US$4 for each woman activating people-centric digital identity, up to 1.75 million women, in the<br>limit of US$7 million<br>• <br>US$5 for each elder activating people-centric digital identity, up to 200,000 elders, in the limit of<br>US$1 million<br>• <br>US$15 for each refugee activating people-centric digital identity, up to 100,000 refugees, in the<br>limit of US$1.5 million|\n|Description|The Program disburses against the number of unique individuals activating people-centric digital identity,<br>disaggregated by type of user (women, elders, refugees).|\n|Data source/ Agency|Annual reports on digital ID implementation by MODEE.|\n|Verification Entity|KACE.|\n\n\nPage | XLI", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 50, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "MODEE’s administrative data", "probe_tag": "confusion", "probe_score": 0.6242539286613464, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 217, "end": 244, "key": "refugee_pads:000181:50:2:0", "source": "camp2", "luna_reason": "Future collection of indicator values is planned from administrative data.", "drop_reason": "promissory", "specificity": "named"}, {"text": "Annual reports on digital ID implementation by MODEE", "probe_tag": "confusion", "probe_score": 0.8198044300079346, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1319, "end": 1371, "key": "refugee_pads:000181:50:2:1", "source": "camp2", "luna_reason": "Named annual reports cited as the data source for DLI verification.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "based\ndata sharing from authoritative sources (data sharing). The sharing of personal data should be, where relevant and possible,\nunder the control or consent of the data subject or person to whom that data relates. A person’s data is not necessarily all\nin one place or in one database, and in most cases, it is maintained by an authoritative source, such as a government\nministry or a public entity. An example is a record of achievement in education (proof that the person has a qualification,\nsuch as a degree), a medical record (details of the person’s current medication and conditions), or an entitlement\ndocument, such as a national identity card (identifying the person’s legal name). Holding and managing all this data in a\nsingle database is impractical and creates security vulnerabilities. Sharing this data securely and reliably under the consent\nof the individual offers many advantages over silos of data and functionality. People should have the ability to manage their\nconsent with a particular service or dataset, including the ability to review and revoke consent as necessary. Taking a\n\n\n27 Digital Public Infrastructure (DPI) refers to digital ID, payment, and data exchange capabilities that are fundamental to enabling\nservice delivery at scale and supporting innovation in the digital economy. DPI provides reusable and foundational digital platforms\nthat allow public and private sector service providers to build and innovate their products and services.\n\n\nPage | 52", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 61, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "record of achievement in education", "probe_tag": "confusion", "probe_score": 0.4909738302230835, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 419, "end": 453, "key": "refugee_pads:000181:61:2:0", "source": "camp2", "luna_reason": "Merely names an example document; no existing data use, finding, or analysis is shown.", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nCash for Jobs Project (P175327)\n\n\n\n\n\n\n\n\n\n|in the National Social Registry - households that are Social from refugee social registry<br>refugees, disaggregated by gender registered in the national Registry households will be<br>social registry collected and inserted<br>in the social registry|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Households in targeted areas included<br>in the National Social Registry - host<br>communities, disaggregated by<br>gender<br>Households registered in<br>the Social Registry that live<br>collines hosting refugees<br>Annual<br> <br>National<br>Social<br>Registry<br> <br>The Social Registry will<br>inform on the number<br>of households that<br>were registered in<br>collines hosting<br>refugees<br> <br>Agency handling the<br>social registry<br>|Households in targeted areas included<br>in the National Social Registry - host<br>communities, disaggregated by<br>gender<br>Households registered in<br>the Social Registry that live<br>collines hosting refugees<br>Annual<br> <br>National<br>Social<br>Registry<br> <br>The Social Registry will<br>inform on the number<br>of households that<br>were registered in<br>collines hosting<br>refugees<br> <br>Agency handling the<br>social registry<br>|Households in targeted areas included<br>in the National Social Registry - host<br>communities, disaggregated by<br>gender", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 66, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "social registry", "probe_tag": "drop", "probe_score": 0.012344248592853546, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 295, "end": 310, "key": "refugee_pads:000130:66:0:1", "source": "camp2", "luna_reason": "Standalone table content naming a registry; no eligible existing-data use shown.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " as a<br>result of the project<br>interventions|Baseline,<br>MTR and End<br>of project<br>|Independent<br>consulting<br>firms and the<br>project M&E<br>system<br>|baseline, MTR and end<br>of project surveys and<br>project M&E system<br>|independent firms and<br>PCUs<br>|\n|Land area under sustainable landscape<br>management practices|The indicator measures, in<br>hectares, the land area for<br>which new and/or improved<br>sustainable landscape<br>management practices have<br>been introduced. Land is the<br>terrestrial biologically<br>productive system|<br>Quarterly<br>|Quarterly<br>progress<br>reports,<br>|Routine data<br>collection/GEMS<br>|PCUs<br>|\n\n\n\nPage 57 of 80", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000113", "page": 62, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "project surveys", "probe_tag": "drop", "probe_score": 0.005508652422577143, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 191, "end": 206, "key": "refugee_pads:000113:62:1:0", "source": "camp2", "luna_reason": "Project surveys are project-generated data collection, not existing data use.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "Routine data", "probe_tag": "drop", "probe_score": 0.010983358137309551, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 613, "end": 625, "key": "refugee_pads:000113:62:1:1", "source": "camp2", "luna_reason": "Standalone table-cell phrase naming routine data collection", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "**The World Bank**\nDjibouti Integrated Slum Upgrading Project (P162901)\n\n\neffectiveness, and will be composed of a seasoned civil engineer, an environmental and social specialist, a\nmonitoring and evaluation specialist, a procurement specialist, and a financial management specialist. The\nPCU will be reinforced as needed by a communications officer, an urban planner, and international experts.\nProject coordination will remain with the ARULOS Director. In line with the Government decision to reinforce\npublic institutions, PCU members will be selected among existing ARULOS staff or through external hiring\nbased on terms of reference acceptable to the IDA and described in the Project Implementation Manual\n(PIM).\n\n\n7. **Other institutions involved in project implementation.** For certain activities, the ARULOS will rely on\nother institutions (DATUH, Land Directorate, and the municipal institutions) within their range of\ncompetencies; though fiduciary responsibility will be retained by ARULOS. For those partnerships, each\ninstitution will designate a focal point. The PIM defines in detail the responsibilities and obligations of each\nparty.\n\n\n8. DATUH will coordinate the preparation of the urban plans. For these activities, it will elaborate the\nterms of reference for envisaged studies and will monitor the work of consulting firms to ensure timely and\nhigh-quality deliverables.\n\n\n9. The Land Directorate will be charged with steering studies on land registration and, in collaboration\nwith the prefectures, will ensure the creation of a land information system and inventory of land properties,\nstarting first in Balbala Ancien. The Land Directorate will benefit from technical support, the purchase of\nneeded equipment, and capacity building in order to undertake its tasks.\n\n\n10. The Municipality of Djibouti and the Commune of Balbala will play a critical role in achieving the social\ncohesion around the infrastructure investments within the neighborhood. They will support community\nmobilization and preservation of public spaces identified to receive infrastructure and services as part of\nupgrading plans. They will notably ensure that new", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000015", "page": 54, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "land information system", "probe_tag": "drop", "probe_score": 0.04451633244752884, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1553, "end": 1576, "key": "refugee_pads:000015:54:0:0", "source": "camp2", "luna_reason": "The system will be created by the project, so its data does not yet exist.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": " analytics (ASA) (P176730), a payment\nsystems assessment is being carried out. The assessment will evaluate the performance of the payment system used under Merankabandi and will\nassess its scalability. In addition, the assessment will identify other existing e-payment options in the country that could complement the phonebased system in the case this is not scalable at national level.\n29 The _colline_ (“hill”) is the lowest administrative unit in Burundi\n30 This amount might be revised during the project implementation based on the Consumer Price Index.\n31 A mapping exercise of NGOs implementing human capital development and productive inclusion activities was carried out during project\npreparation. The assessment showed that there is an important number of international and national NGOs operating in all provinces of the\ncountry.\n\n\nPage 21 of 86", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 25, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Consumer Price Index", "probe_tag": "drop", "probe_score": 0.0021, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 539, "end": 559, "key": "sample:refugee_pads:000130:25:2:0", "source": "gold", "luna_reason": "Existing price index used to revise the project amount.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "also be provided to properly levy, collect and account for local duties and taxes. NaCSA staff would be\ngiven an opportunity to visit Community Driven Development Projects in comparable countries to\ncapitalize on their experiences. Regional and district line ministry staff would be trained in community\nmobilization, conflict resolution, social capital building, and technical appraisal skills.\n\n\n(b) Substantial IEEC activities linked to the various sub-projects are envisaged. These activities\nwould be undertaken using existing IEC materials endorsed by the various line ministries. For example,\nin the case of the rehabilitation of a health post, IEC messages could be envisaged to inform the\npopulation on the proper use of insecticide treated bed nets as a means of preventing malaria.\n\n\n(c) Monitoring and evaluation at the community, district, regional and central levels would be\ngiven high priority, and linked regularly and directly with NaCSA decision making on NSAP policy,\nstrategy and operational matters. These activities would be directly undertaken, or commissioned by,\nstaff of NaCSA's Planning, Monitoring and Evaluation Directorate. The Project Design Matrix (logical\nframework, Annex 1) would form the basis for monitoring NSAP outputs, outcomes and impact. An\nassessment of project status would accompany each NaCSA work program and budget submitted\nsemi-annually to the NaCSA Board. Other M&E activities would include a pre-project Social\nAssessment; establishment of NSAP baseline data (in conjunction with the collection of data for the\nCRRP Implementation Completion Report); social assessments during implementation; annual technical\naudits; beneficiary assessments; incorporation of NaCSA into GOSL's semi-annual public expenditure\ntracking surveys (PETS); and independent impact assessments.\n\n\nIn addition to conventional sub-project monitoring and evaluation (incorporated in the\nsub-project cycle as outlined in the Operations Manual), a pilot participatory monitoring and evaluation\nsystem would be introduced in a representative sample of the predominant types of CDP sub-projects.\nBeneficiary communities would identify quantitative and qualitative indicators", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000012", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NSAP baseline data", "probe_tag": "drop", "probe_score": 0.030066322535276413, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1493, "end": 1511, "key": "refugee_pads:000012:36:0:0", "source": "camp2", "luna_reason": "Establishment of NSAP baseline data is a planned project data-production activity.", "drop_reason": "production", "specificity": "vague"}, {"text": "public expenditure\ntracking surveys", "probe_tag": "confusion", "probe_score": 0.30910515785217285, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1743, "end": 1778, "key": "refugee_pads:000012:36:0:1", "source": "camp2", "luna_reason": "Planned incorporation into future monitoring surveys, not cited existing data use.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "**INDONESIA**\n**EMERGENCY REHABILITATION OF THE DRAINAGE AND FLOOD PROTECTION**\n\n**SYSTEM OF BANDA ACEH PROJECT**\n\n\n**Annex** 3: **Projects Results Summary**\n\n\n\n**Project Intervention**\n\n**Logic**\n\n\nSustainable post-tsunan\nProject Purpose\nRe-establish\nsustainable urban\nenvironment in Banda\nAceh to provide a less\nrisky physical\nenvironment for the\neconomic recovery,\nfacilitating investment\nand long term\nsustainability of the\naffected areas.\n**Objective 1**\nFast track protection\nagainst tidal incursion\nto vulnerable areas.\n\n\n**Objective 2**\nEmergency protection\nagainst stormwater and\ntidal incursion to\nvulnerable areas.\n\n\n**Objective 3**\nSustainable operation\nand maintenance of\ndrainage system in\nBanda Aceh\n\n\n\nChronic tidal\nincursion in the\nproject area is\nprevented within three\nmonths.\nChronic tidal and\nstorm water incursion\nin the project area is\nprogressively\nprevented over an 10 \n15 month period\nPumps and valves\noperate correctly as\nand when required.\n\n\nMarine incursions are\nprevented\n\n\nStorm water i s\nremoved without\ncausing flooding\n\n\n\n**Verifiable Indicators** **Means of Verification** **Assumptions**\n**of Achievement**\n\n\n\nreconstruction and dew\n\n100% protection of\npopulation against\ndesign intensity storm\nwater flooding and\ntidal flooding\n\n\n\npment in Aceh\nAbsence of visual\nevidence; reports o f\nflooding events associated\nwith design intensity\nevents.\n\n\nAbsence of visual evidence\nand reports of flooding\nevents associated with\ndesign intensity events.\n\n\nAbsence of visual evidence\nand reports of flooding\nevents associated with\ndesign intensity events.\n\n\nRecords of pump\noperation.\n\n\nVisual inspection of valve\noperation.\n\n\nAbsence of visual evidence\nand reports of flooding\nevents associated with\ndesign intensity events.\n\n\n22\n\n\n\nSystem designs are\nappropriate.\n\n\nOperation and\nmaintenance of the\nsystems are sustained.\n\n\nLong-term drainage\nplanning is appropriate\nto the growing needs of\n\nBanda Aceh\n\n\nSystem designs are\nappropriate.\n\n\nConstruction i s\nappropriate.\nSystem designs are\nappropriate.\n\n\nConstruction i s\nappropriate.\n\n\nOperators maintain\nrecords.\n\n\nManagers inspect\nrecords.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000122", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Records of pump\noperation", "probe_tag": "drop", "probe_score": 0.04250580072402954, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1583, "end": 1608, "key": "refugee_pads:000122:27:0:0", "source": "camp2", "luna_reason": "Logframe verification record, not an existing dataset used for analysis.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": "|MoLG|Ministry of Local Government|\n|---|---|\n|MoLHUD|Ministry of Lands, Housing and Urban Development|\n|MoWT|Ministry of Works and Transport|\n|NDP|National Development Plan|\n|NEMA|National Environmental Management Agency|\n|NERAMP|Northeastern Road Corridor Asset Management Project|\n|NGO|Non-Governmental Organization|\n|NR|National Road|\n|NSP|Nominated Service Provider|\n|OPM|Office of the Prime Minister|\n|PAP|Project Affected Person|\n|PDU|Procurement and Disposal Unit|\n|PIU|Project Implementation Unit|\n|PPSD|Project Procurement Strategy Document|\n|PSC|Project Steering Committee|\n|PSI|Project Safety Impact|\n|RAMS|Road Asset Management System|\n|RAP|Resettlement Action Plan|\n|ReHOPE|Refugee and Host Population Empowerment|\n|ROW|Right of Way|\n|RSW|Sub-Window for Refugees and Host Communities|\n|RSSAT|Road Safety Screening and Analysis Tool|\n|SEA|Sexual Exploitation and Abuse|\n|SEP|Stakeholder Engagement Plan|\n|SH|Sexual Harassment|\n|SIDA|Swedish International Development Cooperation Agency|\n|SOP|Standard Operating Procedures|\n|SPD|Standard Procurement Document|\n|STA|Settlement Transformation Agenda|\n|STEP|Systematic Tracking of Exchanges in Procurement|\n|TAC|Third-party Audit Consultant|\n|TOR|Terms of Reference|\n|TSDP|Transport Sector Development Project|\n|UDHS|Uganda Demographic and Health Survey|\n|UNHCR|United Nations High Commissioner for Refugees|\n|UNRA|Uganda National Roads Authority|\n|UPDF|Uganda Peoples’ Defense Forces|\n|URF|Uganda Road Fund|\n|USAID|United States Agency for International Development|\n|US$|United States Dollar|\n|UXO", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000146", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Uganda Demographic and Health Survey", "probe_tag": "drop", "probe_score": 0.022064194083213806, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1276, "end": 1312, "key": "refugee_pads:000146:3:0:0", "source": "camp2", "luna_reason": "Survey is only defined in a glossary; no data use or finding is shown.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "ية**||\n\n\n|لخدملا|Col2|Col3|\n|---|---|---|\n||**  البيانات الذاتية**|**  البيانات الذاتية**|\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nالمصدر: الوكالة الوطنية لنظام معلومات الدولة\n\n\n.إعادة تصميم الخدمات اإللكترونية المختارة المستهدفة في إطار هذا المشروع وسيتمهنا في يتمثل الهدف . **هيكلة العمليات التجارية إعادة** .15\n\nتنفيذ األنشطة التالية: (أ) تحليل شامل للخدمات يشمل الخطوات القانونية والتقنية واإلدارية واإلجرائية التي تحتوي على روابط وأنظمة\n\" وخطة عمل لخدمات إعادة الهيكلة ؛ (ج) وضع معاييرالحقةات \"العمليللولوجيا المعلومات المطلوبة )؛ (ب وضع خرائطوتغييرات تكن\n\nالرصد والتقييم ، باإلضافة إلى أنظمة اإلبالغ لقياس آثار إعادةو )؛ (هـالحقة\"داعمة لتنفيذ الخرائط \"ال (د) إعداد وثائق؛ الخدمة لكل خدمة\n\nهيكلة. ال\n\n\nية ي", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000140", "page": 39, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "البيانات الذاتية", "probe_tag": "drop", "probe_score": 0.027297865599393845, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 48, "end": 64, "key": "refugee_pads:000140:39:3:0", "source": "camp2", "luna_reason": "Standalone table cell/header; source citation appears separately and does not make it data use.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "البيانات الذاتية", "probe_tag": "confusion", "probe_score": 0.8916854858398438, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 48, "end": 64, "key": "refugee_pads:000140:39:3:1", "source": "camp2", "luna_reason": "Standalone table cell without an attributed finding or data use.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " / LHW and PMU,<br>DOH<br>|\n|Children under 1 year immunized with the<br>first dose of measles vaccination in target<br>districts|<br>Percentage of children<br>under 1 immunized at EPI<br>centres, PHC, and in the<br>community in target<br>districts.|Bi-Annually<br>|DHIS, EPI MIS<br>|Routine HMIS<br>|DHIS/EPI<br>|\n|Women receiving iron/folic acid<br>supplementation during pregnancy in<br>target districts|Percentage of all pregnant<br>women receiving iron/folic<br>acid supplementation at<br>PHC facilities, or in the<br>community in target<br>districts.|Bi-Annually<br>|DHIS, LHW<br>MIS<br>|Routine HMIS<br>|IMU, PMU, DOH<br>|\n|Health professionals (doctors, nurses,<br>non-medical staff) receiving refresher and<br>on-the-job training|Number provincial and<br>district staff trained<br>(Cumulative number).|Bi-Annually<br>|PMU<br>|PMU Records<br>|IMU, PMU, DOH<br>|\n\n\n\nPage 38 of 48", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000126", "page": 42, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "PMU Records", "probe_tag": "drop", "probe_score": 0.047011904418468475, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 835, "end": 846, "key": "refugee_pads:000126:42:1:0", "source": "camp2", "luna_reason": "Standalone table cell naming a project monitoring record source.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000100", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MOE reports", "probe_tag": "drop", "probe_score": 0.034246839582920074, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 385, "end": 396, "key": "refugee_pads:000100:30:0:0", "source": "camp2", "luna_reason": "MOE reports are cited as evidence of increased enrollment.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " implementation of project activities as per the implementation work plan\n\nin a timely and high quality manner;\n\n\nb) Monitoring the project performance with regard to achievement of project activities and\n\nif necessary, modify and/or redirect activities to maximize the potential impact of the\nproject;\n\n\nc) Establishing a basis for evaluating the project with regard to achievement of the overall\n\ndevelopment objective;\n\n\nd) Establishing working partnerships with PHCCs, Prime Minister’s (PM) office responsible\n\nfor the NPTP program, Hospitals (OPD) to gather and/or access the relevant data to\noptimize the M&E outputs for each component and sub-component under an integrated\nM&E plan;\n\n\ne) Organizing data collection from different stakeholders and facilitating verification,\n\nanalysis of the data/information received from various stakeholders;\n\n\nf) Liaising with implementing agencies and partners required for implementation of key\n\ntechnical instruments (i.e. facility surveys, beneficiary assessments etc.); and\n\n\n53", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 52, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "facility surveys", "probe_tag": "drop", "probe_score": 0.01811016909778118, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 969, "end": 985, "key": "refugee_pads:000020:52:1:0", "source": "camp2", "luna_reason": "Planned facility surveys are listed as project monitoring instruments, not existing data used.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "beneficiary assessments", "probe_tag": "confusion", "probe_score": 0.18750400841236115, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 987, "end": 1010, "key": "refugee_pads:000020:52:1:1", "source": "camp2", "luna_reason": "Assessment implementation is planned project data production, not use of existing findings.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\nbuses, motorbikes, cars, and trucks (modes used by refugees/hosts and for trade)\n(iii) Time of closure of Project road corridor in a year for movement of trucks (days)\n(iv) Percentage increase in trade volumes using the Project road (dis-aggregated by refugees, hosts)\n\n(b) enhance the capacity of UNRA to manage environmental, social and road safety risks\n\n(v) Fully operational Environmental and Social Management System in place\n(vi) Crash data entered into system, publicly reported, and used in decision making (yes/no)\n(vii) Annual Number of fatalities or serious injuries involving construction vehicles or at construction\n\nsites\n\n\n**B. Project Components**\n\n\n43. The project will have the following components as detailed below.\n\n\n44. **Component 1: Road Upgrading Works (Total US$145.8 million; IDA: US$125.8 million equivalent, GoU:**\n**US$20 million).**\n\n\n1(a) Upgrading - to bituminous paved road standard - and widening of about 105 km of KobokoYumbe-Moyo road corridor.\n1(b) Carrying out supervision of civil works under part 1(a) of the Project.\n1(c) Carrying out environmental and social risks management (including implementation of action\nplans to address among others gender-based violence, sexual exploitation and abuse, violence\nagainst children and HIV/AIDS), monitoring and evaluation, third party integrated performance\naudits and road user satisfaction surveys.\n1(d) Preparation of Project’s environmental and social risk management documents as well as\ndetailed engineering designs of civil works and carrying out land acquisition, and resettlement\nand rehabilitation associated with upgrading works under Part 1(a) and maintenance of the road\ncorridor for five years post-construction.\n\n45. This", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000146", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "road user satisfaction surveys", "probe_tag": "drop", "probe_score": 0.046286437660455704, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1453, "end": 1483, "key": "refugee_pads:000146:25:0:1", "source": "camp2", "luna_reason": "Project will carry out these planned surveys; no existing survey data are used.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "PRS : LIBERIANS IN COTE D’IVOIRE\n\n\n35. The demographic structure of the refugee population is somewhat difficult\nto evaluate, because the age groups used are not the same as those in the national\npopulation census (Table 2). However, demographic tables allow an estimate of the\nage structure of the refugee population according to the standard classification: the\nproportion in the age group 0-14 would be 45.2 per cent and for the 15-59 bracket\n50.0 per cent. These data clearly point to a population with a higher dependency ratio\nthan the national one: more women, more children, and more old people. However,\nit must be borne in mind that the national figure is strongly influenced by the fact\nthat so many residents of Côte d’Ivoire are foreign nationals, many of whom are\ntemporary migrants and these are disproportionately male and working-age adult.\nThe male: female ratio for Ivorian citizens is only 98.3. Furthermore, the rural areas\nalso have a higher percentage of children and elderly (46.1 and 4.9 per cent,\nrespectively). All this indicates that the age structure of the refugee population may\nnot really be all that different from the Ivorian one; there remains, however, a noted\npreponderance of women, which may be due to the differential impact of the civil\nwar on the sexes. The consequence of such a demographic structure is a somewhat\nlower capacity for economic self-sufficiency.\n\n\n**Table 2. Demographic structure**\n\n\n\n\n\n\n|Liberians (1997 refugee census)|Col2|All residents (1998 population census)|Col4|\n|---|---|---|---|\n|0-4 years old|14.8 %|||\n|5-17|38.9 %|0-14|42.9 %|\n|18-59|41.2 %|15-59|53.2 %", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001267", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "national\npopulation census", "probe_tag": "keep", "probe_score": 0.9037995934486389, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 187, "end": 213, "key": "reliefweb:001267:15:0:0", "source": "camp2", "luna_reason": "Existing census data are compared with refugee demographic estimates and population figures.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "-Sub-Saharan-Africa)</u>\n\n\nThis paper **examines individual-level deprivations of women and men in forcibly**\n\n**displaced households and host communities, as well as intrahousehold**\n\n**inequalities, building on prior analysis of the tailored Multidimensional Poverty**\n\n**Index (MPI) in Ethiopia, Northeast Nigeria, Somalia, South Sudan, and Sudan** .\n\nThe MPI measures deprivations in education, health, living standards, and financial\n\nsecurity, by combining 15 indicators across these four dimensions. For the six\n\nindividual-level indicators (years of schooling, school attendance, pregnancy care,\n\nearly marriage, legal identification, and unemployment) spanning the education,\n\nhealth, and financial security dimensions, the authors identify which household\n\nmembers are deprived: their gender and their age, and what proportion of eligible\n\nhousehold members are deprived. The analysis draws on household survey data in\n\nthe five countries <sup>13</sup> [^13: In Ethiopia, the Skills Profile Survey (2017) sampled refugees in and around camps in the Tigray, Afar, Gambella,\nBenishangul Gumuz, and Somali regions. In Nigeria, the IDP Survey (2018) sampled IDPs and host communities in six\nnortheastern states (Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe). In Somalia, the High Frequency Survey (2017)\nsampled IDPs and host communities in secure parts of the country. In Sudan, the IDP Profiling Survey (2018) sampled IDPs\nand neighboring host communities in the Abu Shouk and El Salam camps, in Al-Fashir. And in South Sudan, the High\nFrequency Survey Wave 4 (2017) sampled IDPs and host communities in urban areas of seven of the ten pre-war states\n(Western Equatoria, Central Equatoria, Eastern Equatoria, Northern Bahr-El-Ghazl, Western Bahr-El-Ghazal, Warrap, Lakes\nstate).] .\n\n\nMain results:\n\n\n- In Ethiopia, there are statistically significant gender gaps in school attendance\n\namong the refugee population (3 percentage points for all refugee households, 5\n\npercentage points for MPI poor", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000595", "page": 28, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household survey data", "probe_tag": "keep", "probe_score": 0.925336480140686, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 904, "end": 925, "key": "reliefweb:000595:28:1:0", "source": "camp2", "luna_reason": "Existing household surveys underpin the analysis; footnote identifies country-specific survey rounds.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "Skills Profile Survey", "probe_tag": "keep", "probe_score": 0.9357767701148987, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 986, "end": 1007, "key": "reliefweb:000595:28:1:1", "source": "camp2", "luna_reason": "Named survey data underlies the paper’s household-level deprivation analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "Chapter 6\n\n\nResettlement is a way to save lives and safeguard\nhuman rights by assisting refugees in countries that\ncannot provide them with appropriate protection\nand support. Of all cases submitted by UNHCR in\n2020, 86 per cent were for survivors of torture and/\nor violence, people with legal and physical protection\nneeds, and particularly vulnerable women and\ngirls. <sup>**112**</sup> Just over half (51 per cent) of all resettlement\nsubmissions concerned children.\n\n\nAccording to government statistics, in 2020 the\nUnited States welcomed 9,600 resettled refugees\nfrom 51 countries, predominantly refugees originating\nfrom the Democratic Republic of the Congo (25 per\ncent), Ukraine (18 per cent) and Myanmar (17 per\ncent). A further 9,200 refugees were resettled to\nCanada, most commonly Syrians, Iraqis and Eritreans.\nResettlement to both countries dropped precipitously\nfrom 2019, when 30,100 refugees were resettled in\nCanada and 27,500 in the United States. In 2020,\nEuropean countries collectively welcomed 11,600\nresettled refugees.\n\n\nOverall, Syrians accounted for one-third of resettled\nrefugees in 2020, followed by Congolese (12%). The\nother resettled refugees were from 82 countries\nof origin, including Iraq, Eritrea, Myanmar, Ukraine,\nSudan and Afghanistan.\n\n\nUNHCR is calling on more countries to expand thirdcountry solutions like resettlement. It is also urging\nthem to resettle more refugees, where possible,\nand to make family reunification and complementary\npathways more accessible to refugees.\n\n\n**Local integration**\n\n\nWhen repatriation and resettlement are not viable\noptions, some refugees are able to achieve a third\ndurable solution: building a new life in their country\nof asylum. There are millions of refugees around the\nworld who live in protracted situations with little hope\nof ever returning home. Local integration of refugees\ncan include the provision of legal status, including\nappropriate alternatives under domestic regulations\non long-term residence, and naturalization.\n\n\n\nRefugees must be prepared to adapt to their\nnew country", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000757", "page": 47, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "government statistics", "probe_tag": "keep", "probe_score": 0.9459478855133057, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 486, "end": 507, "key": "reliefweb:000757:47:0:0", "source": "camp2", "luna_reason": "Government statistics support concrete refugee resettlement figures.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "\nin their efforts to protect and assist displaced\npopulations. In 2024, sub-national data on IDPs was\nreported for 31 countries and covered almost all\n(98 per cent) of the total IDP population protected/\nassisted by UNHCR. Based on the available data, at\nleast 42 per cent of IDPs reside in urban areas, <sup>**159**</sup>\n\n\n\nand approximately one-quarter live in settlements,\nincluding camps, <sup>**160**</sup> both in urban and rural settings.\n\n\nAge- and sex-disaggregated data for IDPs was\navailable for 16 countries, 2 fewer than the\nprevious year. This represents 58 per cent of the\nIDP population reported by UNHCR, while sex\ndisaggregation was available for 60 per cent of the\nIDP population.\n\n\nWomen and girls made up 53 per cent of all IDPs,\nwhile children accounted for 46 per cent of IDPs\nworldwide. Countries with the highest proportion\nof internally displaced children included Somalia\n(66 per cent) and Burkina Faso (56 per cent), while\nthe lowest proportion of children were reported in\ncountries such as Mexico (19 per cent) and Ukraine\n(24 per cent). <sup>**161**</sup>\n\n\n**Displacement in the context of**\n**disasters**\n\n\nIn addition to conflict and violence, people were\ndisplaced within their countries due to disasters, with\nrecord levels reported in 2024. Disasters include\npeople displaced due to extreme weather events,\nsuch as floods and storms, and those displaced due\nto geophysical events, such as earthquakes. The\nglobal forced displacement does not include people\ndisplaced due to disasters.\n\n\nDuring the year, 45.8 million internal displacements\ndue to disasters were reported, with 9.8 million\npeople remaining displaced within their own\ncountry at the end of 2024, according to the Internal\nDisplacement Monitoring Centre. <sup>*", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001242", "page": 43, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Age- and sex-disaggregated data for IDPs", "probe_tag": "keep", "probe_score": 0.9061403870582581, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 449, "end": 489, "key": "reliefweb:001242:43:1:0", "source": "camp2", "luna_reason": "Existing disaggregated data supports reported coverage and demographic findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
