diff --git "a/annotate_rafael.jsonl" "b/annotate_rafael.jsonl"
--- "a/annotate_rafael.jsonl"
+++ "b/annotate_rafael.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": "br>exceed the end targets because the RF is based on data from 2017, which was the last time<br>MoES had a comprehensive Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of the project. The<br>new, recently developed EMIS is being populated with values to be available by the end of the<br>year.|Current values are based on a survey conducted by the PCU in August/September 2023. Values<br>exceed the end targets because the RF is based on data from 2017, which was the last time<br>MoES had a comprehensive Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of the project. The<br>new, recently developed EMIS is being populated with values to be available by the end of the<br>year.|Current values are based on a survey conducted by the PCU in August/September 2023. Values<br>exceed the end targets because the RF is based on data from 2017, which was the last time<br>MoES had a comprehensive Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of the project. The<br>new, recently developed EMIS is being populated with values to be available by the end of the<br>year.|Current values are based on a survey conducted by the PCU in August/September 2023. Values<br>exceed the end targets because the RF is based on data from 2017, which was the last time<br>MoES had a comprehensive Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004008", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey conducted by the PCU", "probe_tag": "keep", "probe_score": 0.9298258423805237, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 420, "end": 447, "key": "fcv_pads_east_africa:004008:3:1:0", "source": "camp2", "luna_reason": "Current values are based on this completed survey.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "survey conducted by the PCU", "probe_tag": "keep", "probe_score": 0.9169759750366211, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 420, "end": 447, "key": "fcv_pads_east_africa:004008:3:1:2", "source": "camp2", "luna_reason": "Current values are based on the PCU survey's existing results.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "#### **CHAPTER 3: SOCIO- ECONOMIC ENVIRONMENT**\n\n**2.1 Total economic value (Forest Use/Economic values)**\nThe population of Nakasongola District, particularly in sub-countries surrounding\nthe two CFR’s of Katugo and Kasagala has steadily been increasing; which has\nboth direct impacts on the forest resources. Table 8 shows the population trend\nof these sub-counties.\n\n**_Table 8: Population Growth and Distribution in Sub-counties_** **.**\n\n\n\n|Sub-county|Land Area<br>(km) 2|No. of people<br>(1991)|No. Of<br>people (2002)|Population<br>Density<br>persons/km2|\n|---|---|---|---|---|\n|Kakooge|554.99|17,475|20,615|37|\n|Wabinyonyi|437.73|16,977|13,621|31|\n|**Total**|||||\n\n\n_Source: Nakasongola Local Government 2002 (Population census)_\n\nThe two (2) CFRs are major grazing areas for cattle. Although this is illegal, cattle\nowners overlook legal implications. It should be noted that Kasagala, has no\ngrazing land vegetation limitation compared to Katugo Plantation (the planted\narea of Kasagala is still quite small). Table 9 indicates the cattle stocking in subcountries.\n\n**_<u>Table 9: Cattle stocking in sub-countries Adjacent to CFRs.</u>_**\n\n|Forest Reserve|Sub- county Adjacent|No. Of cattle|\n|---|---|---|\n|Katugo|Kakooge|19,342|\n|Kasa", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015910", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Nakasongola Local Government 2002", "probe_tag": "keep", "probe_score": 0.9298536777496338, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 683, "end": 716, "key": "fcv_pads_east_africa:015910:20:0:0", "source": "camp2", "luna_reason": "Source citation for population census data presented in the table.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**Kenya Informal Settlements Improvement Project: Machakos Region**\n<u>Resettlement Action Plan Report for Kariobangi Informal Settlement</u>\n\n\n**DEFINITION OF TERMS USED IN THIS REPORT**\n\nThe following terms shall have the following meanings, unless the context dictates\notherwise <sup>1</sup> [^1: Water Supply and Sanitation Service Improvement Project (WaSSIP). 2007. Resettlement Policy Framework, RP\n583. Government of the Republic of Kenya\nRepcon Associates. 2011. The Kenya Informal Settlements Improvement Programme: Resettlement Policy] :\n\n**Census** : A field survey carried out to identify and determine the number of Project Affected\nPersons (PAP) or Displaced Persons (DPs) within the project area boundaries. The meaning\nof the word also embraces the criteria for eligibility for compensation, resettlement and other\nmeasures emanating from consultations with affected communities.\n\n**Project Affected Person:** This is a person affected by land use or acquisition needs of the\nKenya Informal Settlements Improvement Project (KISIP). The person is affected because\ns/he may lose “title to land or right to its use”, and/or “title rights or other rights to\nstructures constructed on the land” (thus s/he may lose, be denied, or be restricted access to\neconomic assets, shelter, income sources, or means of livelihood). The person is affected\nwhether or not s/he must move to another location.\n\n**Compensation:** The payment in kind, cash or other assets given in exchange for the\nacquisition of land including fixed assets thereon.\n\n**Cut-off date:** The date of commencement of the census of PAPs or DPs within the project\narea boundaries. This is the date on and beyond which any other person who occupies the\nland delineated for project use, will not be eligible for compensation.\n\n**Effective cut-off date:** The date of the meeting held at the conclusion of the census survey\nbut before disclosure of", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018022", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "census of PAPs or DPs", "probe_tag": "keep", "probe_score": 0.9141238927841187, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1597, "end": 1618, "key": "fcv_pads_east_africa:018022:5:0:0", "source": "camp2", "luna_reason": "Defined census concept, not cited as existing data used for analysis or finding.", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
 {"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n**Figure 3: Survival rates in primary education.**\n\n\n\n100\n\n\n90\n\n\n80\n\n\n70\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<u>100</u>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nGrade1 Grade2 Grade3 Grade4 Grade5 Grade6 Grade7 Grade8 Grade9\n\n\nSource: Facing Forward, 2017\n\n6. **In spite of increased access to schooling, the average level of education of the work force remains low and does**\n**not meet labor market requirements.** Uganda will need to absorb an additional 600,000 new entrants to the labor\nmarket each year between 2014-2020. In order to sustainably increase welfare, these entrants must find productive\nemployment. <sup>9</sup> [^9: Uganda job diagnostics/strategy, World Bank, 2018, draft.] Estimates from the National Household Survey (UNHS) (2016) show that only entrants with postsecondary education can escape informal sector work. In order to increase the employability and productivity of the\nexpanding workforce, supply of quality education, especially for low-income, rural households and girls, is critical.\nAccording to the UNHS, only one in five people aged 15 and above completed secondary education. Thus, a large\nnumber of youth enter the job market without foundational skills of basic literacy and numeracy, as well as generic\nskills essential for life and work.\n\n**B.** **Sectoral and Institutional Context**\n\n7. **Uganda is the pioneer in terms of introducing universal access to secondary education in Sub-Saharan Africa.** The\nsecondary education sub-sector in Uganda is centrally managed and comprises six grades, Senior 1 (S1) to Senior 6\n(S6). S1-S4 is categorized as ordinary (‘O’) level, or lower secondary, while S5-S6 is Advanced (‘A’) level, or upper\nsecondary. In 2007, Uganda introduced the Uganda", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014224", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "National Household Survey", "probe_tag": "keep", "probe_score": 0.9112979769706726, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 764, "end": 789, "key": "fcv_pads_east_africa:014224:4:0:0", "source": "camp2", "luna_reason": "2016 household survey provides evidence on escaping informal sector work.", "usage_type": "evidential", "specificity": "named"}, {"text": "UNHS", "probe_tag": "keep", "probe_score": 0.9550170302391052, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1088, "end": 1092, "key": "fcv_pads_east_africa:014224:4:0:1", "source": "camp2", "luna_reason": "UNHS supports the finding that one in five completed secondary education.", "usage_type": "evidential", "specificity": "named"}]}
-{"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:019789", "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:019789:9:1:0", "source": "camp2", "luna_reason": "Named survey reports access findings on drinking water and sanitation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "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 data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012423", "page": 19, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "keep", "probe_score": 0.9508841633796692, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 272, "end": 283, "key": "fcv_pads_east_africa:012423:19:1:0", "source": "camp2", "luna_reason": "Survey data underpin enrollment comparisons, while noting education-level separation limits.", "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:010150", "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:010150:38:1:1", "source": "camp2", "luna_reason": "Survey data supports reported enrollment-rate differences across expenditure quintiles.", "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:010150:38:1:2", "source": "camp2", "luna_reason": "Household Survey data supports the finding that parents withdraw girls from school.", "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:010431", "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:010431:38:1:1", "source": "camp2", "luna_reason": "Existing survey data supports enrollment-rate comparisons and separation limitations.", "usage_type": "evidential", "specificity": "vague"}]}
-{"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": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010287", "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": "fcv_pads_east_africa:010287:19:0:0", "source": "camp2", "luna_reason": "Survey data supports a reported enrollment-rate disparity by expenditure quintile.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "report should include budget allocation and expenditure data that should be consistent with the KPI\nreport.\n\n39. While the KPI data has quality issues particularly related with the comprehensiveness of\nthe data capture, the practice if encouraging. It is understood, the system building effort is a process\nthat passes through obstacles and challenges and the end result cannot be achieved in one go. The\neffort requires continuous engagement and resource. The aim is to streamline the thinking and\nnecessity of collecting data and measuring performance of procurement through KPIs. In the past\nnone of the regulatory bodies considered this to be their basic duty, instead investing all their time\non audit and trainings. The regulatory bodies are now putting great effort in the endeavor. It requires\ncollecting and entering data at each stage of procurement process for each item. The envisaged\ncapacity and streamlining of the system take time to reach a dependable stage. The initial aim was\nto make the exercise be a catalyst and eye opener for the regulatory bodies to improve the oversight\nsystem and achieve higher. And the exercise has fulfilled this objective. The below figures indicate\nthe results of the two indicators using data collected the past three years (EFY 2010-2012).\n\nTable 8: Average Bid Process Period [days]\n\n\n\n\n\n\n\n\n\nAmhara 51 52 44\nOromia 85 76 100\nSNNP 36 66 42\nTigray 52 47 59\n\nFigure 1: Share of Open Bid\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\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\n14", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017679", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "KPI data", "probe_tag": "confusion", "probe_score": 0.6392220258712769, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 123, "end": 131, "key": "fcv_pads_east_africa:017679:13:0:1", "source": "camp2", "luna_reason": "Generic KPI data is noted, but no attributed finding is tied to it.", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "data collected the past three years", "probe_tag": "confusion", "probe_score": 0.5361679196357727, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1238, "end": 1273, "key": "fcv_pads_east_africa:017679:13:0:2", "source": "camp2", "luna_reason": "Past data support reported indicator results and tables.", "usage_type": "evidential", "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": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009579", "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": "fcv_pads_east_africa:009579:32:0:0", "source": "camp2", "luna_reason": "Survey scorecard is presented as improving across semesters.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "317.7** 2,967.97 **3,958.17**\n\n\n\n\n     - Estimate.\n\n -  - Fbugh Estimate.\n```\na/ MOE took over Primary Education from County Councils.\n```\n\n/ Includes **8,927.53** for D.E.B.\nc/ Includes **520.0** fees _from_ Municipal <sup>and</sup> <sup>City</sup> <sup>Councils.</sup>\n\n/ Includes fees for th:,ee Government primary schools **(1967-1969)** (60.oo Kn thousands\n```\n  in 67-68 and 50.00 K\" thousands in 1969-70 and 51.5 for 1971).\ne/ Only for fonnal education. It excludes nurseries and youth centers.\n\nSources: MOE Annual Reports, Economic Surveys 1970, 1971, 1972.\n\n```", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009907", "page": 48, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Economic Surveys", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 532, "end": 548, "key": "fcv_pads_east_africa:009907:48:3:0", "source": "camp2", "luna_reason": "Source-line citation identifies Economic Surveys underlying the presented table data.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "should be highlighted to key partners such as local politicians, community groups and bodies who may have\nprovided or be using some of the data, especially where joint collection took place. All municipal planning\nstaff should be aware of the content of the report.\n\n\n**Considerations**\n\n\n- **Focus monitoring on the most vulnerable populations and the most significant hazards:** Monitoring\ncan build on GIS mapping of hazards and vulnerabilities from the evidence base stage, as discussed in\nsection 1, with focused monitoring of impacts on the most vulnerable communities and in the vicinity of the\nmost significant hazards/risks. This could, for instance, include a focus on informal settlements and slums,\non vulnerable infrastructure like schools, and on areas identified to be at particularly high risk of flooding,\ndroughts and water scarcity, wildfires, landslides and unstable soils, or volcanic and seismic hazards. An\nexample of a risk-based indicators is distance between vulnerable housing and hospitals (critical\norigin/destination pairs). Monitoring can thus help to capture the most urgent concerns and determine the\nextent to which planning policies and development management and control are building resilience,\nparticularly for the most vulnerable. Potentially vulnerable unplanned and planned development in high-risk\nareas should be recorded and investigated. This will help to determine if enforcement measures are\nadequate in preventing unplanned development and hence driving resilience.\n\n\n- **Monitor collaboratively:** This can save time, money, and effort and avoid duplication. Useful monitoring\ndata could have been collected and/or used by other municipality departments, neighbouring municipalities,\nCounties, central government agencies such as NEMA and NCA or other public bodies (such as health\nservices collecting pollution data or emergency services collecting data on the impact of past hazard\nevents). However, it is important to check third party data to ensure it is from a reliable source. Another\nimportant part of collaboration in monitoring is using survey data and/or testimonials from local communities\nliving and working in or near new development.\n\n\n-", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007238", "page": 32, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "pollution data", "probe_tag": "confusion", "probe_score": 0.11850050091743469, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1851, "end": 1865, "key": "fcv_pads_east_africa:007238:32:0:1", "source": "camp2", "luna_reason": "The sentence describes services collecting pollution data as a monitoring activity.", "drop_reason": "production", "specificity": "vague"}, {"text": "survey data", "probe_tag": "confusion", "probe_score": 0.8870877027511597, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 2096, "end": 2107, "key": "fcv_pads_east_africa:007238:32:0:2", "source": "camp2", "luna_reason": "Generic survey data is mentioned without an attributed finding or concrete analytical claim.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"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:013716", "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:013716:7:1:0", "source": "camp2", "luna_reason": "Named index supports a concrete lowest-in-world development ranking.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " 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 not applicable for those contracts identified in the Procurement\nPlan tables;\n\n\nWorks: is not applicable for those contracts identified in the Procurement\nPlan tables\n\n\n**Other Relevant Procurement Information.**\n\n\nThe project has a CDD component and the project’s procurement\narrangements for community-based procurement will be in line with the\nprovisions of the Procurement Regulations and “Guidance Note for Design and", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002589", "page": 1, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "confusion", "probe_score": 0.14812472462654114, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 29, "end": 52, "key": "fcv_pads_east_africa:002589:1:1:0", "source": "camp2", "luna_reason": "Procurement planning paperwork, not substantive reuse of an external data resource.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018329", "page": 29, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Inter-regional disparities in Expenditure Surveys", "probe_tag": "confusion", "probe_score": 0.6577687859535217, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 590, "end": 639, "key": "fcv_pads_east_africa:018329:29:0:0", "source": "camp2", "luna_reason": "Table indicator fragment, not an analyzed or cited data resource.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "PETS surveys", "probe_tag": "confusion", "probe_score": 0.8346704244613647, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 721, "end": 733, "key": "fcv_pads_east_africa:018329:29:0:1", "source": "camp2", "luna_reason": "Named expenditure-tracking surveys cited among reports informing sector indicators.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "|Table 3: Salient Features of the CSA Branch Offices (BO)|Col2|Col3|Col4|Col5|Col6|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|No|Location|City/Town<br>Population(2007)|Total<br>Population<br>of<br>Enumeration<br>Areas<br>Covered by<br>BO(2007)|Annual Agriculture<br>Sample Survey (AGSS)|Annual Agriculture<br>Sample Survey (AGSS)|Large and<br>Medium Scale<br>Industry<br>Survey|Human<br>Resources|\n|No|Location|City/Town<br>Population(2007)|Total<br>Population<br>of<br>Enumeration<br>Areas<br>Covered by<br>BO(2007)|Typical # of<br>Enumerators<br>Engaged|Typical #<br>of<br>Households<br>Covered|Typical # of<br>Business<br>Establishments<br>Covered|# of Staff<br>(statistician)|\n|1|Addis<br>Ababa|2,739,551|2,739,551|N/A|N/A|1170|71(3)|\n|2|Adama|220,212|5,528,584|169|5,066|248|95(7)|\n|3|Ambo|48,171|4,506,347|83|2,482|207|112(7)|\n|4|Arba M", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018905", "page": 61, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Sample Survey (AGSS)", "probe_tag": "confusion", "probe_score": 0.32999154925346375, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 269, "end": 289, "key": "fcv_pads_east_africa:018905:61:0:1", "source": "camp2", "luna_reason": "Standalone survey header inside a table, not an independently used data mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "**CENTRAL** **BANK** OF **KENYA** **-** **RECONCILIATION**\n\n\nSTATEMENT **AS** **AT:** **28.06.2019**\n**OFF-SHOREA/CNO:** **81** **G.LA/CNO:** **1000175621**\n**DETAILS** DTISCURRENCY **A0260885749** **EQUITY-JUD.** PERFORM. IMPROV. PRJ\n**1.8ALANCE AS** PER OFFSHORE **STATEMENT:** **US** **AMOUNTS 2,546.53** REMARKS **ACTIONJTAKEN**\n\n\n**2.ADD** **DEBITS** **NOT** **IN** NRB\n\n\n**3.LESS** CREDITS **NOT** **IN** NRB\n\n\n4.ADD **DEBITS** **NOT** **IN** OFFSHORE\n\n\n**5LESS** CREDITS **NOT** **IN** OFFSHORE\n\n\n**6.BALANCE AS** PER CBK LEDGER (2,546.53) **2,546.53**\n\nPrepared **By:** Muthuri K.E Checked **by:**\nApproved **By:**\n\nDate: **01.07.2019** Date: **9** Date:", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017634", "page": 57, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "CBK LEDGER", "probe_tag": "confusion", "probe_score": 0.12005552649497986, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 525, "end": 535, "key": "fcv_pads_east_africa:017634:57:0:0", "source": "camp2", "luna_reason": "Ledger used for routine financial reconciliation, not substantive data analysis.", "drop_reason": "bookkeeping", "specificity": "named"}]}
-{"text": "**The World Bank**\nHealth Sustainable Development Goals Program-for-Results (P123531)\n\n|Contraceptive prevalence rate (CPR) (for rural women<br>only)|32%|37.7%|38%|\n|---|---|---|---|\n|Percent of pregnant women taking iron and folic acid<br>(IFA)|42.1%|60%|54.1%|\n|Percent of Children 6-59 months receiving Vitamin A<br>Supplements|45%|45%*|53%|\n\n\n\n- No updates will be verified by next DHS survey planned for 2021\nData sources: Ethiopia Demographic Health Survey (EDHS) 2016 report; 2019 Mini-DHS; Nutrition Data Verification Joint Review Mission Report,\nDec 2018; 2012 HMIS Data Quality Assessment (DQA) Report; 2014 HMIS DQA and current data from 2018 SARA report.\n\n\n4. With respect to the three IPF sub-components, the Program status is as follows:\n\n\n**(a)** **_Sub-component_** **_I: Support for Civil Registration and Vital Statistics (CRVS) System_** : The February 2022\nimplementation support mission noted improvements in the implementation of the remaining activities. Advocacy,\nawareness raising activities and workshops on CRVS have been conducted at federal, regional, woreda and kebele\nlevels that included cultural and religious leaders to create public awareness on the importance of CRVS. A\nMemorandum of Understanding (MOU) was signed between the Addis Ababa City religious leaders and the Addis\nAbaba City Administration Vital Event Agency to closely work on the CRVS agenda. The regional Vital Events\nRegistration Agencies (RVERAs) and cultural and religious leaders also signed an MOU to strengthen vital events\nregistration system in the regions. The printing of awareness education materials (in four languages) is complete and", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005887", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Ethiopia Demographic Health Survey", "probe_tag": "confusion", "probe_score": 0.8912624716758728, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 428, "end": 462, "key": "fcv_pads_east_africa:005887:5:0:0", "source": "camp2", "luna_reason": "Named survey cited as a data source for health indicator results.", "usage_type": "evidential", "specificity": "named"}, {"text": "2014 HMIS DQA", "probe_tag": "confusion", "probe_score": 0.4083731174468994, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 613, "end": 626, "key": "fcv_pads_east_africa:005887:5:0:4", "source": "camp2", "luna_reason": "Named 2014 HMIS data quality assessment cited as a source for indicator data.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "Bl.f Project Management Reports In order to prepare quarterly BEPE 31 December 2001\n(PMRs) PMRs, one must be able to print a\nbudget situation on an automatic\nand punctual basis, to conduct\nanalyses on variances, establish\nunit costs for different program\nindicators, and plan commitments\nand expenditures.\n\n\n\nThe BEPE will prepare the first\ndraft PMR for IDA review.\nFollowing comments/approval, the\nfinal report will be prepared and\nused by the BEPE on a reporting\nbasis only.\n**_B.2._** _Procedures manualfor_\n_financial management_\n\nB2.a General Operations Manual Organization guide which would BEPE 30 June 2001\ndefine the roles and responsibilities\nof the BEPE in order to facilitate\ncommunication and exchange of\nproject inforrnation.\nB2.b Formalizing procedures by Description of each operation: BEPE 30 June 2001\nan Organizational Procedures - supporting documents for\nManual. inputs/outputs\n\n                         - information flow\n\n                         - roles of each agency\n\n                         - data needed\n\n                         - control mechanisms\nB2.c Formal presentation of Project indicators (following data BEPE 30 June 2001\nmanagement reports. consolidation): internal, external\naudit, IDA.\n\n**_R3. Audit_**\n\n\nB3.a Appointment of an auditor. Selection of an auditor whose BEPE 31 March 2001\ncontract would be renewable based\non satisfactory performance.\n\n**C. PROCUREMENT**\n\n\n**_C.l._** _BEPEFunction_\nCl .a No procedures manual exist. Prepare a detailed procedures Technical 30 June 2001\nmanual which would outline the unit/\nfunction of the organization, the BEPE\nvarious activities being\n\nundertaken, the steps for each\nactivity and the respective\n_ responsibilities.\nC .b Procurement function lacks a Recruit a qualified and seasoned MEN/ 30 June 2001\nsenior officer. procurement officer, and train BEPE\nexisting junior procurement staff in", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019800", "page": 57, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data BEPE 30 June 2001\nmanagement reports", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1139, "end": 1180, "key": "fcv_pads_east_africa:019800:57:0:0", "source": "camp2", "luna_reason": "Fragment from an action-plan table, not an independently used data source.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": " for mathematics\nand 70% for science and social science).\n<u>2. Increase in the number of teachers with required qualifications and competence: A total of 83,309primary teacher trainees and 24,856 secondary</u>\nteacher trainees graduated from diploma and post-graduate diploma teaching programs during the project period. 106,063 in-service primary\nteachers completed their upgrading programs from certificate to diploma, and 59,069 secondary teachers from bachelor degree (in non-teaching\nfields) to PGDT. In addition, 70,226in-service English language teachers, and 27,811 mathematics and science teachers attended short-term\ntraining programs as part of their continuous professional development. In all cases, achievements have exceeded the targets.\n<u>3. Teacher effectiveness: Data based on 21,363 re-inspected schools on school inspection standards including teaching and assessment practices</u>\nshow that the index of teacher effectiveness has improved from the 2016 baseline of 45.4% in Level 1 and 59.3% in Level 2 schools to 46.4% in\nLevel and 59.5% in Level 2 schools in 2018.\n<u>4. School grants utilization: The 2016 school grant utilization survey confirmed that 100% of the schools surveyed (38,425) had used at least half of</u>\ntheir grants for teaching and learning domain of their school improvement program (SIP). However, the 2018 grant evaluation survey confirmed that\nonly about 74% of the schools surveyed (41,835) did so.\n<u>5. ICT in education. After a long delay, e-cloud infrastructure (involving a server connected to 80 terminals) has been installed in 300 secondary</u>\nschools and 10 universities to provide ICT-enabled quality learning. Efforts to hire a consultant to design and implement Learning Management\nSystem for schools that offers online instruction were not successful. Instead, MoE collected digital", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016303", "page": 1, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2018 grant evaluation survey", "probe_tag": "confusion", "probe_score": 0.628038763999939, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1349, "end": 1377, "key": "fcv_pads_east_africa:016303:1:1:1", "source": "camp2", "luna_reason": "Existing 2018 survey supports the reported 74% school-grant utilization finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of the project. The<br>new, recently developed EMIS is being populated with values to be available by the end of the<br>year.|Current values are based on a survey conducted by the PCU in August/September 2023. Values<br>exceed the end targets because the RF is based on data from 2017, which was the last time<br>MoES had a comprehensive Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of the project. The<br>new, recently developed EMIS is being populated with values to be available by the end of the<br>year.|Current values are based on a survey conducted by the PCU in August/September 2023. Values<br>exceed the end targets because the RF is based on data from 2017, which was the last time<br>MoES had a comprehensive Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of the project. The<br>new, recently developed EMIS is being populated with values to be available by the end of the<br>year.|Current values are based on a survey conducted by the PCU in August/September 2023. Values<br>exceed the end targets because the RF is based on data from 2017, which was the last time<br>MoES had a comprehensive Education Management Information System (EMIS). Enrollments in<br>target areas have increased in the interim for reasons outside the influence of the project. The<br>new, recently developed EMIS is being populated with values to be available by the end of the<br>", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004008", "page": 3, "chunk": 6, "split": "holdout_annotate", "spans": [{"text": "survey conducted by the PCU", "probe_tag": "confusion", "probe_score": 0.8449428081512451, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 300, "end": 327, "key": "fcv_pads_east_africa:004008:3:6:2", "source": "camp2", "luna_reason": "Past survey data is explicitly used as the basis for current values.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "data from 2017", "probe_tag": "confusion", "probe_score": 0.5417219400405884, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 414, "end": 428, "key": "fcv_pads_east_africa:004008:3:6:3", "source": "camp2", "luna_reason": "Bare date-only data qualifier cannot inherit EMIS source from surrounding context", "drop_reason": "ref_list", "specificity": "vague"}]}