 {"text": ".\nThey are to be added to the multiple other refugee\npopulations that Jordan hosts, including 66,362 Iraqis,\nand more than 7,972 from Sudan, Somalia, and other\ncountries.\nThe continuously worsening economic situation in\nJordan due to COVID-19 was one of the motives to\nreturn to the country of origin. According to CARE2021\nAnnual Needs Assessment, refugees expressed\ntheir beliefs that reduction in assistance – caused by\nunderfunding humanitarian programs and the absence\nof one refugee approach implementation - is a strategy\nto persuade them to return to their countries of origin <sup>3</sup> .\nAccording to data of the Department of Statistics in\nJordan for the third quarter of 2021, unemployment rate\nhas reached 23.2% (21.2% for males and 30.8% for\nfemales), which represents a decrease in employment\nrates by 1.5% for males and 2.3% for females\n\n\n3 2021 Annual Needs Assessment – Care, Jordan, Page 5 https://data.\nunhcr.org/en/documents/details/92107\n\n\n\ncomparing to the second quarter of the same year. The\nstatistics reflect a constant impact of COVID-19 on the\neconomic situation of Jordan and labor market with a\nslight enhancement by 0.7% compared to the second\nquarter of 2020.\nRefugee occupations are generally limited to either\ninformal work in the field of agriculture, construction,\nmanufacturing, or incentive-based volunteering\nopportunities which are mainly available in refugee\ncamps. Confining opportunities to these sectors and\nthe expensive fees of issuing work permits are the main\nchallenges that limited refugees from participating in\nthe labor market and may expose them to significant\nrisks of detention and exploitation. Moreover, only\nSyrian refugees in Jordan are legally allowed to work.\nThose from other countries, including Iraq, Yemen,\nSudan and Somalia, are not able to apply for permits <sup>4</sup> .\nAs of September 2021, the number", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001068", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "CARE2021\nAnnual Needs Assessment", "probe_tag": "keep", "probe_score": 0.9734445810317993, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 315, "end": 347, "key": "reliefweb:001068:4:1:0", "source": "camp2", "luna_reason": "Named assessment supports refugees’ reported beliefs about reduced assistance.", "usage_type": "evidential", "specificity": "named"}, {"text": "data of the Department of Statistics", "probe_tag": "keep", "probe_score": 0.9470546841621399, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 613, "end": 649, "key": "reliefweb:001068:4:1:1", "source": "camp2", "luna_reason": "Department of Statistics data supports reported unemployment and employment-rate findings.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "\n7 Includes movement through official crossing points.\n8 [Movements recorded through border monitoring (UNHCR Afghanistan 2024 Border Monitoring Report).](https://data.unhcr.org/en/documents/details/114012)\n9 UNHCR Regional Protection Monitoring System (RPMS) dashboard indicates Türkiye as previous country of asylum for 27 per cent of Afghan nationals. Furthermore,\nRPMS indicates that 50 per cent of the Afghan nationals in Türkiye fled Afghanistan between one and five years ago, and 9 per cent fled Afghanistan more than five\nyears ago, before undertaking onward movements from Türkiye to the EU. Many Afghan nationals interviewed have lived for a long time in Türkiye and often in Iran\nbefore their onward movements due to, for example, administrative measures that force people to move from one province to another, loosing jobs and housing, and\nthe earthquakes.\n10 A significant pathway for refugees, asylum-seekers and migrants en route to Europe from the Middle East, Asia and Africa with Türkiye as the main transit country to\nreach Greece, Cyprus and Bulgaria.\n\n\n**REGIONAL BUREAU FOR ASIA AND THE PACIFIC (RBAP) & REGIONAL BUREAU FOR EUROPE (RBE) |** JULY 2025 3", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000518", "page": 2, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "UNHCR Afghanistan 2024 Border Monitoring Report", "probe_tag": "keep", "probe_score": 0.9243109226226807, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 104, "end": 151, "key": "reliefweb:000518:2:2:1", "source": "camp2", "luna_reason": "Named border monitoring report provides recorded movement evidence.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "### 2. Needs assessment and programme design\n\n**The assessment process: 1993 group**\n\n\n23. The decision to introduce a cash grant for the 1993 returnees in addition to\nthe existing return package, whilst prompted by the need to develop a managed\nresponse to the critical slowdown in repatriation, nonetheless emerged from a\ncomprehensive needs assessment process in early 2007. An earlier Joint Assessment\nMission (JAM) conducted in Tanzania in 2006 had contributed to a decision to\ndowngrade non-essential assistance in the camps, resulting in the termination of\nincome-generating activities and the announcement that secondary schools would\nnot re-open in September 2007. The Tanzania JAM recommended that a JAM also be\nundertaken in Burundi, examining food security and other assistance requirements\nfor returnees.\n\n\n24. Building on this, an assessment of reintegration needs in Burundi began in\nlate 2006 and early 2007 with a study of 4,807 returnee households carried out by the\nInstitut des Statistiques et d’Etudes Economiques du Burundi (ISTEEBU). Their\nreport, issued in April 2007, covered issues such as economic activity, education,\nnature of identity documents, health status, shelter, perceptions of security, food\nsecurity, agricultural activity, reasons for return and relationships with the receiving\ncommunity. <sup>12</sup> [^12: Institut de Statistiques et d’Etudes Economiques du Burundi (ISTEEBU), WFP, UNHCR and other\nagencies (2007), Enquête d’évaluation de la réintégration durable des rapatriés Burundais, Résultats\nDéfinitifs, Bujumbura, April]\n\n\n25. It cited a number of reasons for the slowdown in repatriation: the food crisis\n(notably a weak first harvest in 2006); limited progress in the negotiations with FNL;\nand significant socio-economic challenges in return areas. However, it was noted that\nthe second half of 2006 had started well, with a better second harvest, the conclusion\nof an agreement with the FNL, and the establishment of the Commission Nationale\ndes Terres et Autres Biens (CNTB) with a mandate to address land-related disputes.", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001142", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "study of 4,807 returnee households", "probe_tag": "confusion", "probe_score": 0.4142763912677765, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 931, "end": 965, "key": "reliefweb:001142:9:0:0", "source": "camp2", "luna_reason": "Completed household study supplied concrete reintegration needs findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "\n32. Recognizing the important role that **_sports_** **_and cultural activities_** can play in social\ndevelopment, inclusion, cohesion, and well-being, particularly for refugee children and\nyouth, partnerships will be pursued between relevant foundations; international\norganizations; non-governmental organizations; sporting and cultural associations\nfederations, and organizations; the private sector; and experts to increase access to sporting\nand cultural facilities and activities in refugee-hosting areas. <sup>14</sup>\n\n\n**6.** **Data and evidence**\n\n\n33. Reliable, comparable, and timely data, including population and socio-economic data,\nis critical for evidence-based measures to: improve conditions for refugees and host\ncommunities; assess the impact of large numbers of arrivals on host countries; and identify\nappropriate solutions. <sup>15</sup>\n\n\n34. Specific actions by States and other relevant stakeholders could include:\n\n\n - promoting the development of common standards for the collection, analysis, and\ndissemination of age and gender-disaggregated data on refugees and asylum-seekers, <sup>16</sup>\nincluding making primary population and socio-economic data (and underpinning\ncollection methodologies) accessible to relevant stakeholders as appropriate;\n\n - supporting the inclusion of refugees and host communities in national strategies for the\ndevelopment of statistics;\n\n - resourcing national data collection systems on the situation of refugees and host\ncommunities, including socio-economic and demographic status, using national surveys,\npopulation and housing censuses, and administrative sources as relevant; and\n\n\n<sup>12</sup> E.g. participation of refugee children and youth in policy and decision-making through local\n\nrefugee youth councils, building on UNHCR’s Global Youth Advisory Council.\n\n<sup>13</sup> [Including: ICORN Cities of Refuge; the Global Network of Cities, Local and Regional](https:", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000731", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "population and socio-economic data", "probe_tag": "confusion", "probe_score": 0.22053922712802887, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 613, "end": 647, "key": "reliefweb:000731:4:1:0", "source": "camp2", "luna_reason": "Existing data is identified as supporting evidence-based measures and impact assessment.", "usage_type": "declaration", "specificity": "vague"}, {"text": "national surveys", "probe_tag": "confusion", "probe_score": 0.6391144394874573, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1555, "end": 1571, "key": "reliefweb:000731:4:1:2", "source": "camp2", "luna_reason": "Listed as a source for planned national data collection, without existing data use.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "population and housing censuses", "probe_tag": "confusion", "probe_score": 0.16336162388324738, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1573, "end": 1604, "key": "reliefweb:000731:4:1:3", "source": "camp2", "luna_reason": "Planned resourcing of national data collection, not use of an existing census.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "~~•~~<br>~~Reduction in mobility~~<br><br> <br>|~~•~~<br>~~Reduction in mobility~~<br><br> <br>|~~•~~<br>~~Reduction in mobility~~<br><br> <br>|\n||~~•~~<br>~~Gender violence/~~<br>transactional sex|||~~•~~<br>~~Reduction in~~<br>accessibility|~~•~~<br>~~Reduction in~~<br>accessibility||\n||~~•~~<br>~~Reduction in resources~~<br>|||~~•~~<br>~~Increase in resources~~<br>|~~•~~<br>~~Increase in resources~~<br>||\n||~~and services(e.g. health,~~<br>education,  community<br>services, protection, food)|||~~and  services in host~~<br>country|~~and  services in host~~<br>country||\n\n\n\n(Spiegel P, UNHCR, 2003)\n\nAn analysis of available data has made it possible to describe several different scenarios in which\nthe relationship between HIV/AIDS and conflict presents different epidemiological patterns:\n\n\n\n**i.** **Prolonged Conflict Retarding the Progression of HIV**\nPopulation-based HIV behavioural and biological surveillance surveys from the Centers\nfor Disease Control and Prevention have shown lower than expected HIV prevalence\nrates in Sierra Leone (0.9% in accessible areas covering 79% of the population and\nSouthern Sudan (2.3% HIV prevalence among pregnant women in antenatal clinics", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000612", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "available data", "probe_tag": "confusion", "probe_score": 0.7487298250198364, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 622, "end": 636, "key": "reliefweb:000612:3:1:0", "source": "camp2", "luna_reason": "Available data are explicitly analyzed to describe conflict-related epidemiological scenarios.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "#### **METHODOLOGY**\n\n\n\n\n\n\n\n\n\n\n\n\n|GEOGRAPHIC<br>COVERAGE|National coverage, excluding the Transnistrian region.|\n|---|---|\n|**SAMPLING**|**Non-probability purposive sampling approach**, constructed based on cross-referenced<br>population figures from the UNHCR Multi-Purpose Cash Assistance (MPCA) beneficiary list,<br>the General Inspectorate for Migration (IGM) Temporary Protection (TP) list, and the REACH<br>area monitoring exercise. Settlements with fewer than 5 refugee HHs were excluded from the<br>sampling frame.<br>**Sampling frame at settlement level**(admin 2).|\n|**DESIGN**|HH surveys were distributed based on**regional stratification**(North, Centre, South, Chisinau).|\n|**DATA COLLECTION**|Primary data was collected through in-person quantitative HH-level surveys from**3 June to 12**<br>**July** **2024** by enumerators from the REACH Initiative.|\n|**SAMPLE SIZE**|622 HHs (with the overall minimum target of interviews sampled being 597), covering 1,204<br>individual HH members.|\n|**WEIGHTS**|**Regional weights** were applied to national-level findings only to correct for distortions in<br>proportionality created by the sampling design (i.e., stratification by region), as the majority of<br>refugee HHs are concentrated in the Chisinau region, with fewer HHs in more rural areas.|\n\n\n\n5", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001669", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "HH surveys", "probe_tag": "confusion", "probe_score": 0.18497581779956818, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 588, "end": 598, "key": "reliefweb:001669:4:0:1", "source": "camp2", "luna_reason": "Survey distribution describes data collection, not use of existing survey data.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "/insights/annexes/forcibly-displaced-maps.html)</u>\n\n\n\nThese two categorizations are compared graphically\non the next page. A detailed breakdown of the\npopulation that UNHCR protects and/or assists is\nprovided in <u>[Annex Tables 1 – 3](https://www.unhcr.org/refugee-statistics/insights/annexes/trends-annexes.html)</u> by category and\ncountry.\n\n\nThe figures in this report are based on data reported\nby governments, non-governmental organizations\nand UNHCR. Numbers are rounded to the closest\nhundred or thousand. As some adjustments may\nappear later in the year in the Refugee Data Finder, <sup>**8**</sup>\nfigures contained in this report should be considered\nas provisional and subject to change. Unless\notherwise specified, the report does not refer to\nevents occurring after 30 June 2023.\n\n\n<u>[View annex tables by category and country.](https://www.unhcr.org/refugee-statistics/insights/annexes/trends-annexes.html)</u>\n\n\n\n**6** See the <u>[Methodology page of UNHCR’s Refugee Data Finder for a definition of each population group.](https://www.unhcr.org/refugee-statistics/methodology/)</u>\n**7** The total number of people forcibly displaced is calculated using UNHCR, UNRWA and IDMC statistics.\n**8** [See: UNHCR’s Refugee Data Finder.](https://www.unhcr.org/refugee-statistics)\n\n\nUNHCR > **MID-YEAR TRENDS 2023** 3", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001065", "page": 2, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Refugee Data Finder", "probe_tag": "confusion", "probe_score": 0.8865642547607422, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 571, "end": 590, "key": "reliefweb:001065:2:1:0", "source": "camp2", "luna_reason": "Named UNHCR data resource cited regarding report figures and later adjustments.", "usage_type": "declaration", "specificity": "named"}, {"text": "IDMC statistics", "probe_tag": "confusion", "probe_score": 0.8727556467056274, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1189, "end": 1204, "key": "reliefweb:001065:2:1:1", "source": "camp2", "luna_reason": "IDMC statistics are used to calculate total forced displacement.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " children typically do not\nreceive the intensive language education,\nintroductory classes or other preparatory\nprogrammes they would receive in schools in host\ncountries in Europe. Since language-learning is a\nmulti-year endeavour, postponing language\neducation can significantly set back the educational\ntrajectory of refugee children and youth. <sup>68</sup>\n\n\nNot knowing the language(s) of instruction in a host\ncountry also has a negative impact on mental health\nand well-being, as shown by the Impact/Save the\nChildren data. 14 per cent of refugee caregivers of\nchildren and adolescents cited ‘not knowing the\nlanguage of the host community’ as a safety and\nwell-being risk. <sup>69</sup>\n\n#### **Livelihoods of parents**\n\n\nGiven the large amount households headed by\nsingle female refugees from Ukraine, access to\npre-school and school education for children is\ncrucial to allow women to find employment and\nallow for the time and space to take care of\nessential daily routines. If access to pre-school and\nschool is not ensured, female heads of household\nmay not be able to cope, or be left with no choice\nbut to return to Ukraine despite the unfavourable\nsecurity situation.\n\n\n\n16 **U N H C R R E G I O N A L B U R E A U F O R E U R O P E,** S E P T E M B E R 2 0 2 3", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001135", "page": 15, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Impact/Save the\nChildren data", "probe_tag": "confusion", "probe_score": 0.845857560634613, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 500, "end": 529, "key": "reliefweb:001135:15:1:0", "source": "camp2", "luna_reason": "Named organizations’ data supports the reported caregiver safety-risk finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " boys aged 13-18, and 10 girls aged 12-17. Informed consent was sought from all\nparticipants prior to the data gathering activity. The FGD data are not representative, given that\nsaturation was not sought for this exercise.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n_Newer adolescent peer educators at the_\n_ARHN youth center._\n\n\n\n14", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000501", "page": 17, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "FGD data", "probe_tag": "confusion", "probe_score": 0.11591754853725433, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 135, "end": 143, "key": "reliefweb:000501:17:2:0", "source": "camp2", "luna_reason": "FGD data support the concrete finding that results are not representative.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "|Asylum Levels and Trends in Industrialized Countries, 2008|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.3604869544506073, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 288, "end": 300, "key": "reliefweb:000427:31:0:0", "source": "camp2", "luna_reason": "Span appears within a table caption and describes reporting frequency.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.22712811827659607, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 288, "end": 300, "key": "reliefweb:000427:31:0:2", "source": "camp2", "luna_reason": "Generic data phrase embedded in a table caption and coverage note.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "annual data", "probe_tag": "confusion", "probe_score": 0.09387979656457901, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 338, "end": 349, "key": "reliefweb:000427:31:0:3", "source": "camp2", "luna_reason": "Fragment occurs within a table caption and does not independently cite used data.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "is characterized by the absence of natural tree cover, except for some sparsely\n\n\ndistributed hawthorns. For a brief period before June, the land is covered with a\n\n\nvariety of flowering and grassy plants.\n\n\nThe mule is the beast of burden in the mountains, and the camel on the steppe. Other\n\n\ndomesticated animals include horses, donkeys, cattle, sheep, goats, and chickens.\n\n\nBees also are kept. <sup>14</sup> [^14: ( _Ibid._, [s.d.])]\n\n\n**[2.2]** **KEY DEMOGRAPHIC, CULTURAL, SOCIAL AND**\n\n**ECONOMIC DATA**\n\n\n**↘** **_THE DATA IN THIS SECTION REFERS TO WHOLE OF SYRIA AND NOT JUST NWS_**\n\n\n- **DEMOGRAPHIC DATA**\n\n\nThere is a significant population density along the Mediterranean coast. Larger\n\n\nconcentrations found in the major cities of Damascus, Aleppo and Homs. More than\n\n\nhalf of the population lives in the coastal plain, the province of Halab, and the\n\n\nEuphrates River valley. <sup>15</sup> [^15: (CIA, 2022)]\n\n\nThe largest city in Syria is not its capital Damascus, but Aleppo, which is situated in the\n\n\nNorth East of the country. Aleppo's population was recorded at 2,132,100 in the 2004\n\n\nCensus, although it has dropped dramatically since, given the conflict and millions\n\n\nfleeing the country. Updated estimates on city populations are unavailable or may be\n\n\nskewed due to the fluctuations caused by the chaos. <sup>16</sup> [^16: (World Population Review, [s.d.])]\n\n\nDamascus is the second largest city in Syria, with a population of 1,711,000 (estimate,\n\n\n2009). It holds the record as the oldest continually inhabited city in the world; there is\n\n\nadditional evidence of human habitation in Damascus dating back to 9,000 BC\n\n\n(however,", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001407", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "DEMOGRAPHIC DATA", "probe_tag": "confusion", "probe_score": 0.34950119256973267, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 599, "end": 615, "key": "reliefweb:001407:10:0:0", "source": "camp2", "luna_reason": "Standalone section heading, not an analyzed or cited data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "**Kadir serves a customer** with a freshlymade bolony – bread stuffed with\nspinach and onion. The 13-year-old\nAfghan and his family have faced many\nchallenges since returning to Kabul from\nthe Islamic Republic of Iran, including\nthe loss of his father.\n\n\n\nUNHCR Global Trends 2012 **31**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000089", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR Global Trends", "probe_tag": "confusion", "probe_score": 0.16310887038707733, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 256, "end": 275, "key": "reliefweb:000089:30:0:0", "source": "camp2", "luna_reason": "Standalone report citation lacks visible data use or attributed finding.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": "**1. Access to Essential Health and Nutrition**\n**Services throughout the Displacement Cycle**\n\n\nAt all stages of the displacement cycle – fleeing from active conflict, crossing borders, stabilization, protracted\nstays as refugees and eventual return home when possible – refugees require access to essential health and\nnutrition services. However, many challenges may be faced including disruption in continuity of care for those\nwith chronic conditions, user fees, long distances to health facilities and sub-optimal health care quality.\n\n\nIn 2021, the second year defined by the COVID-19 pandemic restrictions, continuity of access to health and\nnutrition services, as well as impact on health outcomes, remained a high priority. UNHCR and partners monitored\nrefugee access to services through multiple means, including through surveys and the **Integrated Refugee Health**\n**Information System** (iRHIS) that collates and analyses a comprehensive set of health and nutrition data visualizing\ntrends over time. iRHIS data covers 155 sites in 22 countries covering over 5 million refugees.\n\n\n**KEY INDICATORS**\n\n\n**Indicator** **2021** **2020** **Standard**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe under-five mortality rate, an important indicator of child health and the social, economic and\nenvironmental conditions in which children and their families live, remained stable globally and below\nemergency thresholds. There are concerns about the impact of COVID-19 and service continuity disruptions\non childhood immunization. UNHCR worked with partners and communities on maintaining access to and\nuptake of routine vaccinations and this will continue to be a focus in 2022.\n\n\n\n<u>6</u>", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000502", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "iRHIS", "probe_tag": "confusion", "probe_score": 0.8957180976867676, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 901, "end": 906, "key": "reliefweb:000502:5:0:0", "source": "camp2", "luna_reason": "Named health information system whose data are used to monitor refugee service access.", "usage_type": "declaration", "specificity": "named"}, {"text": "health and nutrition data", "probe_tag": "confusion", "probe_score": 0.3128024935722351, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 958, "end": 983, "key": "reliefweb:000502:5:0:1", "source": "camp2", "luna_reason": "iRHIS analyzes the data to visualize health and nutrition trends over time.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "iRHIS data", "probe_tag": "keep", "probe_score": 0.9443785548210144, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1014, "end": 1024, "key": "reliefweb:000502:5:0:2", "source": "camp2", "luna_reason": "Named iRHIS data reports coverage across sites, countries, and refugees.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " GAM at 30 percent and\n4 percent respectively, while Mahama has the highest\nburden of anaemia at 45 percent and stunting rates of 30\npercent. The difference between GAM in the refugee and\nthe host populations is minimal. In all camps except\nMahama, anaemia was lower than in the host population,\nbut when aggregated this difference is minimal (33 percent\nin the camps vs. 37 percent in the host population).\nHowever, average stunting prevalence in refugee camps is\n14 percent lower than the national prevalence of stunting\nin Rwanda (23 percent vs. 37 percent). The could be\nbecause the refugee camps are a controlled setting that\nallow for 1) high coverage of nutrition specific and\nsensitive interventions, 2) implementing partners with\nhigher staffing levels and, 3) increased complementarity\nacross sectors. Much could be learnt from the refugee\nsettings and applied at scale to the host communities to\ndecrease the rates of stunting.\n\n\n\n**Figure 3:** The prevalence of stunting for children under 5 years\nof age in the refugee camps and host population in 2018.\nTriangle and blue script outline indicates refugee camps (WFP,\n2018; UNHCR and WFP, 2018).\n\n\n**Figure 4:** The prevalence of GAM for children under 5 years of\nage in the refugee camps and host population in 2018 (WFP,\n2018; UNHCR and WFP, 2018).\n\n\n**Figure 5:** The prevalence of anaemia for children under 5 years\nof age in the refugee camps and host population in 2015\n(comparisons for 2018 were not possible because anaemia data\nin the host population was not available) (NISR, 2015; UNHCR\nand WFP, 2015).\n\n\n\n7 Complete details of the findings, a full list of data sources used, and references can be found in the full report.\n\n8 Comparisons for 2018 were not possible because anaemia data in the host population is not available.\n\n\n6 |", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001546", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "anaemia data", "probe_tag": "confusion", "probe_score": 0.5994589328765869, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1486, "end": 1498, "key": "reliefweb:001546:7:1:0", "source": "camp2", "luna_reason": "States anaemia data were unavailable, without using them for analysis or substitution.", "drop_reason": "availability", "specificity": "vague"}]}
-{"text": " application publicly displayed and potentially scrutinised by a Court. Alternatively, such a\ncouple may not know that the requirement to apply for permission exists. If a Buddhist woman\nand non-Buddhist man live together without marrying, or marry without registering the marriage first (both of which would be in breach of the 2015 Myanmar Buddhist Women’s Special\nMarriage Law), <sup>130</sup> NGO representatives expressed their concern that authorities will refuse to\nupdate the household registration list to demonstrate that they are in fact living together.\n\n\nSimilarly, NGO representatives reported that if women are in a polygamous marriage and living\nwith their husband and his other wives (which would be in breach of the 2015 Practicing of\nMonogamy Law), then authorities may also refuse to update their household registration list.\n\n\nAlternatively, NGO representatives discussed that women in either or both of the situations\nabove may simply avoid authorities altogether and not apply to update their household\nregistration list (or register births or apply for and update citizenship documentation) if they\nunderstand they are living in breach of the 2015 Myanmar Buddhist Women’s Special\nMarriage Law and/or 2015 Practicing of Monogamy Law.\n\n\nIn all of these situations, without an accurate household registration list it may be difficult for\nwomen to obtain or replace their own citizenship documentation at the required ages of 18,\n30 and 45, since a household registration list can be required for this process. This may also\nimpact children’s ability to obtain citizenship documentation because this process usually\nrelies on proving the citizenship of the child’s ancestors, as well as the provision of a household\nregistration list.\n\n\n\n<mark>22</mark>", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000092", "page": 27, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household registration list", "probe_tag": "confusion", "probe_score": 0.7139204144477844, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 484, "end": 511, "key": "reliefweb:000092:27:1:1", "source": "camp2", "luna_reason": "Names an administrative registry without showing its data used for analysis or targeting.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "|Asylum Levels and Trends in Industrialized Countries, 2008|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|Col13|Col14|Col15|Col16|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|**Table 5. Applications submitted by country of asylum and origin, 2007**<br>Covering the 44 countries which provided monthly data to UNHCR (exception: data for Italy is based on annual data).<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 5. Applications submitted by country of asylum and origin, 2007**<br>Covering the 44 countries which provided monthly data to UNHCR (exception: data for Italy is based on annual data).<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 5. Applications submitted by country of asylum and origin, 2007**<br>Covering the 44 countries which provided monthly data to UNHCR (exception: data for Italy is based on annual data).<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 5. Applications submitted by country of asylum and origin, 2007**<br>Covering the 44 countries which provided monthly data to UNHCR (exception: data for Italy", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.4426555633544922, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 328, "end": 340, "key": "reliefweb:000427:17:0:0", "source": "camp2", "luna_reason": "Generic data phrase embedded in a table header and coverage description.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.33951205015182495, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 328, "end": 340, "key": "reliefweb:000427:17:0:2", "source": "camp2", "luna_reason": "Generic data phrase appears within a table caption and coverage description.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "Amid a learning crisis,\nglimmers of success…\n\n\nFor the first time in UNHCR’s education report, we are\npresenting data on national academic assessments to\nbetter understand how refugee students are faring as\nlearners. This is vital to measure since many countries\nare undergoing a learning crisis: more than half of\nchildren in low and middle-income countries are unable\nto read and understand a simple story by the end of\nprimary school, with the level as high as 80 per cent in\nlow-income countries. <sup>9</sup>\n\n\nLearning inequality disproportionately affects the most\nvulnerable – a problem that was exacerbated when the\nCOVID-19 pandemic forced schools across the world to\nshut. Because 83 per cent of refugees and Venezuelans\ndisplaced abroad are hosted in low and middle-income\ncountries, <sup>10</sup> the potential consequences of this inequality\nare clear.\n\n\nHowever, going by the measure of exam results,\nrefugee students can point to a record of success. In 23\ncountries that reported results, 74 per cent of primarylevel refugee students passed national tests, while the\nfigures for lower and upper secondary were 65 and 63\nper cent respectively.\n\n\n9 The State of Global Learning Poverty: 2022 Update – World\nBank.\n\n10 Global Trends: Forced Displacement in 2021 - UNHCR.\n\n\n8 **ALL INCLUSIVE** | The campaign for refugee education\n\n\n\nOf course, the numbers of refugees taking national tests\nis often very low – in Cameroon, for example, a pass\nrate of 74 per cent at lower secondary level is based on\nonly 154 refugee students sitting the exams. But it does\nreinforce the point that where they get the opportunity,\nrefugee students grasp it with both hands.\n\n\nWhen it comes to taking exams, however, there is\na clear gender imbalance: at primary level, of those\nrefugee students who sat national tests in our reporting\ncountries, only 39 per cent were girls. For lower and\nupper secondary level exams, the figures", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001255", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on national academic assessments", "probe_tag": "confusion", "probe_score": 0.8011259436607361, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 113, "end": 150, "key": "reliefweb:001255:7:0:0", "source": "camp2", "luna_reason": "Assessment data supports reported refugee student exam results and learning analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "## **LIMITATIONS**\n\nWidespread insecurity severely impacted data collection and\ninterrupted humanitarian activities in the field. Protection\ncomponents related to human rights and protection monitoring were\nparticularly impacted throughout Q3, with disruptions and capacity\ngaps further worsening in the second half of August and into\nSeptember, following the Taliban's takeover.\n\n\n_Protection Monitoring in Trinikot City, Urozgan Province (©UNHCR)_\n\nLimitations and considerations regarding Q3 data include:\n\n\n - Many partners including those involved with protection\nmonitoring, opted to diversify or change **the modalities of data**\n**collection** as the context changed. In remote locations instead\nof in-person interviews, monitoring activities took place by\nphone. Community-based protection monitoring was impacted\nby the restrictions to work placed on female staff and remote\nwork arrangements did not enable sufficient space and privacy\nto guarantee full protection of female beneficiaries.\n\n\n\n\n- **Serious concerns exist about data protection**, especially on\nGBV. Recording and storage of GBV data was put on hold until\nits collection could be done in a safe manner in accordance\nwith GBViE Minimum Standards for data protection.\n\n- Direct **data on GBV is limited** by the risks of asking and\nreporting on questions that may lead to disclosures that can be\nretraumatizing and be especially harmful in areas where there\nis no response service. As such, there is limited data on the\nperpetrators of threats against women and girls.\n\n- The **lack of availability of cash and the closure of banks**\nimpacted protection monitoring activities, which are staffintensive, and challenged the collection of data at provincial\nlevels.\n\n- The range of security challenges and operational constraints\nincluding **movement restrictions** imposed by the Taliban\nadministration impeded the capacity of protection partners to\ncollect high quality data and to deliver humanitarian\nassistance.\n\n- UNAMA experienced increasing difficulty in maintaining its\n**verification standards for civilian casualties**, due", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001240", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "GBV data", "probe_tag": "confusion", "probe_score": 0.3471273183822632, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1101, "end": 1109, "key": "reliefweb:001240:2:0:1", "source": "camp2", "luna_reason": "GBV data collection was paused pending safe future collection.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "**a.** Actions and policies need to be grounded in\nthorough knowledge and understanding of land and\nproperty dynamics prevalent in areas of planned\nrelocation. For example, multiple forms of land and\nproperty frameworks (traditional/customary, collective and individual, private and social, formal and\ninformal, local versus national, etc.) may co-exist;\nthere may be a disconnect between the formal State\nland tenure laws and the way land and property\nrelations are actually managed on the ground; and\ninformal land tenure arrangements and/or existing\ncadastres and land title registries may not be reliable,\netc.;\n\n\n**b.** Macro-level policy setting needs to be accompanied by micro-level political engagement, since land\nand property relations are highly contextual and\noften highly politicized;\n\n\n**c.** The feasibility of action should be ascertained\nfrom the outset, with policies grounded in a realistic\nassessment of institutional capacities. <sup>58</sup>\n\n\n73. Among the multiple sources of potentially valuable guidance on land, housing, and property are:\nthe FAO Voluntary Guidelines on the Responsible\nGovernance of Tenure of Land, Fisheries, and Forests in the Context of National Food Insecurity, the\nUnited Nations Principles on Housing and Property\nRestitution for Refugees and Displaced Persons, and\nguidance on evictions. <sup>59</sup>\n\n\nCOMPENSATION AND RESTITUTION\n\n\n74. Experience from DIDR, in particular, indicates\nthat cash-based compensation schemes alone have\nrarely prevented impoverishment risks and impacts.\nIn-kind compensation, however, entails less risk\nand such compensation remains one indispensable\nmeans of making reparations for what has been lost.\nCertain forms of compensation schemes can fail relocated communities, thereby compounding vulnerability. For example, when compensation is provided\n\n\n\nin the form of ‘cash for land’, safeguards need to be\nput in place to avoid the sudden and concomitant\ninfusion of money into the market from pricing out\nrelocated communities. Compensation", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000184", "page": 23, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "cadastres", "probe_tag": "confusion", "probe_score": 0.6240593194961548, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 553, "end": 562, "key": "reliefweb:000184:23:0:0", "source": "camp2", "luna_reason": "Names cadastral records without showing their data informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "vague"}, {"text": "land title registries", "probe_tag": "confusion", "probe_score": 0.10017847269773483, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 567, "end": 588, "key": "reliefweb:000184:23:0:1", "source": "camp2", "luna_reason": "Registry is mentioned only as potentially unreliable, without showing data use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": " countries studied in OECD\ncountries plus Brazil in the respective years.\n\n\nThere is further undercoverage with respect to data\non family permits: the data obtained for some host\ncountries exclude permits for family reunification\nwith a person under international protection (Japan,\nMexico) or under subsidiary international protection\n(Switzerland), whereas the data for Ireland exclude\nchildren below the age of 16 and the data for Canada\nexclude family members who reunified with persons\nissued with non-humanitarian permits.\n\n\n# 5 Analysis of admission trends\n\n\n\nOver the 2010–2019 period, a combined total of\nfour million new asylum applications were submitted\nin OECD countries and Brazil by nationals of\nAfghanistan, Eritrea, Iran, Iraq, Somalia, Syria and\nVenezuela. In the same period, close to 1.5 million\nfirst-time residence permits were granted by OECD\ncountries and Brazil to nationals of the seven\ncountries for family, work, or education-related\n\n\n\nreasons, including about 156,000 in 2019 alone.\nDuring the decade, about 2.2 million individuals\nof the same nationalities were recognized as\nrefugees or granted a subsidiary form of protection\nand 572,000 persons from the seven populations\nconcerned arrived in OECD countries and Brazil\nthrough resettlement programmes.\n\n\n\n<u>14</u>", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001237", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data for Canada", "probe_tag": "confusion", "probe_score": 0.302289217710495, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 425, "end": 440, "key": "reliefweb:001237:12:1:1", "source": "camp2", "luna_reason": "Existing Canadian data support a concrete coverage-exclusion finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "Refugee women founded the Heriyetu Foundation at Nakivale settlement in Uganda – a group that has launched a wine-making business, pharmacy and savings and\nloans programme. © UNHCR/Esther Ruth Mbabazi\n\n\n~~X~~ **~~Inclusive Programming~~**\n\n\n\n\n\n\n\n**3** Core Action 1 of the AGD Policy is applicable to UNHCR primary data collection activities. It applies only to operational data, defined as data and information that\npertains to a crisis/situation, the persons affected by the crisis/situation, and the response to the crisis/situation.\n\n\n14", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000271", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "operational data", "probe_tag": "drop", "probe_score": 0.02806559018790722, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 362, "end": 378, "key": "reliefweb:000271:12:0:0", "source": "camp2", "luna_reason": "Defines a generic data category without showing existing data use.", "drop_reason": "system_registry", "specificity": "vague"}]}
-{"text": "**</sup>\n\n\n\nTable 3 **| High frequency surveys conducted** | 2020-2021\n\n\n\n\n\n\n\n\n\n|Country|FDP Rounds<br>available|Months|Defined Survey Population(s)|\n|---|---|---|---|\n|Bangladesh|2|Apr/May 2020<br>Oct/Dec 2020|Refugees: Cox’s Bazar camps<br>Host: Cox’s Bazar district residents|\n|Djibouti|1|Dec/Jan 2020/2021|Refugees: camps and urban non-camp<br>Host: national urban|\n|Ethiopia|2|Sep/Oct 2020<br>Oct/Nov 2020|Refugees: camps and urban non-camp<br>Host: national|\n|Iraq*|4|Monthly:<br>Oct 2020 – Jan 2021|IDPs (camps, non-camps): Kurdistan Region of Iraq, North<br>Returned IDPs (IDPs in location of return): Kurdistan<br>Region of Iraq, North<br>Host: non-displaced in Kurdistan Region of Iraq, North|\n|Yemen*|9|Monthly:<br>Apr – Dec 2020|IDPs: national<br>Host: non-displaced national|\n\n\nNot receiving JDC support:\n\n\n\n\n|Kenya|3|May/Jun 2020<br>Jul/Sep 2020<br>Oct/Nov 2020|Refugees: camps and urban non-camp<br>Host: national|\n|---|---|---|---|\n|Uganda|2|Oct/Nov 2020<br>Nov/Dec 2020|Refugees: in camps<br>Host: national|\n\n\n\n\n    - Surveys in Iraq and Yemen executed as partnership between World", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000757", "page": 59, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "High frequency surveys", "probe_tag": "drop", "probe_score": 0.04648377746343613, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 24, "end": 46, "key": "reliefweb:000757:59:1:0", "source": "camp2", "luna_reason": "Standalone table header naming survey category, not a data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "Surveys in Iraq and Yemen", "probe_tag": "confusion", "probe_score": 0.7173240780830383, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1035, "end": 1060, "key": "reliefweb:000757:59:1:1", "source": "camp2", "luna_reason": "The sentence states these surveys were executed, indicating data production.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "**UNHCR News**\n\n\nHQP100\nP.O. Box 2500\nCH-1211 Geneva 2\nTel +41 22 739 85 02\nFax +41 22 739 73 14\nwww.unhcr.org\n@RefugeesMedia\n\n\n# PRESS RELEASE\n\nand highly visible consequences of the world’s conflicts and the terrible suffering they\ncause has been dramatic growth in numbers of refugees seeking safety by undertaking\ndangerous sea journeys, including on the Mediterranean, in the Gulf of Aden and Red\nSea, and in Southeast Asia.\n\n\n**Half are Children**\n\n\nUNHCR’s Global Trends report shows that in 2014 alone 13.9 million became newly\ndisplaced – four times the number in 2010. Worldwide there were 19.5 million refugees\n(up from 16.7 million in 2013), 38.2 million were displaced inside their own countries (up\nfrom 33.3 million in 2013), and 1.8 million people were awaiting the outcome of claims\nfor asylum (against 1.2 million in 2013). Alarmingly, over half the world’s refugees are\nchildren.\n\n\n“With huge shortages of funding and wide gaps in the global regime for protecting\nvictims of war, people in need of compassion, aid and refuge are being abandoned,”\nsaid Guterres. “For an age of unprecedented mass displacement, we need an\nunprecedented humanitarian response and a renewed global commitment to tolerance\nand protection for people fleeing conflict and persecution.”\n\n\nSyria is the world’s biggest producer of both internally displaced people (7.6 million) and\nrefugees (3.88 million at the end of 2014). Afghanistan (2.59 million) and Somalia (1.1\nmillion) are the next biggest refugee source countries.\n\n\nEven amid such sharp growth in numbers, the global distribution of refugees remains\nheavily skewed away from wealthier nations and towards the less wealthy. Almost nine\nout of every 10 refugees (86 per cent) were in regions and countries considered\neconomically", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000905", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Global Trends report", "probe_tag": "keep", "probe_score": 0.9179668426513672, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 464, "end": 484, "key": "reliefweb:000905:1:0:0", "source": "camp2", "luna_reason": "UNHCR report is cited as showing displacement and refugee figures.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "Information Management as Coordination Support\n\n\n\n3RP 2017-18 reporting\n\n\n\nActivityInfo: an online Inter-Agency 3RP reporting platform\n\n\n\nTo support coordination, **an online**\n**platform is rolled-out to collect reports on the**\n**8 Sectors’ activities** carried out by about 80\npartners. Reporting on ActivityInfo enables each\npartner/user to:\n\n- Collect, Manage, analyse and geo-locate their\nown activities.\n\n- View and extract reports on all the activities of\nother agencies in the response.\n\n- Integrate their activities within the entire\nresponse.\n\n- Reinforce partnerships and reduce costs and\ntime on reporting.\nTo familiarize the partners with the tool, training\nsessions were provided to more than 500 staff of\nall agencies with users access to the databases.\n\nA time line for reporting is also agreed upon as shown below:\n\n\n\nA screen-shot of ActivityInfo, **www.activityinfo.org** while partners are\nentering achievement data on their activities:\n\n\n\n2017-18: Information flow/roles and responsibilities/timeframes for monthly reporting on ActivityInfo\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|\n|---|---|\n|||\n\n\n\n**irqerbim@unhcr.org**\n\n\n\n22", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001003", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "achievement data", "probe_tag": "confusion", "probe_score": 0.06988970190286636, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 920, "end": 936, "key": "reliefweb:001003:19:0:0", "source": "camp2", "luna_reason": "Data are being entered into a project reporting platform, not analyzed as existing evidence.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "_Source: Authors’ calculation of 2024 survey data._\n\n\n**Livelihood opportunities for the Shona community have improved significantly since gaining citizenship,**\n\n**particularly in terms of financial access and job prospects – as well as protection outcomes, such as reduction in**\n\n**harassment by law enforcement.** According to the survey data, over half of the Shona community reported that\n\ncitizenship has enhanced their access to banking and mobile wallet services, making it easier for them to save,\n\ninvest, and manage their finances. Increased job opportunities were cited by 47 percent of respondents, reflecting\n\nhow the ability to present formal identification has opened new avenues for employment and economic\n\nparticipation. Importantly, 46 percent of the Shona noted a reduction in harassment by law enforcement, which\n\nhad previously hindered their movement and limited their economic activities. This improvement has enabled more\n\nindividuals to seek employment and conduct business without fear of arbitrary detentions or fines.\n\n\n_Figure 6: Impacts on receiving citizenship on livelihood opportunities_\n\n\n_Source: Authors’ calculation of 2024 survey data._\n\n\n**[www.unhcr.org](http://www.unhcr.org/)** 8", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000886", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2024 survey data", "probe_tag": "confusion", "probe_score": 0.880567729473114, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 33, "end": 49, "key": "reliefweb:000886:7:0:0", "source": "camp2", "luna_reason": "2024 survey data underlies authors’ calculations and reported livelihood findings.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "survey data", "probe_tag": "keep", "probe_score": 0.9693896770477295, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 335, "end": 346, "key": "reliefweb:000886:7:0:1", "source": "camp2", "luna_reason": "Survey data supports reported percentages and concrete livelihood findings.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "identified. This poses a challenge from a financial viewpoint. As a consequence, this ends up\nbeing often neglected.\n\n\n➔ _Coordination between environmental and humanitarian actors_\n.\nThere is not too much exchange of information between the two communities. The workshop\noffered an opportunity to bring together humanitarians and environmentalists within the GIFMM\nto discuss how to strengthen this collaboration beyond the workshop itself.\n\nSome collaborations exist, for example, WWF has been working with Oxfam on issues of natural\nresource management and has had a great experience of partnership. WWF and WFP have also\nbeen collaborating in some parts of Colombia where there is geographical overlap of their\nactivities. This collaboration has focused on food security and climate change, and where WFP\nlack in environmental data and technical expertise, WWF and the MoE has helped to fill the gap.\n\nThe WWF representative suggested that it would be beneficial to create a national directory of\nlocations where all organizations are working, in order to encourage more partnerships across\nthe humanitarian, development and conservation communities.\n\n**Part 2: Environmental data in humanitarian contexts**\n\nThe second part of the workshop focused on environmental data use in humanitarian contexts,\nincluding a discussion on data sharing and geospatial data. The discussion followed a\npresentation of MapX and some results from participatory mapping exercises held with the\nChichituy indigenous community (see presentation in Annex B). The questions posed to\nparticipants included:\n\n## ➔ What are the types of environmental data your organization uses for operations? ➔ Which are the main sources of these data? Are these data accessible? ➔ Do you use remote sensing data from platforms such as MapX to overcome data\n\nlimitations?\n\nParticipants were interested in learning more about MapX and connections of spatial data to the\nNEAT+. To summarize the discussions specifically about MapX and NEAT+:\n\n\n➔ _Types of environmental data_\n\nType of environmental data used by some of the organizations attending the workshop include\ndata on climate, WASH,", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000102", "page": 54, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "national directory of\nlocations", "probe_tag": "confusion", "probe_score": 0.1630377471446991, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 979, "end": 1010, "key": "reliefweb:000102:54:0:0", "source": "camp2", "luna_reason": "Proposed directory creation; the data resource does not yet exist.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "Among the Somalis and Ethiopians who reach South Africa, an estimated fifty percent\ncontinue their journey onward to destinations beyond the African continent (IOM\n2009). The southward flow from the Horn of Africa, of course, is only part of the\npicture. Others head north, while many move east across the Gulf of Aden to Yemen.\nAvailable statistics from the Mixed Migration Task Force <sup>5</sup> [^5: The Mixed Migration Task Force (MMTF) was formed in 2007 to address the needs of migrants,\nrefugees and asylum seekers crossing the Gulf of Aden. The Task Force members include the Danish\nRefugee Council (DRC), Norwegian Refugee Council (NRC), IOM, UNHCHR, UNHCR, UNICEF\nand UNOCHA.] indicate that in 2008, more\nthan 50,000 people made the perilous voyage in smugglers‟ boats. At least 590\ndrowned and another 359 were reported missing along the different East Africa\nmigration routes.\n\n_The Great Lakes region_\n\nMixed movements from the Great Lakes region are to date poorly documented. The\ncycle of violence in the DRC since the mid-1990s has generated large numbers of\nrefugees and asylum seekers. Tanzania, Uganda, Rwanda and Burundi all host\nsizeable Congolese refugee populations (approximately 60,000 each in Tanzania,\nUganda and Rwanda, and over 20,000 in Burundi).\n\nAlthough the 2006 elections in the DRC, following the peace agreement that brought\nthe second Congolese war to an end, have brought relative stability to some areas of\nthe country, other regions continue to suffer from violence and displacement. Attacks\nby the Lord‟s Resistance Army in north-eastern DRC, complex conflicts related to\nidentity, ethnicity and nationality, as well as rising levels of sexual violence in the\nKivus, have exacerbated the humanitarian crisis in that country. There is a concern\nthat the lack of protection experienced by many Congolese citizens may be\nperpetuated and reinforced by a possible withdrawal of MONUSCO forces in 2011.\n\nSince the 1990s, there has been a considerable growth in the movement of people", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000802", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "statistics from the Mixed Migration Task Force", "probe_tag": "confusion", "probe_score": 0.8992757797241211, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 339, "end": 385, "key": "reliefweb:000802:9:0:0", "source": "camp2", "luna_reason": "Task Force statistics support the reported 2008 migration figures.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "Chapter 9\n\n\nThere are notable differences in the availability\nof detailed age- and sex-disaggregated data by\npopulation group and country of asylum. Detailed\ndemographic data is available for 79 per cent of\nrefugees, <sup>**140**</sup> but just 36 per cent of asylum-seekers.\n\n\nRegional variations in the availability of age- and\nsex-disaggregated demographic data are significant.\nThey range from 6 per cent in Southern Africa to\n68 per cent in Asia and the Pacific. Europe and\nthe Americas, which host about three-quarters\nof the global asylum-seeking population, provide\ndetailed demographics only for 51 and 11 per cent\nof their asylum-seeking population respectively.\nWhile some demographic data for asylum-seekers\nis available for many European countries, the data is\noften not directly interoperable with UNHCR’s due\nto inconsistent age cohorts. UNHCR’s age cohorts\nhave been designed to align, where possible, to UN\nconventions and to capture information to support\nthe monitoring of critical benchmarks in humanitarian\nprogramming. <sup>**141**</sup>\n\n\nNotable improvements in the demographic coverage\nin 2020 included data for Venezuelans displaced\nabroad, for whom the availability of age and sex\ndata soared from just one per cent in 2019 to 47 per\ncent in 2020, due to newly available official data in\nColombia. Continuing to improve the availability of\ndemographic data is a priority for UNHCR, which is\nexploring alternative data sources to estimate missing\ndata with statistical modelling (e.g. the regional\nmodelling presented in Chapter 2).\n\n**a. Sub-national coverage**\n\n\nRecording the locations of forcibly displaced and\nstateless populations is crucial to ensure effective\nhumanitarian responses within countries. In large\ncountries such as Syria and the Democratic Republic\nof the Congo, new displacement can be highly\nlocalized, sometimes within a specific region or city.\nUNHCR documents the locations of forcibly displaced\npopulations in its annual statistical reporting. In 2020,\nsome 102 of", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000757", "page": 67, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "demographic data", "probe_tag": "confusion", "probe_score": 0.3762858808040619, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 158, "end": 174, "key": "reliefweb:000757:67:0:0", "source": "camp2", "luna_reason": "Demographic data supports a concrete 79-percent availability finding.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "data for Venezuelans displaced\nabroad", "probe_tag": "confusion", "probe_score": 0.673909604549408, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1128, "end": 1165, "key": "reliefweb:000757:67:0:2", "source": "camp2", "luna_reason": "Data coverage finding for Venezuelans is quantified and attributed to official Colombian data.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " y en el marco del\ntrabajo interagencial con ONUSIDA, se desarrolló un\nfolleto informativo sobre acceso a la salud integral y\nprevención de VIH, enfocado en población extranjera\nen el país, el que fue ofrecido en unos exhibidores\nespecialmente diseñados, que cuentan en su costado\ncon información sobre los Espacios de Apoyo en Chile.\nPara garantizar la protección de grupos especialmente\nvulnerables, ACNUR cuenta con una alianza de trabajo\ncolaborativo con el Servicio Nacional de la Mujer y\nla Equidad de Género, que permite la derivación a la\nred especializada en temas de violencia basada en\ngénero (VBG), en todas las regiones, cuando un caso\nsea identificado por una agencia socia. Así, durante\n2021, 208 personas sobrevivientes de VBG recibieron\nservicios especializados en esta materia. En este\ncontexto, también se está elaborando un folleto sobre\nacceso a servicios para personas sobrevivientes de\nVBG.\n\n\nAsimismo, durante 2021 se realizaron 8 diagnósticos\nparticipativos, en formato híbrido, en los cuales\nparticiparon 80 personas, entre 14 a 65 años de edad.\nLos resultados de estos diagnósticos son un insumo\nclave para orientar la planificación del año entrante y\najustar las estrategias de trabajo. De los testimonios\n\n\n\n30 CAPÍTULO 4 / **PRINCIPALES ACTIVIDADES E INICIATIVAS DE ACNUR EN 2021**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001529", "page": 28, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "diagnósticos\nparticipativos", "probe_tag": "confusion", "probe_score": 0.13493096828460693, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 955, "end": 982, "key": "reliefweb:001529:28:1:0", "source": "camp2", "luna_reason": "Completed participatory assessments informed subsequent planning and strategy adjustments.