-{"text": " **4,165,577.22** **0** delayed supporting\ndocuments\n10 POLARIS APPLIED SCIENCESdouet\nINC 1,806,546.24 14/04/2021 **0** 1,806,546.24 **0** delayed supporting\n11NCHLMEGROFHR\ndocuments\nSERVICE GROFHR\nSubRotlI05,1276 **5,736,960.00** **18/04/2018** **0** **5,736,960.00** **0** delayed supporting\n\ndocuments\nGrandTotal **105,466,766** **105,112,766.**\nGrad ota **15,46,66105,46,6**\n\n\n**ANNEX** **4 -** **SUMMARY** **OF FIXED ASSETS** **REGISTER**\n\nThe fixed asset summary is extracted from the asset registers maintained **by** the Project\n\n**26**", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004952", "page": 30, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "asset registers", "probe_tag": "confusion", "probe_score": 0.5739778876304626, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 491, "end": 506, "key": "fcv_pads_east_africa:004952:30:2:0", "source": "camp2", "luna_reason": "Project asset registers are routine fixed-asset bookkeeping records.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": " and Projects**|**Improving the Coordination of Priority Programs and Projects**|**Improving the Coordination of Priority Programs and Projects**|\n|Indicator Name|Baseline|Baseline|Actual (Previous)|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period|Closing Period|\n|Indicator Name|Value|Month/Year|Value|Date|Value|Date|Value|Month/Year|\n|People with enhanced<br>resilience to climate risks<br>(Number of people) CRI|||0|06-Dec-2024|3,000,000|12-Jun-2025|6,000,000|Dec/2028|\n|People with enhanced<br>resilience to climate risks<br>(Number of people) CRI|Comments on<br>achieving targets|Comments on<br>achieving targets|Corporate result indicator introduced recently. Baseline, actual, and targets to be updated<br>next reporting period using data from PIMIS which is still being rolled out.|Corporate result indicator introduced recently. Baseline, actual, and targets to be updated<br>next reporting period using data from PIMIS which is still being rolled out.|Corporate result indicator introduced recently. Baseline, actual, and targets to be updated<br>next reporting period using data from PIMIS which is still being rolled out.|Corporate result indicator introduced recently. Baseline, actual, and targets to be updated<br>next reporting period using data from PIMIS which is still being rolled out.|Corporate result indicator introduced recently. Baseline, actual, and targets to be updated<br>next reporting period using data from PIMIS which is still being rolled out.|Corporate result indicator introduced recently. Baseline, actual, and targets to be updated<br>next reporting period using data from PIMIS", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003145", "page": 9, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "data from PIMIS", "probe_tag": "confusion", "probe_score": 0.6005925536155701, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 760, "end": 775, "key": "fcv_pads_east_africa:003145:9:3:0", "source": "camp2", "luna_reason": "Future reporting update relies on PIMIS data while the system is still being rolled out.", "drop_reason": "promissory", "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": "OCHA Office of Commission for Humanitarian <sup>Assistance</sup>\nPAMC Project Approval and Monitoring Committee\nPETS Public Expenditure Tracking Survey\nPOM Project Operational Manual\nPPA Participatory Poverty Assessment\nQER Quality Enhancement Review\nRUF Revolutionary United Front\nSAPA Social Action and Poverty Alleviation <sup>Program</sup>\nSHARP Sierra Leone HIV/AIDS Response Project\nSLRA Sierra Leone Roads Authority\nSOCAT Social Capital Assessment Tool\nSPP Strategic Planning and Action Process\nTEP Training and Employment Program\nTSS Transitional Support Strategy\nUNAMSIL United Nations Mission for Sierra <sup>Leone</sup>\nUNHCR United Nations High Commission for <sup>Refugees</sup>\nUNICEF United Nations Children's Fund\nUNOPS United National Operations Support\n\n\nVice President: Mr. Callisto Madavo\nCountry Director: Mr. Mats Karlsson\nSector Manager: Mr. Alexandre Abrantes\nTask Team Leader/Task Manager: Ms. Eileen Murray", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013578", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PETS Public Expenditure Tracking Survey", "probe_tag": "confusion", "probe_score": 0.06334574520587921, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 112, "end": 151, "key": "fcv_pads_east_africa:013578:2:0:0", "source": "camp2", "luna_reason": "Glossary definition only; no survey data are cited, analyzed, or used.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": " project<br>planning and execution, ex ante audits and budget controls,<br>procurement data and contract management, integration of e-<br>procurement and IFMIS, compliance with norms and standards for<br>public service management, quality of audits for schools and health<br>facilities, enhancement of the PFM systems for transition to accrual<br>accounting and performance reporting, publication of financial<br>statements, and use of performance audits.<br>|**All results areas**<br>|\n|The public sector wage<br>bill study lessons learned<br>from state corporation<br>and county governments <br>(SRC 2019)|• There is widespread use of both automated and manual HRM systems.<br>It is essential to mainstream and strengthen the use of an integrated<br>HRMIS for the public sector that incorporates existing functionalities in<br>the Integrated Payroll and Personnel Database and Government<br>Human Resource Information System across public sector institutions<br>to reduce wastages and curb abuse of resources.|**KRA 2:**Intergovernmental<br>Coordination, Institutional<br>Performance, and Human<br>Resource Management<br>|\n\n\n\n5. **KDSP II will strengthen climate governance at the county level through actions that complement the FLLoCA**\n**program (P173065).** FLLoCA is the World Bank’s primary operation to strengthen sub-national climate change governance\nin Kenya. It supports counties to integrate climate change considerations into planning, budgeting, implementation, and\ndecision-making, including by strengthening the understanding of climate risk and vulnerability linked to investments.\nKDSP II will complement FLLoCA’s activities by enhancing the links between county planning and budget execution through\nthe establishment of project management committees, civilian anti-corruption oversight committees", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005140", "page": 48, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Integrated Payroll and Personnel Database", "probe_tag": "confusion", "probe_score": 0.38485801219940186, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 833, "end": 874, "key": "fcv_pads_east_africa:005140:48:1:0", "source": "camp2", "luna_reason": "Names a personnel database without showing its data informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "**_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)_** shall apply for those contracts identified in\nthe Procurement Plan tables\n\n\n**Activities where Rated Criteria is applied** _as specified under paragraphs_\n_5.50_ of the Procurement Regulations is Applicable.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005833", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.03388669341802597, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 157, "end": 180, "key": "fcv_pads_east_africa:005833:1:0:0", "source": "camp2", "luna_reason": "Procurement planning paperwork, not substantive reuse of data.", "drop_reason": "bookkeeping", "specificity": "descriptive"}, {"text": "Procurement Plan tables", "probe_tag": "confusion", "probe_score": 0.08397133648395538, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 157, "end": 180, "key": "fcv_pads_east_africa:005833:1:0:1", "source": "camp2", "luna_reason": "Routine procurement planning tables, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "/sup> <sup>project</sup>\nvehicles procured, financial management <sup>measures</sup> <sup>in place</sup> <sup>and Single</sup> <sup>Fiduciary Management Units</sup> <sup>**(SFMU)**</sup>\n\nformed in phase 1 Counties.\n\n\n\nDigital Public Works (Pilot) **-** <sup>Digital</sup> <sup>Public Works (DPW) which</sup> <sup>is under</sup> <sup>piloting</sup> <sup>phase</sup> <sup>in Nairobi</sup> <sup>county</sup>\nsettlements of Embaksi KCC, <sup>Kahawa</sup> <sup>Soweto</sup> <sup>and</sup> <sup>Embakasi</sup> <sup>Village</sup> <sup>intends</sup> <sup>to:</sup> <sup>Create</sup> <sup>high-quality</sup> <sup>urban</sup>\n\ngeographic data that <sup>will</sup> <sup>**be**</sup> <sup>used</sup> <sup>to</sup> <sup>inform</sup> <sup>future</sup> <sup>urban</sup> <sup>planning</sup> <sup", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007160", "page": 11, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "geographic data", "probe_tag": "drop", "probe_score": 0.03688989207148552, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 618, "end": 633, "key": "fcv_pads_east_africa:007160:11:3:0", "source": "camp2", "luna_reason": "Future planned use of geographic data, not evidence of existing data analysis.", "drop_reason": "promissory", "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": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013784", "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": "fcv_pads_east_africa:013784:30:0:0", "source": "camp2", "luna_reason": "MOE reports are cited as evidence for increased enrollment.", "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:010177", "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:010177:62:2:0", "source": "camp2", "luna_reason": "Generic data qualifier lacks an attributed finding or concrete analytical use.", "drop_reason": "bare_stat", "specificity": "descriptive"}, {"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:010177:62:2:1", "source": "camp2", "luna_reason": "Named database cited as the source producing the table's economic data.", "usage_type": "declaration", "specificity": "named"}]}
-{"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:008521", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "random survey", "probe_tag": "drop", "probe_score": 0.014762614853680134, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1487, "end": 1500, "key": "fcv_pads_east_africa:008521:16:0:1", "source": "camp2", "luna_reason": "Project staff will carry out the survey to establish a future baseline.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "|PI-25.1|Segregation of duties|A|A|A|A|A|A|A|\n|---|---|---|---|---|---|---|---|---|\n|PI-25.2|Effectiveness of<br>expenditure<br>commitment controls|C|B|B|C|C|C|C|\n|PI-25.3|Compliance with<br>payment rules and<br>procedures|B|A|B|B|B|B|B|\n|**PI-26**|**Internal audit**|**D+**|**D+**|**C+**|**C+**|**C+**|**C+**|**C+**|\n|PI-26.1|Coverage of internal<br>audit|A|A|B|B|A|A|A|\n|PI-26.2|Nature of audits and<br>standards applied|C|C|C|C|C|C|C|\n|PI-26.3|Implementation of<br>internal audits and<br>reporting|C|C|B|B|A|A|A|\n|PI-26.4|Response to internal<br>audits|D|D*|C|A|B|B|A|\n|**PI-27**|**Financial data**<br>**integrity**|**B **|**B **|**B+**|**B **|**C+", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017679", "page": 29, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Financial data", "probe_tag": "drop", "probe_score": 0.0173, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 585, "end": 599, "key": "sample:fcv_pads_east_africa:017679:29:0:0", "source": "gold", "luna_reason": "Standalone table label, not an independently used data resource.", "drop_reason": "table_artifact", "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:019064", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.027876049280166626, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 226, "end": 240, "key": "fcv_pads_east_africa:019064:31:0:0", "source": "camp2", "luna_reason": "NaCSA monitoring data serves as verification evidence for beneficiary indicators.", "usage_type": "evidential", "specificity": "named"}, {"text": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1188, "end": 1214, "key": "fcv_pads_east_africa:019064:31:0:2", "source": "camp2", "luna_reason": "NaCSA administrative data is declared as a source for program performance information.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "Goods: 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", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002519", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan\ntables", "probe_tag": "drop", "probe_score": 0.033398985862731934, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 59, "end": 82, "key": "fcv_pads_east_africa:002519:2:0:0", "source": "camp2", "luna_reason": "Procurement planning document used for contract identification, not substantive data analysis.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|\n|KE-NAROK COUNTY-272924-<br>NC-DIR / Purchase of softwar<br>e and access license for M-sh<br>amba mobile DAT Cohort|IDA / 59000|Supporting County Communi<br>ty-Led Development|Post|Direct Selection|Direct|||12,000.00|0.00|Pending Impl<br>ementation|||||2022-02-15||2022-02-22||||||||2022-03-15||2022-09-11||\n|KE-NAROK COUNTY-272989-<br>GO-DIR / Purchase of digital<br>mobile equipment devices fo<br>r Hello tractor DAT cohort|IDA / 59000|Supporting County Communi<br>ty-Led Development|Post|Direct Selection|Direct|||1,750.00|0.00|Under Imple<br>mentation|||||2022-02-15|2020-05-24|2022-02-20|2020-05-24|||||||2022-03-13||2022-09-09||\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|CONSULTING FIRMS|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|Col13|Col14|Col15|Col16|Col17|Col18|Col19|Col20|Col21|Col22|Col23|Col24|Col25|Col26|Col27|Col28|\n|---|---|---|---|---|", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006496", "page": 6, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "amba mobile DAT Cohort", "probe_tag": "drop", "probe_score": 0.019085215404629707, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 155, "end": 177, "key": "fcv_pads_east_africa:006496:6:2:0", "source": "camp2", "luna_reason": "Fragment from a procurement table entry, not a standalone data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017306", "page": 63, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9460182785987854, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 960, "end": 998, "key": "fcv_pads_east_africa:017306:63:1:0", "source": "camp2", "luna_reason": "Named database cited as the source of the presented data table.", "usage_type": "declaration", "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:014952", "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:014952:6:0:0", "source": "camp2", "luna_reason": "Named index provides the cited ranking supporting Djibouti's poor social indicators.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**ALTERNATIVES TO THE APPROACH TAKEN IN REGARD TO THE**\n**SHREDDING TENDER**\n\n\nThe water hyacinth is a reflection of the wider problem of eutrophication of Lake Victoria.\nWater hyacinth can be found in most African Great Lakes. For example, one can see individual\nhyacinth plants in Lake Malawi, and it is likely that the hyacinth has been present in Lake\nMalawi at least as long as it has in Lake Victoria. Yet there are no mats of hyacinth in Lake\nMalawi, and it is not a major problem there. The difference is in the quality of lake water. Lake\nVictoria is eutrophic and Lake Malawi is oligotrophic. If the water hyacinth were not present in\nLake Victoria, then the nutrient bound in the hyacinth mats would, in all likelihood be tied up in\nphytoplankton or other plants living in the Lake. **_<u>The hyacinth do not ADD nutrients as implied</u>_**\n**_<u>in the complaints, they only make use of the nutrients already in the water. The sources of the</u>_**\n**_<u>nutrients in the Lake are surface runoff from the catchment and atmospheric deposition.</u>_**\n**_<u>Control of the eutrophication process has little or nothing to do with water hyacinths, which</u>_**\n**_<u>are really only a symptom of the “illness” (i.e. nutrient enrichment of the Lake) rather than</u>_**\n**_<u>the “illness” itself.</u>_** .\n\n\nGiven that it would be impossible to do a thorough EA in anything less than 3-5 years or\nmore (the time it would take to collect the minimum amount of baseline data, assuming that the\nLVEMP suffers from no", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020447", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "baseline data", "probe_tag": "confusion", "probe_score": 0.2009, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1466, "end": 1479, "key": "sample:fcv_pads_east_africa:020447:33:0:0", "source": "gold", "luna_reason": "Refers to baseline data collection required in future.", "drop_reason": "production", "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:019683", "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:019683:65:0:0", "source": "camp2", "luna_reason": "States epidemiological data are unavailable without analyzing or substituting estimates.", "drop_reason": "availability", "specificity": "descriptive"}]}
+{"text": "Resettlement Policy Framework                                                  Page **31** of **73**\n\n\n   - Being near a service centre where the resettlement area imposes transport costs\nto get the service;\n\n\n   \n##### **Method of property valuation**\n\n\nThere are at least two main methods for property valuation: cost replacement method and\nmarket value method. In the first method all assets are listed, materials of constructions are\nidentified, current costs to replace those assets is then calculated based on a unit rate for the\ndifferent components. Depreciation of the materials or assets may be considered in the\ncalculation. The critical issue in replacement method is land value. Land of a similar size\nmaybe replaced but the value of land is not only its size; rather it is the location value. In\nprivate ownership of land location factor has to be considered in determining the location and\nsize of the new plot; whereas in cases of public ownership of land the principle is to replace\nland of a similar size or standard size for the category of use in an appropriate location.\n\n\nIn the second method, the market value method, there are two approaches:\n\n\nCase 1: Assets are inventoried, conditions are determined, current unit rate for the\ncomponents is defined and applied, depreciation rate is applied to the cost of the cost of the\nconstruction, land value is determined based on value index as determined by land market\ninventory, value of good name for the trade is valuated based on market inventory. Therefore,\nthe value of the property is the sum of the current value of the construction, the good name of\nthe trade, and land value.\n\n\nCase2: Value of property may be determined based on a research using broker’s data for the\nvalue of property in an area where the property is located; or the property may be auctioned to\ndetermine its real market value.\n\n\nThe principle used for property valuation in cases where the property is to be demolished is\nthe cost replacement method. This method is used in all regional", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015996", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "land market\ninventory", "probe_tag": "confusion", "probe_score": 0.4344801902770996, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1426, "end": 1447, "key": "fcv_pads_east_africa:015996:30:0:0", "source": "camp2", "luna_reason": "Existing market inventory determines the value index used in property valuation.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "broker’s data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1726, "end": 1739, "key": "fcv_pads_east_africa:015996:30:0:2", "source": "camp2", "luna_reason": "Broker data are used to determine property value through market research.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "Annex 2\nPage 4 of 4\n\n**Project Component 3 -** US$ **4.10 million**\n\n**Improve the Government's Capacity to Manage Sector Reforms** will be addressed through:\n(i) supporting the activities of the CNOSEGE in its effort to coordinate the reforms and raise\nresources to support the reform; (ii) capacity building support to the Ministry of Education key\nunits such as the Planning Unit _(Service de la Planification),_ and the Education Projects Bureau\n(BEPE); and (iii) other technical assistance necessary to improve private public partnership in\neducation, development of an effective gender strategy, and possible reforms in textbook policy.\n\n\n_Detailed Description of Sub-components:_\n\n\n_(i) CNOSEGE:_ The Executive Secretariat of CNOSEGE is responsible for implementing the\nreform program. The project will finance the secretariat including its fund-raising activities.\n\n\n_(ii) Support to MOE Planning Unit:_ The project will finance capacity building of the Ministry of\nEducation's Planning Unit, through expert assistance in dealing with the collection of educational\nstatistics, the production of a _carte scolaire_ and analysis of census or household survey data, and\nkey staff in the BEPE including the purchase of project management tools (finance and\nprocurement). The planning unit will also carry out the monitoring and evaluation studies\nrequired under the project. In addition, the unit will implement and monitor the Environmental\nManagement Plan (EMP).\n\n\n_(iii) Additional Technical Assistance_ will also be provided to enable the ministry to develop more\ncost effective strategies including exploring the possibility of cost effective public/private\npartnerships. Technical Assistance will also be provided to develop strategies to reduce the\ngender gap in enrollments as well as the gap by income group. Pilot studies will also be financed\nunder the credit for optimal designs in school construction, demand financing, sanitation upkeep\nand maintenance, and", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010914", "page": 35, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "census or household survey data", "probe_tag": "confusion", "probe_score": 0.10401755571365356, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1138, "end": 1169, "key": "fcv_pads_east_africa:010914:35:0:0", "source": "camp2", "luna_reason": "Planned capacity-building activity to analyze data, not an existing analysis used here.", "drop_reason": "promissory", "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": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021039", "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": "fcv_pads_east_africa:021039:10:0:0", "source": "camp2", "luna_reason": "Past survey attributed to CDC and tied to HIV prevalence findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "###### Resettlement Action Plan (RAP) For Dire Dam Rehabilitation Project\n\n**7.3 Method of Valuation**\n\nThere are three commonly known methods of valuing assets and properties, namely,\nincome based approach, replacement cost a market data or comparable sales\napproach. However, in this RAP, the methodology for valuing assets is referred at Full\nReplacement Cost. Full Replacement Cost is one method of valuation of property and\nthat determines the amount of replacement through compensation.\n\nThe concept of Full Replacement Cost is based on the premise that the costs of\nreplacing productive assets that would be expropriated for purpose of project activity.\nThe replacement cost approach involves; direct replacement of expropriated assets and\ncovers an amount that is sufficient for asset and property replacement.\n\n**7.4 Valuation for permanent loss of Farm Land / Crop Loss**\n\nThe project impact is perceived in terms of permanent land loss/crop loss will be\ncreated because of the need to expand the existing sanitary zone by limited size.\nAccordingly it is apparent some part of farm land that is owned by individuals will be\nexpropriated.\n\nAccording to the information obtained from PAPs and physical observation the farm\nland is used in most case to cultivate wheat and been. With this consideration the\nproductivity of the land is considered based on above mentioned dominantly produced\ncrop using data that is obtained from Woreda Agriculture office.