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " such as reading glasses were\nhighlighted as the recurrent concerns linked to access to\nassistive devices.\n\n\nThe participants of the focus group discussion in Jordan\nand Lebanon highlighted the link between assistive\ndevices and access to education. One young Syrian boy\nin Jordan shared how he had waited for eye glasses.\nOnce received, he was able to start school. A girl who had\ninitially been waiting for medical boots had later been\nenrolled in school. A Syrian boy in Lebanon explained\nhow significant the impact that an electric wheelchair\ncan have on quality of life and ability to function\nindependently.\n\n\nAs highlighted by the key informants, the current\nchallenges and barriers to accessing devices include:\nlack of availability of specialised devices (prosthetics,\nmedical boots, white canes) in many countries; lack of\nfunding for specialised devices with higher costs, such as\nelectric wheelchairs. Additionally, there is currently no\nquantitative data available on specific types and numbers\nof devices required that can be used to inform annual\nprogram planning for. In Jordan, the closure of one of the\nNGO projects in Zaatari camp (not UNHCR funded) has\nleft a significant gap in the provision of hearing aids in\nthe camp.\n\n\nIn Turkey, there is potential for persons with disabilities\nto receive government funded devices. However, at the\ntime of the mapping, information about the number of\npersons with disabilities supported with devices was\nnot available. In Lebanon, Algeria, Morocco, Jordan and\n\n\n33", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001114", "page": 34, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "quantitative data", "probe_tag": "confusion", "probe_score": 0.7489809393882751, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 950, "end": 967, "key": "reliefweb:001114:34:1:0", "source": "camp2", "luna_reason": "States quantitative data is unavailable without analyzing a finding or substitute estimate.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": "/lawethiopia.com/index.php/volume-3/6747-proclamation-no-1263-2021-definition-of-powers-and-duties-of-the-executive-organs-proclamation)</u>\nWhile RRS has, in effect, maintained its traditional mandate, it does not yet have an established Regulation\ndetailing its powers, responsibilities and functions, including how it seeks to foster coordination. Having\na legally defined power, structure and accountability would assist RRS in clearly articulating and strengthening\nits protection mandate.\n\n\nThe refugee community governance structures have continued to function and provide refugee inputs\nand feedback to the Government in the prescribed period. However, the level of functionality of other\nassociations such as women’s associations, youth associations and religious leaders’ associations has\ncontinued to vary from area to area. These associations are registered by RRS but lack legal personality.\nThe <u>[Grievances and Appeals Handling Directive No 03/2019, which sets out grievance mechanisms relating](https://www.coursehero.com/file/77988168/Refugee-Draft-Directive-2pdf/)</u>\nto misconduct committed by RRS has not yet been functional.\n\n\nA national population census has not been conducted since 2007, although refugees have been included\nin administrative data collection. RRS has continued to provide refugee vital events data to the ICS and\nrefugee education data to the Ministry of Education (MoE). The steps taken at the sectoral level to include\nrefugees in education sector planning have been further strengthened. Refugee data have been included in\nthe Rapid Justice Sector Assessment that was conducted from July 2020-July 2021 at the national level by\nthe government Justice Sector Steering Committee commissioned by UN agencies (UN Women, UNODC,\nUNDP, UNICEF, and OHCHR).\n\n\n**2.4** **Access to", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001338", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "refugee vital events data", "probe_tag": "confusion", "probe_score": 0.08590587973594666, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1316, "end": 1341, "key": "reliefweb:001338:5:1:1", "source": "camp2", "luna_reason": "Existing refugee vital-events data are provided to ICS as an institutional data resource.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "refugee education data", "probe_tag": "confusion", "probe_score": 0.18185986578464508, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1357, "end": 1379, "key": "reliefweb:001338:5:1:2", "source": "camp2", "luna_reason": "Data are merely provided to the ministry, with no shown analytical or decision use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
+{"text": "# PROVINCES DE KWANGO, KWILU, MAÏ-NDOMBE\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Violations et abus de droits en décembre 2023|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Provinces**|**Droit à la**<br>**propriété**|**Droit à**<br>**l’intégrité**<br>**physique**|**VBG**|**_Total_**|**_% _**|\n|**Kwilu**|15|0|16|**_31_**|**_48_**|\n|**Maï-Ndombe**|12|13|9|**_34_**|**_52_**|\n|**TOTAL**|**27**|**13**|**25**|**_65_**|**_100_**|\n\n\n\n- Contrairement au mois de novembre avec 207 violations et abus de droits,\nce sont **65** violations et abus des droits de l’homme qui ont été\ndocumentées durant le mois de décembre <sup>**6**</sup> dans les provinces de Kwilu\n\n\n6 <u>Rapport mensuel de monitoring de protection Bandundu mois de décembre 2023 Kadima Foundation</u>\n<u>et UNHCR</u>\n\n\n\net Maï-Ndombe : 27 violations du droit à la", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001633", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Rapport mensuel de monitoring de protection", "probe_tag": "confusion", "probe_score": 0.8645585179328918, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 645, "end": 688, "key": "reliefweb:001633:11:1:0", "source": "camp2", "luna_reason": "Named monitoring report cited for documented human-rights violations.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " cycle permanent de vulnérabilité et de violence.\n\n\nA cela s’ajoute les effets du changement climatique (inondations et sècheresses), la réduction et/ou la dégradation des\nressources socio-économiques des ménages, la propagation des maladies et épidémies, ainsi qu’un accès limité aux moyens\nde subsistance (faible production agricole, détérioration des échanges), à l’eau potable et aux soins de santé primaires. D’après\nl’Indice de Risque Climatique pour les enfants publié par l’UNICEF en 2021, le Tchad est le 2ème pays au monde où les enfants\nsont les plus exposés aux risques des effets du changement climatique. Dans ce contexte, les femmes et filles sont de plus en\nplus exposées aux risques accrus de violences par leur partenaire ou sont contraintes d’adopter des mécanismes négatifs de\nsurvie.\n\n\nLa situation de protection au Tchad devient de plus en plus préoccupante, notamment en raison des incursions des groupes\narmés non étatiques (GANE) et des individus armés, ainsi que du faible accès des populations aux services essentiels. Selon les\ndonnées du Projet 21, un mécanisme interagence de monitoring de la perception des populations sur l’évolution de leur\nenvironnement et des risques de protection, 5 657 incidents individuels de violations graves des droits humains ont été\ncollectés entre janvier et octobre 2024. Bien que toutes les tranches d’âge soient touchées, la population active de 18", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000315", "page": 2, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Indice de Risque Climatique pour les enfants", "probe_tag": "confusion", "probe_score": 0.8789287209510803, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 424, "end": 468, "key": "reliefweb:000315:2:1:0", "source": "camp2", "luna_reason": "UNICEF's 2021 index supports Chad's ranking for children's climate-risk exposure.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "15%), child headed-HHs (11%), persons with disabilities\n(11%), elderly person headed-HHs (10%), single male headed-HHs\n(7%), persons with life-threatening health issues (7%) and\nunaccompanied and separated children (6%). The main reasons for\nbeing unable to access these services are being unable to pay for the\nservice (22%), lacking documentation (19%), facing\ndiscrimination/exclusion (15%), assistance not reaching people in\nneed (16%), and assistance not being what people need (14%).\n\nProtection monitoring data highlighted that women and girls face\nincreased barriers to accessing services, with their freedom of\nmovement being limited. This is further compounded by the low\n\n\n\nrates of women’s access to civil documentation, with 35% of FGDs\nstating that women and girls lack the Tazkera, compared to only 1%\nof FGDs stating the same for men. In Households Surveys, 22,8% of\nfemale respondents reported lacking documentation compared to\n9,9% of male respondents.\n\n**2.2.3** **Feeling of Safety**\nThe feeling of safety was impacted during this reporting period, with\na 10% decrease in the percentage of those that responded that they\nfeel safe (69% in Q3 compared to 79% in Q2). In Q3, 27% of\nrespondents stated that there was no change in their security\nsituation (30% decrease from Q2 and 36% decrease Q1), 37%\nmentioned that the security situation had worsened (7% increase\nfrom Q2 and 9% decrease Q1) and 36% mentioned that the security\nsituation had improved (23% increase from Q2 and 37% increase\nfrom Q1). The contributing factors indicated for the worsening\nsecurity situation data are increased conflict between government\nand anti-government", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001240", "page": 8, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Protection monitoring data", "probe_tag": "confusion", "probe_score": 0.8917604088783264, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 491, "end": 517, "key": "reliefweb:001240:8:1:0", "source": "camp2", "luna_reason": "Existing monitoring data supports concrete findings about barriers faced by women and girls.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "Households Surveys", "probe_tag": "keep", "probe_score": 0.9411242008209229, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 854, "end": 872, "key": "reliefweb:001240:8:1:3", "source": "camp2", "luna_reason": "Household survey findings report documentation gaps by respondent sex.", "usage_type": "evidential", "specificity": "vague"}, {"text": "security situation data", "probe_tag": "confusion", "probe_score": 0.49387645721435547, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1573, "end": 1596, "key": "reliefweb:001240:8:1:4", "source": "camp2", "luna_reason": "Data are used to identify contributing factors behind worsening security conditions.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "**Processing:** Removing irrelevant or inaccurate information, reformatting contents to\nbe interpretable by an analytic software, and otherwise validating the data collection.\n\n\n\n\n\n\n|Developing<br>Storage<br>Guidelines|To be useful, data collected from surveys and traditional data collection methods,<br>FRRM, and “Child Friendly Spaces” and from other MHPSS programmes/<br>interventions needs to be stored in a safe way for responsible data use and<br>reuse and to maintain confidentiality of personal/identifying information.<br>However, the RD4C team was not able to verify how data collected on MHPSS<br>was stored by UNICEF, UNHCR, partners and the Government of Uganda. Little<br>knowledge is available on whether there were backup systems, deletion<br>practices, or reviews of storage procedures.|\n|---|---|\n|**Building Robust**<br>**Security**|The RD4C team was not able to verify whether there were** policies or**<br>**procedures  in place to prevent unauthorized access, data breaches, data loss,**<br>**and data misuse.** Interviews with key stakeholders did not reveal any specialized<br>training on data handling and data security.|\n|**Establishing**<br>**Internal Access**<br>**& Security**<br>**Protocols**|The RD4C team was not able to verify whether there were**particular restrictions**<br>**regarding data access**—including tiered access to raw data, password protocols,<br>secure server rooms, change history and audit trails, and internal processing<br>safeguards.|\n|**Categorizing**<", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000499", "page": 29, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data collected on MHPSS", "probe_tag": "confusion", "probe_score": 0.12517386674880981, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 582, "end": 605, "key": "reliefweb:000499:29:0:0", "source": "camp2", "luna_reason": "Data storage could not be verified; no analyzed finding or substantive use is shown.", "drop_reason": "availability", "specificity": "descriptive"}]}
+{"text": "|GOAL 2: Ensure that alternatives to detention are available in law and implemented in practice|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|Col13|Col14|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|2013 detention baseline – UNHCR Global Strategy<br>– Beyond Detention 2014-2019|2013 detention baseline – UNHCR Global Strategy<br>– Beyond Detention 2014-2019|Canada|Hungary|Indonesia|Israel|Lithuania|Malaysia|Malta|Mexico|Thailand|United Kingdom|United States|Zambia|\n|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to immigration detention.|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to immigration detention.|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to immigration detention.|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to immigration detention.|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to immigration detention.|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to immigration detention.|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to immigration detention.|**SUB-GOAL 1:** \u0007Legal and policy frameworks include alternative(s) to", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000853", "page": 37, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2013 detention baseline", "probe_tag": "confusion", "probe_score": 0.8480205535888672, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 249, "key": "reliefweb:000853:37:0:0", "source": "camp2", "luna_reason": "Standalone table header naming a baseline column, not an independently used data source.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
+{"text": "Darwanaji and Teferi Ber) received theoretically 37% and 12% of all returnees during\nthe period under consideration, but in real terms they received only 27% and 5%.\n\nConversely, Hargeisa and Gabiley received \"officially\" 41% and 9% of the returnees\nwhile \"actually\" the percentages were 55% and 13%. We should however still bear in\nmind that the greatest impact of all was during the spontaneous or self-repatriation\nphase. These differences were not caused - as commonly assumed during the period\nunder consideration (1997-99) - by an \"urbanisation\" of refugees in the camps, i.e.\nrefugees of rural or pastoral origin who got used to easy access to social services in\nthe camps and perceive greater job opportunities in urban areas and as a result decide\nnot to repatriate to their ancestral areas in the bush.\n\nTo be sure, we cannot exclude that this phenomenon played some role in this period\nand maybe a greater role subsequently in other camps, such as the Aware camps <sup>21</sup> [^21: Refugees in the Aware camps (Camaboker, Rabasso and Daror) mainly originate from Burao and the\nrural areas between Burao and Hargeisa, such as Salahley and Odweyne However there was also a\nsubstantial minority from Hargeisa. Repatriation from these camps started only after the period under\nconsideration.] .\nBut the view commonly held by many members of the international community and\nmany \"Hargeisawis\" (Hargeisa dwellers) that this people were illegitimately returning\nto Hargeisa instead of the countryside was not supported by evidence.\n\nFirst we can recall how a 1994 survey conducted in the camps by a Somali\nanthropologist graduated from the LSE concluded that \"many urban poor remain in\nHartasheikh…\" <sup>22</sup> [^22: \"Going Back Home\", _op. cit._, see above for the full quote.] . Second, an unpublished \"Social Assessment of Somali Returnees\nin Awadal and Waqooyi Galbeed Regions of NW Somalia\" conducted in 1998 on", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000627", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "1994 survey conducted in the camps", "probe_tag": "keep", "probe_score": 0.942302942276001, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1565, "end": 1599, "key": "reliefweb:000627:24:0:0", "source": "camp2", "luna_reason": "Past survey provides a concrete finding about urban poor in Hartasheikh.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "Social Assessment of Somali Returnees", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1814, "end": 1851, "key": "reliefweb:000627:24:0:1", "source": "camp2", "luna_reason": "Named 1998 assessment cited as evidence about Somali returnees.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "DTM Mali – Avril 2021\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Régions-Cercles<br>-Communes|Enfant ( < 18 ans )|Col3|Col4|Col5|Adulte (18 - 59 ans )|Col7|Col8|Personne âgée ( > 59 ans )|Col10|Col11|Total<br>Femme|Total<br>Homme|Total<br>Individus|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|**Régions-Cercles**<br>**-Communes**<br>|**Ménages**|**F **|**M **|**Total**<br>**Enfant**|**F **|**M **|**Total**<br>**Adulte**|**F **|**M **|**Total**<br>**Personne**<br>**âgée**|**Total**<br>**Personne**<br>**âgée**|**Total**<br>**Personne**<br>**âgée**|**Total**<br>**Personne**<br>**âgée**|\n|**TOMBOUCTOU**|**2250**|**3485**|**3473", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001352", "page": 50, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "DTM Mali – Avril 2021", "probe_tag": "confusion", "probe_score": 0.22621795535087585, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 0, "end": 21, "key": "reliefweb:001352:50:0:0", "source": "camp2", "luna_reason": "Standalone table title introducing tabulated DTM figures", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": " of Refugees.\n\nThe IASC typology can be considered a work in progress. There are other effects of\nclimate change not explicitly dealt with, such as increases in certain diseases and\nepidemics. Some of these effects are related to the ―natural‖ disasters while others can\nperhaps be considered either sudden-onset or slow-onset disasters in themselves. <sup>13</sup>\n\nThere are many other complex links that also need consideration: disasters and\ndegradation can trigger displacement and conflicts, and conflicts and displacement, in\nturn, often cause further environmental degradation.\n\nWe could also add another category to the IASC typology, namely displacement linked to\nmeasures to mitigate or adapt to climate change. For example, biofuel projects and forest\nconservation could lead to displacement if not carried out with full respect for the rights\nof indigenous and local people. <sup>14</sup> [^14: See for example _Resisting Displacement by Combatants and Developers: Humanitarian_\n_Zones in North-West Colombia,_ Geneva: Internal Displacement Monitoring Centre, 2007.]\n\n9 Gleditsch, N P, 2003. Environmental Conflict: Neomalthusians vs. Cornucopians, in _Security and the_\n_Environment in the Mediterranean: Conceptualising Security and Environmental Conflicts_, Berlin:\nSpringer.\n10 Homer-Dixon, T, 1994. Environmental scarcities and violent conflict: evidence from cases. International\nSecurity 19(1): 5-40.\n11 Gleditsch, N P, 1998. Armed Conflict and the Environment: A Critique of the Literature. Journal of\nPeace Research 35(3): 381–400.\n12 German Advisory Council on Global Change, 2007. _Climate Change as a Security Risk_, available at:\n<u>[http://www.wbgu.de/wbgu_jg2007_engl.html](http://www.wbgu.de/wbgu_jg2007_engl.html)</u>\n<u>[13 See for example the Emergency Events Database categories at www.em-dat.be]", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000711", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Emergency Events Database", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1775, "end": 1800, "key": "reliefweb:000711:4:1:0", "source": "camp2", "luna_reason": "Named database cited as source for disaster-category classification.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " persecution were the mostoften reported threats towards women, albeit in a relatively low proportion (2%), whereas for\nchildren the perception of the threat of violence in the community was reported as a risk for\nboys (2%) and girls (3%), alike. Gaps in terms of access to extracurricular activities to children\n\n\n1 UNHCR - Operational data portal, Ukraine refugee situation. Available <u>[online.](https://data.unhcr.org/en/situations/ukraine)</u>\n2 UNHCR - Operational data portal, Ukraine refugee situation. Available <u>[online.](https://data.unhcr.org/en/country/mda)</u>\n3 REACH Area Monitor. Available upon request.", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001671", "page": 3, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "UNHCR - Operational data portal", "probe_tag": "confusion", "probe_score": 0.8981485962867737, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 317, "end": 348, "key": "reliefweb:001671:3:2:0", "source": "camp2", "luna_reason": "Source line identifies UNHCR portal underlying the reported refugee-risk findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "REACH Area Monitor", "probe_tag": "keep", "probe_score": 0.9065302014350891, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 580, "end": 598, "key": "reliefweb:001671:3:2:1", "source": "camp2", "luna_reason": "Named monitoring report cited as the source for reported protection-risk findings.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "-from-)\n<u>south-sudan-1431344971. MSF, “MSF calls on warring parties to respect medical facilities in South Sudan as the</u>\n[humanitarian organization is forced to evacuate staff again”, 9 May 2015, www.msf.org/article/south-sudan-msf-calls-](http://www.msf.org/article/south-sudan-msf-calls-)\n<u>warring-parties-respect-medical-facilities-south-sudan-humanitarian.</u>\n51 UN News Centre _,_ “South Sudan: heavy fighting and reported ‘atrocities’ in northeast force UN to evacuate staff”, 11 May\n[2015, www.un.org/apps/news/story.asp?NewsID=50818#.VZ6VSRawRUY.](http://www.un.org/apps/news/story.asp?NewsID=50818#.VZ6VSRawRUY.)\n52 OCHA, _South Sudan Humanitarian Bulletin: Biweekly Update 30 June 2015_ [, http://reliefweb.int/report/south-](http://reliefweb.int/report/south-)\n<u>sudan/south-sudan-humanitarian-bulletin-biweekly-update-30-june-2015.</u>\n53 South Sudan NGO Forum, _Access survey summary findings_, 20 June 2015. The survey took place between 5 and 13 June.\n81 NGOs (61 INGOs and 20 NNGOs) responded. It did not include UN agencies funds and programmes.\n54 The May and June 2015 Access Snapshots had not been finalized at the time of writing this report.\n\n\n17", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000585", "page": 23, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "May and June 2015 Access Snapshots", "probe_tag": "confusion", "probe_score": 0.8839083313941956, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1079, "end": 1113, "key": "reliefweb:000585:23:2:0", "source": "camp2", "luna_reason": "States snapshots were unfinished, without using findings or data.", "drop_reason": "availability", "specificity": "named"}]}
+{"text": "|-|101,760|97,012|-|-|-|3,790|-|-|202,562|\n|Cayman Islands|36|-|36|13|-|-|-|-|-|52|101|\n|<br>Central African Rep.|7,175|-|7,175|311|46,523|669,906|90,672|-|-|-|814,587|\n|<br>Chad|442,672|-|442,672|3,759|308|170,278|-|-|122,359|-|739,376|\n|Chile|2,053|-|2,053|8,545|-|-|-|-|2,073|452,712|465,383|\n|China, Hong Kong SAR|130|-|130|-|-|-|-|-|-|-|130|\n\n\n72 UNHCR > **GLOBAL TRENDS 2019**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001657", "page": 71, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "GLOBAL TRENDS 2019", "probe_tag": "drop", "probe_score": 0.022953441366553307, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 362, "end": 380, "key": "reliefweb:001657:71:5:0", "source": "camp2", "luna_reason": "Standalone report/table heading, not a cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": "Venezuelans in Chile, Colombia, Ecuador and\n\nPeru – A Development Opportunity\n\n\n8\n\n\n**CPP** Carnet de Permiso Temporal de Permanencia (Temporary Stay Permit)\n\n\n**DTM** Displacement Tracking Matrix\n\n\n**ENAHO** Encuesta Nacional de Hogares (National Household Survey on Living Conditions and Poverty)\n\n\n**ENPOVE** Encuesta Dirigida a la Población Venezolana que reside en el País (Survey Targeted at the Venezuelan Population Residing in Peru)\n\n\n**EPEC** Encuesta a Personas en Movilidad Humana y en Comunidades Receptoras en Ecuador (Human Mobility and Host Communities Survey)\n\n\n**EPTV** Estatuto Temporal de Protección para Migrantes Venezolanos (Temporary Protection Statute for Venezuelan Migrants)\n\n\n**FAO** Food and Agricultural Organization\n\n\n**GDP** Gross Domestic Product\n\n\n**GEIH** Gran Encuesta Integrada de Hogares (Great Integrated Household Survey)\n\n\n**HFPS** High-Frequency Phone Survey(s)\n\n\n**ILO** International Labor Organization\n\n\n**IMF** International Monetary Fund\n\n\n**INEI** Instituto Nacional de Estadística e Informática (National Institute of Statistics and Information)\n\n\n**IPE** Identificador Provisorio Escolar\n\n\n**IOM** International Organization for Migration\n\n\n**LAC** Latin American and the Caribbean\n\n\n**PEP** Permiso Especial de Permanencia (Special Permit of Permanence)\n\n\n**PPT** Permiso por Protección Temporal (Temporary Protection Status)\n\n\n**R4V** Interagency Coordination Platform for Refugees and Migrants from Venezuela\n\n\n**SERMIG** Servicio Nacional de Migraciones de Chile\n\n\n**UN** United Nations\n\n\n**UNDP** United Nations Development Programme\n\n\n*", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001190", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Human Mobility and Host Communities Survey", "probe_tag": "confusion", "probe_score": 0.3090361952781677, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 533, "end": 575, "key": "reliefweb:001190:7:0:3", "source": "camp2", "luna_reason": "Glossary definition names a survey without showing data use or findings.", "drop_reason": "bare_stat", "specificity": "descriptive"}, {"text": "High-Frequency Phone Survey", "probe_tag": "drop", "probe_score": 0.018633948639035225, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 873, "end": 900, "key": "reliefweb:001190:7:0:6", "source": "camp2", "luna_reason": "Glossary expansion only; no survey data are cited or used.", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
+{"text": "br>2<br>138,586<br>622<br>13,352<br>1<br>211<br>38,323<br>24,107<br>5,488<br>35<br>10<br>1,240<br>802<br>720,307<br>2<br>2,132<br>40|\n\n\n\n70 UNHCR > **GLOBAL TRENDS 2018**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000649", "page": 68, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "GLOBAL TRENDS 2018", "probe_tag": "drop", "probe_score": 0.04940848797559738, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 150, "end": 168, "key": "reliefweb:000649:68:3:0", "source": "camp2", "luna_reason": "Standalone report title without shown data use", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": " <sup>18</sup> compared to Brazilian cohort and the relative\nprobability of registered Venezuelans to be _Bolsa_ _Familia_ (PBF) <sup>19</sup> beneficiaries compared to their\nBrazilian counterpart.\n\n\n\n_Rc_ = <sup>_<u>V enezuelansCadastroUnico/V enezuelansP opulation</u>_</sup>\n\n_BraziliansCadastroUnico/BraziliansP opulation_\n\n\n_Rp_ = <sup>_<u>V enezuelansP BF /V enezuelansCadastroUnico</u>_</sup>\n\n_BraziliansP BF /BraziliansCadastroUnico_\n\n\n\n(3)\n\n\n(4)\n\n\n\nThis relative probability index has an easy interpretation. A _Ri_ of 0.5 means that Venezuelans are\nhalf as likely as Brazilian to be found in sector _i_ . Abramitzky et al. (2020), Carneiro et al. (2020)\nand Fryer and Levitt (2004) point out that the relative probability index is sensitive to outliers and\nadvocates the use of F-Index, which is a monotonic transformation of the relative probability index.\nThe _F_ _−_ _Index_ is measured by the following expression:\n\n_<u>Ri</u>_\n_Fi_ = 100 _⇤_ 1 + _Ri_ (5)\n\n\nwhere _i_ can be _e_, _f_, _c_ and _p_ . This paper reports the F-Index in the main body of the paper. The\nrelative probability index is reported in the appendix. The _F_ _−_ _Index_ runs from 0 to 100, with\nhigher number signalling more integration. A F-index of 0 means that Venezuelans are not present\nat all", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000075", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "V enezuelansCadastroUnico", "probe_tag": "drop", "probe_score": 0.034728724509477615, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 217, "end": 242, "key": "reliefweb:000075:12:1:0", "source": "camp2", "luna_reason": "Formula variable fragment names no eligible data resource.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": "Improving Data Collection and Analysis\n\n#### IMPROVING DATA COLLECTION AND ANALYSIS\n\n\nData collection and analysis is the backbone of results-based SGBV programming. It is critical to\nthe effectiveness of targeted service delivery, advocacy, policy development, and accountability\nand monitoring. Survivors are often afraid of being stigmatized, thus, actual prevalence figures\nare hard to identify. Efforts in **Syria** are currently underway to generate service provision data\nto better analyse SGBV trends and patterns through needs assessments, feedback from health\nand psycho-social service providers, and reports from mobile teams. UNHCR supported the\ngovernment of **Turkey** in conducting a survey which identified early marriages, polygamous\nmarriages and domestic violence as leading problems affecting Syrian refugees. Data and\nfeedback collected from Participatory Assessments in **Yemen** inform UNHCR’s SGBV programmes.\nUNHCR authored a report, entitled “Women Alone”, on Syrian refugee women who are heads of\nhousehold in **Jordan**, **Lebanon**, and **Egypt** focusing on the issues of housing, food, health, work\nand financial security, changed roles, isolation, and sexual and gender-based violence.\n\n\nGBV Information Management System\n\n\nUNHCR has supported the rollout of the Gender-Based Violence Information Management\nSystem (GBVIMS) to ensure the safe, ethical, and confidential collection, management and\nsharing of SGBV data in various operations. GBVIMS is a data management system that enables\nservice providers working with SGBV survivors to collect, store, analyze, and share data related\nto reported incidents of SGBV in a safe and confidential manner. GBVIMS is designed to allow\nfor the aggregation of non-identifiable (anonymized) data on reported SGBV cases to inform\nprevention and response programming, policy development and advocacy, resource mobilization,\nmonitoring and evaluation. It also helps to identify gaps in follow up and service delivery. As part\nof UNHCR’s", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000871", "page": 37, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "service provision data", "probe_tag": "confusion", "probe_score": 0.40322571992874146, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 456, "end": 478, "key": "reliefweb:000871:37:0:0", "source": "camp2", "luna_reason": "The sentence states efforts are underway to generate this data.", "drop_reason": "production", "specificity": "vague"}, {"text": "SGBV data", "probe_tag": "drop", "probe_score": 0.03549296408891678, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1440, "end": 1449, "key": "reliefweb:000871:37:0:2", "source": "camp2", "luna_reason": "Data collection is described, not use of an existing dataset.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "**ARRA** Agency for Refugee and Returnee\n\nAffairs\n**CRRF** Comprehensive Refugee Response\n\nFramework\n**CTE** College of Teacher Education\n**DEED** Digital Education Enrolment Data\n**DFID** Department for International\n\nDevelopment of UK Government\n**ECCE** Early Childhood Care and Education\n**ECW** Education Cannot Wait\n**<mark>ESDP</mark>** <mark>Education Sector Development Plan</mark>\n**ETWG** Education Technical Working Group\n**GCR** Global Compact on Refugees.\n**GEQIP-E** General Education Quality\n\nImprovement Programme for Equity\n**GER** Gross Enrolment Rate\n\n**GPE** Global Ppartnership for Education\n**GPI** Gender Parity Index\n**GRF** Global Refugee Forum\n**ICT** Information Communication\nTechnology\n**<mark>IDP</mark>** <mark>Internally Displaced Person</mark>\n**IGAD** Intergovernmental Authority on\n\nDevelopment\n\n\n\n**KPI** Key Performance Indicator\n**MoE** Ministry of Education.\n**MoS** HE Ministry of Science and Higher\n\nEducation.\n**MoU** Memorandum of Understanding\n\n\n**NGO** Non- Governmental Organization\n**OOS** Out-of-School\n**REB** Regional Education Bureau\n**SDG** Sustainable Development Goal.\n**TVET** Technical and Vocational Education\n\nand Training\n**UASC** Unaccompanied and Separated\n\nChildren\n**UNESCO** United Nations Educational,\n\nScience and Cultural Organization\n**UNICEF** United Nations Children’s Fund\n**UNSDCF** United Nations Sustainable\n\nDevelopment Cooperation\nFramework\n**USAID** United States Agency for\nInternational Development\n**WASH** Water, Sanitation and Hygiene\n\n\n2", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000503", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Digital Education Enrolment Data", "probe_tag": "drop", "probe_score": 0.012906559742987156, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 147, "end": 179, "key": "reliefweb:000503:1:0:0", "source": "camp2", "luna_reason": "Glossary definition only; no data use, analysis, finding, or cited figures.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": " colombianos que residen en Ecuador, la\n\nRepública Bolivariana de Venezuela, Costa Rica y Panamá, a quienes se\nconsidera que están en una situación similar a la de los refugiados.\n\n\n**(11)** Alrededor de 13.300 congoleños que llegaron a Uganda fueron\n\nconsiderados refugiados prima facie, mientras que 13.700 presentaron una\nsolicitud individual de asilo. Los que llegaron a Burundi y Kenia pasaron por\nla determinación individual de la condición de refugiado.\n\n\n\n<mark>TABLA 1</mark> **Poblaciones de refugiados por regiones de ACNUR \u0003|** 2014\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Regiones de ACNUR<br>- África Central y Grandes Lagos<br>- Este y Cuerno de África<br>- África del Sur<br>- África Occidental|Principio-2014|Col3|Col4|Final -2014|Col6|Col7|Variación (total)|Col9|\n|---|---|---|---|---|---|---|---|---|\n|Regiones de ACNUR<br>- África Central y Grandes Lagos<br>- Este y Cuerno de África<br>- África del Sur<br>- África Occidental|Refugiados<br> 508.600<br> 2.003.400<br> 134.500<br> 242.300|Personas en<br>situación<br>similar a<br>la de los<br>refugiados<br> 7.400<br> 35", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000206", "page": 9, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Poblaciones de refugiados por regiones de ACNUR", "probe_tag": "drop", "probe_score": 0.04190222918987274, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 487, "end": 534, "key": "reliefweb:000206:9:3:0", "source": "camp2", "luna_reason": "Table title introducing refugee population data, not an independently usable data mention.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
+{"text": "##### **4. Objectives of the Gender Analysis**\n\nThe specific objectives of the gender analysis were to:\n\n1. Analyze refugee population demographics.\n2. Assess refugee community practices and cultural patterns for household and care arrangements.\n3. Identify the concerns and needs of women, girls, boys and men in relation to shelter.\n4. Establish what needs to be considered in the provision of Shelter services.\n\n##### **5. Methodology**\n\n\nAlthough both quantitative and qualitative methods were used to answer the gender analysis questions,\nthe study was designed to be more qualitative <sup>1</sup> than quantitative to allow for respondents (from the openended nature of the qualitative inquiry) to describe their shelter related needs, experiences, challenges,\nbehaviors, cultural practices, etc., for better understanding of their gender specific needs. Data was\ncollected using different methods including desk review (extracting both quantitative and qualitative\ninformation); key informant interviews (KIIs) during the regular monthly shelter working group meetings\nand focus group discussions (FGDs) were conducted at Zaatari and Azraq camps on the 23rd and 26th\nof October 2016 in coordination with the M&E team in NRC.\n\n##### **5.1 Data Analysis**\n\n\nQualitative data from KIIs and FGDs was categorized at gender analysis objective level with analysis of\ntrends in each objective - by grouping similar responses on each gender dimension.\nQuantitative methods were used to analyze the data with tabulations and frequencies to supplement the\nqualitative data. Triangulation of these methods was used to confirm validity of data and reliability was\nensured through use of standard data collection tools.\n\n##### **5.2 Constraints and Challenges of the Gender Analysis**\n\nThe analysis was conducted taking in consideration the impact of the changing context of the ongoing\nSyrian Crisis. Under these circumstances, the lack of", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000927", "page": 8, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Qualitative data", "probe_tag": "confusion", "probe_score": 0.09196177870035172, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1263, "end": 1279, "key": "reliefweb:000927:8:0:0", "source": "camp2", "luna_reason": "Existing qualitative interview and focus-group data were analyzed for gender-related trends.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "qualitative data", "probe_tag": "drop", "probe_score": 0.023073051124811172, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1552, "end": 1568, "key": "reliefweb:000927:8:0:1", "source": "camp2", "luna_reason": "Qualitative data is explicitly analyzed using tabulations and frequencies.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": "................................................................... 32**\n\n\n**Population Data Analysis** Mid-Year Review Regional Bureau for Southern Africa | June 2024", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001265", "page": 2, "chunk": 7, "split": "holdout_annotate", "spans": [{"text": "Population Data", "probe_tag": "drop", "probe_score": 0.00545911630615592, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 77, "end": 92, "key": "reliefweb:001265:2:7:0", "source": "camp2", "luna_reason": "Generic title phrase with no cited data use, finding, or source.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": "|ANNEXE: Liste des incidents|Col2|Col3|Col4|Col5|\n|---|---|---|---|---|\n|N <br>Localités<br>Descripton de l’incident<br>Personnes affectées par l’incident<br>Actons entreprises et/ou<br>préconisées|N <br>Localités<br>Descripton de l’incident<br>Personnes affectées par l’incident<br>Actons entreprises et/ou<br>préconisées|N <br>Localités<br>Descripton de l’incident<br>Personnes affectées par l’incident<br>Actons entreprises et/ou<br>préconisées|N <br>Localités<br>Descripton de l’incident<br>Personnes affectées par l’incident<br>Actons entreprises et/ou<br>préconisées|N <br>Localités<br>Descripton de l’incident<br>Personnes affectées par l’incident<br>Actons entreprises et/ou<br>préconisées|\n|Région du Nord<br>|Région du Nord<br>|Région du Nord<br>|Région du Nord<br>|Région du Nord<br>|\n|1. <br>|Région du<br>Nord/Province<br>du<br>Yatenga/Tanga<br>ye|Enlèvement<br>d’un<br>pay", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000792", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Liste des incidents", "probe_tag": "drop", "probe_score": 0.03846234083175659, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 9, "end": 28, "key": "reliefweb:000792:12:0:0", "source": "camp2", "luna_reason": "Standalone table title introducing an incident list", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "including routine immunization for women and children, as well as polio vaccinations and\nVitamin A for children under five. Measures with respect to education concern primary and\nsecondary levels, literacy classes, including educational material for adult men and women,\nconstruction/rehabilitation and furnishing of schools, and the recruitment and training\nof teachers. Vocational training and business development training services will include\nlinkages to micro-credit schemes, essential employment toolkits upon graduation, a survey to\ncatalogue skills related to employment creation under relevant National Priority Programmes\n(NPP) and bilateral programmes, with training and educational programmes that link skills\nwith jobs. Other interventions concern the provision of access to clean drinking water and\nsanitation. During Phase I, MoRR capacity will be enhanced to enable it to effectively provide\nsupport, and oversight. Provincial MoRR offices will receive infrastructure and capacity\ndevelopment support, and senior staff will be trained in various management fields.\n\n\nProjects to empower young people (roughly 25% of returnees) will be undertaken to equip\nthem with effective life skills, provide training and study opportunities, and encourage their\nactive involvement in the social, cultural, and economic life of their communities.\n\n\nSince monitoring and evaluation (M&E) are an integral part of the Solutions Strategy; MoRR\nand UNHCR have initiated discussions with independent local research institutes as potential\npartners for this task. Such partners will have no role in site selection or implementation. Before\nan intervention is undertaken at a site, baseline data will be collected, including information\nabout the community, access to services, livelihoods, ethnic and geographic data, and will\ninclude more qualitative information through random interviews with households. These\ndata will be used to develop qualitative and quantitative indicators by which progress towards\nachieving parity among returning refugees and their host community can be measured.\n\n\nThe M&E partners will not only participate in a mid-term and final evaluation, but also\nundertake regular monitoring, analysis, making recommendations on progress against agreed\nindicators, identifying constraints and good practice, and documenting lessons", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001138", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "baseline data", "probe_tag": "drop", "probe_score": 0.02776966243982315, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1678, "end": 1691, "key": "reliefweb:001138:13:0:0", "source": "camp2", "luna_reason": "Baseline data will be collected before intervention, so it is planned production.", "drop_reason": "production", "specificity": "vague"}, {"text": "ethnic and geographic data", "probe_tag": "drop", "probe_score": 0.04404040053486824, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1787, "end": 1813, "key": "reliefweb:001138:13:0:1", "source": "camp2", "luna_reason": "Baseline data will be collected before intervention, making this planned data production.", "drop_reason": "production", "specificity": "vague"}]}
 {"text": "ANNEXES\n\n\n**Annex tables 3 through 29 can be downloaded from the UNHCR website at:**\nhttp://www.unhcr.org/globaltrends/2016-GlobalTrends-annex-tables.zip\n\n\n58 UNHCR > **GLOBAL TRENDS 2016**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000712", "page": 57, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "GLOBAL TRENDS 2016", "probe_tag": "drop", "probe_score": 0.019520100206136703, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 169, "end": 187, "key": "reliefweb:000712:57:0:0", "source": "camp2", "luna_reason": "Report title is merely displayed, with no cited finding or demonstrated data use.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": "`o` **Work** with banks to increase cash flow and adapt to\n\nallow humanitarian partners to deliver assistance\nprojects in a timely manner.\n\n`o` **Reduce** the growing threat of forced eviction against\n\nthousands of families living on land belonging to the\nState.\n\n`o` **Conduct** a national mine action survey to capture the\n\nextent of the contamination\n\n`o` **Provide** unconditional access for humanitarian\ndeminers to access communities for demining,\neducation and ERW removal.\n\n5. **ENGAGE** with emerging governance systems to sustain the\ngains made securing land rights, particularly women’s through\nformal and informal systems in Afghanistan and to **USE** land\nissues as an entry point to strengthen women’s rights by\nkeeping a focus on documenting land rights (customarily or\nformally) as a foundation for women’s social and economic\nempowerment.\n\n6. **SUPPORT** removal of deadly contamination and mines, and\nfacilitate access to educate men, women, boys and girls to the\nrisks from mines, IED, and other explosive devices through risk\neducation.\n\n\n7. **MAINSTREAM** PSEA in all aspects of the humanitarian\nresponse, ensuring all humanitarian actors are accountable for\ntheir actions and uphold the highest standards of conduct and\ndiscipline.\n\n\n\n8. **BUILD** capacities of humanitarian partners to identify\npotentially at-risk individuals or trafficking victims, and to\nprovide multisectoral responses to increased risks of trafficking\nin persons **BY** :\n\n\n`o` **Invest** in training and awareness raising of local health\n\nauthorities and clinics to develop appropriate\ntechniques for interviewing and examining patients\nwho may be trafficked or at risk of being trafficked.\n\n`o` **Support** flexible funding for local partn <mark>ers</mark> <mark>at border</mark>\n\n<mark>crossing points, so as to provide safe shelters,", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001240", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "national mine action survey", "probe_tag": "drop", "probe_score": 0.04217124730348587, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 282, "end": 309, "key": "reliefweb:001240:14:0:0", "source": "camp2", "luna_reason": "Survey is proposed for future data collection, not existing data use.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": " transparency – maximizing the availability of<br>disaggregated data – confdentiality, and privacy to ensure personal data is not<br>abused, misused, or putting anyone at risk of identifcation or discrimination,<br>in accordance with national laws and the Fundamental Principles of Ofcial<br>Statistics.|\n|5|Human and technical capacity<br>to collect, analyse, and use<br>disaggregated data must be<br>improved, including through<br>adequate and sustainable<br>fnancing|We recognize that collecting and analysing disaggregated data requires<br>the development of specifc skills. We recognize the need to fnance data<br>collection, analysis, and use appropriately and sustainably so that high-quality<br>data can be collected and used by governments as well as by businesses, civil<br>society, and citizens.|\n\n\n\n_Source:_ Global Partnership for Sustainable Development Data, 2022\n\n\nOne clear pathway for increasing the availability of data\non refugees is intentionally including them in existing\nDCEs rather than conducting additional ad hoc DCEs\nor having them included in an unrepresentative way in\nlarger DCEs covering their area of residence. Historically,\nthe use of proxies in capturing refugee status has been\ncommon practice in research on refugees. Assessing\nthe research landscape on economic integration,\nDonato and Ferris (2020, p. 24) state that ‘most studies\ndifferentiate refugees from other immigrants without\nobserving refugee status directly. Instead, they use\nnational origin to approximate refugee status or create\nsynthetic cohorts’. Similar methods have been used\nwith OECD’s Programme for International Student\nAssessment (PISA) data to distinguish between the\nperformance of ‘natives’ and ‘migrants’ (Behr and\nFugger, 2020), and nationality is also used in many\nEMIS as a proxy for refugee status (UNESCO, 2023;\nUIS and UNHCR,", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 17, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "disaggregated data", "probe_tag": "drop", "probe_score": 0.022404396906495094, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 50, "end": 68, "key": "reliefweb:000382:17:1:0", "source": "camp2", "luna_reason": "Generic data availability principle, without cited use, finding, or analysis.", "drop_reason": "availability", "specificity": "vague"}, {"text": "disaggregated data", "probe_tag": "drop", "probe_score": 0.02209661528468132, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 50, "end": 68, "key": "reliefweb:000382:17:1:1", "source": "camp2", "luna_reason": "Generic data availability principle, with no cited finding or analytical use.", "drop_reason": "availability", "specificity": "vague"}]}
-{"text": " او نورو هاون ګ او پاکستان لهران ی ونه ګ افغانان د اهر کال زر\n\nړنیو غانانو لومدونکو افیرته ی راستن. د بانمن ړی کیتی نور هم زې ولن ټ د جذب ظرف کوربه د ځایي ر ډې د رې شم ګ رات والو ډله کبله صورت مومي. د ک\n\nاودونکو هیا ېځ ېک. د بیی شامل دې خدماتو ته السرسی،ا می تعل او حقوقي مرستیاځ، روغت پناهی، اوو یتړا ېک ړ خوا،ه ی مع،شت ې مک ځ ته السرس\n\nپالنیی ای مخت ندوي او هم په ملي پرېن ېښ ګرڅدونکو افغانانو اندیې د راستن ېک ځ من ته راغل په۲۰۱۶ې DiREC) چوي ی ه یټ کم (دونکو اجراېراستن\n\n.کوي ون ګډ د تنه ښ غو ۍ رامونو ېک د هغوګې ون ړ جو او پرو\n\n\nچارو وزارت سره په فعاله��ونکو ېوالو او راستنګړې هګ ت", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001336", "page": 2, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "DiREC", "probe_tag": "drop", "probe_score": 0.024346014484763145, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 434, "end": 439, "key": "reliefweb:001336:2:2:0", "source": "camp2", "luna_reason": "Named entity with no demonstrated data use or cited resource.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "*, **Cyprus**, **Georgia**,\n**Germany**, **Greece**, **North Macedonia**, **Switzerland**, the\n**Netherlands**, **Turkey** and **Ukraine** . <sup>24</sup> Finally, in **India**, a\nwide range of communication and information channels\nhave been established, including a webpage <sup>25</sup> on\nregistration, refugee status determination, durable\nsolutions, assistance and services.\n\n\n\nResearch on communication needs have been\nconducted at regional and national levels ( **Algeria**,\n**Morocco**, **Turkey** and **Mauritania** ) to adapt\nCommunications with Communities strategies, focusing\non people with specific needs, as well as people in transit\nand in remote areas. Another example of this is the\nregional interagency Information and Communication\nNeeds Assessment conducted in 15 Latin American and\nCaribbean countries in 2019 (see the promising practice\non this in the relevant box).\n\n\nIn **Sri Lanka**, UNHCR regularly communicates with\npersons of concern about key developments through\ncommunity meetings and visits to displacement\ncentres, quarterly large-scale community outreach\nactivities, weekly individual counselling appointments,\nand communication by e-mail, fax, landline and mobile\nphones.\n\n\nIn **Venezuela**, UNHCR also works with community\nstructures who are trained in the identification of\npersons with specific needs, community mobilization\nand the AGD approach. The community structures\nare in charge of conducting outreach to persons with\nspecific needs, including women and children at risk,\nolder persons at risk, LGBTI persons, indigenous people\nand persons with disabilities, conducting information\nsessions and disseminating referral pathways.\n\n\nVenezuelan Warao refugee leader, Adriana, broadcasts information\nthrough her community radio show at the Carlos Gomes shelter in Manaus,\nnorthern Brazil.\n**Photo credit", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000345", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "regional interagency Information and Communication\nNeeds Assessment", "probe_tag": "drop", "probe_score": 0.04359767585992813, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 702, "end": 769, "key": "reliefweb:000345:23:1:0", "source": "camp2", "luna_reason": "Completed 2019 assessment is cited as an existing regional communication-needs resource.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": " and challenges in how data is translated from insight and into action.\nFor the purposes of this research, the following data lifecycle was used:\n### ‣ PLANNING : Defining the specific purposes/objectives of the data activity, the\n\nend-users and uses of the insights, identifying relevant partnerships, and\ndesigning a strategy to implement the data activity ( _who_ does _what when_, and\n_how_ ).\n### ‣ COLLECTION : Gathering data directly from those in the field or collating it from\n\nsurveys, censuses, voting or health records, business operations, web-based\ncollections, and other relevant, accessible sources.\n\n\n5", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000499", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "voting or health records", "probe_tag": "confusion", "probe_score": 0.1127677857875824, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 506, "end": 530, "key": "reliefweb:000499:5:1:2", "source": "camp2", "luna_reason": "Listed as sources being gathered during a data-collection activity, not analyzed data.", "drop_reason": "production", "specificity": "vague"}, {"text": "web-based\ncollections", "probe_tag": "drop", "probe_score": 0.00612482987344265, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 553, "end": 574, "key": "reliefweb:000499:5:1:3", "source": "camp2", "luna_reason": "Names generic web collections without showing analysis, findings, or substantive data use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "�„ Support the sector to interpret and analyse the differences for women, girls, boys and men and\nencourage this in order to shape the development of appropriate activities.\n\n\n�„ Support the inclusion of gender equality measures (ADAPT ACT C framework <sup>40</sup> ) in implementation\nactivities and monitoring and evaluation.\n\n\n�„ Contribute sector information and analysis to facilitate an overview of gender equality measures in\nhumanitarian action.\n\n\n�„ Promote inter-sector linkages for gender mainstreaming.\n\n\n**3. Capacity Development**\n\n\n�„ Identify the needs of colleagues for information and training in gender equality mainstreaming.\n\n\n�„ Support the Sector Coordinator to develop and deliver sector-appropriate gender in programming\nworkshops and training in the Gender Marker.\n\n\n�„ Encourage staff to raise gender equality issues in the sector.\n\n\n**4. Knowledge Management**\n\n\n�„ Participate in IATF’s Sector Gender Focal Point Network.\n\n\n�„ Share information and experiences with the Sector Gender Focal Point Network.\n\n\n40 **ADAPT ACT C** stands for: **A** nalyse gender differences; **D** esign services to meet needs of all; **P** articipate equally; **T** rain women and\nmen equally; **A** ddress GBV in sector programmes; **C** ollect, analyse and report sex- and age-disaggregated data; **T** arget actions\nbased on a gender analysis; **C** oordinate actions with all partners.\n\n\n64 **Gender Equality Promising Practices:** Syrian Refugees in the Middle East and North Africa (Geneva: UNHCR, December 2017)", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000401", "page": 65, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "sex- and age-disaggregated data", "probe_tag": "drop", "probe_score": 0.0397709421813488, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1275, "end": 1306, "key": "reliefweb:000401:65:0:0", "source": "camp2", "luna_reason": "Instruction to collect and report data, not use of an existing resource.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "<u>Discriminatory dispute resolution mechanisms: Customary courts and government officials are addressing land disputes</u>\nwith limited awareness of/support from related legislative or administrative bodies. Discriminatory rulings are reportedly\npassed with little consultation or opportunities to contest.\n\n\n<u>Financial burden of proving land ownership: In various locations in order to secure land ownership individuals must pay</u>\nfor a land survey. The cost of a land survey can be prohibitive, particularly for recent returnees. In some cases, the\nindividual that is able to pay for the land survey first has a greater chance of securing land ownership, as opposed to\nprocesses that support decisions made based on rightful ownership.\n\n\n<u>Lack of legislation implementation: This increases the risk for breach of HLP rights. The weak efficacy and fairness on the</u>\napplicability of the plural land regime, which allows the co-existence of statutory and customary land tenure regimes,\nmay undermine HLP rights, particularly those of vulnerable groups as women, child-heeded households, the elderly,\namongst others. The ongoing delay in the approval of the National Land Policy, under development since 2006,\nundermines filling gaps in HLP related legal frameworks that draw from the Land Policy. The legal insecurity weakens the\nability of HLP agencies to respond appropriately at the field and national level.\n\n\n<u>Registration and documentation: The absence of a harmonized and coherent national land registration and</u>\ndocumentation system contributes to the increase in land disputes and hinders the resolution of disputes. The current\nregistry is outdated and lacks capacity to handle the number of cases. Without a harmonized system, different systems\nof registration have emerged at Peri-urban, state and sub national levels, leading to confusion and contested claims.\nGiven this situation, the system is open to exploitation and as such private landowners have been able to rent or sell their\nland and properties to multiple parties thereby creating disputes.\n\n\n<u", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001146", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "land survey", "probe_tag": "drop", "probe_score": 0.04718257114291191, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 443, "end": 454, "key": "reliefweb:001146:1:0:0", "source": "camp2", "luna_reason": "Survey is mentioned as a costly land-service requirement, not used as data.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "article databases. Whilst both data sources could be used for the early detection of existing events,\ndata from news article databases could additionally be used to try to build prediction models for future\nevents.\n\n#### **Nexus between events and forced displacement**\n\n\nThe question of the characteristics of and circumstances under which events lead to sizable forced\ndisplacement is closely interconnected with the previous and the following research question. Identifying the relevant factors through a classification model allows (i) a more targeted search for, and\npotentially prediction of, relevant events, and (ii) more targeted modeling of prediction models for the\nmagnitude, demographic, and direction of forced displacement. According to the system of forced\ndisplacement, as outlined in Figure 2, both factors at the macro-level, meso-level, and micro-level <sup>5</sup>\n\nplay in at this stage.\n\n\nEvent characteristics can be derived from either traditional data sources, e.g., ACLED, or from data\nsources described in the previous section. Likewise, data from variables at the meso- and microlevel can, to a large extent, be derived from traditional data sources. However, Big (Crisis) Data can\nsupplement with valuable and timely information at this stage, that otherwise wouldn’t be accessible.\nData sources that track and reflect the decision to migrate, as well as the planning process before\nmigration, can add further information to traditional data sources. E.g., data from internet searches\nor social media sites that inquire about flight routes or host countries or sentiment analyses on social\nmedia that reflect how threatened individuals feel by the event. <sup>6</sup>\n\n\n**Relevant sources of Big (Crisis) Data**\n\n\n**Internet searches** Google Trends tracks its user’s search queries and IP-addresses and calculates\naggregated trends for searched keywords based on the location information of the IP-address. These\ntrend", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001630", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Big (Crisis) Data", "probe_tag": "confusion", "probe_score": 0.1363721638917923, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1189, "end": 1206, "key": "reliefweb:001630:17:0:2", "source": "camp2", "luna_reason": "Generic data resource is described as potentially useful, without demonstrated data use or finding.", "drop_reason": "system_registry", "specificity": "vague"}, {"text": "Big (Crisis) Data", "probe_tag": "drop", "probe_score": 0.022481774911284447, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1189, "end": 1206, "key": "reliefweb:001630:17:0:4", "source": "camp2", "luna_reason": "Conceptual data category described as potentially useful, without actual data use or finding", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "other hand, the same vastness means that searching for valuable and applicable information can\nresemble a search for a needle in a haystack [7].\n\n\nTo assess the information in Big (Crisis) Data that is valuable for predictive models of forced displacement, we evaluate each data source by using three criteria: (A)ccuracy, (B)ias, and (S)calability\n(ABS).\n\n\n   - Accuracy: Big Data generally suffer from a low signal-to-noise ratio [8, 3]. Especially content\nfrom social network sites is prone to contain false, misleading, or irrelevant information: bots\nwith sales ads that use trending hashtags to gain traction and actors with political agendas or\ntrolls who post deceptive or false information all contribute to to the noise on social network\nsites. Likewise, satellite images require intensive training of advanced deep learning algorithms\nto extract usable information from pixels, and advanced natural language processing algorithms\nare needed to extract relevant information from text sources in various languages and dialects\nwhich often contain spelling and grammatical errors.\n\n\nIn short, the effort of filtering the signal from the noise can, in some instances, become substantial and can thereby impact the scalability of the data source.