\n\nHence, the land that will be expropriated from the farmers is initially valuated in\nconsidering the average crop yield obtained per hectare against the land size that would\nbe lost as the result of project activity.\n\n**7.5 Valuation for Grazing land**\n\nGrazing land in the area has a considerable economic benefit for the local communities\nin the aspect of raising livestock for different purpose including livestock products used\nfor domestic consumption and market consumption and livestock labour for different\npurpose.\n\nWith this consideration the benefit of grazing land for ones household is valuated\nagainst grass obtained from one", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020132", "page": 48, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PAPs", "probe_tag": "confusion", "probe_score": 0.6107338070869446, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1192, "end": 1196, "key": "fcv_pads_east_africa:020132:48:0:0", "source": "camp2", "luna_reason": "Names information providers, not an eligible data resource", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "data that is obtained from Woreda Agriculture office", "probe_tag": "confusion", "probe_score": 0.8700133562088013, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1409, "end": 1461, "key": "fcv_pads_east_africa:020132:48:0:1", "source": "camp2", "luna_reason": "Agriculture office data directly informs crop-yield valuation calculations.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "27. **Adequacy of monitoring and evaluation arrangements:** Regular monitoring and\nevaluation allowed the project to produce good quality data for management and evaluation.\nTracer studies provided data on key performance indicators. Three Beneficiary\nAssessments were carried out with samples of youth, employers, and trainers to provide\nfeedback on project implementation, constraints, and interns’ and employers’ satisfaction\nwith the program. In addition, an employer tracer survey was conducted to collect feedback\nfrom employers on program implementation, quality of training, and interns’ retention rates.\nThe evaluation of the project merits recognition for being based on a rigorous random\nexperimental design.\n\n28. **Relationships and coordination with partners/stakeholders:** The project\nmaintained good working relationships with all its key stakeholders and partners.\n\n29. **Adequacy of transition arrangements for regular operation of project-**\n**supported activities after loan/credit closing:** Lessons learned have been shared with\nrelevant government institutions ready for KYEP scale up. Plans have been put in place to\nutilize private sector employers and the staff who were involved in implementation of the\nKYEP in the scale up of the program.\n\n\n**CAPACITY BUILDING AND POLICY DEVELOPMENT COMPONENT**\n\n30. The following table summarizes the activities planned, tasks carried out, and results\nachieved.\n\n**<u>Table of Activities</u>**\n\n\n\n\n\n|Activities|Tasks carried out|Achievements/Resu<br>lts|\n|---|---|---|\n|1. Facilitating<br>release of<br>funds to<br>KEPSA|Requisitioning for funds from the World Bank<br>through the National Treasury to KEPSA and<br>back-flow reporting.|The flow of funds to<br>KEPSA was<br>consistent<br>throughout the<br>project life,", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017049", "page": 65, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "employer tracer survey", "probe_tag": "confusion", "probe_score": 0.27297458052635193, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 463, "end": 485, "key": "fcv_pads_east_africa:017049:65:0:0", "source": "camp2", "luna_reason": "Survey was conducted to collect feedback, so it is project-produced data.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": " from the last JRIS mission (99,344,644 ETB).\n\n  - **_LH grant performance_** : 2,608,253,185 ETB disbursed for 78,005 HHs and 2,561,639,214 ETB grant\ntransferred to 77,155 (55,526F) HHs.\n\n  - **_Employment:_** from the first wave beneficiaries, 72,430 (52,315F) and 1,956(913F) employed in\nself-employment and wage employment pathways, respectively.\n\n  - **_Impact Evaluation:_** The baseline data (collected in January 2022), follow-up I (Sept/Oct 2023), and\nFollow-up II (Sept/Oct 2024) fieldwork data have been collected and the final datasets have been\nsubmitted to the WB.\n\n\n19", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005761", "page": 18, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "fieldwork data", "probe_tag": "confusion", "probe_score": 0.37098032236099243, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 490, "end": 504, "key": "fcv_pads_east_africa:005761:18:2:0", "source": "camp2", "luna_reason": "The sentence states that project fieldwork data were collected, indicating production rather than use.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": ".g. bitumen binders\nfor asphalt concrete). Although climate change is not in the manual, it can be included using the\nmethod in Section 3.2.4 and applying the new temperatures in\nthe calculations.\n\n\n#### **3.3 Structural resilience**\n\nStructural design is critical to the resilience of buildings and\nother structures, to withstand environmental shocks and\nstresses during the project’s lifetime. In terms of physical\nresilience, in addition to changes in temperature resulting\nfrom climate change, structural design should also take into\naccount actions of wind, and seismic design. The frequency\nand magnitude of high wind events, or earthquakes, in Kenya\nare not anticipated to be impacted by climate change and\nthus ‘normal’ application of the relevant design codes will\nprovide structural resilience.\n\n\nThe following codes should be applied for structural resilience:\n\n\n    - The draft National Building Code 2022\n\n\n### **Summary**\n\n- Follow the draft National\nBuilding Code 2022\n\n\n- Any gaps? – the National\nBuilding Code should be\nupdated to reflect the\nEurocodes\n\n\n\n\n- Where there are gaps in the National Building Code, the Code itself should be updated\nto reflect Eurocodes to make it easier for municipal officials and local builders to\nunderstand standards and the requirements. The following Eurocodes in particular may\nbe relevant:\n\n\n`o` Eurocode 1: Actions on structures - Part 1-4: General actions - Wind actions, the\n\nexisting wind map for Kenya is valid, climate change is anticipated to have limited\nimpact on maximum gust speed. Wind data, as necessary, can be provided by\nKMS.\n\n\n21/61", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007268", "page": 21, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "wind map for Kenya", "probe_tag": "confusion", "probe_score": 0.7015323042869568, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1443, "end": 1461, "key": "fcv_pads_east_africa:007268:21:1:0", "source": "camp2", "luna_reason": "Existing wind map informs assessment of climate impacts on maximum gust speed.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "Wind data", "probe_tag": "confusion", "probe_score": 0.5102018713951111, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1548, "end": 1557, "key": "fcv_pads_east_africa:007268:21:1:1", "source": "camp2", "luna_reason": "Data availability is stated, without an analyzed finding or actual use.", "drop_reason": "availability", "specificity": "vague"}]}
+{"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:009595", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "1997 poverty\n\nassessment", "probe_tag": "confusion", "probe_score": 0.6263846755027771, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1107, "end": 1131, "key": "fcv_pads_east_africa:009595:24:0:0", "source": "camp2", "luna_reason": "The sentence describes a planned update, not actual use of existing assessment findings.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "**8**\n\n\n**by** electronic means. In full recognition that the Association shall rely upon such representations\nand warranties, including without limitation, the representations and warranties contained in the\n_Terms and Conditions of Use ofSecure Identification Credentials in connection with_ _Use_ **_of_**\n_Electronic Means to Process Applications and Supporting Documentation_ (\"Terms and\nConditions of Use of **SIDC\"),** the Recipient represents and warrants to the Association that it will\ncause such persons to abide **by** those terms and conditions.]\n\n\nThis Authorization replaces and supersedes any Authorization currently in the Association\nrecords with respect to this Agreement.\n\n\n[Name], [position] Specimen Signature:\n\n\n[Name], [position] Specimen Signature:\n\n\n[Name], [position] Specimen Signature:\n\n\nYours truly,\n\n\n/ signed /\n\n\n[Position]", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013075", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Association\nrecords", "probe_tag": "confusion", "probe_score": 0.13275255262851715, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 640, "end": 659, "key": "fcv_pads_east_africa:013075:7:0:0", "source": "camp2", "luna_reason": "Routine association records referenced administratively, not used as data.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
+{"text": "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 partners, including the Bank.\n\nEducation. Although gross primary school enrollment rose by about 7% when the government\nrecently introduced universal free primary education, low enrollment, education of children who were\nforcibly recruited during the war, and gender imbalance are still an issue (male/female pupil ration of\n165:100) and only 52% of teachers are qualified. A large number of schools were rehabilitated through\nthe IDA financed CRRP Project.\n\nRisk and Vulnerability. The biggest risk that Sierra Leone's poor face is a return to civil\nconflict, political instability and chaos in public administration that would prevent the government from\nresponding to the population's needs for food, shelter and economically productive activity. The project\nis expected to respond to this risk through investments in rehabilitation, employment, and the\nreinforcement of basic services. As conditions improve, endogenous resistance to a resurgence of\nconflict is expected to increase. However there is still a need to understand the profile of risks, identify\nhigh risk groups, define the interface between vulnerability mapping and poverty mapping, coordinate\npublic programs to reduce nsks and reinforce the coping capacity of the poor. Initially, a participatory\nassessment of risks and vulnerability will be commissioned using available and forthcoming data from\nthe living standards measurement survey (LSMS) of 2003. Risk and vulnerability concepts have already\nbeen introduced into the PRSP preparation process by including appropriate questions in the 2003\nLSMS. This should enhance the poverty diagnostic dimensions of the PRSP, and inform the\ndevelopment of strategies to ensure that poverty levels do not increase.\n\nRisk and vulnerability concepts would be introduced in the design of individual sub-projects\nselected by communities. Sub-projects would address the most common risks faced by communities,\nsuch as inadequate", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011693", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "living standards measurement survey", "probe_tag": "confusion", "probe_score": 0.4707256555557251, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1571, "end": 1606, "key": "fcv_pads_east_africa:011693:10:1:0", "source": "camp2", "luna_reason": "Existing 2003 survey data are used for risk and vulnerability assessment.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "2003\nLSMS", "probe_tag": "keep", "probe_score": 0.9626069068908691, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1760, "end": 1769, "key": "fcv_pads_east_africa:011693:10:1:1", "source": "camp2", "luna_reason": "Questions are being added to a forthcoming survey, so its data do not yet exist.", "drop_reason": "production", "specificity": "named"}]}
+{"text": " foundation for democratic and sustainable local\n\n\n\ndevelopment. The Community Development Program will finance social and economic\ninfrastructure and support social capital building activities to facilitate the restoration of basic\nsocial services such as health and education and provide an incentive for teachers, health workers\nand displaced persons to return to their communities. The Rural Public Works and Shelter\nprograms will provide employment for demobilized soldiers and unemployed youth, housing for\ndisplaced persons and feeder roads to stimulate local economic activities. The innovative\nactivities including training and technical support will strengthen local government capacity to\nplan, contract, manage and sustain investments in local development and engage a wide array of\n\n\n\nstakeholders in participatory processes that contribute to sustainable local development.\n\n\n\nTargeting will be consistent with the Government's 2002-2003 National Recovery\nStrategy and the March 3, 2002 Transitional Support Strategy. Resources will be directed to (a)\nnewly accessible areas that have not received any support in more than a decade; and (b) remote\nareas that have received little, if any support from the ongoing IDA-financed CRRP or other\nsimilar projects. The results of the living standards measurement survey currently underway will\nbe available at the end of 2003 and will be used to review the validity of existing targeting\nmodalities.\n\n\nTarget Populations: Target groups include demobilized soldiers and unemployed youth,\nrefugees, IDPs, female-headed households, child laborers, orphans, primary school dropouts,\n\n\n_- 8 -_", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012096", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "living standards measurement survey", "probe_tag": "confusion", "probe_score": 0.25301676988601685, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1291, "end": 1326, "key": "fcv_pads_east_africa:012096:12:1:0", "source": "camp2", "luna_reason": "Survey is currently underway; its results will become available and be used later.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "** <br> <br>|\n|<br>Sub-component 2.1: Improving availability of<br>essential HPTs and delivery of key RMNCAH<br>and NCDs interventions at the primary care<br>level (US$90 million):|<br>**HPTs for Climate Sensitive diseases**: Pharmaceuticals for climate sensitive<br>conditions such as malaria, diarrheal diseases, and other climate sensitive<br>conditions will be included in the pharmaceutical list. This will improve the<br>capacity of primary care level facilities to provide better health services in<br>the face of the increasing burden of disease due to climate change. Seasonal<br>case and pharmaceutical consumption data will be used to inform<br>procurement of the pharmaceuticals to ensure adequate supplies based on<br>seasonal patterns to address climate sensitive conditions.**(adaptation)**<br> <br>|\n|Sub-component 2.3:  Improving access to and<br>utilization of quality health services in<br>refugee and host communities (US$40<br>million)|<br>**Climate sensitive community health service planning:** Climate sensitive<br>planning including the use of climate vulnerability and meteorologic data<br>will be used to guide the distribution of essential HTPs, diagnostic and<br>medical equipment avoiding stormy, heavy rains and heavy flooding days. <br>Specifically, data on climate vulnerable locations and data on previous use<br>of HPTs for climate sensitive diseases as well as patterns of pharmaceutical<br>use following climate shocks will be used to ensure adequate quantities of<br>pharmaceuticals are being used.  To ensure pharmaceuticals are available<br>ahead of shocks and that these do not impact distribution, funding will be<br>made available, and planning", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000910", "page": 46, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "case and pharmaceutical consumption data", "probe_tag": "confusion", "probe_score": 0.11961445957422256, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 589, "end": 629, "key": "fcv_pads_east_africa:000910:46:1:0", "source": "camp2", "luna_reason": "Future planned use of data to inform pharmaceutical procurement", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": " scenario 2 (60 percent in yields increase over the\n20 years) would be economically desirable (no returns and negative NPV). The results given in the table\nabove are based on the assumptions of the third scenario (doubling of yields over the 20 years).\nFurthermore, because former agricultural projects showed that doubling yields is a challenging target to\nachieve, those returns are not very robust. The sensitivity analysis also suggests that a contributing factor\nfor the moderate efficiency of KAPP phase 1 have been low yields in maize and potato in 2008: a 25\npercent increase in maize yields in 2008 would have improved the FRR and ERR up to 41 percent and 59\npercent, respectively. The project is also sensitive to input and output prices. If the inputs’ price increases\nsignificantly by 10 percent or the output price decreases by 10 percent, the ERR would fall below the 12\npercent threshold, suggesting risks to economic sustainability.\n\n**(e)** **Price data**\n\n13. Like in many other low-income countries, collecting rural price data is a significant challenge, as\nno official rural price data exists. The calculations use average price data collected on internet trade\ninformation platforms <sup>18</sup> [^18: www.ratin.com] and other documentation from KARI. Price data is not disaggregated by\ngeographical region or around the agricultural cropping cycle. It is based on average values, therefore\nignoring the sometimes hefty price fluctuations during the cropping cycle. All costs and benefits were\ncalculated in constant 2009 prices.\n\n14. A specific effort was made to derive economic prices from financial prices. It is assumed the\nproject will not generate any exportable output. FAO’s “food balance sheets” <sup>19</sup> [^19: http://faostat.fao.org/site/368/default.aspx#ancor. The import/ domestic supply ratio is around 18%.] show that Kenya depends\non food imports to assure its", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010100", "page": 48, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "rural price data", "probe_tag": "confusion", "probe_score": 0.56160569190979, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1030, "end": 1046, "key": "fcv_pads_east_africa:010100:48:1:2", "source": "camp2", "luna_reason": "Existing-data gap is declared and motivates use of substitute price data.", "usage_type": "declaration", "specificity": "vague"}, {"text": "average price data collected on internet trade\ninformation platforms", "probe_tag": "confusion", "probe_score": 0.7189151048660278, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1136, "end": 1204, "key": "fcv_pads_east_africa:010100:48:1:3", "source": "camp2", "luna_reason": "Existing price data from internet platforms directly support economic calculations.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "food balance sheets", "probe_tag": "confusion", "probe_score": 0.728156566619873, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1708, "end": 1727, "key": "fcv_pads_east_africa:010100:48:1:4", "source": "camp2", "luna_reason": "FAO food balance sheets support the stated import-domestic supply ratio.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nInnovative Systems to Promote Integrated, Resilient and Enhanced Responses to Women and Girls’ Health\n(P504281)\n\n\n3. **Ethiopia reports the third highest electricity access deficit in Sub-Saharan Africa.** The greatest access deficits are\nfound in rural and deep-rural areas. About 96 percent of urban households are connected to the grid (99.9 percent in\nAddis Ababa), while only 27 percent of rural households have access to electricity services.\n\n\n4. **Ethiopia is highly vulnerable to climate change.** Ethiopia is one of the most drought-prone countries in the world,\nand the frequency and intensity of droughts are being exacerbated by climate change. Over the past 100 years, Ethiopia\nhad experienced 19 periods of widespread and severe food shortages due to droughts, affecting an average of 1.5 million\npeople annually.\n\n5. Inadvertently, the health sector contributes to air pollution. Pollutants from traditional incinerators in big cities\nlike Addis Ababa have negative impacts on the health of women and girls living in remote rural areas where particles\nfrom these pollutants have been traced in untreated waters fetched by these mothers and girls for household usage.\n\n6. **Challenges remain in Ethiopia’s digital development landscape.** Data from 2023 shows that Ethiopia had 66.80\nmillion active cellular mobile connections; 75% of Ethiopian men and 55% of women own a cell phone. More broadly,\n30.7 percent of all internet users in Ethiopia engaged with at least one social media platform in January 2023. Of the\nsocial media user base at that time, 34.1 percent were female, and 65.9 percent were male.\n\n7. These contexts and disparities affect service delivery challenges. Reliable electricity and water are necessary to\noperate health facilities; women in climate-affected and rural areas are less likely to use facilities that are understaffed,\nlack water and electricity and functioning equipment. They are more likely to not", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003054", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data from 2023", "probe_tag": "confusion", "probe_score": 0.3267033100128174, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1273, "end": 1287, "key": "fcv_pads_east_africa:003054:3:0:0", "source": "camp2", "luna_reason": "Bare date-only data qualifier lacks an identified source or producer.", "drop_reason": "ref_list", "specificity": "vague"}]}
+{"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:019922", "page": 29, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "M&E data", "probe_tag": "confusion", "probe_score": 0.11440254747867584, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 961, "end": 969, "key": "fcv_pads_east_africa:019922:29:1:1", "source": "camp2", "luna_reason": "Existing agency monitoring data is declared as a project-report source.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": " approaches that<br>support structural strengthening, like roofing material that can sustain strong winds and rains, incorporating<br>defense mechanisms against floods, landslides, and soil erosion (US$3M); iii) introduce or improve rainwater<br>harvesting systems (US$4M) and drainage and sanitation systems (US$4M) where appropriate; iv) all<br>beneficiary schools will need to plant trees, enabling instruction to continue in the shade during high heat<br>days (US$2M); v) implement an awareness campaign on climate change (US$1M), including information on<br>school-specific evacuation protocols at the onset of climate-related emergencies; vi) the child-friendly schools<br>interventions will include content on environmental safety and protocols at the onset of climate change-<br>induced emergencies like flash floods, increasing the capacity of teachers, pupils, school management, and<br>community’s capacity to address climate change-related issues (US$1.2M); vii) the updated BRMS will include<br>design considerations for schools to be used as shelters during climate related and other emergencies (such as<br>use of wind-resistant materials, emergency lighting, and backup power supply) (US$2M).<br> <br>The proposed climate interventions will be financed by IDA. All infrastructure activities under DLI #5<br>(US$189M) are to address existing vulnerabilities due to climate change and extreme climate events expected<br>in the future.|\n|RA 3: Supporting<br>Use of Data for<br>Improved<br>System<br>Management|<br>DLI #6. Percentage<br>of schools with<br>student-level data<br>in EMIS|**_M", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002824", "page": 29, "chunk": 6, "split": "holdout_annotate", "spans": [{"text": "student-level data", "probe_tag": "drop", "probe_score": 0.04099338501691818, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1568, "end": 1586, "key": "fcv_pads_east_africa:002824:29:6:0", "source": "camp2", "luna_reason": "Standalone indicator fragment within a DLI table", "drop_reason": "table_artifact", "specificity": "named"}, {"text": "EMIS", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1593, "end": 1597, "key": "fcv_pads_east_africa:002824:29:6:1", "source": "camp2", "luna_reason": "EMIS data underpin the stated percentage indicator for schools with student-level records.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "|No|Questions|Responses|\n|---|---|---|\n|1 <br>|What is your preferred mode of communication during<br>project preparation, implementation and Closure?<br>|Phone calls, letters, emails, TV’s, radio talk shows among others.<br> <br> <br> <br> <br> <br>|\n|2 <br>|<br>How do you normally get information about community,<br>project activities?  (e.g for NEMA, explain about disclosure<br>and feedback and the multi-sectoral approach towards<br>disseminating information)<br>|Letters,<br>emails,<br>phone<br>calls,<br>Community<br>feedback,<br>reconnaissance surveys, RAP reports among others.<br>|\n|3 <br>|<br>Are there any limitations about time of day or location for<br>public consultations? Day/Time/location preferences<br>|Day time is most appropriate for consultations and most especially<br>morning hours as long as there is efficient and effective<br>mobilization.<br>|\n|4 <br>|What need-specific resources might be needed to enable<br>vulnerable, marginalized people participate in meaningful,<br>free prior informed and fair consultation process?<br>|<br>The vulnerable group need people whom they are familiar with in<br>the communities like L. Cs to be speak to them during community<br>engagements.<br> <br>|\n|5 <br>|Describe briefly what kind of information should be<br>disclosed, type of method that should be used to<br>communicate to each stakeholder group? What kind of<", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003663", "page": 60, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "reconnaissance surveys", "probe_tag": "drop", "probe_score": 0.009473798796534538, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 539, "end": 561, "key": "fcv_pads_east_africa:003663:60:0:0", "source": "camp2", "luna_reason": "Merely names surveys as an information source without citing findings or actual data use.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": "24\n\n\n**During negotiations the following assurances were received:**\n\n\n1. Agreement on triggers for subsequent phases\n2. Agreement on monitoring and impact assessment studies\n3. Agreement on project monitoring indicators\n4. Agreement on finalized bidding documents for the first batch of schools\n\n\n**Actions to be included in Development Credit Agreement:**\n\n\n_Financial_\n\n\n1. Audits and Project Management Reports.\n2. Dated covenant on the selection of the auditor before March 31, 2001.\n\n\n_Management_\n\n\n1. Daied covenant on a baseline survey to establish gender and social class distribution of students\nbefore December 31, 2001.\n2. Provide regular reports on monitoring indicators and prepare a draft midterm report for review\nwith IDA before September 15, 2002.\n\n\n**In addition the following Management conditions are included in supplemental letters attached**\n**to the Developinent Credit Agreement:**\n\n\n1. Triggers from Phase I to Phase II in APL\n2. Triggers from Phase II to Phase III in APL\n\n\nH. READINESS **FOR IMPLEMENTATION**\n\n\nL. a) The engineering design documents for the first year's activities are complete and ready for the\n\nstart of project implementation.\nD b) Not applicable.\n\n3 2. The procurement documents for the first year's activities are complete and ready for the start of\nproject implementation.\n\n\nK/ 3. The Project Implementation Plan has been appraised and found to be realistic and of satisfactory\n\nquality.\n##### D 4. \"he following 7tems are lacking and are discussed under loan conditions (Section G):", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014680", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "baseline survey", "probe_tag": "drop", "probe_score": 0.04908192902803421, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 529, "end": 544, "key": "fcv_pads_east_africa:014680:27:0:0", "source": "camp2", "luna_reason": "Baseline survey is a planned future activity under a dated covenant.", "drop_reason": "production", "specificity": "vague"}]}
 {"text": " and<br>labor force<br>indicators and<br>better real<br>sector economic<br>used to inform<br>the third<br>Medium-Term<br>Plan (MTP-3)|<br>Poverty<br>monitoring<br>statistics used<br>in third revenue<br>sharing formula<br>by the Kenya<br>Commission on<br>Revenue<br>Allocation<br>(KCRA)|Annual|<br>Program<br>Progress<br>Report|<br>KNBS|\n|<br>**Produce regular**<br>**poverty**<br>**monitoring data**<br>**and statistics**|<br>☐|<br>☒|<br>Yes/No|<br>Poverty statistics<br>are outdated<br>(2005/06) and<br>insufficient<br>capacity to<br>monitor poverty<br>at least once<br>every 3 years<br>|<br>Kenya<br>Integrated<br>Household<br>Budget Survey<br>KIHBS<br>2015/16 partly<br>conducted and<br>progress report<br>produced and<br>available online|<br>Updated<br>benchmark<br>(2015/16)<br>poverty<br>measures<br>produced and<br>disseminated|<br>Poverty<br>monitoring data<br>collected by<br>Kenya<br>Continuous<br>Household<br>Survey (KCHS)|<br>KCHS poverty<br>estimates<br>produced and<br>disseminated|<br", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011647", "page": 43, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "monitoring data", "probe_tag": "drop", "probe_score": 0.025536341592669487, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 382, "end": 397, "key": "fcv_pads_east_africa:011647:43:2:0", "source": "camp2", "luna_reason": "The row requires producing regular monitoring data, so it describes data production.", "drop_reason": "production", "specificity": "vague"}, {"text": "KCHS", "probe_tag": "confusion", "probe_score": 0.8054195642471313, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 939, "end": 943, "key": "fcv_pads_east_africa:011647:43:2:2", "source": "camp2", "luna_reason": "KCHS estimates are presented as produced and disseminated project outputs.", "drop_reason": "production", "specificity": "named"}]}
-{"text": "**The World Bank** Implementation Status & Results Report\nSecond Kenya Devolution Support Program (P180935)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|that have put in place core<br>governance arrangements<br>to manage public funds<br>(Number)|Allocated Amount|0.00|0.00|Col5|0.00|\n|---|---|---|---|---|---|\n|3 : Participating counties<br>that have increased their<br>OSR by at least 5% annually,<br>over and above the rate of<br>inflation (Number)|Value|n/a|||30|\n|3 : Participating counties<br>that have increased their<br>OSR by at least 5% annually,<br>over and above the rate of<br>inflation (Number)|Allocated Amount|0.00|0.00|0.00|0.00|\n|4 : Participating counties<br>that have prepared and are<br>implementing action plans<br>to reduce the stock of<br>pending bills and maintain it<br>at minimal levels (Number)|Value|0|||25|\n|4 : Participating counties<br>that have prepared and are<br>implementing action plans<br>to reduce the stock of<br>pending bills and maintain it<br>at minimal levels (Number)|Allocated Amount|0.00|0.00|0.00|0.00|\n|5 : Participating counties<br>that have integrated their<br>HR records, authorized staff<br>establishment and payroll,<br>and uploaded cleaned<br>payrolls in the HRMIS<br>(Number)|Value|0|||25|\n|5", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001731", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "HRMIS", "probe_tag": "drop", "probe_score": 0.041727062314748764, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1183, "end": 1188, "key": "fcv_pads_east_africa:001731:9:0:0", "source": "camp2", "luna_reason": "System name appears only within a table indicator row, without substantive data use.", "drop_reason": "table_artifact", "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:016286", "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:016286:45:6:0", "source": "camp2", "luna_reason": "Routine procurement compliance reporting, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "expenditure survey from 2010 with the unit record population census data from 2008\n\nusing the ELL approach. This poverty map serves as our benchmark. We then ignore\n\nthe population census data and obtain a second poverty map for Malawi by combining\n\nthe household expenditure survey data with predictors of poverty derived from publicly\n\navailable remote sensing data.\n\n\nAn important motivation for using data from Malawi is that we have access to the\n\nexact coordinates of the survey PSUs. This enables us to produce the remote-sensing\nbased poverty map both using the publicly available geographic coordinates (that have\n\nbeen subjected to random offset to protect the anonymity of households) and exact\n\ncoordinates (that are not publicly available) to investigate whether the random offsets\n\nmight undermine the approach - and inspect the correspondence.\n\n\nOur findings are two-fold. First, assessments of the correspondence between the\n\nremote-sensing-based poverty estimates and the census-based poverty estimates de\npend on how the correspondence is evaluated. The two approaches reveal the same\n\npatterns in the geography of poverty in Malawi; it is hard to tell the difference in a\n\nside-by-side comparison of the two poverty maps. The statistical correlation between\n\nthe two different small area estimates of poverty is above 0.9, again confirming their\n\nclose correspondence. However, there are districts for which the two approaches obtain\n\nmarkedly different estimates of poverty. Accordingly, poverty maps obtained using re\nmote sensing data can be expected to do well when the decision maker is interested\n\nin estimates or comparisons of poverty between assemblies of areas. Yet, the decision\n\nmaker may not be served as well by remote-sensing-based estimates when the focus\n\nis on estimates for specific small areas. Second, the random offsets embedded in the\n\ngeographic coordinates of the public use data do not meaningfully alter the estimated\n\ngeography of poverty. But they may, however, lead to an under-estimation of the stan\ndard errors of the small area poverty estimates (i.e. an over-estimation of precision)", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001165", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "population census data", "probe_tag": "keep", "probe_score": 0.9696381092071533, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 170, "end": 192, "key": "prwp:001165:6:0:2", "source": "camp2", "luna_reason": "Malawi’s 2008 census data underpin the benchmark poverty map and comparison.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "public use data", "probe_tag": "keep", "probe_score": 0.9544360637664795, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1908, "end": 1923, "key": "prwp:001165:6:0:6", "source": "camp2", "luna_reason": "Public-use data underpin findings about geographic offsets and poverty estimates.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": ", gets a value of unity). The median of this measure across the 122 programs is 1.25. The\n\n\nhighest value is 4.0 (for Argentina’s _Trabajar_ program). By contrast, the value estimated by\n\n\nChen et al., for the DB program is 8.3, making it a better performer by this measure than all the\n\n\nprograms surveyed by Coady et al. (2004).\n\n\nNonetheless, the overall impact on poverty appears to be modest. In the same sample,\n\nChen et al., find that the poverty gap index ( _C_ _j_ / <sup>_Z_</sup> _j_ ), based on income net of DB receipts, is\n\n\n2.28%; on adding in DB payments it only falls to 2.06%. (Among participants only, the\n\n\ncorresponding figures are 19.92% and 14.23%; the higher index for participants reflects the\n\n\nprograms’ targeting to the poor.) This largely reflects weak coverage of the poor, as identified\n\n\n\nby the UHSS.\n\n\n\n18 Performance improves if one allows for measurement errors in the UHSS, and\n\n\n\n18 This echoes observations from some of the literature on targeting in developing countries that has\npointed to the inadequacies of focusing solely on the problem of avoiding leakage to the non-poor, largely\nignoring the duel problem of incomplete coverage. In particular, see Cornia and Stewart (1995) who\n\n\n13", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003510", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "UHSS", "probe_tag": "keep", "probe_score": 0.9459839463233948, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 828, "end": 832, "key": "prwp:003510:14:1:0", "source": "camp2", "luna_reason": "UHSS identifies the poor and supports the coverage finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "EMDEs.\n\n\nData\n\n\nThe estimation relies on bilateral trade costs from the UNESCAP-World Bank Trade\nCosts Database. Following Novy (2013) and Arvis et al. (2013), bilateral trade costs are\nobtained as geometric averages of flows between countries i and j. They are computed\naccording to the formula below:\n\n_(Xii Xjj)/(Xij Xji)_ <sup>1/2 (</sup> <sup>_σ_</sup> <sup>-1)</sup>,\n\nwhere _Xij_ represents trade flows between countries _i_ and _j_ (goods produced in _i_ and sold\nin _j_ ) and _σ_ refers to the elasticity of substitution. This measure captures international\ntrade costs relative to domestic trade costs. Intuitively, trade costs are higher when\ncountries trade more domestically than they trade with each other, i.e., as the ratio ( _Xii_\n_Xjj_ )/( _Xij Xji_ ) increases. Intra-national (that is, domestic) trade is proxied by the difference\nof gross output and total exports.\n\n\nTrade costs thus computed implicitly account for a wide range of frictions associated\nwith international trade, including transport costs, tariffs, and nontariff measures, and\ncosts associated with differences in languages, currencies and import or export\nprocedures. Trade costs are expressed as ad valorem (tariff) equivalents of the value of\ntraded goods and can be computed as an aggregate referring to all sectors of the\neconomy, but also specifically for the manufacturing and agriculture sectors.\n\n\nEstimation\n\n\nGravity equations are widely used as a workhorse to analyze the determinants of\nbilateral trade flows. Chen and Novy (2012) and Arvis et al. (2013) also employ a\ngravity specification to analyze the determinants of bilateral trade costs in a\ncross-sectional", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001145", "page": 28, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNESCAP-World Bank Trade\nCosts Database", "probe_tag": "keep", "probe_score": 0.9659513235092163, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 72, "end": 111, "key": "prwp:001145:28:0:0", "source": "camp2", "luna_reason": "Named database provides bilateral trade costs used in estimation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " the factor\nloadings. To tackle this problem, Shi and Lee (2017) develop a bias correction that\nyields an asymptotically normal, properly-centered estimator. The estimations reported\nbelow using common factors employ the bias-corrected estimator.\n\n#### **3 Data**\n\n\nWe assess the international comovement of equity returns using a balanced panel data\nset comprising 40 advanced and emerging countries over 1995:1 to 2016:3    - a total of\n3,480 quarterly observations. Because advanced countries tend to exhibit higher real\nand financial openness, as well as larger and more liquid financial markets, than other\ncountries, we consider separately a subsample of 25 advanced economies, comprising\n2,175 observations. Table A1 in the appendix provides the complete list of countries.\nFollowing Hirata, Kose, Otrok and Terrones (2013), we measure equity prices by the\nstock market price index for each country. Real equity returns are then given by the first\ndifference of the log of equity prices deflated by the consumer price index. <sup>9</sup> We collect\nthe equity price index data from the OECD Statistics Database, except in the cases of\nArgentina, Hong Kong and Peru, for which we draw the data from Investing.com. <sup>10</sup>\n\nFigure 1 depicts the cross-country average of the real equity returns. It displays very\nsimilar fluctuations over the two country samples, including a sharp decline around the\nfourth quarter of 2008, at the onset of the global crisis.\n\nAs already mentioned, we consider three covariates of equity returns: real GDP,\nshort term interest rates and private credit. The GDP data comes from the OECD\nStatistics Database and the International Financial Statistics (IFS) of IMF and\ncomplemented with national statistics sources as well as the Federal Reserve Bank of\nSt. Louis Economic Data (FRED). Credit is measured by domestic credit to the\nprivate sector,", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007442", "page": 9, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "data from Investing.com", "probe_tag": "keep", "probe_score": 0.9075446128845215, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1195, "end": 1218, "key": "prwp:007442:9:3:3", "source": "camp2", "luna_reason": "Investing.com data provide equity price inputs for calculated real returns.", "usage_type": "evidential", "specificity": "named"}, {"text": "Federal Reserve Bank of\nSt. Louis Economic Data", "probe_tag": "keep", "probe_score": 0.9835756421089172, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1771, "end": 1818, "key": "prwp:007442:9:3:5", "source": "camp2", "luna_reason": "Named economic database used as a source for GDP data.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "Our perspective on EWAP dynamics in EMDEs is motivated by the literature on structural change.\nA key dynamic among EMDEs is the movement of economic activity out of agriculture and into\nnon-agriculture. Labor markets in these two sectors have very different operating features:\nagricultural labor markets are dominated by self-employment in low-density rural areas, whereas\nnon-agricultural labor markets are dominated by formal or informal employment in higher-density\nurban areas. Additionally, many policy and institutional differences are likely to have very\ndifferent effects on labor markets in these two sectors. For these reasons, the process of structural\nchange will plausibly give rise to dynamics in aggregate labor market outcomes, as activity\nswitches from largely self-employment in rural areas to formal or informal employment in urban\nareas. Long-run labor market outcomes will thus reflect the steady state outcomes in the nonagricultural sector.\nOur methodology for studying EWAP dynamics draws heavily on the growth literature that studies\nconvergence patterns in cross-country panel data sets. Specifically, following the literature on\nconditional convergence, we include country fixed effects in our convergence regressions to allow\nfor the possibility that each country is converging to its own steady-state level of EWAP. When\nimplementing this procedure, we also control for two time-varying driving forces: productivity\nand population.\nOur analysis of EWAP dynamics proceeds in two steps. The first step runs convergence\nregressions for EWAP. A by-product of this first step are country-specific steady-state values for\nthe EWAP. In the second step, we examine the correlation between these steady-state levels and\nvarious indicators.\nOur first step delivers three key results. First, while there are many countries with very similar\nsteady-state EWAP levels, there are many countries with steady-state EWAP levels that display\nlarge deviations from the mean. Second, higher population growth is associated with significantly\nlower EWAP. Third, higher productivity growth is also associated with", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001532", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "cross-country panel data sets", "probe_tag": "keep", "probe_score": 0.9241855144500732, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1084, "end": 1113, "key": "prwp:001532:4:0:0", "source": "camp2", "luna_reason": "Generic dataset reference without an attributed finding or concrete data use", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": ", this appears to be the only paper that relies exclusively on the rich data available from\nhousehold consumption surveys to measure the welfare implications of various types of digital\ntechnologies, that is, mobile phone access, fixed broadband Internet, and mobile broadband Internet.\n\nThe analysis applies a robust methodology that can be used to assess the impact of mobile and fixed\nbroadband Internet across Sub-Saharan Africa as more data on coverage and connectivity become\navailable. In addition, the results contribute an important perspective to the policy discussion on the\ndegree to which digital infrastructure can serve as a welfare- and resilience-enhancing mechanism. By\ndemonstrating that broadband coverage can improve consumer welfare and reduce poverty, the paper\nsupplies evidence on the positive spillovers of connectivity. This empirical evidence can be useful to\npolicy makers in addressing public investment gaps across various sectors of infrastructure.\n\nThe rest of the paper is structured as follows. Section 2 describes the data sources, while section 3\npresents the estimation strategy. Section 4 discusses the results, and section 5 concludes.\n\n\nhttp://www.africabandwidthmaps.com/. Internet traffic in countries runs first through national backbone or fiber-optic\nnetworks, which are then connected to end users through last-mile infrastructure, such as fiber cables, copper cables,\nwireless transmission, or cellphone towers. 2G, 3G, and 4G mobile coverage maps have been obtained from three major\ntelephone communication providers—Orange (or the local subsidiary Sonatel), Senegal Expresso, and Tigo—and Mobile\nCoverage Maps (database), Collins Bartholomew, HarperCollins Publishers, Glasgow,\nhttps://www.collinsbartholomew.com/mobile-coverage-maps/.\n4 Bahia et al. (2020) are a notable exception. They explicitly test the impact of 3G and 4G technologies on consumption\nand poverty using data on Nigeria.\n\n\n3", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000119", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household consumption surveys", "probe_tag": "keep", "probe_score": 0.916936457157135, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 92, "end": 121, "key": "prwp:000119:4:1:0", "source": "camp2", "luna_reason": "Surveys are used to measure welfare effects of digital technologies.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**APPENDIX**\n\n\n**Appendix 1: Constructing the Exporter Dynamics Database Using Customs Data at the**\n\n**Exporter-Level**\n\n\nThe measures included in the Database are computed using customs data from 45 countries at the\nexporter-product-destination-year level covering the universe of export transactions. <sup>35</sup> [^35: The providers of the raw datasets for each country were mostly governmental agencies, mainly customs offices. Appendix 1 in\nCebeci et al. (2012) provides a complete list of the countries included in the Database, the periods for which data is available, and\nthe data sources.] For 11\ncountries (Brazil, the Arab Republic of Egypt, Estonia, Lao PDR, New Zealand, Norway, Portugal,\nSpain, Sweden, and Turkey), we do not have access to the raw data and the statistics were\ncalculated for us by researchers or institutions with access to the raw data. Pooling across the raw\ndatasets for the remaining 34 countries, we obtain a panel with 15 million unique observations at\nthe country-firm-product-destination-year level which is the raw dataset used to construct the\nDatabase. Some of the variables in this cross-country raw dataset were subjected to a series of\ncleaning procedures or had peculiarities that we briefly describe below: firm codes, country of\ndestination, product and export values. <sup>36</sup> [^36: Cebeci et al. (2012) describe the cleaning procedures in further detail. Note that the cross-country raw dataset at country-firmproduct-destination-year level includes also quantities exported.]\n\nRegarding firm codes, exporters are uniquely identified by their actual names, their tax\nidentification number or artificial unique codes randomly created by our data providers. In the case\nof Albania, Burkina Faso, Cambodia, Cameroon, Mexico, and Uganda their firm coding systems\nunderwent changes in 2007 and in the case of Yemen in 2008. Hence, it is not possible to calculate\nexporter dynamics measures in the years when those changes occur.\n\nRegarding the country of destination variable, two cleaning operations are", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006500", "page": 45, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Exporter Dynamics Database", "probe_tag": "keep", "probe_score": 0.9338422417640686, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 46, "end": 72, "key": "prwp:006500:45:0:0", "source": "camp2", "luna_reason": "Appendix describes constructing the database from customs data", "drop_reason": "production", "specificity": "named"}, {"text": "raw\ndatasets", "probe_tag": "confusion", "probe_score": 0.13549426198005676, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 891, "end": 903, "key": "prwp:006500:45:0:3", "source": "camp2", "luna_reason": "Raw datasets are pooled to construct a panel with 15 million observations.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": ".503*** 0.877***\nHH Married 0.188 0.0615 1.192***\nHH Gender - HH Married -0.21 -0.221 -1.532**\n**Quality** **of** **Dwelling**\nNumber of Rooms 0.0614* 0.0527 -0.0260\nQuality of Walls\n\n(baseline=Low)\n\nMedium -0.175 -0.314 0.509*\nHigh -0.444*** -0.564*** -0.254\n**Assets**\nTV -0.0738 -0.0483 0.382\nFridge 0.078 0.259* -0.527\nStove -0.273*** -0.372*** -0.939**\nBicycle 0.354*** 0.408* 0.368\nCar -0.280** -0.486*** -0.319\nIron 0.0453 0.113 -0.260\n\n\nConstant 0.819*** 0.0513 -2.585***\n\n\nObservations 4,577 1,289 359\n<u>Pseudo</u> <u>R-squared</u> <u>0.141</u> <u>0.19</u> <u>0.357</u>\nRobust standard errors (not reported)\n\n*** p _<_ 0.01, ** p _<_ 0.05,              - p _<_ 0.1\nSource: Authors’ estimations based on GHS and ACLED Data\n\n\n37", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007320", "page": 39, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "ACLED Data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 721, "end": 731, "key": "prwp:007320:39:1:1", "source": "camp2", "luna_reason": "Named ACLED data underpin authors’ regression estimations.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "FAO. 2008. Global Change in Net Primary Productivity (1981-2003). Rome: Food and Agricultural\nOrganization.\n\n\nFAO. 2010. Global survey of agricultural mitigation projects. Rome: Food and Agricultural Organization.\n\n[Available on the internet at http://www.fao.org/docrep/012/al388e/al388e00.pdf.](http://www.fao.org/docrep/012/al388e/al388e00.pdf)\n\n\nFAO. 2010. Land use systems of the World – East Europe and Central Asia. Available on the internet at:\n\nwww.fao.org/nr/lada/\n\n\nFAO. 2011. FAO statistical databases. Food and Agriculture Organization. Available on the internet at\n\nfaostat.fao.org\n\n\nFAO-UNESCO. 2007. Soil Map of the World: Organic carbon pool – Topsoil. Available on the internet at\n\nwww.fao.org\n\n\nGhosh, P. and J. Puri (eds). 1994. Joint implementation of climate change commitments: Opportunities and\n\napprehensions. Tata Energy Research Institute, New Delhi.\n\n\nGold Standard Foundation. 2010. The Gold Standard Premium quality carbon credits requirements. Available\n\non the Internet at www.cdmgoldstandard.org.\n\n\nGraff-Zivin, Joshua and Leslie Lipper. 2008. Poverty, risk, and the supply of soil carbon sequestration.\n\nEnvironment and Development Economics 13(3), 353-73.\n\n\nGrubb, Michael, Christiaan Vrolijk and Duncan Brack. 1999. The Kyoto Protocol: A Guide and Assessment.\n\nLondon: Earthscan/ James and James.\n\n\nGulbrandsen Lars H. and Steinar Andresen. 2004. NGO influence in the implementation of the Kyoto\n\nProtocol: Compliance, flexibility mechanisms, and sinks. Global Environmental Politics 4(4), 54-75.\n\n\nHaites, Erik, Maosheng Duan and Stephen Seres. Technology", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005251", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "FAO statistical databases", "probe_tag": "confusion", "probe_score": 0.30829542875289917, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 488, "end": 513, "key": "prwp:005251:36:0:1", "source": "camp2", "luna_reason": "Bibliographic entry naming FAO databases without showing data use.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": " IDP data focus only on internally displaced populations to which it extends protection or assistance. IDMC\ncoverage of IDP data is more expansive and in 2015 included additional data on: (a) 26 countries accounting for 4.5\nmillion IDPs including some significant IDP hosting countries (Turkey, India, Ethiopia, Bangladesh and Kenya); and (b)\nIDPs in countries where UNHCR is active who are not protected or assisted by the agency. In 2015, IDMC’s aggregate\nfigure for conflict-induced internal displacement was 3.3 million higher than UNHCR’s aggregate figure for IDPs\nprotected or assisted by the agency.\n\n29 IDMC’s 2016 report presents both data sets alongside each other. In certain contexts, there can be significant\noverlaps in these two groups; however data systems may be maintained separately for conflict-induced displacement\nand natural disasters (e.g. in Afghanistan) leading to possible gaps or double counting if these categories are combined.\n\n30 The IOM Displacement Tracking Matrix (DTM) is a system to track and monitor displacement and population mobility.\nIt is designed to regularly and systematically capture, process and disseminate information to provide a better\nunderstanding of the movements and evolving needs of displaced populations, whether on site or en route. It has been\nactive in over 40 countries since its inception in 2004. See http://www.globaldtm.info/.\n\n31 This is typically defined as nomads not having access to their traditional routes, but routes can vary.\n\n32 IDMC has recently adjusted their methodology to facilitate greater comparability across situations and improvements\nare reflected in IDMC’s end-2015 data.\n\n33 This is not necessarily a problem if the purpose of the registration system is to delineate entitlements to assistance\nrather than to determine status.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006980", "page": 15, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "IOM Displacement Tracking Matrix", "probe_tag": "confusion", "probe_score": 0.6939594149589539, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 966, "end": 998, "key": "prwp:006980:15:2:2", "source": "camp2", "luna_reason": "Names a displacement-tracking system without showing its data being used.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "end-2015 data", "probe_tag": "confusion", "probe_score": 0.8540361523628235, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1646, "end": 1659, "key": "prwp:006980:15:2:3", "source": "camp2", "luna_reason": "IDMC’s dated data supports the claim that methodology improvements were reflected.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "Source: Authors’ calculations based on predicted probability from model 3 for ELMPS 2012 and ELMPS 2018, see Table 4\n\n\nNotes: Firm age category “don’t know” was combined with 5 years or above.