\n\n\n   - Bias: To produce user-generated content, exhaust data on the internet or CDRs requires some\nform of access to electronic devices. However, although the global penetration rate for cell\nphones and the internet increases every year, it hasn’t reached full saturation yet. Studies\nhave shown that this lack in saturation is not equally distributed across all demographics but\nleads to a user demographic that is more Western, more urban, more educated, and more male\n\n[8, 9, 10]. Although cell phone penetration rates at the household level are high in developing\ncountries, male household members have immediate access to the device and often exclude\nwomen and minors. Younger and less educated people prefer communication channels with\ndirect communication, like Instagram, Pinterest, and Facebook, whilst Twitter and LinkedIn", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001630", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Big (Crisis) Data", "probe_tag": "drop", "probe_score": 0.021457504481077194, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 176, "end": 193, "key": "reliefweb:001630:7:0:0", "source": "camp2", "luna_reason": "Introduces a broad data category without citing specific data or showing concrete analytical use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "public evidence of registrable rights (ownership, leases, mortgages etc.) held by specific individuals and\n\n\nassigns priority among them as per law. <sup>4</sup> [^4: Such protection is based on either a document lodged for registration and a way to prioritize among documents (often based on the time of\nregistration) in a system of deeds or a search by the registrar at the point of registration (in a title registration system). See Arrunada and Garoupa\n(2005) for a conceptual comparison and economic evaluation of different registration systems and Arruñada (2012) for the importance of registries\nfor impersonal exchange with third parties.] This facilitates impersonal trade by protecting third parties’ rights\n\n\n(Arrunada _et al._ 2019); expands the range of potential contractual partners and options by reducing the\n\n\nscope for moral hazard due to asymmetric information; and provides the basis for enforcement of rights via\n\n\nthe courts as a last resort.\n\n\nAlthough not costless, having rights documented and mechanisms for enforcing them clearly defined has\n\n\nseveral advantages. It provides private benefits by (i) increasing investment incentives and reducing the\n\n\nneed to spend resources on non-productive activities to maintain land rights; (ii) expanding contractual\n\n\noptions and the range of potential contracting partners for land transfers; (iii) improving credit access if\n\n\nthere are liquid sales markets and collateral can be registered and enforced at low cost; and (iv) empowering\n\n\nindividuals, especially women, who were traditionally often disadvantaged by making enforcement of\n\n\nrights easier and encouraging entrepreneurship. It also provides public benefits by (i) improving functioning\n\n\nof land and associated markets for mortgages and insurance via public price data; (ii) providing the basis\n\n\nfor effective land us regulation and planning; and (iii) enhancing state capacity and the social contract by\n\n\nallowing fair taxation and incentivizing tax payment in return for public goods that can increase land prices.\n\n\n_Investment instead of ‘guarding labor’ and other defensive measures:_ Although undocumented rights are\n\n\nsufficient to incentivize short-to medium-term investment,", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001009", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "public price data", "probe_tag": "confusion", "probe_score": 0.8763829469680786, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1786, "end": 1803, "key": "prwp:001009:10:0:0", "source": "camp2", "luna_reason": "Public price data are identified as supporting functioning land and associated markets.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "elements of EU policy, the government established the digital SAR registry platform, using it to implement\n\nthe EU-supported producer support grant targeted to small farmers (< 120 ha) among many others.\n\n\n**2.1 Ukraine’s agricultural sector**\n\n\nWith more than 40 million ha of some of the most fertile agricultural land globally, Ukraine has traditionally\n\nbeen a key global supplier of agricultural commodities, especially sunflower oil, maize, and wheat. Before\n\nthe war, agriculture contributed about 10% to GDP and 42% of the country’s exports. The sector’s structure\n\nwas shaped by de-collectivization in the early 2000s when some 7 million landowners were provided with\n\nland shares of about 4 ha each. Some 20 million ha of Ukraine’s agricultural land is farmed by formalized\n\nlarge farms, often firms with links to foreign capital markets (Deininger _et al._ 2018) that lease land from\n\nowners. About 12 million ha is estimated to be cultivated by small and household farms many of which\n\nlack the resources to register formally and may also not be covered by the country’s agricultural statistics.\n\nIn 2002, about 9.2 million ha was state or communal land and an unknown share of this land was\n\n‘privatized’, often in non-transparent ways that imposed significant losses to the public (Nivievskyi 2020).\n\nThe country has one annual growing season with winter crops (wheat, rye, barley, rapeseed) sown in fall,\n\nsummer crops (barley, maize, sunflower, soybean) in the spring and harvest from July to November.\n\n\nIn 2019 and 2020, Ukraine enacted far-reaching land governance reforms including allowing sales of\n\nagricultural land through the stepwise lifting of a moratorium on such transactions that had been in\n\nplace since 2001. This was expected to allow use of land as collateral for credit to deepen domestic capital\n\nmarkets and, in the agricultural sector, support diversification,, especially by smallholder producers, away", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001504", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "digital SAR registry platform", "probe_tag": "confusion", "probe_score": 0.62943035364151, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 54, "end": 83, "key": "prwp:001504:7:0:0", "source": "camp2", "luna_reason": "Registry platform is used to implement a targeted producer support grant.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "Inequality within countries has fallen over time for many countries (World Bank 2016). If data from the\n1990s are used, the 67 <sup>th</sup> percentile is closer to 45 for consumption and 50 for income (Table 5).\nHowever, if the most recent Gini coefficient of each country is used, a threshold of 40 still roughly\ncorresponds to the 67 <sup>th</sup> percentile for income and consumption distributions (38.8 for consumption and\n40.3 for income).\n\n_Table 5: 67_ <sup>_th_</sup> _percentile using other time periods of Gini coefficients_\n<u>1990s</u> <u>2000s</u> <u>2010s</u> <u>Latest</u>\n\nConsumption 44.1 42.0 39.5 38.8\n\nIncome 47.7 47.2 38.6 40.3\n\n<u>Combined</u> <u>45.1</u> <u>42.2</u> <u>39.3</u> <u>39.1</u>\n\n\n<mark>The fact that the summary statistics of Gini coefficients across income and consumption surveys is</mark>\n<mark>similar appears to contradict our earlier statement that income inequality tends to be higher than</mark>\n<mark>consumption inequality. However, the sample of countries using income or consumption aggregates</mark>\n<mark>is not representative of all countries. Across the 18 countries in PIP that have both income- and</mark>\n<mark>consumption-based surveys from the same year (Annex Table A.3), the average Gini coefficient</mark>\n<mark>derived from consumption-based-surveys is 4.5 Gini points lower (", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001530", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "consumption-based-surveys", "probe_tag": "confusion", "probe_score": 0.8496435284614563, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1287, "end": 1312, "key": "prwp:001530:10:0:1", "source": "camp2", "luna_reason": "Surveys provide the Gini coefficient finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "(2004) and take averages over the relevant years. The pre-war years are divided into two\n\n\nsub-periods (1992-1996 and 1997-2001) and the war years correspond to 2002-2007 and\n\n\npost war years 2008-2011.\n\n\nThe digital maps of the communes/departments and road network are used to compute\n\n\nthe distances from each commune center to all six trade routes identified in Figure 1. The\n\n\ndistance of a location is estimated as the ‘arc distance’ from the commune center to the\n\n\nnearest point on the road along a route. Each commune/department is then assigned\n\n\nto the route which is closest to it. Using this shortest distance, we compute distances\n\n\nfrom the centroid of each commune to all West African cities with population of 35, 000\n\n\nor more in 1996 from the consolidated urban database by Blankespoor, Khan and Selod\n\n(2017), which draws upon population data from Brinkhoff (2018). <sup>16</sup> These arc distances\n\n\nare combined with city population to define a measure of market access which is elaborated\n\n\nin the empirical estimation section below.\n\n##### **(6) Empirical Issues and Strategy** **(6.1) Empirical Models** **Employment Pattern: A Triple-Difference Strategy with Location** **Fixed Effect**\n\n\nTo investigate how the trade disruption caused by the civil war in Cˆote d’Ivoire may have\n\n\naffected the resource allocation across the Abidjan and non-Abidjan areas in Mali and\n\n\nBurkina Faso, we adopt an empirical model that takes advantage of the panel data by\n\n\ncombining sub-district level fixed effect with a triple-difference set-up. With a two-period\n\n\npanel of employment shares, the regression specification is as follows:\n\n\n_Yija −_ _Yijb_ = _β_ 0 + _β_ 1 _DT_ + _β_ 2 _", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002156", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "consolidated urban database", "probe_tag": "confusion", "probe_score": 0.6830410361289978, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 762, "end": 789, "key": "prwp:002156:20:0:0", "source": "camp2", "luna_reason": "Named urban database used to compute city distances and market access.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " subsidies. Wealthier deciles included the largest share\nof total subsidy beneficiaries (blue bars) and the largest share of all households within each\ndecile that are beneficiaries (red bars). The differences between the top three deciles and the\nremaining ones are remarkable in all countries, although less pronounced in Nigeria. As noted\nabove, in Niger, the poor (i.e., the first four deciles) do not benefit from the subsidy at all;\nUganda shows a similar pattern, and in Mali only the fourth decile shows a very small amount\nof beneficiaries. We conclude that in the five African countries analyzed, and using the\nhousehold data, tariff data, and the methodology described, consumption subsidies are\nregressive (albeit relatively less so in Nigeria).\n\n\n12", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002124", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household data", "probe_tag": "confusion", "probe_score": 0.5484499335289001, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 621, "end": 635, "key": "prwp:002124:13:1:0", "source": "camp2", "luna_reason": "Household data are explicitly used to conclude consumption subsidies are regressive.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "largest 4 countries in our sample. <sup>13</sup> Regression results for the reduced sample are provided in Table\n\n\n8. For brevity, only some of the specifications are shown. Table 8 clearly shows that the qualitative\n\n\nnature of the relationship between corruption (overall corruption, incidence and depth of petty\n\n\ncorruption) and _Population_ remains intact.\n\n\n3.6 _Additional controls_\n\n\nStarting with our final baseline specification (column 4, Table 4), we experimented by adding\n\n\nsome more controls for extra robustness. The controls include dummy variables for the region\n\n\n(region fixed effects) <sup>14</sup> ; religious affiliation of countries captured by the proportion of population\n\n\nthat is Catholic, Muslim and Protestant (omitted category is all other religions) <sup>15</sup> ; a measure of the\n\n\nindependence of the judiciary taken from Freedom House’s Economic Freedom of the World\n\n\ndatabase (Judicial independence); and a measure of the functioning of the government based on\n\n\nwhether elected officials determine the policies of the government, steps taken by the government\n\n\nto combat corruption and whether the media and public can freely express their views regarding\n\n\ncorruption, and if the government is answerable to the electorate between elections and if it works\n\n\nwith transparency, taken from Freedom House’s Economic Freedom of the World database\n\n\n(Functioning of the government). <sup>16</sup> There is no qualitative change in our main results due to these\n\n\ncontrols (Table A3 in the Appendix provides the full results).\n\n\n13 The largest 4 counties excluded have a population of more than 190 million and include Brazil, China, India, and\nIndonesia. We experimented with alternative samples such as excluding the largest 5 percent and the smallest 5 percent\nof the countries, but this did not change the qualitative nature of the results discussed in this section.\n14 The regions are Sub-Saharan Africa, East Asia and the Pacific", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000204", "page": 26, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Economic Freedom of the World\n\n\ndatabase", "probe_tag": "keep", "probe_score": 0.9673721194267273, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 874, "end": 914, "key": "prwp:000204:26:0:0", "source": "camp2", "luna_reason": "Database measure is used as a robustness control in regression analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " acquisition and or exercise market power, e.g., by taxing or requiring\n\nelectronic auction if use right concentration exceeds a certain level, may be gainfully explored.\n\n\n_Informality:_ Most studies assume that the benefits from formalization accrue to those directly affected and\n\nassess the impact of informal land rights by comparing parcels with and without rights using discontinuities\n\nin space (Ali _et al._ 2014; Hawley _et al._ 2018) or time (Beg 2022) for identification although rights may\n\nreturn to informality (Galiani and Schargrodsky 2016; Gutierrez and Molina 2020) if the cost of subsequent\n\nregistration is high (Ali _et al._ 2021). Informal rights can substitute for formal ones to some extent (Lanjouw\n\nand Levy 2002). They offer short-term advantages (Niu _et al._ 2021) but impose costs in the short (Tellman\n\n_et al._ 2021) and the medium term (Henderson _et al._ 2021; Navarro and Turnbull 2014). Yet, if it yields rents\n\nfor intermediaries (Krishna _et al._ 2020), informality may be difficult to eliminate politically. <sup>1</sup>\n\n\nWe depart from a view of informality as a purely private issue by using fields as a basic unit of agricultural\n\nland use. This allows estimating external effects of three types of informality that we expect to affect land\n\nprices via different channels. First, parcels not mapped in the cadaster or registered in the registry of rights\n\n\n1 A detailed model and discussion of costs and benefits of informality in the labor market for Mexico (Bobba _et al._ 2022); biased response to\ninfrastructure improvement in Ethiopia (Perra _et al._ 2024), and externalities due to tax reform in Pakistan (Waseem 2018).\n\n\n3", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001374", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "registry of rights", "probe_tag": "confusion", "probe_score": 0.42694419622421265, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1380, "end": 1398, "key": "prwp:001374:4:1:1", "source": "camp2", "luna_reason": "Registry status defines parcels used to estimate land-price effects of informality.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "), slightly below\n\n\nthe minimum wage for a full-time worker in most sectors. Wage work was eight times more common\n\n\nthan self-employment. Most work was relatively short-term, with median and mean tenures of 2\n\n\nand 7 months respectively.\n\n\nOf the sample, 97% searched for work in the week before the baseline. In that week, they\n\n\nspent on average 17 hours and 242 South African rand (40 USD PPP) searching. The relatively\n\n\nhigh search costs suggest that welfare gains for workseekers are possible from improved search\n\n\ntargeting. Workseekers submitted on average 10 applications in the preceding month and received\n\n\n1.2 offers, though the medians for both measures are zero. The job search and application process is\n\n\nsomewhat formal: 38% of the candidates employed at endline reported that they submitted written\n\n\napplications for their current job and 47% reported that they had a formal interview.\n\n\n**2.5** **Assessments**\n\n\nWe conduct six assessments with workseekers: communication, concept formation (similar to a\n\n\nRaven’s test), focus, grit, numeracy, and planning. Firms have demonstrated interest in the results\n\n\nof these assessments, though they obviously also use other information in hiring decisions. Client\n\n\nfirms have paid Harambee to screen roughly 160,000 prospective workers using these assessments.\n\n\nAppendix A describes each assessment in detail, their psychometric properties, and how some\n\n\nHarambee client firms use them in hiring.\n\n\nEach assessment session is led by two or three industrial psychologists, who manage a team of\n\n\n12See Garlick et al. (2019) for an experimental validation of labor market data from phone surveys in this setting.\n\n\n10", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001763", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "labor market data", "probe_tag": "confusion", "probe_score": 0.8832507729530334, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1627, "end": 1644, "key": "prwp:001763:11:1:0", "source": "camp2", "luna_reason": "Cited phone-survey data are used in an experimental validation.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " the statistical determination of a break could benefit from knowledge of the economic\nhistory of a country. However, except for well-known events, an in-depth understanding of the timing of\nactual events, shocks, or crises is beyond this study's scope (given the number of countries). In the\nestimation, we also consider a dummy when the time patterns of the right- and left-side variables begin to\ndiverge over their past behavior, combining breakpoint unit root tests, visual inspection, and, if available,\nrelevant economic information <sup>13</sup> to determine possible timings.\n\n\n13 Such as country reports from the World Bank, IMF, Economist Intelligence Unit (EIU), or Wikepedia.\n\n\n11", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000629", "page": 12, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "country reports", "probe_tag": "confusion", "probe_score": 0.6009185314178467, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 598, "end": 613, "key": "prwp:000629:12:2:0", "source": "camp2", "luna_reason": "Reports from named institutions inform breakpoint timing determination.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " not\nsystematic, we would risk bias in the analysis if we included only the available data.\n\n**We use data for the 2003 to 2017 period, from Eurostat, the Organisation for Economic**\n**Co-operation and Development (OECD), and** **_fDi Markets_** **(Financial Times).** Given our\nempirical goal, and considering data availability constraints, we have collected the largest possible\nset of data at the NUTS-3 level from three main sources to cover the longest possible time period,\nnamely from 2003 to 2017. On economic growth and industrial structure, we use Eurostat data from\nthe _Regio_ database on GDP, population, employment, land area, and sectoral Gross Value Added\n(GVA) – for agriculture, industry (mining; electricity; manufacturing), construction, market\nservices, <sup>13</sup> [^13: Wholesale and retail trade; transport; accommodation and food service activities; information and communication; financial and\ninsurance activities; real estate activities; professional, scientific and technical activities; administrative and support service activities.] and non-market services. <sup>14</sup> [^14: Public administration and defence; compulsory social security; education; human health and social work activities; arts,\nentertainment and recreation; other service activities; activities of household and extra-territorial organisations and bodies.] Missing values in the NUTS-3 level regional series have been\nfilled in by linearly interpolating NUTS-2 level data. On innovation, we use microdata on patents\nfiled under the Patent Co-operation Treaty (PCT) from the _REGPAT_ database provided by the OECD,\naggregated at the NUTS-3 level by priority year and inventor’s residence using the fractional count\ncriterion. On FDI, we use data on inward ‘greenfield’ FDI from the _fDi Markets_ database provided\nby the Financial Times. Of particular interest for our purposes, the _fDi Markets_ database collects\ninformation on individual investment projects in terms of year, destination region at the NUTS-3 (or\ncity) level", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000335", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NUTS-2 level data", "probe_tag": "confusion", "probe_score": 0.14596961438655853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1459, "end": 1476, "key": "prwp:000335:6:1:1", "source": "camp2", "luna_reason": "Existing regional data are used to interpolate missing NUTS-3 values.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "_fDi Markets_ database", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1786, "end": 1808, "key": "prwp:000335:6:1:4", "source": "camp2", "luna_reason": "Named database provides inward greenfield FDI data used in analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " are\nincluded to enable the actual tax liabilities of taxpayers to be modelled, including non-standard reliefs\nwhere the required information is included in the survey. To examine the VAT or excise taxes, household\nbudget survey data can be used as these surveys typically provide a breakdown of total consumption\nacross a large number of consumption categories, enabling differentiation between consumption subject\nto different VAT rates and different excise tax rates.\n\n\nBefore calculating progressivity or other metrics, some adjustments (in addition to basic data cleaning)\nmay be made to the microdata to adjust for limitations associated with that data. For example, a common\nproblem with income survey data is that incomes at the top end are often underreported, and various\nmethods can be applied to adjust for this (see, e.g., Blanchet et al., 2022; Ruiz and Woloszko, 2016).\nMeanwhile, in the absence of income survey data, if consumption survey data is being used to model the\nPIT, adjustments based on savings patterns can be made to proxy better for income data. A parallel paper\nexamines such techniques (including greater use of tax return microdata) in detail. Further discussion of\nthese techniques is left to that paper.\n\n\nAdditional adjustments may also be made to specify the welfare metric and the unit of analysis. For PIT\nanalysis, where income data is available it will be the preferred starting point in calculating a welfare\n\n\n8", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001110", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "income data", "probe_tag": "confusion", "probe_score": 0.7479665279388428, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1063, "end": 1074, "key": "prwp:001110:9:1:5", "source": "camp2", "luna_reason": "Generic income data is mentioned as a proxy target without an attributed finding.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": ", particularly in dryland areas (Rohde et al., 2017). Second, GDEs\nare important for the livelihoods of populations in rural areas that are typically more vulnerable. An unfettered provision of solar\npumping could lead to a deterioration of GDEs on which pastoralists rely for their cattle while also expanding agricultural land to\nareas previously used for transhumance and grazing, heightening tensions between farmers and pastoralists (Rodella, Zaveri and\nBertone, 2023). Third, beyond their importance for wildlife – including for migratory birds – GDEs play an essential role in carbon\nstorage (Mendonça et al. 2017). Countries seeking to reduce their emission by switching groundwater pumping to solar, owe to\nconsider the carbon impacts of compromising the role GDEs play as carbon sink.\n\n\nFor those reasons, the results highlight the necessity for policymakers and development partners to collaborate upstream on largescale solar energy deployment in regions with high irrigation potential, such as SSA, that will facilitate easier and cheaper access to\nmuch-needed solar pumping irrigation but require enforceable policy and regulation to protect against unintended consequences,\nsuch as the deterioration or destruction of GDEs. Our analysis also highlights the need for more data on GDEs from location to the\nservices they provide to people and the environment to monitor better their health and address situations of poor groundwater\nmanagement that could threaten their existence. The proper monitoring of GDEs can thus be an efficient strategy to contribute early\nwarning information on the mismanagement of groundwater resource and help prevent or remedy impacts.\n\n##### 7. Conclusion\n\n\nWe proposed an analytical hierarchy process to evaluate the risk posed to groundwater dependent ecosystems (GDEs) by an\nuncontrolled expansion of access to groundwater through photovoltaic pumping in sub-Saharan Africa. More specifically, we\nevaluated the risk of over exploitation of groundwater resources which could endanger GDEs, and we considered the following\ninput data: global horizontal irradiance, renewable groundwater resources", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001392", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on GDEs", "probe_tag": "confusion", "probe_score": 0.3976620137691498, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1286, "end": 1298, "key": "prwp:001392:11:1:0", "source": "camp2", "luna_reason": "States a need for more data, without citing existing data or an analyzed finding.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": " Endogenous variables are 𝒀𝒀𝒕𝒕 = [𝚫𝚫𝒒𝒒𝒕𝒕, 𝚫𝚫𝒚𝒚𝒕𝒕, 𝒑𝒑𝒕𝒕] <sup>′</sup>, where 𝚫𝚫𝒒𝒒𝒕𝒕, 𝚫𝚫𝒚𝒚𝒕𝒕, 𝒑𝒑𝒕𝒕 denote the loggrowth is only available on a quarterly basis, the exercise is conducted with quarterly averages of\nmonthly data. Other variables that have been used in forecasting commodity prices include\nindicators of global economic conditions, world output gap, capacity utilization, industrial\nproduction and exchange rates (Baumeister, Korobilis and Lee 2022; Dées et al. 2007; Kaufmann\net al. 2004; Tang and Hammoudeh 2002; Zamani 2004; Lalonde, Zhu and Demers 2003; Ye, Zyren\nand Shore 2006).\n\n\n\nand Shore 2006).\n\nIn the prediction step, 1-step-ahead prediction at the time origin 𝒉𝒉, 𝒀𝒀 <sup>�</sup> 𝒉𝒉(𝟏𝟏), and the associated\nforecast error, 𝒆𝒆𝒉𝒉(𝟏𝟏) are:\n\n𝟒𝟒\n\n𝒀 𝒉 𝟏\n\n\n\n𝟒𝟒\n\n𝒀 𝒉 𝟏\n\n\n\n𝟒𝟒\n\n<u>𝒀</u> <sup><u>�</u></sup> <u>𝒉𝒀</u> 𝒉(𝟏𝟏) = �𝑨𝑨𝒊𝒊𝒀𝒀𝒉𝒉+𝟏𝟏−𝒊𝒊,\n\n𝒊𝒊=𝟏𝟏\n\n\n\n𝒀 𝒉 𝟏\n\n𝒊𝒊=𝟏𝟏\n\n\n\n𝒆𝒆𝒉𝒉(𝟏𝟏) = 𝒖𝒖𝒉𝒉+𝟏𝟏.\n\n\n\nFoodstuffs include butter, cocoa beans, corn, cottonseed oil, hogs, lard, steers, sugar, and wheat. It is developed by\nthe Commodities Research Bureau.\n12 We adopt a log-level commodity price model following Kilian and Murphy (2014). As they suggested, it is not clear\nwhether commodity prices should be modeled in log-levels or log-differences. The advantage of the level specification\nis that impulse responses of log-level price models are consistent with sign-restriction", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000851", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.7058315277099609, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 211, "end": 223, "key": "prwp:000851:13:1:0", "source": "camp2", "luna_reason": "Existing monthly data are used as quarterly averages in the forecasting exercise.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": "fatigue is crucial to inform the inferential consequences of response fatigue, we assess whether the\n\nplacement of the women’s food consumption module differs by maternal and household\n\ncharacteristics.\n\nWe find significant impacts of fatigue: respondents who received the dietary diversity\n\nmodule earlier in the survey report significantly higher dietary diversity score. Delaying the arrival\n\nof the dietary diversity module by about 15 minutes leads to 8-17 percent underestimation in\n\ndietary diversity score. This is a striking result given the relatively short difference in the timing\n\nof the food consumption module between the treatment and control groups. The impact of fatigue\n\nappears to be more pronounced for food groups that are infrequently consumed, consistent with\n\nevolving evidence that these food groups are prone to other sources of measurement error. We also\n\nfind significant and intuitive heterogeneity in respondents’ vulnerability to fatigue. For example,\n\nolder women and less educated women are prone to fatigue than younger and more educated ones.\n\nMoving the module on diet diversity had a larger effect on responses provided by mothers in larger\n\nhouseholds, consistent with the idea that women in larger households might face more distractions\n\nwhen answering phone surveys or are simply more vulnerable to the effects of fatigue. Relatedly,\n\nthis systematic underreporting of dietary diversity for larger households may contribute to the\n\ninverse relationship between food demand and household size documented in developing countries\n\n(Lanjouw and Ravallion, 1995; Deaton and Paxson, 1998; Gibson, 2002; Gibson and Kim, 2007).\n\nAlthough our findings come from a specific rural women sample and phone surveys in\n\nrural Ethiopia, the implication and relevance of our findings are likely to extend to FTF surveys\n\nand other settings involving phone surveys. While the impact of fatigue in choice experiments and\n\ndiaries is well-documented (e.g., Bradley and Daly, 1994; Savage and Waldman, 2008; Silberstein\n\nand Scott, 2011; Beegle et al., 2012; Hess et al., 2012; Schündeln, 2018; Battistin et al", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000074", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "FTF surveys", "probe_tag": "confusion", "probe_score": 0.25069403648376465, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1833, "end": 1844, "key": "prwp:000074:6:0:1", "source": "camp2", "luna_reason": "Refers to a survey category without citing its data or attaching a finding", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