\n\n\n\n44", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000524", "page": 45, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "ELMPS 2012", "probe_tag": "confusion", "probe_score": 0.7204289436340332, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 78, "end": 88, "key": "prwp:000524:45:0:0", "source": "camp2", "luna_reason": "Named survey round used for authors’ model-based calculations.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "18\n\n\nFigure 3: Indexes of real international prices and real producer prices of rice and wheat,\n\ndeveloping countries’ unweighted average, 1972-76 (1972 = 100).\n\n\n(a) Rice\n\n\n400\n\n\n\n350\n\n\n300\n\n\n250\n\n\n200\n\n\n150\n\n\n100\n\n\n50\n\n\n0\n\n\n(b) Wheat\n\n\n\n\n\n400\n\n\n350\n\n\n300\n\n\n250\n\n\n200\n\n\n150\n\n\n100\n\n\n50\n\n\n0\n\n\nNote: Countries included are: Argentina, Bangladesh, Brazil, Chile, Colombia, Cote d’Ivoire,\nDominican Republic, Ecuador, Ghana, India, Indonesia, Kenya, Korea, Madagascar,\nMalaysia, Mozambique, Nigeria, Pakistan, Philippines, Senegal, Sri Lanka, Sudan, Taiwan,\nTanzania, Thailand, Uganda, Zambia, and Zimbabwe.\n\n\nSource: Authors’ compilation based on data in Anderson and Valenzuela (2008).", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004591", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data in Anderson and Valenzuela", "probe_tag": "confusion", "probe_score": 0.7068085670471191, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 644, "end": 675, "key": "prwp:004591:19:0:0", "source": "camp2", "luna_reason": "Source data used in authors’ compilation of the presented price indexes.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " non-consumption data are reliable. The consumption models use household\nand individual characteristics such as educational attainment and employment status of household members,\nhousehold composition and the like. This S2S approach is useful if price adjustments or poverty lines are\nnot comparable over time, but non-consumption data are comparable. Given some key assumptions are\nsatisfied, Christiansen et al. (2012) and Ahmed et al. (2013) corroborate the reliability of this approach\nusing data from various countries.\n\nNISR (2016) estimates a poverty trend between 2010/11 and 2013/14 using the S2S approach and compares\nit with the official poverty trend between 2010/11 and 2013/14 in NISR (2015). Following Tarozzi (2002),\nNISR (2016) estimates a logistic regression model to predict the probability of being poor from nonconsumption data using EICV4, predicts a poverty rate from a model using EICV4, and applies it to nonconsumption data in EICV3. Using this approach, they find that the poverty rate of EICV3 is 44.6 percent,\nwhich is almost the same as the official poverty estimate for EICV3, i.e., 44.9 percent. NISR (2016) also\nestimates the poverty rate of EICV4 using this approach (39.0 percent), which is almost identical to the\nofficial estimate of EICV4 (39.1 percent). The S2S analysis, therefore, also confirms that the official trend\nis reliable.\n\n\nIn Rwanda, the reduction in food budget shares over time also corroborates the poverty decline. Typically,\nincreases in income are strongly associated with a declining share of the budget spent on food (Engel’s\nlaw). We examine if this is true in the case of Rwanda. We estimate real food budget shares, expressed in\nJanuary 2014 prices, for 2010/11 and 2013/14 and find that the real food", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007505", "page": 15, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "non-consumption data", "probe_tag": "confusion", "probe_score": 0.0627371072769165, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1, "end": 21, "key": "prwp:007505:15:1:1", "source": "camp2", "luna_reason": "Data are explicitly judged reliable and used in poverty estimation analysis.", "usage_type": "evidential", "specificity": "vague"}, {"text": "nonconsumption data", "probe_tag": "confusion", "probe_score": 0.8965495228767395, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 829, "end": 848, "key": "prwp:007505:15:1:2", "source": "camp2", "luna_reason": "Existing data used in poverty prediction and tied to reported poverty-rate findings.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "people may also gain from conflict in terms of income and wealth and this may explain why some people\n\n\ndo not move. The defining attributes of the alternative choices are very different from any other model\n\n\nand the task of economics is to understand what these defining attributes should be.\n\n\nIn terms of independent variables, “push” factors become more important than “pull” factors in forced\n\n\ndisplacement models. The intensity of a conflict may be more important than the income opportunities\n\n\nin potential destination areas. In addition to the classic socioeconomic variables, risk aversion, stress,\n\n\nanxiety, other traits of personality and behavioral factors in general have to be well understood and\n\n\nmeasured. Hence, one could think of four essential blocks of independent variables including individual\n\n\nor household socioeconomic characteristics, “push” factors, “pull” factors and behavioral factors. Also,\n\n\naccess to and dissemination of information related to the conflict in the place of origin but also in the\n\n\npotential places of destination may be crucial for people to make choices. This is where social psychology,\n\n\nbehavioral economics and neuroeconomics may offer insights into such choices.\n\n\nForced displacement data are also unusual in their form. Deciding on whether to flee or not to flee a\n\n\nconflict (the migration choice) can be an individual or household choice and risk coping strategies may\n\n\ninclude temporary migration, shuttling between places, migration of only selected members of the\n\n\nhouseholds or migration of the whole household. This implies that individuals may stay put throughout\n\n\nthe period observed, join or leave the household during the period, or have several episodes of out and\n\n\nimmigration. Households may decide to leave and come back several times. In econometric terms, this\n\n\nmeans that longitudinal data may be left and right censored and have spells within. They are therefore\n\n\nthe most complex set of panel data possible and require particular treatment of data and modeling.\n\n\nSurvival or duration models can usually accommodate many of these complexities but it is very rare to\n\n\nfind similar data sets used in published articles. Collecting such type of data", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007029", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Forced displacement data", "probe_tag": "confusion", "probe_score": 0.18687224388122559, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1228, "end": 1252, "key": "prwp:007029:15:0:0", "source": "camp2", "luna_reason": "Data are analyzed as unusually structured longitudinal displacement records.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "s) and advanced machine-learning\ntechniques have especially promising applications in developing countries, as they can potentially\ngenerate reliable poverty data at a far lower cost than conventional household surveys.\n\n\nCDR analysis can play a vital role by filling the spatial and temporal gaps left by traditional\nresearch methods. By making inferences based on cellular network usage, CDR analysis can\nreliably project the evolution of poverty dynamics over a specific timeframe. Unlike censuses and\nhousehold surveys, CDR analysis is quick and relatively inexpensive and can be performed by a\nsmall team of statisticians using records that are already collected by Mobile Network Operators\n(MNOs).\n\n\nGuatemala offers a prime example of the limits of traditional data collection. The country’s\nmost recent Population and Housing Census, dates from 2002, and all national poverty data are\nderived from just four household surveys conducted over the past 25 years. For example, the most\nrecent 2014 household survey ( _Encuesta Nacional de Condiciones de Vida_, ENCOVI) covered\n\n\n**3**", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006965", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household surveys", "probe_tag": "confusion", "probe_score": 0.8881399631500244, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 201, "end": 218, "key": "prwp:006965:4:1:1", "source": "camp2", "luna_reason": "Generic survey category is only a comparison, not cited as used data.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "; the effective weighted average is found to equal\n45 percent (data from DATAPREV, SUB, Plano Tabular da DIIE, and Ministerio da fazenda).\n\n\n<u>1</u>\n##### 10 The expression stated in dynamic terms: kGRt = (α( 1 + qt ) / [( 1 + nt )( 1 + gt )]α ) 1 −α .\n\n\n14", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005733", "page": 15, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "DATAPREV", "probe_tag": "keep", "probe_score": 0.921302318572998, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 73, "end": 81, "key": "prwp:005733:15:3:0", "source": "camp2", "luna_reason": "Named administrative source supplying data for the weighted-average calculation.", "usage_type": "evidential", "specificity": "named"}, {"text": "Ministerio da fazenda", "probe_tag": "confusion", "probe_score": 0.7966734170913696, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 115, "end": 136, "key": "prwp:005733:15:3:3", "source": "camp2", "luna_reason": "Named source cited for the 45-percent calculation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": ". Achievements and challenges in Cameroon’s infrastructure sectors 8\nTable 2. Trading across borders in Central African countries 10\nTable 3. Cameroon’s road indicators benchmarked 12\nTable 4. Condition and type of road corridors passing through Cameroon 15\nTable 5. Port indicators for selected ports 17\nTable 6. Comparative performance ofCentral African railways, 2005 19\nTable 7. Benchmarking of Cameroon’s air transport indicators 21\nTable 8. Cameroon's irrigation potential 25\nTable 9. Cameroon’s water and sanitation indicators benchmarked 26\nTable 10. Cameroon’s power indicators benchmarked 31\nTable 11. AES Sonel’s hidden costs 34\nTable 12. Cameroon’s ICT indicators benchmarked 36\nTable 13. Africa’s ICT prices, 2008 39\nTable 14. Illustrative investment targets for infrastructure in Cameroon 39\nTable 15. Indicative infrastructure spending needs in Cameroon for 2006 to 2015 40\nTable 16. Financial flows to Cameroon’s infrastructure, 2001-2006 41\nTable 17. Cameroon’s potential gains from greater operational efficiency 42\nTable 18. Funding gaps by sector 46\nTable 19. Savings from innovation 47\n\n\niv", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004998", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "ICT indicators", "probe_tag": "confusion", "probe_score": 0.06470555067062378, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 661, "end": 675, "key": "prwp:004998:5:1:1", "source": "camp2", "luna_reason": "Standalone table-header fragment, not an independently usable data mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "26\n\n\nstatus to determine the district‘s autonomy status; and where there is only a central hospital,\n\n\nwe use the central hospital‘s status to determine the district‘s autonomy status. When deriving\n\n\nour autonomy variable, we exclude specialized hospitals for mental illness, rehabilitation,\n\n\nleprosy, tuberculosis, pediatrics, and traditional medicine, because they tend to provide\n\n\nmainly subsidized or highly specialized services.\n\n\nOutcome variables\n\n\nOur outcome variables include the number of hospital outpatient visits and the\n\n\nnumber of inpatient admissions. In both cases, we also estimate models capturing simply\n\n\nwhether a visit or admission occurred. The recall period in both cases is 12 months, and the\n\n\ndata on utilization are available for every household member. In addition, we explore the\n\n\nimpacts of autonomization on total out-of-pocket spending on hospital outpatient and\n\n\ninpatient care, as well as the average out-of-pocket spending per visit and admission. The\n\n\nexpenditure data have been converted to real values using the Vietnam consumer price index.\n\n\nCovariates in the estimating equation\n\n\nOur covariates include two variables that are unlikely to be correlated with the\n\n\nautonomy status of the local hospital ―market‖ but which we include to increase the precision\n\n\nof our estimates. These include the individual‘s health insurance status (some insurance\n\n\ncoverage is specific to the individual in Vietnam, while other coverage applies to all\n\n\nhousehold members), and the household‘s per capita consumption. The latter is a\n\n\nconsumption aggregate reflecting not just market expenditures but also other elements of\n\n\nconsumption such as the value of home-grown produce and the imputed rent of an owned\n\n\nhouse. In addition to these variables, we include whether the household lives in a rural area –\n\n\nthis may be correlated with the timing of the autonomization of the hospitals in the\n\n\nhousehold‘s district.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005304", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "expenditure data", "probe_tag": "confusion", "probe_score": 0.38888928294181824, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 997, "end": 1013, "key": "prwp:005304:27:0:1", "source": "camp2", "luna_reason": "Expenditure data are converted using Vietnam’s consumer price index for analysis.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "Portugal SIMPOC Labour Force Survey 2001\nCentral African Rep. MICS Multiple Indicator Cluster Survey 2000\nRwanda MICS Multiple Indicator Cluster Survey 2000\nSenegal MICS Multiple Indicator Cluster Survey 2000\nSierra Leone MICS Multiple Indicator Cluster Survey 2000\nSouth Africa SIMPOC Survey of Activities of young people 1999\nSudan MICS Multiple Indicator Cluster Survey 2000\nSwaziland MICS Multiple Indicator Cluster Surveys 2000\nTanzania SIMPOC Integrated Labour Force Survey 2001\nTogo MICS Multiple Indicator Cluster Survey 2000\nTrinidad and Tobago MICS Multiple Indicator Cluster Survey 2000\nTurkey SIMPOC Labor Force Survey 1999\n\nMultipurpose\n\nUganda Survey National Household Survey UNHS-2 2202-2003\n\nUzbekistan MICS Multiple Indicator Cluster Surveys 2000\n<u>Venezuela</u> <u>LSMS</u> <u>Encuesta de Hogares por Muestreo</u> <u>2003</u>\n\n\n18", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003332", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MICS Multiple Indicator Cluster Survey", "probe_tag": "confusion", "probe_score": 0.8854237198829651, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 62, "end": 100, "key": "prwp:003332:17:0:1", "source": "camp2", "luna_reason": "Names an existing MICS survey as a cited data resource.", "usage_type": "declaration", "specificity": "named"}, {"text": "LSMS", "probe_tag": "confusion", "probe_score": 0.5916993618011475, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 785, "end": 789, "key": "prwp:003332:17:0:13", "source": "camp2", "luna_reason": "Named LSMS survey listed as an existing data source.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "Looking at the pattern of commitments in the UR by the range of commitment and degree\n\n\nof development, a similar pattern develops to that observed in trade policy on goods: the degree of\n\n\nliberalization appears to increase with the level of income -- as shown in Table 14. Lower-income\n\n\ncountries appear to have committed to much less liberalization than higher-income ones. The\n\n\nsame conclusion can be drawn by looking at the commitments of the fifty developing countries\n\n\nwhose trade regimes were analyzed more systematically. Indeed, the pattern in Table 14 has a\n\n\nstriking parallel to the pattern in Table 3 above, with the lower the developing country income,\n\n\nthe lower the number of commitments and hence the highest the remaining protection. (See also\n\n\nBorchert, Goortiiz and Mattoo 2011, p.123.) The basic justification low-income countries make\n\n\nfor not liberalizing their service sector is the same infant industry argument used for so very long\n\n\nin the areas of merchandise trade. There are obvious dangers and limits to such a strategy as many\n\n\ndeveloping countries have realized in the areas of goods. These dangers have to be seriously\n\n\nevaluated by low-income developing countries which continue to protect their service sectors.\n\n\nOn the other hand the table shows that this relationship between the extent of liberalization\n\n\nand the level of development did not hold true for the financial services sector which includes\n\n\nbanking and insurance. In this case there is basically no pattern discernible, with most groups of\n\n\ncountries liberalizing about a quarter of the maximum possible -- if one weighs partial restrictions\n\n\nin each of the modes of supply. Again the LDCs made the fewest commitments. Only nine of the\n\n\ntwenty nine LDC made any commitments. But those which did, on average made greater\n\n\nliberalizing commitments than other developing countries.\n\n\nEarlier analysis (Mattoo 1998) suggests that in the area of commitments on commercial\n\n\npresence for financial services, Latin American countries tend to limit the number of suppliers,\n\n\nwhile Asian economies limit either solely the percentage of equity", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005614", "page": 65, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "commitments of the fifty developing countries", "probe_tag": "confusion", "probe_score": 0.8246782422065735, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 431, "end": 476, "key": "prwp:005614:65:0:0", "source": "camp2", "luna_reason": "Names commitments, not an eligible data resource or source.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "\nduring this period drove the gains, and what elements of the approach were successful.\n\n\nFirst, we separate growth in the value of cereal production (teff, wheat, barley, maize and sorghum)\nfrom growth in the value of cash crop production (coffee, chat, nueg and sesame) and examine what\ntype of growth was most strongly associated with poverty reduction (Table 7, column 1). The regression\nresults show that gains were more strongly associated with growth in cereal, not cash crop, production.\n\n\nNext, we explore the determinants of growth in cereal production and examine the relationship\nbetween cereals growth and weather, prices and the use of improved inputs. Given these regressions do\nnot use poverty data, we are also able to include in the regression years in which poverty data are not\navailable. As such the panel is expanded to include all years from 1996 to 2011 (with the exception of\n2002 and 2003 for which there are no data). The regressions include only the main crop‐producing zones\nin the sample, and exclude Afar, Somali, Harari, Addis Ababa and Dire Dawa.\n\n\nDespite substantial increases in the use of fertilizer over this period, the regression estimates in columns\n2 and 3 indicate that on average increased fertilizer was not associated with growth. This is quite\nstriking, but consistent with other literature that shows that returns to use of fertilizer are highly\nweather dependent in Ethiopia (Christiaensen and Dercon 2010), and that the ratio of the price of\nfertilizer to cereals has been quite varied over time (Spielman et al 2007). Given the literature shows\n\n\n16", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007323", "page": 17, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "poverty data", "probe_tag": "confusion", "probe_score": 0.6968235969543457, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 702, "end": 714, "key": "prwp:007323:17:1:0", "source": "camp2", "luna_reason": "States poverty data are not used or available, without analyzing them.", "drop_reason": "availability", "specificity": "vague"}]}
-{"text": "</sup> _y_ <sup>_′_</sup> <sup>_, θ_</sup> _p_ <sup>_′_</sup> <sup>_}_</sup> <sup>.</sup> <sup>The</sup> <sup>reason</sup> <sup>is</sup> <sup>that</sup>\n\ntransfers to the Ricardian household do not alter the discounted flow of expected after-tax income\nof the Ricardian household when _θa_ <sup>_′′_</sup> <sup>= 0.</sup>\n\n\n\n_a_ <sup>_′′_</sup> <sup>= 0.</sup>\n\n\n\n3.3. **Calibration.** **General** **Parameters**\n\nMany of the most important parameters are not country specific, and so we calibrate these to\n\ninternational data or take them from the literature. The most important are the persistence of\n\ncommodity price shocks, which we calibrate to a weighted average of oil prices and gas prices taken\n\nfrom BJS2013. The overall persistence ( _ρ_ = 0 _._ 93) is a weighted average of oil prices ( _ρ_ = 0 _._ 94) and\ngas prices ( _ρ_ = 0 _._ 89) as many oil exporters also produce gas. <sup>15</sup> We set _β_ = 0 _._ 96 so that long-run\n\nannual real rate of interest is 4%. The coefficient of risk aversion _σ_ = 2, which is a standard\n\nparameter in the literature. We follow Galí _et", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007026", "page": 13, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "international data", "probe_tag": "confusion", "probe_score": 0.686920702457428, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 508, "end": 526, "key": "prwp:007026:13:3:0", "source": "camp2", "luna_reason": "International data inform calibration of model parameters and commodity-price persistence.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "BJS2013", "probe_tag": "keep", "probe_score": 0.9307494163513184, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 710, "end": 717, "key": "prwp:007026:13:3:1", "source": "camp2", "luna_reason": "Cited source for oil and gas price persistence calibration.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " coffee % total land size 0.58 0.58 0.00 1.00 0.00 0.79\nYield of coffee per hectare 3323.31 3273.56 49.75 0.83 100.09 0.72\nShare of red cherry sold to Fairtrade\nCoop (%) 94.47 94.55 -0.08 0.94 0.03 0.98\n\n**Panel B: Head of Household (N=1197)**\nGender (% Male) 0.89 0.87 0.02 0.24 0.01 0.53\nAge 50.22 49.65 0.57 0.53 0.41 0.65\nYears of schooling 3.92 3.82 0.11 0.63 0.09 0.73\nMarried 0.86 0.84 0.02 0.44 0.01 0.59\n\n**Panel C: Children aged 6-14 (N =1880)**\nGender (% Male) 0.01 0.69\nAge 0.14 0.25\nYears of schooling 0.05 0.65\nCurrently attending school -0.01 0.44\n\n**<u>Source:</u>** <u>Authors’ analysis based on an agricultural household survey conducted in 2015.</u>\n**Note:** Sample means computed from the first survey carried out in July 2015. P-values refer to the null\nhypothesis of equality of means between self-reported and proxy-reporting measures. Proxy respondents\ninclude head of households and spouses.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000466", "page": 39, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "agricultural household survey", "probe_tag": "confusion", "probe_score": 0.768385112285614, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 616, "end": 645, "key": "prwp:000466:39:1:0", "source": "camp2", "luna_reason": "Authors’ analysis is based on the completed 2015 household survey.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**9**\n\nthe conversion factor is determined **by** interacting supply and demand for foreign exchange.\n\nIt is shifts in these supply and demand schedules that give rise to price (i.e., exchange rate)\n\nchanges. Thus it should be recognized that the exchange rate is a price that balances the\n\ndesire to exchange one currency for another in order to effect trade in goods and services.\n\nThe introduction of restrictions into the price system prevents the price from fulfilling a\n\nstabilizing function of equalizing supply and demand, thus affecting relative prices, the\n\nprofitability of individual activities, and thus resulting in distortions in resource allocations.\n\n\nConversion Factor and Price Levels of Traded/NonTraded Goods\n\n**13.** The imposition of price measures (tariffs, specific taxes, import surcharges, advance\n\ndeposits on imports, export taxes and subsidies, and multiple exchange rates) and non-price\n\nmeasures (quotas, licencing **)** alter relative price levels between sectors, e.g., traded goods\n\nand nontraded goods. Here we are confronted with the issue of the distinction between\n\n\"traded goods (sector)\" and \"nontraded goods (sector)\" as well as between \"tradables\" and\n\n\"nontiadables.\" In very general terms, traded goods can be regarded as those that can be\n\nimported (and exported), while nontraded goods are those without close, foreign-produced\n\nsubstitutes and must therefore be supplied **by** domestic producers. More specifically, traded\n\ngoods can be regarded as \"goods that are sufficiently substitutable with goods produced\n\nabroad that there exists an international market; nontraded goods are those that are not\n\n**highly** substitutable with foreign-produced goods so that international trade in these goods\n\ndoes not exist\".' **A** very narrow dichotomy is that given in the foreign trade statistics in the\n\n\n**6**\nGeorge **", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000198", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "foreign trade statistics", "probe_tag": "confusion", "probe_score": 0.8797375559806824, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1816, "end": 1840, "key": "prwp:000198:15:0:0", "source": "camp2", "luna_reason": "Foreign trade statistics are cited as the basis for the goods-sector dichotomy.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"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:010305", "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:010305:45:6:0", "source": "camp2", "luna_reason": "Routine procurement progress reporting for project administration, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "|Col1|PSNP IV|Col3|IMPLEMENTATION STATUS REPORT (ISR) RF<br>INDICATOR TRACKING SHEET|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n||**PSNP IV**|**PSNP IV**|**Reported as of August 28, 2018**|**Reported as of August 28, 2018**|**Reported as of August 28, 2018**|**Reported as of August 28, 2018**|\n|<br>|<br>|<br>|30-Jun-18|30-Jun-18|30-Jun-18|30-Jun-18|\n|<br>|<br>|<br>|Numerator|Denominator|Percentage|Absolute Value<br>(Y/N, absolute<br>number, days, etc)|\n|13|**% OF CLIENTS RECEIVING REGULAR PAYMENTS WITHIN THE**<br>**AGREED TIME FRAME (20 DAYS FOR CASH AND 30 DAYS FOR**<br>**FOOD) **<br>|**% OF CLIENTS RECEIVING REGULAR PAYMENTS WITHIN THE**<br>**AGREED TIME FRAME (20 DAYS FOR CASH AND 30 DAYS FOR**<br>**FOOD) **<br>|||28.5%||\n|<br>|**CASH **|<br>|||40%||\n||RAW DATA<br>SOURCES:||||FIC<br>Report||\n||COMMENTS<br>||This", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017191", "page": 52, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "RAW DATA", "probe_tag": "drop", "probe_score": 0.0318, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 769, "end": 777, "key": "sample:fcv_pads_east_africa:017191:52:0:0", "source": "gold", "luna_reason": "Standalone table label, not an independently used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "83. _Procurement Delays:_ Cost of the civil works component at the time of bidding\nvaried substantially from that at the feasibility and detailed design stage due to delays in\nthe procurement process of about four years. The eventual bid prices could therefore not\nenable the project to be implemented as appraised and consequently some components\nhad to be dropped. In future, design reviews and updates of the cost estimates will be\nne **c** essary just before calling for bids. It would also be advisable to avoid a long\nprequalification period. It is also worthwhile to explore the possibility of commencing\nprocurement prior to credit effectiveness in order to provide for procurement lead-time.