+{"text": " the survey rounds. This data provides insight into potential\n\nchanges through which market or non-market transactions land was acquired. For women, we see a\n\nsharp increase in the probability that a parcel was purchased: this increases by 7.5pp in our pooled\n\nestimates, roughly a 35 percent increase relative to the round 3 control mean. This seems to be\n\nreplacing sharecropping as a mode of acquisition, which drops by 3.6pp in our pooled estimates\n\n(significant at 10 percent), with a particularly sharp drop in round 3. For men, we also see a\n\nsignificant increase in purchases of 7.1pp, with declines not only in sharecropping, but renting as well\n\n(the latter significant at 10 percent). Taken together, these results suggest that both men and women\n\nare taking advantage of the clarification of property rights that certification provides to move from\n\nrental contracts of various forms to land purchases.  It is also worth noting that there is a significant\n\nincrease of 10 percentage points, in round 3, in the acquisition of land through inheritance for men.\n\n\nIn Table 7, Panel A we examine how improved security translates into changes in overall\n\nlandholdings controlled by women and men. Since we do not have a plot panel, we cannot accurately\n\nmeasure sales, but the overall level of holdings reveal a significant amount of land being released.\n\nWomen reduce their number of plots in the pooled estimates by 0.068, with the largest reduction\n\nhappening in round 3. They also end up having significantly smaller plots, a reduction of about 0.14\n\nhectares using the round 3 estimates. Putting these two measures together at the owner level, we can\n\nsee a reduction in aggregate individual land holdings of about a quarter of a hectare in round 3.\n\n\n18", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002191", "page": 19, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "plot panel", "probe_tag": "confusion", "probe_score": 0.2755018472671509, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1227, "end": 1237, "key": "prwp:002191:19:1:0", "source": "camp2", "luna_reason": "States missing panel data without analyzing or substituting estimates.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": " but even\nin that context incorporating geospatial data led to an increase in precision roughly equivalent to\ndoubling the sample size. These results are only suggestive, however, and an important outstanding\nresearch agenda is to compare small area estimates of monetary poverty obtained using geospatial data\nto those obtained from standard census-based poverty maps directly from census data. This can confirm\nthat the encouraging results presented above apply to monetary poverty.\n\n\nA final caveat, which applies to small area estimation in general, is the challenge of measuring local\ntransient shocks. In the context of geospatial data, key indicators used to generate model predictions,\nsuch as building counts, are not necessarily affected by local economic shocks. This also poses an issue\nfor traditional census-based poverty maps, as the census predictions tend to rely heavily on indicators\nsuch as educational attainment and household size that may also fail to track local shocks. Empirical Best\nmethods partly address this issue by incorporating welfare information from the sample. Nonetheless,\nfuture research is needed to explore which geospatial indicators better reflect local economic shocks.\n\n\nOverall, the results from an evaluation exercise using data from two countries demonstrate major\nefficiency gains from combining survey data with geographically comprehensive geospatial data to\ngenerate small area estimates of non-monetary poverty. These efficiency gains came at no cost to\ncoverage in Sri Lanka and a moderate cost in coverage rates in Tanzania, and the latter can be addressed\nthrough further refinements to the methodology. The financial cost of incorporating geospatial data is\nlow, relative to the cost of achieving similar efficiency gains by surveying additional households. While\nthere is room for further methodological improvement, these techniques can currently be applied at\nmodest cost to generate more granular and informative estimates of non-monetary welfare.\n\n\n43 Chambers and Das (2017) propose a similar strategy of adjusting traditional ELL estimates to correct for biased\nestimates of mean squared error.\n44 See Belghith et al, 2020. This corresponds to the marginal R2 reported in Table 6.\n\n\n42", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002095", "page": 43, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "census-based poverty maps", "probe_tag": "confusion", "probe_score": 0.8909046053886414, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 343, "end": 368, "key": "prwp:002095:43:1:0", "source": "camp2", "luna_reason": "Referenced only in a proposed future comparison, not an actual data use.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": " identify goods with\nlinear Engel curves given prevailing prices, under different prices this\nlinearity may fail.\n\nHowever, from a practical point of view it may be possible to identify\ngoods with linear Engel curves in one period, and then we may get\nlucky: in a subsequent period perhaps relative prices will not have\nchanged in such a way that linearity will be compromised, and our\nsub-aggregate will work for measuring poverty.\n\n\n4.1. **Data.** In the remainder of this paper we test our luck using data\nfrom expenditure surveys in Rwanda, Uganda, and Tanzania. <sup>5</sup> All\nsurveys are large multipurpose household consumption surveys, representative at both national and urban/rural levels with large sample\nsizes. In Uganda about 3000 households were interviewed each year, in\nTanzania between 3000 and 4000 each year, and in Rwanda the number of households increased substantially from 6900 to 14300 household\nobservations per year.\n\n\n5. Rwanda: Enquete Int´egrale sur les Conditions de Vie des m´enages de Rwanda\n(EICV1) 2001 and (EICV2) 2006 . Uganda: Uganda National Household Survey\n(UNHS) 2005/06 and 2009/10. Tanzania: Tanzania National Panel Survey (NPS)\n2008/09 and 2010/11.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002089", "page": 16, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Tanzania National Panel Survey", "probe_tag": "keep", "probe_score": 0.9250173568725586, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1138, "end": 1168, "key": "prwp:002089:16:2:2", "source": "camp2", "luna_reason": "Named panel survey data are used to test the poverty measurement approach.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "_Source_ : Authors' estimates using 2021 GEIH data, information from the CEQ Institute, and the World Bank.\nNote: The results for all countries other than Colombia were obtained by applying the old CEQ methodology, which\namong other things did not include indirect effects of indirect taxes and accounted for in-kind income differently, while\nthe results for Colombia and Ecuador were obtained by applying the new CEQ methodology.\n\n#### **6. The 2022 tax reform: Exploring its potential impact**\n\n\nIn November 2022, the Tax Reform for Equality, Social Justice, and Fiscal Adjustment\nConsolidation Act, which will take effect in fiscal year 2023, was introduced and approved by the\ncongress. This tax reform included changes in income tax and complementary taxes for both\nindividuals and companies, especially through the reduction of deductions and tax exemptions in\nthe personal income tax, changes in rates for some sources of income and adjustments in the\ndeductibility of royalties, as well as changes in discounts for investments made in technological\ndevelopment and innovation.\n\nThe reform also contemplated the creation of a permanent wealth tax. In addition, it included\nchanges in the rates on the national carbon tax and the creation of the national tax on single-use\nplastic products used for packaging or wrapping goods. Finally, the approved law created health\ntaxes, which impose tariffs on ultra-processed sugary beverages, as well as on ultra-processed\nindustrially produced food goods with a high content of added sugars, sodium, or saturated fats.\n\nIn order to evaluate the redistributive impacts of the reform using the microsimulation tool\ndescribed throughout this paper, the specific sections of the reform that can be captured by the\nhousehold surveys used in the model are simulated, in particular the items of the reform\ncorresponding to: (i) the reduction in the cap on personal income tax exemptions and deductions;\n(ii) the homogenization under the general schedule rate paid on dividend income; (iii) the\nintroduction of", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000584", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "household surveys", "probe_tag": "confusion", "probe_score": 0.5969599485397339, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1758, "end": 1775, "key": "prwp:000584:36:0:1", "source": "camp2", "luna_reason": "Existing household surveys are used in the microsimulation model.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": " _new_ toilet.\n\n\nTable 4: Reported loan use\n\n\nSanitation &\nNew toilet Upgrade Repair Other only Total\n\n<u>other</u>\n\n146 7 2 31 14 200\nSL\n(73%) (4%) (1%) (16%) (7%) (100%)\n\n\n14 0 0 5 1 20\nControl\n(70%) (0%) (0%) (25%) (5%) (100%)\n\n\n160 7 2 36 15 220\nTotal\n<u>(73%)</u> <u>(3%)</u> <u>(1%)</u> <u>(16%)</u> <u>(7%)</u> <u>(100%)</u>\n\n\n_Notes_ : Data source: Client survey and administrative data. Sanitation loan usage was reported for those\nclients who took a sanitation loan according to administrative data from the MFI and confirmed it during the\ninterview. Hence, information is missing for clients who did not confirm to have taken a sanitation loan in the\nsurvey.\n\n\nThe household survey collected information on toilet ownership, whether it was not in use and the\n\n\nreasons for this, and a number of dimensions of toilet quality, which allow us to directly test whether\n\n\nhouseholds made a variety of sanitation investments. We focus on three types of sanitation investments:\n\n\n(i) construction of new toilets; (ii) repair of existing toilets; and (iii) upgrade of toilets. We measure\n\n\nthe construction of new toilets through (i) toilet ownership, regardless of whether it was functioning,\n\n\n40Even though the evidence presented above suggests that the loan label might have played a role in affecting the\ndemand for the sanitation loan, this does not imply that all households that took a sanitation loan intended to use it for\nsanitation investments. Some of these households could be less sensitive to the label effect and take the", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001768", "page": 27, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "administrative data from the MFI", "probe_tag": "confusion", "probe_score": 0.7522339224815369, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 489, "end": 521, "key": "prwp:001768:27:1:2", "source": "camp2", "luna_reason": "MFI administrative data identify sanitation-loan clients underlying reported usage findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " of the 19 <sup>th</sup> ICLS standards requires household surveys that are used to measure\n\nlabor market engagement – e.g. dedicated labor force surveys (LFS) and multi-topic household surveys –\n\nto differentiate between individuals engaged in own-use production work and individuals engaged in\n\nemployment. While own-use production of goods can take many forms (e.g. collection of firewood or water,\n\nfood preservation, etc. for family use), the revised standards have the largest implications for the\n\nmeasurement of agricultural work, where surveys need to distinguish between a farmer producing for\n\nown/family use or for sale. This, however, is difficult to measure, and historically, there has been scant\n\nempirical evidence and guidance on measurement practices. While the 2007 Standard Classification of\n\nOccupations (ISCO-08) distinguishes “subsistence farmers, fishers, hunters and gatherers” (sub-major\n\ngroup 63) and “market-oriented skilled agricultural workers and forestry, fishery and hunting workers”\n\n(sub-major groups 61 and 62) (ILO 2013a), this separation has had limited practical relevance, as\n\noccupational breakdowns rarely go below the level of major groups (i.e. combining all agricultural\n\n\n1 The International Conference of Labour Statisticians (ICLS) is a standard-setting body in labor statistics, hosted every five years\nby the International Labour Organization (ILO). As per the tripartite structure of the ILO, its participants include experts from\ngovernments (typically officials from the ministries dealing with labor issues and national statistical offices), employers' and\nworkers' associations.\n2 The 19th ICLS also introduced a new ‘forms-of-work’ framework.\n\n\n2", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002436", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "multi-topic household surveys", "probe_tag": "confusion", "probe_score": 0.3025776147842407, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 164, "end": 193, "key": "prwp:002436:3:1:2", "source": "camp2", "luna_reason": "Generic survey category is mentioned conceptually without an attributed finding or existing data use.", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
+{"text": "golanos ou\nestrangeiros, e completar o registo de adultos não-registados, quebrando a cadeia de adultos nãoregistados e de crianças não-registadas;\n\n - Facilitar a naturalização de apátridas ou pessoas em risco de apatridia;\n\n - Criar mecanismos e procedimentos para resolver casos complexos de disputas relativas à nacionalidade,\nparticularmente para os refugiados que regressam e que não têm provas de ligações a Angola, possivelmente\nem coordenação com os antigos Estados de acolhimento;\n\n - Atribuir cartões de identidade e passaportes aos refugiados e requerentes de asilo;\n\n - Considerar a regularização da situação dos migrantes irregulares de longa duração.\n\n\n## 1. INTRODUÇÃO\n#### 1.1. Metodologia e agradecimentos\n\nEste estudo baseia-se na revisão documental da legislação angolana, documentos da ONU, dados quantitativos\ne históricos e na investigação realizada em Angola entre meados de Novembro de 2019 e finais de Fevereiro de\n2020. O Ministério da Justiça e Direitos Humanos, o Serviço de Migração e Estrangeiros no Ministério do Interior,\n\n- Ministério das Relações Exteriores, e o Ministério da Acção Social, Família e Promoção da Mulher partilharam\ninformações valiosas sobre políticas, situações e números relativos à apatridia em geral e pessoas em risco de\napatri", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000443", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "dados quantitativos\ne históricos", "probe_tag": "confusion", "probe_score": 0.6627352833747864, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 812, "end": 844, "key": "reliefweb:000443:6:1:0", "source": "camp2", "luna_reason": "Quantitative and historical data are declared as sources underpinning the study.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "its Public Expenditure\nTracking Survey (PETS)\n\nscorecard inproves each\nsemester\n\n\n\n**Project Components /** **Inputs:** **(budget for** each Project reports: (from Components to\nSub-components: component) Outputs)\n\n\n\n1. Community Driven - US$ 28.0 million (IDA $25.0 <sup>- M&E data</sup> - Cormnunities emnpowered\n\n\n\n**Program** (CDP) million) - Quarterly progress reports; and responsible for\nimplementing sub-projects;\n\n                                                  - Implemnenting partners <sup>are</sup>\ncomnpetent to support\n**2.** Pilot and Special\n\n\n\n**Programs in** Newly cormmunities;\n\n                                                - Implementing partners\n**Accessible** **Areas**\n\n                - US$ 2.0 mnillion (ODA <sup>$1.75</sup> participate in capacity building\n\n\n\n**(a)** **Rural Public Works** million) activities;\n\n                - US$ 2.0 million (IDA <sup>$1.75</sup>                - Operations Manual and\n\n\n\n**(b)** **Shelter** Program **for** million) annexed Handbooks for Direct\n\nFinancing to Communities <sup>and</sup>\n**Vulnerable** **Groups**\n\n               - US$ 10.0 million (IDA <sup>$6.5</sup>                - NaCSA and IDA Public Works are thorough,\n\n\n\n3. **Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**In", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000017", "page": 32, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Public Expenditure\nTracking Survey", "probe_tag": "confusion", "probe_score": 0.8166483640670776, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 4, "end": 38, "key": "refugee_pads:000017:32:0:0", "source": "camp2", "luna_reason": "Named Public Expenditure Tracking Survey is explicitly referenced.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " newly\nestablished and young women entrepreneurs and provide spaces and opportunities for women entrepreneurs to\nenhance their voice and agency in legal and policy processes. For refugees, the local platform chapters will target specific\nbarriers to voice and agency (such as language and specific cultural norms) and the additional barriers women refugees\nhave to business information (such as lack of access to formal business channels, mentors, and inputs). This\nsubcomponent implementation is aligned to the PDM Pillar 5: Community Mobilization and Mindset Change.\n\n35. **The subcomponent will finance:** (a) mobilization costs for the establishment of local platform chapters (20–25\nwomen per platform); (b) establishment of a digital platform for women entrepreneurs and its linkage to other existing\n\n\n34 The poverty incidence (headcount ratio) figures are based on the Uganda National Household Survey (UNHS) 2019/2020.\n\n\nPage 17 of 77", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 21, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Uganda National Household Survey", "probe_tag": "confusion", "probe_score": 0.8860428333282471, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 877, "end": 909, "key": "jdc_operational:000025:21:2:0", "source": "camp2", "luna_reason": "Survey data underpin reported poverty incidence figures.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " the Panel discovered significant communication issues, creating\nradically different understandings of what had been decided or agreed, and why. Whether this\ncould be attributed to language problems in the absence of using the Maa language, the failure to\nadequately disclose critical documents, issues of representation, or other reasons, the fact remains\nthis caused major confusion and contributed to mistrust towards the authorities, as well as tension\nwithin the community.\n\n174. Among good-practice approaches and related Bank Policies that were not followed, or\ncould have been followed more rigorously, several stand out. They constitute lessons for the future:\n\n     - The use of the affected peoples’ language, in this case the Maa language, in the conduct\nof the census and other consultations with the community, including in written\ndocumentation, such as the RAP and census results.\n\n     - Inclusion of traditional structures of authority, specifically the group of Elders.\n\n     - Presentation of wider options to PAPs, for example with regard to housing construction\ntypes, materials, and size, to fit different preferences better.\n\n     - Implementation of necessary livelihood restoration programs.\n\n     - Establishment of a comprehensive baseline of key socioeconomic indicators covering\nall PAPs, and a monitoring system to assess progress in achieving resettlement goals\nthroughout execution of the resettlement plan and to permit adjustments as needed.\n\n\n175. Another factor of relevance and special interest to the PAPs is an expected new Kenyan\nlaw regarding the benefit sharing of certain commercial investments. While this is part of the\n\n\n49", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010946", "page": 57, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "census results", "probe_tag": "confusion", "probe_score": 0.07089398801326752, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 881, "end": 895, "key": "fcv_pads_east_africa:010946:57:1:0", "source": "camp2", "luna_reason": "Existing census results are explicitly referenced as community documentation.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "IEA, 2020. CO2 Emissions from fuel combustion database. [online]. Available at:\nhttps://www.iea.org/data-and-statistics/data-product/co2-emissions-from-fuel-combustion-highlights\n\n[accessed 14 June 2021].\n\n\nILO, 2019. _<mark>Skills for a greener future: A global view” based on 32 country studies</mark>_ <mark>. Geneva: International Labour</mark>\n<mark>Organization.</mark>\n\n\nIPCC, 2014: Summary for Policymakers. In: Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani,\nS. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S.\nSchlömer, C. von Stechow, T. Zwickel and J.C. Minx, eds. _Climate Change 2014: Mitigation of Climate Change._\n_Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change._\nNew York: Cambridge University Press.\n\n\nIPCC, 2019: Summary for Policymakers. In: P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte,\nH.- O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S.\nLuz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M. Belkacemi,\nJ. Malley, eds. _Climate Change", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001287", "page": 43, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "CO2 Emissions from fuel combustion database", "probe_tag": "confusion", "probe_score": 0.41483068466186523, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 11, "end": 54, "key": "prwp:001287:43:0:0", "source": "camp2", "luna_reason": "Bibliographic database entry without shown data use in the passage.", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": "##### **Monitoring of Refugee Inclusion in the National System Indicator 22 .**\n\n|Activity|2020|2021|2022|2023|2024|\n|---|---|---|---|---|---|\n|Refugee education reflected five-year - ESDP at national and sub-<br>national level[1].|0|Target 6 plans<br>(1 national and<br>5 sub-national.||||\n|Refugees education reflected yearly (sub-national plans scale-1-5)|0|Target 5|Target<br>5|Target 5|Target 5|\n|Refugee education reflected in education law/ MoE strategies|0|X||||\n|Budget allocation reflected in MoE/REB plan for refugee education.<br>(regional hosting) Scale 1-5.|0|5|5|5|5|\n|Camp-based schools  receiving support from REB: Inspection,<br>supervision, EMIS data collection, standard school classification|80%|90%|100%|100%|100%|\n|Refugee schools fully managed at field level by REB/MoE (no parallel<br>education systems)|1|2|4|5|5|\n\n\n\n22 The indicators on the table will measure strategic objective 1: Inclusion of refugee education in the National system.", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000503", "page": 39, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "EMIS data", "probe_tag": "confusion", "probe_score": 0.07415251433849335, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 660, "end": 669, "key": "reliefweb:000503:39:0:0", "source": "camp2", "luna_reason": "Span is embedded in a table indicator describing support activities.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "br>**procurement performance:**<br> <br>Piloting individual performance contract approach in the<br>procurement system<br> <br>RRI to support procurement process performance in the pilot|**3.3m**||\n|**Improved**<br>**decision-**<br>**making process**<br>**based on**<br>**reliable**<br>**statistical data**|**Component 4: Enhancing the use of statistics**<br>**for policy making**<br> <br>Timely production of reliable statistical<br>data<br> <br>Statistics widely disseminated|**Subcomponent 4.1: Improvement of poverty-related data**<br> <br>Production of a series of Poverty Notes (based on ECAM 4 and high-<br>frequency surveys)<br> <br>Production of ECAM 5<br> <br>Analysis of the population census<br> <br>Production of the LFS|**5.4m**||\n|**Improved**<br>**decision-**<br>**making process**<br>**based on**<br>**reliable**<br>**statistical data**|**Component 4: Enhancing the use of statistics**<br>**for policy making**<br> <br>Timely production of reliable statistical<br>data<br> <br>Statistics widely disseminated|**Subcomponent 4.2: Strengthening the national accounts production**<br> <br>Quarterly production of improved national accounts", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 82, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "statistical data", "probe_tag": "confusion", "probe_score": 0.1435, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 290, "end": 306, "key": "sample:refugee_pads:000044:82:1:0", "source": "gold", "luna_reason": "Generic statistical data is mentioned without an attributed finding or concrete analysis.", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "ECAM 4", "probe_tag": "confusion", "probe_score": 0.4584, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 599, "end": 605, "key": "sample:refugee_pads:000044:82:1:1", "source": "gold", "luna_reason": null}, {"text": "ECAM 5", "probe_tag": "confusion", "probe_score": 0.0927, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 661, "end": 667, "key": "sample:refugee_pads:000044:82:1:2", "source": "gold", "luna_reason": null}, {"text": "population census", "probe_tag": "confusion", "probe_score": 0.7417, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 693, "end": 710, "key": "sample:refugee_pads:000044:82:1:3", "source": "gold", "luna_reason": null}, {"text": "LFS", "probe_tag": "keep", "probe_score": 0.9679, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 738, "end": 741, "key": "sample:refugee_pads:000044:82:1:4", "source": "gold", "luna_reason": null}]}
+{"text": "**The World Bank**\nUganda Skills Development in Refugee and Host Communities (P176263)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n1 See “Tackling the Demographic Challenge in Uganda (World Bank, 2020).\n2 See https://www.worldbank.org/en/country/uganda/overview.\n[3 State of Skills, ILO, 2020 (https://www.ilo.org/skills/pubs/WCMS_736694/lang--en/index.html)](https://www.ilo.org/skills/pubs/WCMS_736694/lang--en/index.html)\n4 This figure is higher than the regional average of 80%.\n5 United Nations Office for Coordination and Human Affairs. https://www.unocha.org/southern-and-eastern-africarosea/uganda#:~:text=Uganda%20is%20currently%20host%20to,refugees%20are%20from%20South%20Sudan.\n6 World Bank. 2019. Informing the Refugee Policy Response in Uganda. Results from the Uganda Refugee and Host Communities. 2018\nHousehold Survey.\n7 REACH household survey for the World Bank, 2019.\n8 World Bank. 2019. Informing the Refugee Policy Response in Uganda. Results from the Uganda Refugee and Host Communities. 2018\nHousehold Survey.\n9 Ibid.\n10 World Bank. 2019. Informing the Refugee Policy Response in Uganda. Results from the Uganda Refugee and Host Communities.\n2018 Household Survey.\n11 Ibid.\n12 Monitoring Social and Economic Impacts of COVID-19 on Refugees in Uganda: Results from the High-Frequency Phone Survey. 2021.\nWorld Bank and Uganda Bureau of Statistics (UBOS).\n13 The GoU’s TVET Policy (2019) presents a policy vision to prepare a “coordinated, labour-market responsive TVET system", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000016", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "REACH household survey", "probe_tag": "confusion", "probe_score": 0.8058637380599976, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 812, "end": 834, "key": "jdc_operational:000016:12:0:1", "source": "camp2", "luna_reason": "Named household survey cited as an existing source.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "also be provided to properly levy, collect and account for local duties and taxes. NaCSA staff would be\ngiven an opportunity to visit Community Driven Development Projects in comparable countries to\ncapitalize on their experiences. Regional and district line ministry staff would be trained in community\nmobilization, conflict resolution, social capital building, and technical appraisal skills.\n\n\n(b) Substantial IEEC activities linked to the various sub-projects are envisaged. These activities\nwould be undertaken using existing IEC materials endorsed by the various line ministries. For example,\nin the case of the rehabilitation of a health post, IEC messages could be envisaged to inform the\npopulation on the proper use of insecticide treated bed nets as a means of preventing malaria.\n\n\n(c) Monitoring and evaluation at the community, district, regional and central levels would be\ngiven high priority, and linked regularly and directly with NaCSA decision making on NSAP policy,\nstrategy and operational matters. These activities would be directly undertaken, or commissioned by,\nstaff of NaCSA's Planning, Monitoring and Evaluation Directorate. The Project Design Matrix (logical\nframework, Annex 1) would form the basis for monitoring NSAP outputs, outcomes and impact. An\nassessment of project status would accompany each NaCSA work program and budget submitted\nsemi-annually to the NaCSA Board. Other M&E activities would include a pre-project Social\nAssessment; establishment of NSAP baseline data (in conjunction with the collection of data for the\nCRRP Implementation Completion Report); social assessments during implementation; annual technical\naudits; beneficiary assessments; incorporation of NaCSA into GOSL's semi-annual public expenditure\ntracking surveys (PETS); and independent impact assessments.\n\n\nIn addition to conventional sub-project monitoring and evaluation (incorporated in the\nsub-project cycle as outlined in the Operations Manual), a pilot participatory monitoring and evaluation\nsystem would be introduced in a representative sample of the predominant types of CDP sub-projects.\nBeneficiary communities would identify quantitative and qualitative indicators", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017697", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "public expenditure\ntracking surveys", "probe_tag": "confusion", "probe_score": 0.30910515785217285, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1743, "end": 1778, "key": "fcv_pads_east_africa:017697:36:0:1", "source": "camp2", "luna_reason": "Planned incorporation into future monitoring activities, not cited existing survey data.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": " in the IFLS was calculated based\non highest grade completed in an education level. Primary completion takes the value of 1 if a child has completed 6 or more years of schooling and\n0 otherwise. Family background is measured by father’s years of schooling. The Inverse Probability Weighting (IPW) estimates are calculated using\n1975 district level density interacted with time trend. Data sources: Indonesia’s full count census 2000, Duflo (2001), IFLS and IFLS-East.\n\n\n70", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000774", "page": 72, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "IFLS", "probe_tag": "confusion", "probe_score": 0.598488986492157, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 448, "end": 452, "key": "prwp:000774:72:3:1", "source": "camp2", "luna_reason": "Named survey listed as a data source for the analysis.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "> 8<br>_ .._<br> 36<br> 38<br> 21<br> 5<br> 13<br> 27<br> 2<br> 7<br> 3|\n\n\n\n**<mark>Total (44)</mark>** **<mark>360,950 443,590 488,020 596,660 866,020 2,755,240</mark>** **<mark>45%</mark>** **<mark>0.7</mark>** **<mark>2.3</mark>**\n\n\nNotes\n\nSource: Governments, UNHCR. See notes on next page for information on applications registered with UNHCR.\nThis table includes final data for 2010 to 2013 and provisional data for 2014. In the following tables, the 2013 figures are based on the monthly database. This results in some discrepancies.\nAll figures in this table have been rounded to the closest ten.\nA dash (“-”) indicates that the value is zero or not available. Two dots (“..”) indicate that the value is not available.\n\n- This refers to Gross Domestic Product (GDP), Purchasing Power Parity (PPP), per capita.\n\n\n**20** UNHCR Asylum Trends 2014", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000195", "page": 19, "chunk": 9, "split": "holdout_annotate", "spans": [{"text": "monthly database", "probe_tag": "confusion", "probe_score": 0.6201741099357605, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 487, "end": 503, "key": "reliefweb:000195:19:9:0", "source": "camp2", "luna_reason": "2013 figures are explicitly based on this existing database.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "**The World Bank**\nEthiopia Digital ID for Inclusion and Services Project (P179040)\n\n|Col1|open-source data set|\n|---|---|\n|Methodology for Data Collection|Heat map of all registration locations|\n|Responsibility for Data Collection|NIDP|\n|**Improving service delivery**|**Improving service delivery**|\n|**Number of entities using Fayda services for improved delivery of benefits and services (Number)**|**Number of entities using Fayda services for improved delivery of benefits and services (Number)**|\n|Description|Number of entities that are using at least one of the several services offered by Fayda to verify<br>the identity of their beneficiaries/clients, including but not only unique number seeding, yes/no<br>authentications, and sharing of ID attributes|\n|Frequency|Biannual|\n|Data source|Number of API connections to the Fayda Platform|\n|Methodology for Data Collection|Fayda data analytics platform|\n|Responsibility for Data Collection|NIDP|\n|**Number of whom are public entities (Number)**|**Number of whom are public entities (Number)**|\n|Description|Number of public entities that are using Fayda services that are a state, regional, or local<br>authority; a body governed by public law; or a private entity mandated to provide public services|\n|Frequency|Biannual|\n|Data source|Number of API connections to the Fayda Platform|\n|Methodology for Data Collection|Fayda data analytics platform|\n|Responsibility for Data Collection|NIDP|\n|**Number of who are private entities (Number)**|**Number of who are private entities (Number)**|\n|Description|Number of private entities using Fay", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000005", "page": 41, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Ethiopia Digital ID for Inclusion and Services Project", "probe_tag": "confusion", "probe_score": 0.11723528057336807, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 73, "key": "refugee_pads:000005:41:0:0", "source": "camp2", "luna_reason": "Project title, not a cited or used data resource", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n**ANNEX 2: Refugees and Host Communities**\n\n\n\n1. As of December 2021, Chad was hosting more than 560,000 refugees and asylum seekers settled\nin 20 camps and a city in the East, South, and Lake Chad regions across nine provinces, as detailed in Table\n1.1 and the UNHCR map provided at the end of the annex. Five provinces host about 80 percent of the\nrefugees. These include four eastern provinces: Ouaddai (26 percent), Wadi Fira (24 percent), and Sila (12\npercent), Ennedi Est (6 percent), and a southern province: Logone Oriental (11 percent). In the East,\naround 376,000 Sudanese refugees are settled along the border having fled violence in Darfur, many living\nthere for more than a decade. In the south, Chad hosts around 123,880 refugees from the Central African\nRepublic, the majority of whom have been in exile for more than a decade. In Lake Chad, some 19,650\nNigerian refugees who fled Boko Haram now reside in the area on Chad’s western border with Nigeria,\nNiger, and Cameroon. More recently, intercommunity tensions led to the arrival (August 2021–January\n2022) of about 35,900 refugees from Cameroon. An additional number of about 4,970 refugees of\ndifferent origins live scattered in the different camps as well as around 406,570 IDPs in the Lake Chad\narea. Camps are managed by CNARR and the UNHCR.\n\n2. CNARR works with the UNHCR and other partners to register new arrivals, issue documentation,\nand administer refugee camps and sites. It also serves as a technical adviser to the GoC on durable\nsolutions, notably on voluntary repatriation agreements or resettlement. Refugees receive support from\na variety of donors including the World Bank; European Union’s Humanitarian Office; the United States", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 72, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR map", "probe_tag": "confusion", "probe_score": 0.8706690669059753, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 329, "end": 338, "key": "jdc_operational:000051:72:0:0", "source": "camp2", "luna_reason": "UNHCR map supports the reported refugee locations and distribution.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "u>11. Other Information</u>**\n\nThe following data sources, project background reports and studies, relevant publications, and other items\nwill be made available to the consultant:\n\n  - Project Concept Note\n\n  - Pre-feasibility Studies\n\n  - Feasibility studies\n\n  - Population and Land Use Projections,\n\n  - Land Use Plans\n\n  - Drainage and Flood Control Service Needs Surveys,\n\n  - Traffic Management Studies\n\n**<u>11.1 Equipment, Logistics and Facilities</u>**\nThe Consultant shall be responsible for the provision of all the necessary resources to carry out the\nServices; and shall make arrangements for the establishment of office, supporting office equipment and\nfurniture, vehicles, accommodation, utilities, communications, and any other required resources.\n\n**<u>11.2 Duration and Timing of the Services</u>**\nThe time period required for the provision of the services is envisaged to be Four months from the date of\nthe contract.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014297", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Drainage and Flood Control Service Needs Surveys", "probe_tag": "confusion", "probe_score": 0.12944230437278748, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 327, "end": 375, "key": "fcv_pads_east_africa:014297:9:1:1", "source": "camp2", "luna_reason": "Survey materials are listed for future consultant access, not shown as used.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "1999)) most textile mills were founded by foreigners, who owned 62%\n\n\nof wholesale textile trade in Rio, and foreigners soon dominated the manufacturing activities\n\n\nclosely linked to their commercial activities. In both S˜ao Paulo and Rio, the first electricity\n\n\ngenerating companies were founded by foreigners. Birchal (1999) documents that Juis de\n\n\nFora, Minas Gerais, a major steel and manufacturing area from 1858-1912, immigrants were\n\n\nresponsible for 66% of industries (Birchal, 1999, p.26).\n\n\nIn Chile, 70% of steam powered businesses were started by immigrants, roughly 12 times\n\n\ntheir share in the male population. Again, this conforms with other historical accounts.\n\n\nSilva Vargas (1977a) notes that “the lack of entrepreneurs and of qualified national workers\n\n\n6We are very grateful to Richard Sutch for the census sample data and to he and Larry Neal for extremely\nhelpful discussions.\n\n7", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001790", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "census sample data", "probe_tag": "confusion", "probe_score": 0.5022915601730347, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 826, "end": 844, "key": "prwp:001790:9:1:0", "source": "camp2", "luna_reason": "Existing census sample data are acknowledged as a research source.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " characterization of the\nIDP population by a variety of factors, has national\ncoverage, and has temporal and geographical levels\nof disaggregation.\n\n\nSince 2012, the GEIH migration module has been\nexpanded and modified to allow better characterization\nof the population (DANE, 2019). As of mid-2020, the\n\n\n\n**4. COUNTRIES IN FOCUS**\n\n\nGEIH was being redesigned, and two more questions\nwere expected to be added to the migration module.\n\n\nThe National Population and Housing Census (CNPV,\nSpanish acronym) has the purpose of counting\nand characterizing the universe of persons and\nhouseholds residing in Colombia, and it is the\nstatistical operation with the greatest possibilities\nto obtain disaggregated data by population groups,\nbased on their location, gender, migration status,\nand other characteristics. Thus, the CNPV allows the\ngeneration of statistical information that supports\ndecision-making in a variety of areas relevant to the\ninterests for FDPs and it is useful to evaluate the\nscope of development policies targeting specific\ngroups of the population (DANE, 2019).\n\n\nThe official methodological document of CNPV 2018\nconsiders that the census, as a statistical operation\nthat reaches all parts of the country, may be quite\nappropriate for collecting recent information on\ninternal mobility, which cannot be captured through\nother surveys. The variables incorporated into the\nCNPV 2018 allowed for the characterization of the\ninternally displaced population and international\nmigrants (DANE, 2018).\n\n\nIn 2018, the implementation of digital technology\nstrengthened DANE’s data collection processes\nand helped facilitate census processing, especially\nwith the first electronic census (eCensus). Other\ninnovations implemented in this census included the\nprocess of consultation and concertation with ethnic\ngroups, the monitoring and control of the operation,\nand the use of administrative records as input to\nevaluate the census.\n\n\nIn addition to the CNPV and the GEIH, the following\nstatistical operations capture information on IDPs:\n\n**•** Production and analysis of annual migration\nstatistics\n\n**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000141", "page": 25, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "administrative records", "probe_tag": "confusion", "probe_score": 0.19218817353248596, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1888, "end": 1910, "key": "reliefweb:000141:25:1:2", "source": "camp2", "luna_reason": "Administrative records are used as input to evaluate the census.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private\nsector participation in education.\n\n\n_6.3 How does the project involve consultations or collaboration with NGOs or other civil society_\n_organizations?_\n\n\nThe National Educational Forum consulted all stakeholders including NGOs and civil society during\nthe initial preparation. In addition, the project foresees the increased involvement of parent\nassociations or community-based associations in the management of project activities on the ground\n(i.e., operations & maintenance).\n\n\n_6.4 What institutional arrangements have been provided to ensure the project achieves its social_\n_development outcomes?_\n\n\nThe DGEN will be responsible for monitoring the gender gap in enrollment issues, and the gap\nbetween the poorest and the richest quintiles, and related education services available to them. The\ndata collection on enrollment will be strengthened by the capacity building support provided to the\nMinistry of Education's planning unit - thus over time these issues can be effectively monitored.\nTriggers are included in the APL phasing to ensure that various social development goals are met e.g.\ndecreasing the enrollment gap between the rich and the poor, decreasing the gender gap and increasing\ncommunity participation in school management.\n\n\n_6.5 How will the project monitor performance in terms of social development outcomes?_\n\n\nThe MOE planning unit will monitor enrollment paying attention to gender gaps, socioeconomic gaps\n\nand performance of students by socioeconomic class through use of surveys of students.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 24, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "surveys of students", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1811, "end": 1830, "key": "refugee_pads:000147:24:1:0", "source": "camp2", "luna_reason": "Future project monitoring proposes using student surveys; no existing finding is cited.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Verification Protocol Table: Performance-Based Conditions|Col2|\n|---|---|\n|<br>**PBC 1**|<br>Number of newly constructed, equipped and operationalzed lower secondary schools and schools benefiting from<br>additional infrastructure <br>|\n|**Description**|<br>Number of newly constructed and equipped lower secondary schools and schools benefiting from additional infrastructure<br>furnished, equipped and with teachers deployed by the MoES, The PBC 1 is attached to construction of school<br>infrastructure, provision of furniture for classes, equipment, instructional materials, and new teachers.|\n|**Data source/ Agency**|MoES monitoring reports|\n|**Verification Entity**|Independent Verification Agent (IVA) <br>|\n|**Procedure **<br> <br>|The PBC include the following Results: finalization of selection of construction sites at Year 1; procurement for construction<br>concluded at Year 1 & 2; construction commences at Year 1 & 2; construction completed in batches (Year 2 & 3); quality<br>control of completed construction undertaken (Year 3 & 4); and schools fully operationalized with furniture and equipment<br>installed and teachers deployed (Year 3, 4 & 5). The facilities will be utilized as they are completed from Year 3. Details<br>provided in the PAD PBC section.<br> <br>|\n|<br> <br>**PBC 2**|<br>Number of Schools with Child Friendly School Program implemented <br>|\n|**Description**|The PBC 2 is attached to Component 1 and is specifically on subcomponent 1.2. dealing with improving school safety and", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 63, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MoES monitoring reports", "probe_tag": "confusion", "probe_score": 0.3248350918292999, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 717, "end": 740, "key": "jdc_operational:000018:63:0:0", "source": "camp2", "luna_reason": "Source entry appears as a fragment inside a verification protocol table.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": "**Annex 3. Economic Costs and Benefits**\n\n\nA standard ERR was not estimated in the SAR, as is often the case for projects with a primary emphasis on\ncapacity strengthening and institutional reform. The lack of economic data from monitoring and evaluation\nof various project activities makes _ex post_ estimation of an ERR difficult, should it be deemed desirable.\nThe section below provides indicative socio-economic data and a discussion of quantitative results achieved\ncompared to the potential benefits highlighted in the SAR.\n\n\nAmong the gross benefits expected in the SAR are avoided losses related to decline in fishery as a result of\nover-fishing and deterioration in water quality, impacts of water hyacinth infestation, poor quality of water\nsupply for domestic and animal uses, and continued degradation of wetlands.\n\n\n**Economic Importance of the Resource:**\nThe Lake Basin economy is driven by Agriculture and Fisheries (70 percent), including a number of cash\ncrops (including fish exports) and a high level of subsistence fishing and agriculture. It produces in the\norder of USD 5 billion annually (2000-04), increasing from the estimated USD 3-4 billion, in 1996.\nPopulation in the Lake Basin, in that time, has gone up from 25 million to an estimated 30 million people,\nof whom 3 million depend directly or indirectly on fish and fisheries. General standards of living are\nbetween USD 90-270 per capita per annum (based on national figures). It is estimated that fisheries\ncontribute about 3 percent to the riparian economies. The quality of the environment and the status of the\nnatural resources are therefore critical factors in the maintenance and growth of incomes, livelihoods and\npoverty alleviation opportunities in these countries.\n\n\n**Fisheries Sector**\nFish production for the whole lake is currently estimated to be between 400,000 to 600,000 metric tons\nworth USD 400 to 600 millions annually. It is estimated that a majority of this production is artisanal\nfishery. In Uganda, 200,000", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010748", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "economic data", "probe_tag": "confusion", "probe_score": 0.34635496139526367, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 210, "end": 223, "key": "fcv_pads_east_africa:010748:36:0:0", "source": "camp2", "luna_reason": "States missing monitoring data without directly using an attributed finding.", "drop_reason": "availability", "specificity": "vague"}, {"text": "socio-economic data", "probe_tag": "confusion", "probe_score": 0.3394075334072113, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 402, "end": 421, "key": "fcv_pads_east_africa:010748:36:0:1", "source": "camp2", "luna_reason": "Generic data reference lacks an attributed finding tied directly to it.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": " <u>[.pe/sala_situ](https://covid19.minsa.gob.pe/sala_situacional.asp)</u> which include variables for age and\n\n<u>[acional.asp](https://covid19.minsa.gob.pe/sala_situacional.asp)</u> sex, among other COVID-19-related\n\ndata and statistics.\n**Philippines** 1,116 Yes June Department <u>[https://bit.ly/](https://bit.ly/DataDropPH)</u> The Philippines' Department of\n18, of Health <u>[DataDropPH](https://bit.ly/DataDropPH)</u> Health shares to the public daily\n2020 metadata of COVID-19 cases\n\n\n\nMinistry of\nHealth\n\n\n\n<u>[https://covid](https://covid19.minsa.gob.pe/sala_situacional.asp)</u>\n<u>[19.minsa.gob](https://covid19.minsa.gob.pe/sala_situacional.asp)</u>\n<u>[.pe/sala_situ](https://covid19.minsa.gob.pe/sala_situacional.asp)</u>\n<u>[acional.asp](https://covid19.minsa.gob.pe/sala_situacional.asp)</u>\n\n\n\n**Philippines** 1,116 Yes June Department <u>[https://bit.ly/](https://bit.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000211", "page": 27, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "2020 metadata of COVID-19 cases", "probe_tag": "confusion", "probe_score": 0.1646183729171753, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 460, "end": 491, "key": "prwp:000211:27:2:0", "source": "camp2", "luna_reason": "Table-cell metadata description, not evidence of data use.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "Looking beyond the current situation, the full socioeconomic impact of COVID-19 will\n\n\nplay out over the medium- to long-term, especially for developing countries. This\n\n\nhighlights the need for robust tracking mechanisms that collect regular and reliable\n\n\ndata on vulnerable groups, following common standards. High-frequency phone\n\n\nsurveys with multiple rounds, such as those presented in this paper, are examples of\n\n\nsuch a data collection mechanism that can produce much-needed data (as a panel or\n\n\nrepeated cross-section) on how the forcibly displaced fare over time and space in\n\n\nvarious settings. Once harmonized, the data from these surveys will allow for cross\n\ncountry and pooled analyses, and hence can inform global comprehensive\n\n\napproaches to alleviate the socioeconomic repercussions of the pandemic for the most\n\n\nvulnerable.\n\n\nIn most countries affected by forced displacement, including in the eight surveyed in\n\n\nthis paper, those forcibly displaced are rarely represented in national statistics. This is\n\n\nfrequently due to a variety of—often practical—capacity reasons impeding national\n\n\nstatistical offices from addressing this particular population group through their regular\n\n\nwork. For humanitarian and development policy, inclusion of FDPs is a conscious step\n\n\nthat these offices need to take—notwithstanding the technical and financial challenge\n\n\nit poses—over their regular approaches to population statistics. Targeted support and\n\n\ncapacity building from the humanitarian and development community, working more\n\n\nclosely with national statistical offices, will allow for greater visibility of FDPs in\n\n\nsocioeconomic data.\n\n\nThe interim findings in this paper constitute a springboard to deeper analysis through\n\n\ndiscussion of potential drivers of the observed results, analysis of the country-specific\n\n\npolicies and responses in the pandemic in coordination with the socioeconomic\n\n\nmicrodata collected, and review of the trends in these and more countries as\n\n\nharmonized data become available. Important insights could be gained by further\n\n\npursuing questions such as: the degree to which initial economic and social conditions\n\n\nare associated with FDP and host outcomes and convergence; exploration of the\n\n\nexplanatory factors of the (few) examples of positive outcomes or faster recovery; the", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000604", "page": 42, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "socioeconomic data", "probe_tag": "confusion", "probe_score": 0.32440951466560364, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1644, "end": 1662, "key": "reliefweb:000604:42:0:0", "source": "camp2", "luna_reason": "Generic data reference lacks an attributed finding or concrete claim.", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "socioeconomic\n\n\nmicrodata", "probe_tag": "confusion", "probe_score": 0.41359907388687134, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1911, "end": 1936, "key": "reliefweb:000604:42:0:1", "source": "camp2", "luna_reason": "Mentioned as input to potential future analysis, not currently used evidence.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "investments include roads, solid waste management, street lighting, greenery, servicing industrial land and\ntourist sites, parks for micro-enterprises and cottage industries, youth centers and incubators, etc.\nCompliance with the investment menu will be a minimum condition and be verified by the APA each\nProgram year. If a municipal LG has not invested Program funds in full compliance with the investment\nmenu, it will be sanctioned in the following year. Municipal LGs will be required to identify and prepare\ninvestments in a participatory manner and use the screening tools developed under USMID and the new\nDDEG guidelines. Participatory approaches and proper planning and budgeting will be promoted through\nthe annual assessments, and municipal LGs will be incentivized to involve the divisions, the municipal\ndevelopment forum as well as the private sector in the prior dialogue on planning and budgeting as well as\nmonitoring of execution.\n\n10. **Institutional strengthening for infrastructure provision will continue in USMID AF, targeting**\n**both the participating municipalities as well as MoLHUD and MDAs** . Firstly, the participating\nmunicipalities will receive grants to strengthen their capacities to execute their mandates for delivering a\nwide range of urban infrastructure and services. Each municipal LG will be required to develop a\ncomprehensive institutional strengthening plan that will respond to its capacity gaps especially those that\nwill be unearthed by the annual assessments under the Program and to ensure that the plan is executed on\neligible expenditures. The activities will continue to focus on: tooling, discretionary capacity building\n/institutional strengthening, and career development. US$ 10 million will be provided as Municipal\nInstitutional Strengthening Grant (ISG) as part of the overall DDEG allocation. Secondly, MoLHUD, which\nis responsible for the oversight of Program implementation as well as other MDAs, will also receive support\nto perform their mandate for urban development as well as for providing supply driven institutional support\nto the municipalities for activities which can be pooled together for economies of scale and that cut across\nall municipalities", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000168", "page": 55, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "annual assessments", "probe_tag": "confusion", "probe_score": 0.27272140979766846, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 719, "end": 737, "key": "refugee_pads:000168:55:0:0", "source": "camp2", "luna_reason": "Refers to program assessments used as future institutional planning mechanisms.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": " moves to higher\nlevels, up to upper secondary: about 70 percent of children attending pre-primary were at the appropriate age; 63\npercent for primary; 37 percent for lower secondary; and 22 percent for upper secondary.\n\n\n3 United Nations High Commissioner for Refugees (UNHCR), Operational Data Portal.\n4 Pre-primary education services are the responsibility of MFPPE. However, the Ministry of National Education and Civic Promotion (MENPC) is\nresponsible for pre-primary pedagogy.\n5 46 percent were public schools and 15 percent private (Statistics Education Yearbook 2019-2010)\n\n\nAug 03, 2021 Page 4 of 27", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 3, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Statistics Education Yearbook 2019-2010", "probe_tag": "confusion", "probe_score": 0.46737879514694214, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 540, "end": 579, "key": "jdc_operational:000009:3:2:0", "source": "camp2", "luna_reason": "Named yearbook cited as source for school ownership percentages.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "did not have significant impact on the outcome indicators as they were minor\ninterventions (in terms of scope as well as funding) as compared to the others.\n\n\n**3.3** **Efficiency**\n\n**_Rating: Substantial_**\n\n105. The Bank’s disbursement record shows that the project managed to complete its\nplanned activities with a total cost of about SDR 9.87 million (equivalent of US$14.9\nmillion) against the budget for both credit and grant, after the reallocation of SDR 4.46\nmillion (equivalent of US$ 7 million) to the Global Food Crisis Initiative. The\ndisbursement rate as of April 29, 2013 was 92percent. Even though resources were\nreduced from the project budget, the devaluation of the local currency by about 20percent\nduring the project implementation period had provided more Ethiopian Birr per one\nUS$ to carry out project activities. In addition, there was some saving from the\ncompensation payments under the Voluntary Retrenchment Plan (VRP) as the number of\nemployees affected under the plan was lower than originally anticipated. Even though the\nproject was extended for additional 18 months, the operating cost for the project was\nwithin budget and only 81percent of the allocated budget was utilized at the end of the\nproject. The cost efficiency of running the project may be as a result of prudent utilization\nof funds and/ or the government’s contribution for project management.\n\n**Component one –** _Accelerating the Implementation of privatization program_\n\n106. For the economic analysis done during the design, the PAD indicates that due to\nlack of reliable time series data, proxy estimates are used when explicit prices and\ncalibrations factors were not available. Pre-privatization data collected from the\nPrivatization and Public Enterprises Agency (PPESA) does not relate to the numbers used\nin the analysis during design. To carry out a robust quantitative economic analysis for\nthis component for the ICR, complete", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013446", "page": 35, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "time series data", "probe_tag": "confusion", "probe_score": 0.6426217555999756, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1577, "end": 1593, "key": "fcv_pads_east_africa:013446:35:0:0", "source": "camp2", "luna_reason": "Data absence motivates use of proxy estimates in the economic analysis.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " Labor Organization.** “International standard classification of occupations: Structure, group\ndefinitions and correspondence tables.” _International Labor Office, Geneva_ (2012).\n\n**National Institute of Statistics and Censuses.** “Encuesta de Hogares de Propósitos Múltiples.” San Jose,\nCosta Rica (2009).\n\n**National Institute of Statistics and Censuses.** “Encuesta Nacional de Hogares.” San Jose, Costa Rica\n(2020).\n\n\n48", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002138", "page": 49, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Encuesta de Hogares de Propósitos Múltiples", "probe_tag": "confusion", "probe_score": 0.5640513896942139, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 233, "end": 276, "key": "prwp:002138:49:2:0", "source": "camp2", "luna_reason": "Bibliographic entry naming a survey without showing substantive data use.", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": "nie par le gouvernement local (gouvernement de Borno) à la réhabilitation\ndes logements. Certains étaient retournés s'inscrire pour obtenir de l'aide. En effet, il y a une liste d'attente\ngérée par un département qui visite les logements affectés (pour prendre des photos et enregistrer d'autres\ninformations clé). Il y a également eu des rapports sur la réhabilitation de logements de la part de la CroixRouge. Malgré le fait que la plupart des réfugiés aient perdu leur documentation relative au LTP, ils estimaient\nqu’il n’y aurait aucun problème à prouver leur propriété par rapport au bien concerné. A l'instar des personnes\ndéplacées, il n'y avait pas de préférence marquée pour l'aide à la réhabilitation du logement ou aux activités\nde subsistance parmi les réfugiés. La plupart des réfugiés n'ont pas pu sauver leurs biens mobiliers, bien que\ncertains réfugiés aient déclaré avoir été contactés par l'armée afin de rentrer et récupérer leurs biens (réfugiés\nde Mallam-Fatori à Ngagam).\n\n<u>4) Perte de la documentation relative au LTP</u>\n\n\n4", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000230", "page": 3, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "liste d'attente", "probe_tag": "confusion", "probe_score": 0.5496786236763, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 172, "end": 187, "key": "reliefweb:000230:3:3:0", "source": "camp2", "luna_reason": "Waiting list is merely mentioned, with no demonstrated data use or targeting.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": " every three years, this\nformula will be updated regularly. Furthermore, the verification instruments are simple and take into\naccount the lessons learned from experience in other countries. Privacy of beneficiary information i s\nrespected and the time consumed in filling out the pertinent forms i s minimal.\n\nOutcome and output indicator monitoring takes into account lessons learned from other CCT projects and\nwill augment the information gathered. The forms to verify education, health, and training/awareness\nconditions will include basic indicators to facilitate monitoring.\n\n(i) **Improving targeting**\n\n\n_How_ _is_ _it auurouriate to the borrower’s needs?_ Under the existing MOSA systems, the\nassessments made by individual social workers were the sole determinant of eligibility. This\napproach i s too discretionary and can result in errors of inclusion. The new beneficiary evaluation\nand selection process will improve targeting and will also free the social workers to spend more\ntime assisting beneficiary households. Roles, responsibilities, and time allocations of social\nworkers under the new system will be better delineated.\n\n\n(ii) <sup>**Will reverse declining school and health allocations outcomes of children**</sup>\n\n\nPassing grades in Arabic have declined from 71 percent to 38 percent and in math from 54\npercent to 26 percent and dropout rates have increased precipitously. Approximately, 34 percent\nof children under five years old suffer mild anemia and about _9_ percent suffer _acute_ proteincalorie malnutrition. Data on the first population decile in the West Bank and Gaza i s scant, the\ndegree of decline i s likely to have been greater for children in the poorest households. The\nSSNRP program will provide the government and households with an instrument to help mitigate\nthese declines.\n\n\n16", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 19, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Data on the first population decile", "probe_tag": "confusion", "probe_score": 0.6189574003219604, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1546, "end": 1581, "key": "refugee_pads:000047:19:1:0", "source": "camp2", "luna_reason": "States data are scant without an analyzed finding or substitute estimate.", "drop_reason": "availability", "specificity": "vague"}]}