\n\n\n84. _Monitoring and Evaluation Indicators of the Projects:_ At appraisal, the baseline\ndata for the outcome indicators were not provided. These were provided in the ISR4 in\nAugust 2005. As a proxy for increased industrial and agricultural activity, the traffic\nincrease on the project roads was used to reflect the agricultural productivity benefits to\nthe rural population. The lesson learned is that baseline data should be provided at the\nappraisal stage for appropriate reading of the PDO indicators.\n\n\n**7.** **Comments on Issues Raised by Borrower/Implementing Agencies/Partners**\n\n**(a) Borrower/implementing agencies: None**\n\n**(b) Co financiers: No co-financier**\n\n**(c) Other partners and stakeholders** : **None**\n\n\n23", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018941", "page": 34, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "baseline\ndata", "probe_tag": "drop", "probe_score": 0.04448267072439194, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 781, "end": 794, "key": "fcv_pads_east_africa:018941:34:0:0", "source": "camp2", "luna_reason": "Baseline data absence is documented and motivates use of a proxy indicator.", "usage_type": "declaration", "specificity": "vague"}, {"text": "baseline data", "probe_tag": "confusion", "probe_score": 0.11525297164916992, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1105, "end": 1118, "key": "fcv_pads_east_africa:018941:34:0:1", "source": "camp2", "luna_reason": "The sentence recommends future provision of baseline data rather than using it as existing evidence.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": "Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**Innovative Activities**\n\n\n\nresponsibilities of all parties;\nNaCSA retains competent\n**(a) Capacity Building**\n\n\n\nstaff;\n\n                                             - Other governnent and donor\n**(b)** **Information and**\n\nsupport mobilized for\n\n\n\nsupport mobilized for\n**Sensitization**\ndecentralization to\ncomplement NaCSA efforts;\n(c) **Monitoring and**\n\n\n\n**Evaluation**\n\n\n\n**(d)** **Technical Assistance**\n\n\n(e) **Operating** Expenses\n\n\n\n-28", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010305", "page": 32, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "administrative data", "probe_tag": "drop", "probe_score": 0.027727268636226654, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 64, "end": 83, "key": "fcv_pads_east_africa:010305:32:1:0", "source": "camp2", "luna_reason": "Generic administrative data is mentioned without a concrete use or attributed finding.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": "**The World Bank**\nEnhancing Shared Prosperity through Equitable Services (P151432)\n\n\n\n|DLI IN01065485 ACTION<br>DLI 38|9.11: Dire Dawa City Administration and Sidama Region commenced procurement data entry for five basic sectors based on<br>agreed KPIs and furnished data captured in the first three quarters of EFY2014|Col3|Col4|Col5|\n|---|---|---|---|---|\n|**Type of DLI**|**Scalability**|**Unit of Measure**|**Total Allocated Amount (USD)**|**As % of Total Financing Amount**|\n|Output|Yes|Number|10,000,000.00|0.00|\n|**Period**<br>Baseline|**Value**<br>0.00|**Value**<br>0.00|**Allocated Amount (USD)**|**Formula**|\n|2020|||0.00||\n|2022<br>|2.00|2.00|10,000,000.00||\n|**DLI IN01065486 ACTION**<br>**DLI 39**|11.9: PDC, Ministry of Health and Ministry of Water Irrigation and Electricity implement the Digital MRS system|11.9: PDC, Ministry of Health and Ministry of Water Irrigation and Electricity implement the Digital MRS system|11.9: PDC, Ministry of Health and Ministry of Water Irrigation and Electricity implement the Digital MRS system|11.9: PDC, Ministry of Health and Ministry of Water Irrigation and Electricity implement the Digital MRS system|\n|**Type of DLI**|**Scal", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006929", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data captured in the first three quarters of EFY2014", "probe_tag": "drop", "probe_score": 0.012125954031944275, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 268, "end": 320, "key": "fcv_pads_east_africa:006929:36:0:0", "source": "camp2", "luna_reason": "Data capture is part of the project’s procurement data-entry activity.", "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:017166", "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:017166:31:0:0", "source": "camp2", "luna_reason": "Project M&E data listed as future verification machinery, not existing analyzed evidence.", "drop_reason": "promissory", "specificity": "named"}, {"text": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1188, "end": 1214, "key": "fcv_pads_east_africa:017166:31:0:2", "source": "camp2", "luna_reason": "NaCSA administrative data is cited as a verification source for program-awareness indicators.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "ANR/DPs|\n|8|Awareness creation for oversight bodies|At project start-up and<br>midterm|MoFEC and MoANR|\n|9|Commodity management<br> <br>Strengthening the Commodity Management<br>Unit within the MoANR<br> <br>Implementation of the commodity tracking<br>system (from procurement to distribution of<br>the food) piloted by the Food Management<br>Improvement Program of the WFP across<br>PSNP_woredas_ <br> <br>Assessing the staffing gap at all levels and<br>filling those positions<br> <br>Producing quarterly consolidated commodity<br>flow status report by the MoANR to the DPs<br>similar to the IFRs for financial resources<br> <br>Annual commodity audit reports|<br> <br>Three months after<br>effectiveness<br> <br> <br>Ongoing<br> <br>Ongoing<br> <br>Quarterly<br> <br>Annually|MoANR (FFSCD)|\n\n\n\n**_Financial management Covenants and Other Agreements_**\n\n\n48. FM-related covenants include the following:\n\n\n(a) Maintenance of a satisfactory FM system for the program.\n\n\n(b) Submission of IFRs for the program for each fiscal quarter within 60 days of the end\n\nof the quarter by the MoFEC and submission of consolidated commodity flow status\nreport for each fiscal quarter within 60 days of the end of the quarter by the\nMoANR.\n\n\n32", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021160", "page": 39, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Annual commodity audit reports", "probe_tag": "drop", "probe_score": 0.03518615663051605, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 636, "end": 666, "key": "fcv_pads_east_africa:021160:39:1:0", "source": "camp2", "luna_reason": "Annual project audit reporting is planned routine monitoring, not existing data use.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"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:018740", "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:018740:29:2:0", "source": "camp2", "luna_reason": "Embedded in an output-indicators table as project reporting data.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "arbitrary control group. The ENEU sample is representative of\n\n\nmetropolitan areas while the CONALEP graduate tracer survey is representative nationally. The\n\n\ndifference in geographical coverage of the two groups makes comparison difficult. Second, the\n\n\ncontrol groups were constructed ad hoc. The control groups included individuals between the\n\n\nages of 17 and 30: (A) those who have completed lower-secondary education; (B) those who\n\n\nhave completed non-professional, elementary vocational training (CECATI), and (C) those who\n\n\nhave completed one to three years of general academic (non-vocational) high school. Some\n\n\ndoubts remain with respect to the second group, since the ENEU survey does not distinguish\n\n\nbetween formal and informal training/technical courses.\n\n\nLee (1998) compares the individuals from the Encuesta de Egresados 1994 (the treatment\n\n\ngroup) with two other groups. One group comprises all 1991 graduates from upper-secondary\n\n\n6", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002610", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "CONALEP graduate tracer survey", "probe_tag": "keep", "probe_score": 0.9328983426094055, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 93, "end": 123, "key": "prwp:002610:5:1:1", "source": "camp2", "luna_reason": "Named tracer survey used to establish national representativeness and enable comparison.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": ", the present findings could only identify and carefully assess the main effects while\n\n\nhighlighting a few notable impact mechanisms without being exhaustive. Among others, future research\n\n\ncould look at the impact channels in detail in order to deliver a more nuanced understanding of why and\n\n\nunder which conditions e-procurement delivers the hoped for impacts. On the one hand, a more detailed\n\n\nunderstanding of administrative preconditions for successful e-procurement reform can be explored by\n\n\ncombining data from the procuring entity survey with procurement records. On the other hand, a better\n\n\nunderstanding of the constraints imposed and opportunities presented by different bidding markets could\n\n\nbe investigated by additionally drawing on bidder registration data and a tailored bidder survey.\n\n\n98. While more research is needed in this area, our findings already lend themselves to a range of policy\n\n\nrecommendations in and beyond Bangladesh: i) Introduce and expand the scope of e-procurement systems\n\n\nto encompass all public procurement tenders; and ii) Capitalize on the available data in the e-procurement\n\n\nsystem by developing a contract performance dashboard which enables continuous monitoring and\n\n\noptimization of processes in real-time.\n\n\n37", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000946", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "procuring entity survey", "probe_tag": "confusion", "probe_score": 0.43519309163093567, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 529, "end": 552, "key": "prwp:000946:38:1:0", "source": "camp2", "luna_reason": "Future research proposes combining the survey with procurement records.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "||||\n|||||||\n|||||||\n|||~~Taiwan, Ch~~|<br>~~ ina~~|~~Japan~~<br>||\n|||<br>Korea|Hong Ko<br><br>|ng, China||\n||||~~Singapore~~|||\n|||||||\n\n\n0 10,000 20,000 30,000 40,000 50,000\n\nGDP per capita ($US)\n\n\n\n\n\n\n\n\n\n\n- Data refer to 2001 the latest year for which complete data are available. The predicted figures are from a regression of the\nnatural logarithm of total health expenditure (expressed as a share of GDP) on the natural logarithm of GDP per capita. Data are\nfrom the 2005 World Health Report annexes in the cases of Japan, Korea and Singapore. The per capita income data for Hong\nKong (China) and Taiwan (China) are from the World Bank’s World Development Indicators. Data on health spending are from\n<u>http://www.hwfb.gov.hk/statistics/download/dha/en/table1.pdf in the case of Hong Kong (China) and from</u>\n<u>http://www.doh.gov.tw/ufile/doc/200411_Statistic%20of%20Expenditure%20for%20Health,%201991-2003.pdf</u> in the case of\nTaiwan (China).", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003004", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "per capita income data", "probe_tag": "confusion", "probe_score": 0.8891667127609253, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 555, "end": 577, "key": "prwp:003004:3:1:1", "source": "camp2", "luna_reason": "World Bank World Development Indicators provide the income data used in the chart.", "usage_type": "evidential", "specificity": "named"}, {"text": "Data on health spending", "probe_tag": "confusion", "probe_score": 0.6500003337860107, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 675, "end": 698, "key": "prwp:003004:3:1:3", "source": "camp2", "luna_reason": "Health-spending data are cited as sources for the presented comparison.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " higher beliefs about ration portability in the control group four months\n\nafter our experiment. <sup>3</sup> To measure the intensity of government awareness campaigns, we\n\n\nexploit additional, out-of-sample data on beliefs about ration portability which we collected\n\n\nboth before and after our information experiment. We find that the reduction in perceived\n\n\nportability caused by our experiment was driven by states with more intensive government\n\n\n2Specifically, the script told households that not all ration shop owners are aware of the ONORC program,\nthat they should bring their unique ID card called _Aadhaar_ along with a copy of their household’s ration\ncard—which must be linked to their _Aadhaar_ —that the shopkeeper may ask to see additional ID cards, that\nolder versions of ration cards may not be accepted or may require manual adjustment to the ID, that the\nshop must be equipped with an electronic point-of-sale system.\n\n3Under the PDS, state governments are responsible for grain distribution, portability implementation,\nand publicity and awareness campaigns. See, for example, publications by the Ministry of Consumer Affairs,\nFood & Public Distribution [here](https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1749917) and the Ministry of Information and Broadcasting [here.](https://transformingindia.mygov.in/wp-content/uploads/2021/10/ONORC-eng.pdf)\n\n\n3", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000880", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "out-of-sample data on beliefs about ration portability", "probe_tag": "confusion", "probe_score": 0.24749653041362762, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 195, "end": 249, "key": "prwp:000880:4:1:0", "source": "camp2", "luna_reason": "Existing collected data are analyzed to explain changes in perceived ration portability.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "Wives in households with other co-wives are slightly more likely to be involved in decisions directly than\nwives who live with their in-laws. But when they are not directly involved in the decision, these wives are\nless likely to have effective power, particularly in terms of water decisions. In these households, when one\nof the wives is not directly involved in these decisions, the male head of household is making the decision.\nIn either case, wives who are not directly involved in decision-making have little influence in the decision\nmade.\n\nYoung unmarried adults living with their parents are the least likely to be involved in decisions directly\n(Table 5). Few individuals in the younger age bracket make decisions in all seven activities. On average,\nyoung men and women make between two and three decisions directly, with young women making fewer\ndecisions directly than young men across the decision-making activities. When not directly involved in the\ndecisions, young men and women have similar levels of effective power with the exception of expenditures.\nYoung men have more effective power in household expenditure decisions than young women.\nCorrespondingly, the qualitative data suggests younger men often have some involvement in expenditure\ndecisions if they are earning income.\n\nIn terms of water activities, our qualitative data shows that while both young men and women are involved\nin collecting water, they have little direct involvement in the water decisions. The quantitative data confirms\nthat young men and women are directly engaged in less than one decision on average of the three water\nactivities, and that they have similar levels of effective power when not involved in the decision (Table 5).\n\n\n\n**Table 5.** Average share of activities young women and men who are not yet married and living with\nparents are directly engaged in the decision and share of those not directly involved but with effective\n\n\n\n<u>power</u>\n\n\n\n<u>Average share of decision making</u>\nactivities in which women and men\n\n\n\n<u>Average share of decision", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001329", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "quantitative data", "probe_tag": "confusion", "probe_score": 0.8745087385177612, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1493, "end": 1510, "key": "prwp:001329:17:0:2", "source": "camp2", "luna_reason": "Quantitative data supports concrete findings about young adults’ decision-making involvement.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": " 0.00 0.00 0.00\nP-val t1=t2 1.00 0.16 0.65 0.34 0.28 0.66\n\n\nNotes: Outcomes used in Columns 1-5 are constructed from administrative data, whereas the outcome used in Column 6 is constructed from self-reported data. Outcome 1 takes the value of 1 if the respondent\ncompleted at least 1 module on the app or attended 1 session of the in-person training course. Outcome 2 takes the value of 1 if respondent completed at least 8 modules on the app or attended at least 8\nsessions of the in-person training course. Outcome 3 indicates the number of modules started on the app, or the number of classes attended, as there is no similar measure for in-person training. Outcome\n4 indicates the number of modules partially completed, where the respondent completes at least half the lessons in a module, or the number of classes attended, as there is no partial measure for in-person\nattendance. Outcome 5 indicates the number of modules completed on the app, or the number of in-person sessions attended. Outcome 6 indicates the number of courses completed on the app, or the number\nof in-person sessions attended according to self-reported data from the follow-up survey. Results are obtained from OLS regressions of the outcome on three treatment dummies, controlling for LASSO selected\ncontrols, and randomization cohort fixed effects. Robust standard errors are in parentheses. - _p <_ 0 _._ 1, ** _p <_ 0 _._ 05, *** _p <_ 0 _._ 01", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001281", "page": 30, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "self-reported data", "probe_tag": "confusion", "probe_score": 0.5556927919387817, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 195, "end": 213, "key": "prwp:001281:30:1:0", "source": "camp2", "luna_reason": "Self-reported follow-up data construct an outcome used in OLS analysis.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "self-reported data from the follow-up survey", "probe_tag": "keep", "probe_score": 0.9078611731529236, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1119, "end": 1163, "key": "prwp:001281:30:1:1", "source": "camp2", "luna_reason": "Follow-up survey data construct an analyzed outcome in the regression.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "> <u>38.1</u>\n<u>Number</u> <u>of</u> <u>obs.</u> <u>991</u> <u>377</u>\n\n\nNotes: Own calculations based on Malawi Integrated Household Survey (2004/05).\nCash Crops: hybrid maize, groundnuts, cotton and sugar cane.\nFood Crops: maize, cassava, potato, ground beans, rice, finger millet, sorghum, pearl millet, beans, soybeans and\npigeon peas.\n\n\n18", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003768", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Malawi Integrated Household Survey", "probe_tag": "confusion", "probe_score": 0.8361051678657532, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 107, "end": 141, "key": "prwp:003768:20:1:0", "source": "camp2", "luna_reason": "Own calculations are based on this named household survey.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " when the firms self-report. In the following analysis, the paper differenti\n\nates the data used in the estimation by inspections and self-reported data. Given the results\n\n\nin table 3, inspection data are more reliable, but carrying out the same type of analysis for\n\n\nthe self-reported data will help to have a better idea of the kind of reforms that are needed\n\n\nin India’s monitoring system. Even if firms over-report compliance in self-reporting, it still\n\n\nis important information about the behavior of firms regarding environmental regulations.\n\n\n**5.2** **Water** **and** **Air** **Pollution**\n\n\nNext, the paper explores whether there is a higher rate of compliance with air or water\n\n\nenvironmental regulations. This is captured by including a variable equal to one when the\n\n\nmeasures are on air emissions data and omitting the water information variable. Table 4\n\n\nshows that firms seem to comply more with air emissions than with water effluents when the\n\n\ninformation is self-reported, but inspections find that firms tend to be more in compliance\n\n\nwith water regulations.\n\n\n14", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002181", "page": 15, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "inspection data", "probe_tag": "confusion", "probe_score": 0.6751631498336792, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 186, "end": 201, "key": "prwp:002181:15:2:1", "source": "camp2", "luna_reason": "Inspection data are analyzed and judged more reliable than self-reported data.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "As a result, most studies on housing affordability are country specific and rely on policy\n\ndriven thresholds and criteria. By far, the largest literature documenting housing affordability is\n\n\nfrom the United States and Australia. In the United States, there is a large literature in documenting\n\n\nhousing affordability outcomes across cities, income, and race (Quigley and Raphael 2004,\n\n\nMillennial Housing Commission 2002). In Australia, the topic has received substantial empirical\n\n\nas well as methodological attention (Gabriel, et al. 2005, Gan and Hill 2009, Wood, Ong and\n\n\nCigdem 2014, Yates and Gabriel 2006). The United Kingdom, the Netherlands, and Canada are\n\n\nanother set developed economies that have systemically documented affordability in the housing\n\n\nliterature (Milligan 2003, Haffner and Boumeester 2015, Haffner and Boumeester 2010, Moore\n\n\nand Skaburskis 2004, Stone 2006).\n\n\nIn the developing world, China and Malaysia have been the most studied (Chen, Hao and\n\n\nStephens 2010, Yang and Chen 2014, Hashim 2010, Suhaida, et al. 2010). Some cross-country\n\n\nanalysis from Africa has been undertaken using standardized housing expenditure surveys, but it\n\n\nis not clear what drives these cross-country differences (Lozano and Young 2014). The range of\n\n\nthese studies demonstrate the lack of international comparability on the subject and the ongoing\n\n\nsearch for an easily replicable approach across countries (World Bank 2020).\n\n\nDriven by prudential banking regulation, by far the most common approach is to measure\n\n\naffordability as housing expenditure over income, or the expenditure to income ratio. This debt\n\n\nservice concept has grown in popularity globally, although the prevailing thresholds between 20\n\n\nand 40 percent lack simple interpretations and have been critiqued (Mayo, Malpezzi and Gross\n\n\n1986). In many developing countries, definitions of minimum housing or of inadequate housing\n\n\nhave been developed based on housing structures and these definitions often include the materials\n\n\nof the dwelling as well as the type of water and sanitation options for", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001007", "page": 43, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "standardized housing expenditure surveys", "probe_tag": "confusion", "probe_score": 0.16611891984939575, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1128, "end": 1168, "key": "prwp:001007:43:0:0", "source": "camp2", "luna_reason": "Existing surveys are used for cross-country housing affordability analysis.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "\n|Pakistan<br>|1990-91, 2006-07,<br>2012-13, 2017-18<br>(4)<br>|2010, 2011, 2014,<br>2016-2017, 2017-<br>2018 (5)<br>|1994-1998, 1999-<br>2004, 2010-2014,<br>2017-2019<br>|(0)<br>|Every<br>year<br>between<br>2005-<br>2018 (13)<br> <br>|\n|Sri Lanka<br>|1987**, 2006, 2016<br>(3)<br>|(0)<br>|(0)<br>|(0)<br>|Every<br>year<br>between<br>2005-<br>2015 and 2017-<br>2019 (13)<br>|\n|Bhutan<br>|(0)|2010 (1)|(0)|(0)|2013, 2014, 2015<br>(3)|\n\n\n\nAmong these data sources, DHS provided the most comprehensive combination of gender-relevant\n\noutcome variables across all coutnries and time periods. WVS, though not available for all countries in the\n\nregion, was selected due to availability of gender attitide variables that could serve as proxies for relevant\n\nnorms. A brief description of each is included below.\n\n\n+ Special DHS data type and not used.\n\n- Special DHS data type.\n** Not used in the analysis.\n\n\n50", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000571", "page": 51, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "DHS", "probe_tag": "confusion", "probe_score": 0.5766684412956238, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 463, "end": 466, "key": "prwp:000571:51:2:0", "source": "camp2", "luna_reason": "Named DHS data provided gender-relevant outcome variables for analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "### **Does Better Access to Finance Help Firms Deal with the COVID-19** **Pandemic? Evidence from Firm-Level Survey Data**\n\nMohammad Amin <sup>a</sup> and Domenico Viganola <sup>b</sup>\n\nKeywords: COVID-19, Access to Finance, Sales, Firm performance, Pandemic\nJEL Codes: D22, G00, G10, L23, L25\n\n<u>a</u> <u>Corresponding author. Senior Economist, Enterprise Analysis Unit, DECEA, World Bank,</u>\nWashington, DC. Email: <u>[mamin@worldbank.org](mailto:mamin@worldbank.org)</u>\nb Consultant, Enterprise Analysis Unit, DECEA, World Bank, Washington, DC. Email:\n<u>[dviganola@worldbank.org](mailto:dviganola@worldbank.org)</u>\n<u>The findings, interpretations, and conclusions expressed in this paper are entirely those of the</u>\nauthors. They do not necessarily represent the views of the International Bank for Reconstruction\nand Development/World Bank and its affiliated organizations, or those of the Executive Directors\nof the World Bank or the governments they represent.\n<mark>We thank the Enterprise Analysis Unit of the Development Economics Global Indicators</mark>\n<mark>Department of the World Bank Group for making the data available.</mark>\nWe would like to thank Jorge Luis Rodriguez Meza and Norman Loayza for providing very helpful\ncomments. All remaining errors are our own.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000299", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Firm-Level Survey Data", "probe_tag": "confusion", "probe_score": 0.17196901142597198, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 98, "end": 120, "key": "prwp:000299:2:0:0", "source": "camp2", "luna_reason": "Firm-level survey data is identified as the evidence underlying the paper.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "Development Economics Global Indicators", "probe_tag": "confusion", "probe_score": 0.8866388201713562, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1027, "end": 1066, "key": "prwp:000299:2:0:1", "source": "camp2", "luna_reason": "Acknowledges data availability without showing the named source's data being used.", "drop_reason": "availability", "specificity": "named"}]}
+{"text": "Policy Research Working Paper\n8381\nTransnational Terrorist Recruitment\nEvidence from Daesh Personnel Records\u0003\nAnne Brockmeyer\nQuy-Toan Do\nClément Joubert\nMohamed Abdel Jelil\nKartika Bhatia\nDevelopment Research Group\n   &\nMiddle East and North Africa Region\nOffice of the Chief Economist\nMarch 2018\nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002348", "page": 0, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Daesh Personnel Records", "probe_tag": "drop", "probe_score": 0.02417415753006935, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 85, "end": 108, "key": "prwp:002348:0:0:0", "source": "camp2", "luna_reason": "Daesh personnel records are cited as evidence for the working paper's analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Keep formal account|\n|0<br>10<br>20<br>30<br>40<br>50<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>10<br>20<br>30<br>40<br>50<br>Cameroon (2008)<br>1 − 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Tax registeration|0<br>10<br>20<br>30<br>40<br>50<br>Ghana (2013)<br>1 − 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Tax registeration|0<br>10<br>20<br>30<br>40<br>50<br>Rwanda (2013)<br>1 − 4<br>5 − 9<br>10 − 19<br>20 − 99<br>100+<br>Tax registeration|\n\n\n\n19", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000985", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Tax registeration", "probe_tag": "drop", "probe_score": 0.011684377677738667, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 304, "end": 321, "key": "prwp:000985:20:1:1", "source": "camp2", "luna_reason": "Standalone table label, not a cited or used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
 {"text": "Appendix Α: Information on data sources\n\n\nTable A1: List of candidate geospatial variables.\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|Variable|Source|Approximate<br>Resolution|Year|\n|---|---|---|---|\n|Population structure<br>|WorldPop (https://www.worldpop.org)<br>|100 m<br>|2018<br>|\n|Population density|WorldPop<br>|100 m<br>|2018<br>|\n|Temperature<br>|TerraClimate<br>(https://www.climatologylab.org/terraclimat<br>e.html)|4 km<br>|2018<br>|\n|Palmer Draught<br>Severity Index<br>(PSDI)<br>|TerraClimate|4 km<br>|2018<br>|\n|Distance to OSM<br>major roads<br>|WorldPop<br>|100 m<br>|2016<br>|\n|Radiance of night-<br>time lights|VIIRS<br>(https://eogdata.mines.edu/products/vnl/) <br>|500 m<br>|2018<br>|\n|Net primary<br>production|FAO Remote Sensing for Water<br>Productivity (WaPOR) 2.1<br>(https://data.apps.fao.org/wapor/?lang=en)<br>|240 m<br>|2018<br>|\n|Rainfall|Climate Hazards Group InfraRed<br>Precipitation with Station data (CHIRPS)<br>(https://www.chc.ucsb.edu/data/chirps) <br>|5", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001372", "page": 28, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "WorldPop", "probe_tag": "confusion", "probe_score": 0.06145147979259491, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 220, "end": 228, "key": "prwp:001372:28:0:0", "source": "camp2", "luna_reason": "Source entry embedded in a candidate-variable table, not an independent data-use mention.", "drop_reason": "table_artifact", "specificity": "named"}, {"text": "TerraClimate", "probe_tag": "drop", "probe_score": 0.01382560282945633, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 350, "end": 362, "key": "prwp:001372:28:0:2", "source": "camp2", "luna_reason": "Standalone source entry within a table of candidate geospatial variables.", "drop_reason": "table_artifact", "specificity": "named"}, {"text": "FAO Remote Sensing for Water", "probe_tag": "confusion", "probe_score": 0.26230522990226746, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 727, "end": 755, "key": "prwp:001372:28:0:4", "source": "camp2", "luna_reason": "Named geospatial data source listed for net primary production.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": " local content requirements. Last, the\ndevelopment of mechanisms that nudge countries toward greater climate policy alignment to reduce\nfrictions. Examples of such an alignment could be the harmonization of environmental standards and\nregulations as well as of compliance requirements or the adoption of a global carbon price that gradually\nincreases towards its social cost. Should the multilateral development of the framework prove\nchallenging, like-minded countries could start with a multi-party approach similar to the Multi-Party\nInterim Appeal Arbitration Arrangement (MPIA) developed when the WTO dispute settlement\nencountered difficulties.\n\n**Finally, international collaboration is necessary to tackle the challenges of emission intensity metrics**\n**and pricing, especially for goods with complex supply chains and cross-border issues** (WTO, OECD, IMF,\nUNCTAD, and World Bank Group WTO 2024). Efforts should streamline compliance through robust yet\nflexible Monitoring, Reporting, and Verification (MRV) systems and harmonized data for policy and\nstandards compliance. Multilateral solutions are needed to address varying regulatory and compliance\nrequirements, different carbon measurement methods, and non-recognition of domestic standards.\n\n\n**4.4** **Further research**\n\n**This paper has detailed various mitigation policies of the three largest global trading partners and the**\n**exposure of developing countries to their impacts. However, future work could expand this analysis in**\n**several dimensions** . First, the analysis focuses on each policy in isolation. This allows for granularity of the\nsectoral and country discussion. Future research could assess all these policies in a coherent framework\nthat takes into consideration interlinkages across sectors within countries and comparative advantages of\ncountries globally. Second, further research on the impact of various policies on SMEs and smallholder\n\n\n30 In the case of actionable subsidies under WTO rules that reduce foreign countries’ competitiveness, it will be\nimportant to agree on guardrails regarding the ways in which affected countries can respond. Such response\n(antidumping, countervailing duties,", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001477", "page": 29, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "harmonized data", "probe_tag": "drop", "probe_score": 0.04022125154733658, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1030, "end": 1045, "key": "prwp:001477:29:1:0", "source": "camp2", "luna_reason": "Proposed harmonized data for future compliance, not existing data use.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": "1-770.\n\nDechezleprêtre, Antoine, Matthieu Glachant, Ivan Hascic, Nick Johnstone, and Yann Ménière,\n\n(2011), “Invention and transfer of climate change mitigation technologies on a global\nscale: A study drawing on patent data,” Review of Environmental Economics and Policy,\n5(1), 109-130.\n\nDoranova, A., Costa, I., and G. Duysters (2009), “Knowledge base determinants of technology\n\nsourcing in the Clean Development Mechanism projects,” UNU-MERIT Working Paper\n#2009-015.\n\nDoukas, H., C. Karakosta, and J. Psarras (2009), “RES technology transfer within the new\n\nclimate regime: a ‘helicopter’ view under the CDM,” _Renewable and Sustainable Energy_\n_Reviews_, 13, 1138-1143.\n\nEnergy Information Administration (2010), _International Energy Outlook 2010_, Washington,\n\nDC: U.S. Department of Energy.\n\nEsty, Daniel C. (2001), “Bridging the trade-environment divide”, _Journal of Economic_\n\n_Perspectives_, 15(3):113-130.\n\nFisher-Vanden, K. and M.S. Ho (2010), “Technology, Development, and the Environment.”\n\n_Journal of Environmental Economics and Management,_ 59(1), 94-108.\n\nFisher-Vanden, K. and I. Sue Wing (2008), “Accounting for quality: Issues with modeling the\n\nimpact of R&D on economic growth and carbon emissions in developing countries”,\n_Energy Economic_ s, 2771-2784.\n\nGallagher, Kelly Sims. 2006. Limits to leapfrogging in energy technologies? Evidence from the\n\nChinese automobile industry. _Energy Policy._ 34:383-394.\n\n\n50", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005403", "page": 51, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "patent data", "probe_tag": "drop", "probe_score": 0.02290729060769081, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 212, "end": 223, "key": "prwp:005403:51:1:0", "source": "camp2", "luna_reason": "Generic data phrase appears within a bibliography reference title.", "drop_reason": "ref_list", "specificity": "vague"}]}
-{"text": "- access to credit bureau loan-level data – to analyze borrower characteristics\nand assess risk, particularly for consumer loans <sup>64</sup> .\nLonger-term measures would include:\n\n    - data collection on the financial condition of corporates and households (e.g.\nbalance sheets, leverage ratios, income indicators etc.) – to better understand\nthe connection between developments in the real sector and financing patterns\n(i.e. demand- versus supply-side factors)\n\n    - identification and analysis of alternative financing sources for companies and\nhouseholds outside the formal financial system – to quantify their importance\nand assess their impact on formal financing sources\n\n    - development of a more detailed chart of accounts on bank revenues by loan\nproduct (including both interest income and fees) – to assess bank\nperformance when analyzing competition issues in different credit segments.\n\n\n**Transparency and disclosure** : The development and public disclosure of\nstandardized credit affordability indicators (i.e. interest rate time series by type of loan\nproduct and by provider) as well as of accessibility indicators (i.e. loan volumes by\nproduct, firm size, economic sector and state) would greatly contribute to a more\ntransparent credit market. As has been the experience in other countries, publication of\nthese indicators could provide a further impetus to competition across credit providers <sup>65</sup>\nand help borrowers become aware of credit pricing differences and hence more\nselective <sup>66</sup> ; these indicators could also allow the authorities to better track credit market\ndevelopments and formulate policy in areas such as financial access and competition.\n\n\n**Promotion of SME financing** : As mentioned previously, the prospects for SME\nfinancing growth are less positive relative to other market segments, at least in the short\nterm. Given the importance of SMEs for Mexico’s economy, the authorities will need to\ncontinue to promote SME financing and strengthen the credit infrastructure for this\nmarket segment. In", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003471", "page": 40, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "credit bureau loan-level data", "probe_tag": "confusion", "probe_score": 0.4172615110874176, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 12, "end": 41, "key": "prwp:003471:40:0:0", "source": "camp2", "luna_reason": "Existing credit bureau data are used to analyze borrower characteristics and risk.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "standardized credit affordability indicators", "probe_tag": "drop", "probe_score": 0.04342443868517876, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 983, "end": 1027, "key": "prwp:003471:40:0:1", "source": "camp2", "luna_reason": "Indicators are proposed for future development and disclosure, not cited as existing data.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": " as having gone ‘somewhat well’\n\n\n(26.4%) or ‘very well’ (71.7%).\n\n\nIn conjunction with the survey, we also collected data on the performance of public officials as assessed\n\n\nin their annual appraisal. Each year, public officials are evaluated by their direct manager on the tasks\n\n\nthat they were expected to contribute to. For example, tasks might include ‘Monitor and provide support\n\n\nto the [work] team preparing the budget’ and ‘Support the team to prepare soft and hard copy documents\n\n\nof the budget’. Managers evaluate the quality of contributions bureaucrats make to the tasks they were\n\n\ninvolved in and produce an overall ‘performance’ score. In addition to this performance-related score,\n\n\npublic officials are evaluated on their ‘attitude’ to work, which intends to measure their office behavior\n\n\nand alignment to the organization (Abagisa, 2014; Tereda, 2014). For the year 2016, we collected the\n\n\nperformance, attitude, and total scores (which are a weighted average of performance and attitude scores)\n\n\nfor each official from a subset of the organizations we visited for which they were available.\n\n\n9", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007560", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on the performance of public officials", "probe_tag": "drop", "probe_score": 0.0194, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 118, "end": 161, "key": "sample:prwp:007560:10:1:0", "source": "gold", "luna_reason": "The project explicitly collected this data as part of its survey.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": " days 0.55 948 0.6 361 0.53 335 0.479 0.171\nEngaged in HH non-ag enterprise in last 7 days 0.09 948 0.1 361 0.13 335 0.100 0.563\nEngaged in any work in February 2020 0.82 948 0.84 361 0.86 335 0.088 0.344\n\n\nThe table presents means for treatment households (T) with a child in grade 4 or 8, control households (C) with a\nchild in grade 3, 5, 6, 7, or 9, and mixed households (M) with a child in both grade groups. Data are from the first time\na household is observed, typically in survey round 1 (May-early July) while schools were fully closed. Individual-level\ndata are for the survey respondent.\nColumns on the right present differences and means and p-values for tests of equality for control households compared to treatment and mixed households, separately. The joint F-stat for differences across control and treatment\nhouseholds is 1.12, with p-value 0.305. It is 4.37 (p<0.001) for differences across control and mixed households.\n\n- _p <_ 0 _._ 1, ** _p <_ 0 _._ 05, *** _p <_ 0 _._ 01\n\n\n26", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000092", "page": 27, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Individual-level\ndata", "probe_tag": "drop", "probe_score": 0.0321655198931694, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 546, "end": 567, "key": "prwp:000092:27:2:0", "source": "camp2", "luna_reason": "Generic data description without an attributed finding or analytical use.", "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": "ita_ <sup>is a dichotomous variable of value 1 if we observe all sales, labor, materials and capital</sup>\n\nand zero otherwise. Symmetrically, in the case of sales, we have the following equation\n\n\nPr( _sib_  1| _Di_, _ICi_ )  ( 0 _b_   2 _b_  _Di_   3 _b_  _ICi_  _ib_ ),\n\n\nwhere in this case <sup>_s_</sup> _itb_ <sup>takes value 1 if we observe data for sales.</sup>\n\nTables 6.1 to 6.4 present the estimated results by applying a LPM to model the probability of\nhaving a missing value conditional on the investment climate faced by firms. Concretely, we propose\nfour models for each country. First we consider missing values in TFP conditioning in two different\nvectors of IC variables. The first specification includes the same set of IC variables as that included\nin equation (5); that is, the set of covariates statistically significant in the extended production\nfunction, before imputing missing values by the ICA method. The second specification chooses the\nset of significant correlates starting from the whole set of IC variables and applying a general-tospecific procedure of selection of variables. The case of sales is symmetrical in the sense that model\n\n[3] uses the same set of IC variables as in equation (5), while the specification shown in column [4]\nselects the set of variables as we did in the case of column [2].\n\n\n34", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004536", "page": 35, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data for sales", "probe_tag": "drop", "probe_score": 0.029631059616804123, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 360, "end": 374, "key": "prwp:004536:35:1:0", "source": "camp2", "luna_reason": "Generic data phrase defines an observation indicator, not an attributed finding.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": " (cap on reimbursement and/or services provided at the hospital level)<br>|<br>Global budget (cap on reimbursement and/or services provided at the hospital level)<br>|<br>Global budget (cap on reimbursement and/or services provided at the hospital level)<br>|\n|Uzbekistan||<br>Missing data|<br>Missing data|||||||||||||\n|Uzbekistan||||||||||||||||\n\n\n\nreports.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004181", "page": 48, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "Missing data", "probe_tag": "drop", "probe_score": 0.011477217078208923, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 277, "end": 289, "key": "prwp:004181:48:5:0", "source": "camp2", "luna_reason": "Standalone table cell indicating missing data, not a substantive data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "</sup> <sup>_, D_</sup> _i_ <sup>2</sup> <sup>_, D_</sup> _i_ <sup>3</sup> <sup>for</sup> <sup>whether</sup> <sup>reference</sup> <sup>plot</sup> <sup>_i_</sup>\n\ncontributes, respectively, only flow data, only failure data, or both flow and failure data, and assuming\nthat _µ_ is normally distributed with variance _σµ_ <sup>2,</sup> <sup>the</sup> <sup>full</sup> <sup>log-likelihood</sup> <sup>is</sup>\n\n\n\n_µ_ <sup>2,</sup> <sup>the</sup> <sup>full</sup> <sup>log-likelihood</sup> <sup>is</sup>\n\n\n\n\n \n) _,_ (D.9)\n\n\n\n\n\n\n_i_\n\n\n\n\n<sup>_f_</sup> _i_ <sup>(</sup> <sup>_µ_</sup> <sup>)</sup>\n\n\n\nlog\n\n\n\n��\n\n\n_µ_\n\n\n\n_ℓi_ ( _µ, κµ_ ) _d_ Φ( <sup>_<u>µ</u>_</sup>\n\n_σµ_\n\n\n\nwhere\n\n\n\n_L_ =\n\n\n_ℓi_ ( _µ, ξ_ ) =\n\n\n\n\n<sup>_F_</", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001317", "page": 45, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "flow data", "probe_tag": "drop", "probe_score": 0.018489904701709747, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 194, "end": 203, "key": "prwp:001317:45:1:0", "source": "camp2", "luna_reason": "Flow data are explicitly used as inputs to the likelihood analysis.", "usage_type": "declaration", "specificity": "vague"}, {"text": "failure data", "probe_tag": "confusion", "probe_score": 0.06762287020683289, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 210, "end": 222, "key": "prwp:001317:45:1:2", "source": "camp2", "luna_reason": "Generic data type is merely defined, with no cited source or analytical finding.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": " end of the\ntender. Less than 30 days later, three separate payments were made to different agents that\nwon the contracts, with total values of 11,377 BRL and 3,890 BRL. For the purchase of this\nrelatively simple good, a total of 235 days elapsed between the tender publication and the last\npayment.\n\nThe example above shows the potential of this newly constructed dataset in providing researchers, policy makers, and the civil society with a granular view of how local governments\nin Brazil acquire goods and services and execute their budgets. It also illustrates the potential\nfor similar datasets to be developed in other countries where scattered data might exist but\nrequire upfront investment to be collected, cleaned, and harmonized.\n\n##### **3 Validation**\n\n\nThe flagship dataset for information on municipal public finances in Brazil is the _Sistema de_\n_Informações Contábeis e Fiscais do Setor Público Brasileiro_ (SICONFI). <sup>19</sup> SICONFI contains selfreported information on municipalities’ revenues, expenditures, and balance sheets starting in\n1989, with details on amounts per category and budget execution phase (i.e. commitment, ver\n\n18We note that this connection between public procurement and budget execution is currently only possible\nfor the state of Parana (PR), which provides a table connecting tender IDs to commitment IDs. Approximately\n78% of the procurement IDs and 38% of total commitment IDs can be found within this correspondence table.\n19The dataset was formerly called _Finanças Brasileiras_ (Finbra).\n\n\n9", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000767", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "scattered data", "probe_tag": "drop", "probe_score": 0.036908507347106934, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 642, "end": 656, "key": "prwp:000767:10:1:0", "source": "camp2", "luna_reason": "Data is hypothetical and requires future collection, cleaning, and harmonization.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "Estrin S, Hanousek J, Kočenda E, Svejnar, J., 2009. “The effects of privatization\n\n\nand ownership in transition economies.” _Journal of Economic Literature_,\n\n\n47(3), 699-728.\n\n\nEstrin, S. and V. Perotin, 1991. “Does ownership always matter?” _International_\n\n\n_Journal of Industrial Organization,_ 9(1), 55–73.\n\n\nGaricano, L. 2000. “Hierarchies and the Organization of Knowledge in Production”,\n\n\n_Journal of Political Economy_, 108(5), 874-904.\n\n\nGaricano, L. and E. Rossi-Hansberg. 2006. “Organization and inequality in a\n\n\nknowledge economy”. _Quarterly Journal of Economics_, 121, 1383-1435.\n\n\nGarmaise, M. and T. Moskowitz, 2004, “Confronting Information Asymmetries:\n\n\nEvidence from Real Estate Markets,” _Review of Financial Studies_, 16(4),\n\n\n1007-1040.\n\n\nGiroud, X. 2013, “Proximity and investment: evidence from plant-level data”.\n\n\n_Quarterly Journal of Economics_, 128(2), 861-915.\n\n\nGrinblatt, M. and M. Keloharju 2001. “How Distance, Language, and Culture\n\n\nInfluence Stockholdings and Trades,” _Journal of Finance_, 56, 1053-1073.\n\n\nLi, Lixing and Guangrong Ma 2015. “Government Size and Tax Evasion:\n\n\nEvidence from China.” _Pacific Economic Review_, 20(2), 346-364.\n\n\nLi, Yunsen and Cheryl Long 2013. “Historical Events and Regional Development:\n\n\nEvidence from China’s Third Front Construction.” Manuscript, Xiamen\n\n\nUniversity.\n\n\nMarkevich, A. and E. Zhuravskaya, 2011, “M", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006378", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "plant-level data", "probe_tag": "drop", "probe_score": 0.02909582108259201, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 823, "end": 839, "key": "prwp:006378:27:0:0", "source": "camp2", "luna_reason": "Bibliography entry describing a study, not a data-use claim.", "drop_reason": "ref_list", "specificity": "descriptive"}]}
+{"text": "cases, including journey <br>planning, the mapping of <br>topography, as well as <br>demographic indicators.<br>|<br>Following data must be online to qualify for <br>assessment:<br>• <br>Markings of national traffic routes <br>• <br>Markings of relief/heights <br>• <br>Markings of water stretches <br>• <br>National borders Coordinates - <br>Note: To qualify, data must <br>contain geographic projections <br>that enable to interpret<br>coordinates<br>|\n|Administrative<br>Boundaries<br>|<br>Data on administrative units or areas <br>defined for the purpose of<br>administration by a (local) <br>government.The development of this <br>category draws on work ofFAO Global <br>Administrative Unit Layers <br>(GAUL)project, as well as theUNGIWG. <br>|Open data about <br>administrative zones has<br>many use cases: Who are the <br>candidates in my region? <br>Which government bodies <br>administer my region? How is <br>wealth distributed across <br>regions? The Index assesses <br>two administrative boundary <br>levels (e.g. federal states = <br>level 1, and municipalities = <br>level 2).<br>|Following data must be online to qualify for <br>assessment:<br>• <br>Boundary level 1 <br>• <br>Boundary level 2 (not required, if <br>country has only one level)<br>• <br>Coordinates of administrative <br>zone (latitude,", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001873", "page": 48, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "National borders Coordinates", "probe_tag": "drop", "probe_score": 0.021348094567656517, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 308, "end": 336, "key": "prwp:001873:48:2:3", "source": "camp2", "luna_reason": "Fragment names mapping attributes, not an existing data resource or data use.", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "Data on administrative units or areas", "probe_tag": "confusion", "probe_score": 0.0990719199180603, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 493, "end": 530, "key": "prwp:001873:48:2:4", "source": "camp2", "luna_reason": "Defines an administrative data category without citing its data for analysis or a finding.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
+{"text": "**To Impute or Not to Impute? A Review of Alternative Poverty**\n**Estimation Methods in the Context of Unavailable Consumption Data**\n\n\nHai-Anh H. Dang <sup>*</sup>\n\n\nKey words: poverty, imputation, consumption, wealth index, synthetic panels, household survey\n\nJEL: C15, I32, O15\n\n\n[* Dang (hdang@worldbank.org) is an economist in the Survey Unit, Development Data Group, World Bank, a non-](mailto:hdang@worldbank.org)\nresident research scholar with School of Public and Environmental Affairs, Indiana University, and a non-resident\nsenior research fellow with Vietnam’s Academy of Social Sciences. We would like to thank Gero Carletto, Dean\nJolliffe, and Peter Lanjouw for helpful discussions on related work. We are grateful to the UK Department of\nInternational Development for funding assistance through its Strategic Research Program (SRP) and Knowledge for\nChange (KCP) program.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002315", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Consumption Data", "probe_tag": "drop", "probe_score": 0.014278833754360676, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 115, "end": 131, "key": "prwp:002315:2:0:0", "source": "camp2", "luna_reason": "Title states consumption data are unavailable, without using an existing dataset.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": "> <u>$116.47</u> <u>$20.16</u> <u>0.000</u>\nDiscrepancy between expert’s Round 1 prediction and mean for $61.43 $44.38 0.000\n\n\n\n_<u>Group 1</u>_\n\n\n\n_<u>mean</u>_\n\n\n\n_<u>mean</u>_\n\n\n\nhis/her country/region\n\n\n\n$61.43 $44.38 0.000\n\n\n\nRatio of expert’s Round 1 prediction to mean for his/her\n\n\n\n2.17 0.27 0.000\n\n\n\ncountry/region\n\n\n\nProximity of Delphi estimate to result of an actual SP survey 6.48 5.78 0.043\nDifficulty of successfully implementing a SP survey on this topic 5.47 5.85 0.230\nNumber of CV surveys carried out 7.22 7.18 0.490\nNumber of CE surveys carried out 3.77 3.63 0.448\nNumber of surveys (CV+CE) carried out about biodiversity and 3.22 3.56 0.363\n\n\n\necosystem services\n\n\n\n3.22 3.56 0.363\n\n\n\nNumber of benefit transfer exercises 2.58 2.20 0.329\nJournals: 1 <sup>st</sup> principal component -0.079 -0.272 0.261\nJournals: 2 <sup>nd</sup> principal component -0.118 0.112 0.166\nJournals: 3 <sup>rd</sup> principal component -0.104 -0.215 0.291\nJournals: 4 <sup>th</sup> principal component 0.072 0.148 0.352\nNumber of CV and CE papers published in national and 4.65 2.72 0.012\n\n\n\ninternational journals in past 5 years\n\n\n\n4.65 2.72 0.012\n\n\n\nNumber of", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000008", "page": 27, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "CE surveys", "probe_tag": "drop", "probe_score": 0.017501864582300186, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 547, "end": 557, "key": "prwp:000008:27:1:2", "source": "camp2", "luna_reason": "Fragment appears as a row label within a statistical table.", "drop_reason": "table_artifact", "specificity": "vague"}]}
 {"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**Most Ukrainian refugee households**\n**are led by women alone.** According\nto the 2024 Socio-Economic Inclusion\nSurvey (SEIS), 67% of Ukrainian refugee\nhouseholds are led by women without\nadult partners. When changes are\ncompared to the 2023 edition, the MultiSector Needs Assessment (MSNA) survey,\n5% of households include a person with\ndisability, down from 10% previous year,\n\n\n\nand 48% include a chronically ill person,\ncompared to 49% in 2023. Furthermore,\naverage household size is 2.4 persons\n(compared to 2.7 previous year), 57%\ninclude children (compared to 52%), and\n6% include a pregnant or breastfeeding\nmother (same as previously; UNHCR,\n2025a). Only 15% of households are\nnuclear families with a working age man\nand woman with children.\n\n\n\n**Chart 5. Ukrainian refugee households’ demographic composition**\n\n\n**with no**\n**children (43%)**\n\n\n\n**with one child**\n\n**or more (57%)**\n\n\n\nwith one child\n\nwith two or more children\n\n\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Table 1. 10 poviats with most Ukrainian refugees** **Chart 6. Local population shares of Ukrainian refugees**\n\n\n**1. Warsaw** 109,705\n\n\n**2. Wroclaw** 53,901\n\n\n**3. Cracow** 33,057\n\n\n**4. Poznan** 23,991\n\n\n**5. Gdansk** 17,829\n\n\n**6. Lodz** 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", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2024 Socio-Economic Inclusion\nSurvey", "probe_tag": "keep", "probe_score": 0.9661524295806885, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 159, "end": 195, "key": "jad_paddy_docs:000001:5:0:0", "source": "camp2", "luna_reason": "Named survey supports the reported 67% household composition finding.", "usage_type": "evidential", "specificity": "named"}, {"text": "MultiSector Needs Assessment", "probe_tag": "keep", "probe_score": 0.9620190858840942, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 332, "end": 360, "key": "jad_paddy_docs:000001:5:0:1", "source": "camp2", "luna_reason": "Named survey referenced for household disability and demographic findings.", "usage_type": "evidential", "specificity": "named"}]}
 {"text": "zyciowa-i-ekonomiczna-migrantow-z-Ukrainy-w-Polsce_raport-z-badania-2022-r.pdf)</u>\nService of Ukraine (2021).\n\n\n\nPoland 2023 assess that around 56% <sup>23</sup>\nof refugee arrivals had completed higher\neducation. This means that Ukrainians\nwith higher education were more likely\nto relocate to Poland or leave Ukraine in\ngeneral, having the necessary means to\nachieve this. On average refugees with a\nbachelor’s degree or higher had an over\n30% higher employment rate than peers\nwithout a degree, according to MSNA\nPoland 2023 survey.\n\n\n\n\n\n22  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\n20\n\n\n\n21", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 10, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "MSNA\nPoland 2023 survey", "probe_tag": "keep", "probe_score": 0.9622074365615845, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 512, "end": 535, "key": "jad_paddy_docs:000007:10:3:0", "source": "camp2", "luna_reason": "Named survey supports the reported employment-rate finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "# Abstract\n\n\n\nThe beginning of the full-scale\nwar in Ukraine in February\n2022 resulted in a large outflow\nof refugees, reaching more\nthan 6 million globally.\n\n\nMuch of this exodus happened through the\nPolish border. As of October 2023, almost\n1 million Ukrainian refugees were living in\nPoland. While in the past decade Poland\nexperienced large labour migration from\nUkraine, the refugee inflow had a\ndifferent demographic composition.\nIt primarily included working age women\n(41%) and children (40%). These refugees\nfrom Ukraine did not plan to move, and\nmany had special needs. Despite these\ndifficulties, refugees began entering\nthe labour market surprisingly quickly –\nattaining an employment rate of 28% in\nMay 2022 and 65% in November 2022\n(NBP, 2023). By July-August 2023 Ukrainian\nrefugee households supported themselves,\nwith 80% of their incomes coming from work. <sup>1</sup> [^1: Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.]\n\n\nWe find that refugees from Ukraine who\nremain in Poland as workers, entrepreneurs,\nconsumers, and taxpayers have a positive\nimpact on economic output, which will\nincrease in the long run. Results of our\ngeneral equilibrium Deloitte D.Climate\nmodel show that refugees from Ukraine\ncontributed 0.7-1.1% to the Gross Domestic\nProduct in 2023. In the long-term this effect\nwill grow to 0.9-1.35%. In our model, the\n\n\n\nlong-term is defined as the period over\nwhich the economy fully adjusts to the\nshock of the initial refugee inflow; it does not\ninclude other aspects, e.g. refugee children\ngrowing-up and entering employment.\nThese results are consistent with previous,\nsimilar studies. However, they should be\ntreated as lower-bound estimates, as we do\nnot allow for the possibility of an increase\nin the labour force triggering a positive\nproductivity shock (e.g., due to increased\nspecialisation), because there is little data to\ncredibly estimate its size.\n\n\nA feature of our modelling approach is", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Multi-Sector Needs Assessment Poland 2023 survey data", "probe_tag": "keep", "probe_score": 0.9991, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 923, "end": 976, "key": "sample:jad_paddy_docs:000007:2:0:0", "source": "gold", "luna_reason": "Survey data underlies Deloitte calculations and the reported refugee income finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"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": " 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.** Cumulative changes in main indicators in 2023\n\n\n**SCENARIO 1** **SCENARIO 2** **SCENARIO 3** **SCENARIO 4**\n\n\n\n**Low employment**\n**conservative**\n**productivity**\n\n\n\n**High employment**\n**conservative**\n**productivity**\n\n\n\n**Low employment**\n**baseline**\n**productivity**\n\n\n\n**High employment**\n**baseline**\n**productivity**\n\n\n\nThe main impact of refugees is in growth\nof the economy. Refugees increase both\nsupply as workers and entrepreneurs as\nwell as demand as consumers. Increase\nin GDP is not directly proportional to the\nincrease in population or employment.\nNet benefits are lowered both due to\na decrease in capital to labour ratio as\nwell as an increase in competition on\nthe labour market. Moreover, increase in\ndemand in tight labour market conditions\nresults in higher inflation and lower\nprice competitiveness of Polish products\nwhich lower its overall positive impact.\nNevertheless, the positive impact of\nrefugees on the economy is significant in\nevery scenario considered.\n\n\nIn 2022 it amounts to real GDP\nbeing higher by 0.5-0.8% and in\n2023 cumulatively by 0.7-1.1%.\nThis corresponds to GDP being\nhigher by 24-36.9 billion PLN in\n2023 <sup>43</sup> .\n\n\nIn the long term, total potential GDP should\nbe higher by around 0.9-1.35% due to\nrefugees contributions. <sup>44</sup>\n\n\nOur results are consistent with the\nprevious, similar studies. In estimating\nGDP impacts we take an approach that", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data from Statistics Poland", "probe_tag": "keep", "probe_score": 0.9998, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 242, "end": 269, "key": "sample:jad_paddy_docs:000007:17:2:0", "source": "gold", "luna_reason": null}]}
-{"text": " it is\nprovided, allows over a third of low-income <sup>10</sup> [^10: Those that are below the poverty line]\nhouseholds to de facto live above the poverty line.\nIn Slovakia this effect is the most dramatic –\nsubsidized housing allows an additional 46% of the\nrefugee population to escape poverty.\n\n\n**<u>DECREASE IN THE REFUGEE POVERTY RATE AS A RESULT</u>**\n**OF ACCOMMODATION RENT SUPPORT, %** <sup>**1,2,3**</sup> [^2: Results for the Czech Republic not individually presented due to\nsampling limitations] [^3: 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\nNot adoping\n\ncoping\nstrategies\n\n\n\nStress coping\n\nstrategies\n\n\n\nCrisis coping\n\nstrategies\n\n\n\nEmergency\n\ncoping\nstrategies\n\n\n\nWithout accommodation rent\nsupport\n\n\n\n1. The statistic on emergency strategies may have been affected by\nthe survey wording on illegal work\n\n\nThe Ukrainian refugee population also faces\nfinancial barriers to access critical services: one in\nten households have no health insurance and 22 %\nof those surveyed answered that they cannot afford\nfees at local health care clinics. Households that\ncontain a member with a disability are also more\nlikely to be below the poverty line. This group’s\npoverty rate stands at 59% versus 43% for\nhouseholds with no members with disabilities.\n\n\n**Support with accommodation expenses – an**\n**important vulnerability shield**\nOverall, almost half (48%) of refugee households in\nthe region report receiving accommodation or\nhousing assistance. Twenty percent are living in\n\n\n\n\n\n\n\n\n\n\n\n\n\nWith accommodation rent support\n\n\n\n\n\n\n\nBulgaria Hungary Poland Romania Slovakia Region\n\n\n1. Calculations for Moldova were not conducted, as this country is not\nincluded into the <u>[EU statistics on income and living conditions (SILC)](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)</u>\n<u>[survey,", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "EU statistics on income and living conditions", "probe_tag": "keep", "probe_score": 0.9743, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1816, "end": 1861, "key": "sample:jad_paddy_docs:000000:4:1:0", "source": "gold", "luna_reason": null}]}
+{"text": "**Analysis of the impact of refugees from Ukraine on the economy of Poland**\n\n\n**Economists have advanced an array of factors that could be causing these macro-level effects. While macro-level**\n**regressions show a positive impact of immigration on productivity, they cannot show the exact channels through which**\n**these effects come about. It is thus uncertain which are dominant. Among them are:**\n\n\n# Conclusions\n\n\n\n**Analysis of the impact of refugees from Ukraine on the economy of Poland**\n\n\n\nDeloitte’s D.Climate general equilibrium\nmodel finds that refugees from Ukraine\ncontributed 0.7-1.1% to GDP cumulatively in\n2023. In the long-term this effect will grow\nto 0.9-1.35% as the economy fully adjusts.\nThe increases in government revenue from\ndirect and indirect taxes due to wages\nand private consumption of refugees from\nUkraine was likewise modelled.\nThese increases amounted to 0.8-1.0%\nhigher general government revenues in\n2022, 1.3-1.6% in 2023, and 0.95-1.13%\nin the long term. This implies that, while\nthere are no precise public data on the\ngovernment support to refugees from\nUkraine, while a government official quoted\ncost figures of 15-20 billion PLN in 2022\nand around 5 billion in 2023 <sup>50</sup> [^50: E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of\nNGOs which was combined with spendings of local governments <u>[Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.](https://www.infor.pl/prawo/nowosci-prawne/5635962,Polska-pomoc-dla-Ukrainy-2022-ile-kosztowala.html)</u>] have been\nalready offset by refugees via taxes of\n12.3-15.2 billion PLN in 2022 and 18.2-22.5\nbillion PLN in 2023.\n\n\nAll the modelling results are conservative\nlower bound estimates, as econometric\nstudies from other", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "public data", "probe_tag": "keep", "probe_score": 0.9561, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1044, "end": 1055, "key": "sample:jad_paddy_docs:000007:20:0:0", "source": "gold", "luna_reason": "Absence of precise public data motivates substitute modeled and official estimates.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": " elaboration based on Eurostat\n(Labour Force Survey) data.\n\n\n**Occupational downgrading is**\n**widespread among Ukrainian refugees**\n**in Poland.** SEIS data shows that 40% of\nUkrainian refugees aged 25–64 hold a\ntertiary degree – exceeding the share of\nPolish citizens in the same age bracket,\naccording to Eurostat’s 2023 annual\naverage. While ZUS data available as of\nJune 30, 2024, shows occupational groups\nfor less than half of the socially insured\nin Poland, it reflects a visible mismatch\nbetween the refugees’ education and the\njobs they perform. Only 12% of Ukrainian\nrefugees (less than one-third of the share\nin terms of tertiary education) worked in\noccupational groups which require tertiary\neducation, that is managers, specialists,\nand technicians (ISCO 1-3), compared to\n37% of Polish citizens (almost the same\nas the tertiary education share in the\n25-64 age group).\n\n\n\n2022 2023", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 13, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "SEIS data", "probe_tag": "keep", "probe_score": 0.9975, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 148, "end": 157, "key": "sample:jad_paddy_docs:000001:13:2:0", "source": "gold", "luna_reason": null}, {"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.9902, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 346, "end": 354, "key": "sample:jad_paddy_docs:000001:13:2:1", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **Model calibration**\n\n\n\nWe introduce a positive productivity\nshock into the Deloitte D.Climate\nmodel, reflecting empirical findings that\nrefugee inflows coincided with stronger\nlabour-market outcomes, to offset any\npotential adverse effects. Although higher\nemployment rates among Ukrainian\nrefugees correlate with improved job and\nwage outcomes for Polish citizens, we take\na deliberately conservative approach in\nour general equilibrium simulations. While\ndescriptive statistics and econometric\nestimates point in a positive direction, the\navailable data remain too sparse for firm\n\n\n**Chart 31. Labour market activity rates**\n\nWomen in 15-64 age group\n\n\n\nconclusions. <sup>31</sup> [^31: Deloitte has not received data that would be detailed as to citizenship, poviat, sex, age group, occupational group, and ZUS insurance code that would be suitable\nfor econometric approach.] On the other hand, a default\nDeloitte D.Climate model estimation is\nin line with the previously mentioned\ncanonical model. This yields a 1.35%\ndecrease in wages and a 0.4 percentage\npoint increase in the unemployment rate,\nwhich is implausible. Therefore, a positive\nmarginal productivity of labour shock has\nbeen added to the model and calibrated to\neliminate the impact on the unemployment\nrate throughout the simulation years of\n2022, 2023, and 2024. While it is possible\nthat the unemployment rate could fall\ndespite the influx of Ukrainian refugees due\n\n\n\nto factors other than productivity growth,\nthis is unlikely. Any negative impact could\nonly arise if other workers left the labour\nforce or reduced their working hours. No\nevidence of this is seen in recent Eurostat’s\nLabour Force Survey data for the Polish\neconomy, where activity rates continued\nto grow, while the average number of usual\nweekly hours worked in full- and parttime employment remained fairly stable,\nparticularly for women (who should be\ncloser substitutes for Ukrainian refugees,\nmost of whom are also women; see charts\nbelow).\n\n\n\nAnalysis of the impact of refugees from", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Eurostat’s\nLabour Force Survey data", "probe_tag": "keep", "probe_score": 0.9924, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1729, "end": 1764, "key": "sample:jad_paddy_docs:000001:21:0:0", "source": "gold", "luna_reason": null}]}
+{"text": ">self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|\n\n\n\nNote: Statistically significant results are given in green. Confidence bars reflect standard errors. Sample has been 833 individuals aged 18-64.\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 23. Average number of months since arrival of a Ukrainian refugee by Polish language fluency**\n\nN=702, age 18-64\n\n\n29\n\n\n\nAge Sector\n\n\nNote: Statistically significant results are given in green. n=681, age individuals aged 18-64.\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n\nFluent\n\n\n\nAdvanced\n\n\n\nIntermediate\n\n\n\nNone\n\n\n\nBeginner\n\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n**Chart 24. What Ukrainian", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 16, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9952, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 952, "end": 969, "key": "sample:jad_paddy_docs:000001:16:2:0", "source": "gold", "luna_reason": null}]}
+{"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": "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": " previous\nemployment background, compared to 50% of men. One possible explanation for this discrepancy is the higher\nproportion of men employed in sectors like construction and IT prior to displacement. These fields often\ndemand fewer country-specific qualifications, such as proficiency in the local language, thereby facilitating\neasier integration into similar roles in the host country.\n\n\n\n**<u>DISTRIBUTION OF WORKING AGE POPULATION BY</u>**\n**HIGHEST EDUCATION LEVEL ATTAINED**\n\n\nTechnical or Vocational Bachelor Master's Doctoral\n\n\n\n**<u>WAGE PREMIUMS FOR EDUCATION LEVEL GAINS: HOSTS</u>**\n**VERSUS REFUGEES, %**\n\n\n\nRefugee eduction\nwage premium\n(mean, 2024)\n\n\nBachelor's or\n\nabove\n\n\n\nHosts (2023)\n\n\nRefugees (2024)\n\n\nSource: Survey data, ILO\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n1%\n\n\n\nHost education wage\npremium (median,\n2022)\n\n\nTechnical or\n\nvocational\n\n\n\nNote: Wage premiums computed with lower secondary education as\nthe baseline\n\n\nSource: Survey data, Eurostat, SAG estimates\n\n\n18. The difference in median wages by highest education level attained. Weighted equivalently to refugee weights for comparability\n19. The wage gap for refugees was computed based on the difference in weighted means (instead of the difference in medians)\n\n\n**13**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Survey data", "probe_tag": "keep", "probe_score": 0.9987, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 734, "end": 745, "key": "sample:jad_paddy_docs:000010:12:1:0", "source": "gold", "luna_reason": null}]}
 {"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n© UNHCR / Anna Liminowicz\n\n\nDispersing refugees to weaker labour\nmarkets can also have negative social\noutcomes. Albarosa and Elsner (2022) report\nmore anti-immigrant incidents during the\nEuropean refugee crisis (2015/2016) in areas\nof Germany with high unemployment rates\nand shares of right-wing voters. Damm and\nDustmann (2014) show that immigrant men\ndispersed to areas of Denmark with more\nconvicted criminals, experience higher future\ncrime conviction probabilities, but not overall\nneighbourhood crime rate.\n\n\nThe estimated employment rate of refugees\nfrom Ukraine in Poland is above 60% and\nwas among the highest in the OECD <sup>27</sup> [^27: Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023] .\nAlthough there is uncertainty around\nemployment rate in different countries due\nto uncertainty regarding refugee numbers\n\nwhile MSNA Poland 2023 gives a slightly\nlower figure of 61%. In comparison, the\nemployment rate equalled 61% in the United\n\n\n\nBy refraining from any refugee dispersal\npolicies, Poland and other EU Member\nStates may have improved labour market\ninclusion. In many European countries\nrefugees are geographically dispersed after\narrival to spread the cost of hosting them,\nease the stress on the housing market\nand public services, and to avoid creating\nethnic enclaves. The effects, however, can\nbe detrimental to labour market inclusion\nand may be contrary to other aims of the\npolicy. Dispersal pushes at least some of\nthe refugees into regions with weak labour\nmarkets and few co-nationals already\nsettled, who otherwise could transmit\nimportant information about employment\nopportunities. Fasani, Frattini, and Minale\n(2022) conducted the first cross-country\nstudy of refugee dispersal policies.\nTheir LFS sample covers refugees who\nexperienced dispersal policies in Finland,\nGermany, Ireland, Netherlands, Norway,\nSweden, Switzerland and the UK (no data\nfor Denmark). They find that non-EU15\nrefugees aged 25-64 who arrived when a\ndispersal policy was in place experience\n4.5", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "OECD International Migration Outlook 2023", "probe_tag": "keep", "probe_score": 0.9998, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 778, "end": 819, "key": "sample:jad_paddy_docs:000007:12:0:0", "source": "gold", "luna_reason": null}, {"text": "MSNA Poland 2023", "probe_tag": "keep", "probe_score": 0.9984, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 951, "end": 967, "key": "sample:jad_paddy_docs:000007:12:0:1", "source": "gold", "luna_reason": null}]}
-{"text": "s/average-</u>\n<u>gross-wage-in-the-second-quarter-2024,281,43.html</u>\n\n\n14\n\n\n\n9 These employment rates are very close to the ones from the Polish central bank surveys of Ukrainian refugees, which showed 62% in July 2023 and 68% in July\n2024 (NBP, 2024). NBP (2024) age group was slightly different, describing adults as 18 years or older.\n\n10 See the note on median wage estimation method in the Online Technical Appendix.\n\n11 Since 2021, ZUS has been requesting information about the occupation of non-agricultural workers who first join the social insurance system (most farmers have a\nseparate social insurance system). Unfortunately, this data is not yet comprehensive, as on June 30, 2022, it included 4.8 million people, and June 30, 2024, 7.2 million\n\n- out of about 16 million socially insured workers. Nevertheless, it is still a very large sample and thus a useful proxy, especially in the case of Ukrainian refugees who\npresumably all should have their occupations listed as they did not arrive before 2022.\n\n\n15", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 7, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Polish central bank surveys of Ukrainian refugees", "probe_tag": "keep", "probe_score": 0.9856, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 141, "end": 190, "key": "sample:jad_paddy_docs:000001:7:3:0", "source": "gold", "luna_reason": null}]}
 {"text": "||Szczecin<br>||Gdańsk||||\n||Poznański|Bydgoszcz||~~Katowice~~||||\n|||||Łęczyń|ski||Lubiński|\n\n\n|Col1|Col2|Col3|Col4|Col5|Col6|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|||||||||\n|||||||||\n|||||||||\n|||||Warszawa||||\n|||||||||\n|||||||||\n|||Łodź|Wrocław|Kraków|||R² = 0,16|\n||Poz|nański|Szczecin|||||\n|||Gdańsk<br>~~Bydgoszcz~~||Katowice<br>Łęczy|ński||Lubiński|\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\n\n\n\n8%\n\n\n7%\n\n\n6%\n\n\n5%\n\n\n4%\n\n\n3%\n\n\n2%\n\n\n1%\n\n\n0%\n\n4000\n\n\n10%\n\n\n9%\n\n\n8%\n\n\n7%\n\n\n6%\n\n\n5%\n\n\n4%\n\n\n3%\n\n\n2%\n\n\n1%\n\n\n0%\n\n4000\n\n\n\nUkrainian refugee educational attainment\nimplies from 18% (assuming refugees’\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 agglomeration", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "November 2022\nsurvey", "probe_tag": "keep", "probe_score": 0.967, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 726, "end": 746, "key": "sample:jad_paddy_docs:000007:16:1:0", "source": "gold", "luna_reason": null}]}
-{"text": "s tend to have higher rates of entrepreneurship**\n**than native workers.** There may be different reasons for this\nas perhaps immigrants have character traits that make them\nmore inclined towards entrepreneurial activity (unclear in the\ncase of refugees), or maybe it is a way to avoid occupational\ndowngrading as immigrants find it difficult to prove their\neducational and professional credentials from home countries.\nNotwithstanding the reason, such effects are observed across\nthe OECD countries (OECD, 2011). In a recent paper, Anelli,\nBasso, Ippedico, and Peri (2023) look at Italian data, finding that\none standard deviation increase in emigration rate generates\n4.8% decline of business formation in the municipality of origin.\nThe authors use existing migration networks to ensure causality\nof the results. Nevertheless, it is unclear whether immigrantcreated businesses are more successful from the native\nones, but one could speculate that a higher rate of trying new\nbusiness ideas spurs more successes.\n\n\n\nThe escalatation of war 2022 in Ukraine\ncaused a large inflow of refugees into\nPoland. While some refugees from Ukraine\nhave since returned to Ukraine or gone\nfurther to Germany or other countries,\nin October 2023 close to 957 thousand\nremained in Poland (identified by active\nPESEL UKR numbers). They consist\nprimarily of children and working aged\nwomen. Despite the forced nature of\ndisplacement, war trauma, and caregiving\nresponsibilities, refugees from Ukraine\nvery quickly entered the labour market\nas employees and entrepreneurs. The\nprecise number of refugees from Ukraine\nworking in Poland remains uncertain,\nwith our estimates ranging from 225 to\n350 thousand. The lower bound is the\nnumber of social security registrations and\nunderstates the actual figure, as some jobs\nmay not require social contributions or\nremain in the informal sector. The higher\nbound is the product of employment rates\nfrom surveys of refugees from Ukraine,\nand their working age population from\nthe active PESEL UKR database. By JulyAugust 2023 Ukrainian refugee households\nsupported themselves, with 80% of", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 20, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Italian data", "probe_tag": "keep", "probe_score": 0.9915, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 582, "end": 594, "key": "sample:jad_paddy_docs:000007:20:3:0", "source": "gold", "luna_reason": "Italian data support the reported business-formation finding.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "PESEL UKR", "probe_tag": "keep", "probe_score": 0.9915, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1296, "end": 1305, "key": "sample:jad_paddy_docs:000007:20:3:1", "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": " 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": "\nfell into the last two categories (GUS,\n2024). However, to become promoted\nto an appointed or chartered teacher, a\nforeigner must possess Polish, EU, Swiss,\nor other EEA citizenship (Babakova et al.,\n2024). In effect, only 0.4% of Ukrainian\nrefugees were teachers (ZUS-registered\nin mid-2024) compared to 2.2% of Polish\ncitizens. There were more teachers’\nassistants, who are not regulated, than\n\n\n\nactual teachers. Furthermore, the data\npresented in chapter 2 shows that the\nmedian net wages of Ukrainian refugees\nin the teaching profession are just\nPLN 3,500, constituting 66% of what the\nhost population earns, the lowest earnings\nof all sectors.\n\n\n**Occupational licensing rules regarding**\n**citizenship have been relaxed for**\n**medical professions in the wake of**\n**the COVID-19 pandemic in 2020 and in**\n**February 2022, but those were often**\n**makeshift arrangements.** According to\nthe Babakova et al. (2024) report, during\nthe COVID-19 pandemic, practicing medical\nprofessionals from Ukraine were allowed\n\n\n#### **4.3 Language wage premium**\n\n\n\nEnglish for Speakers of Other Languages\nprogramme in Massachusetts. The policy\ntargeted all immigrants, including those\nwho had lived in Massachusetts for\nseveral years, with data for 2008–2016 and\n4,700 individual lottery applicants. Authors\nfound a causal effect, with annual earnings\nincreasing by USD 2,400. These earnings\ngains generated additional tax revenue\nthat produced a 6% return for taxpayers.\nSchmid (2023) studied African refugees\nwho applied for asylum in Switzerland\nbetween 2008 and 2017. He exploited the\nrandom assignment of refugees to French,\nGerman, and Italian cantons, as well as\ntheir prior language knowledge (e.g. French\nspeakers placed in French or German\nspeaking cantons). The results showed that", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 15, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data\npresented in chapter 2", "probe_tag": "keep", "probe_score": 0.9968, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 434, "end": 461, "key": "sample:jad_paddy_docs:000001:15:1:0", "source": "gold", "luna_reason": null}, {"text": "data for 2008–2016", "probe_tag": "keep", "probe_score": 0.9905, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1234, "end": 1252, "key": "sample:jad_paddy_docs:000001:15:1:1", "source": "gold", "luna_reason": null}]}
-{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n© UNHCR / Anna Liminowicz\n# **3.** Economic impact modelling\n\n\n\nSimple back-of-the-envelope calculations\ngive the intuition behind how additional\nworkers help to grow the economy.\nThe simplest estimate would be to assume\nthat an increase of employment by 1.4-2.2%\nwill grow the Gross Domestic Product by\nan equal percentage. In such a case, we\nwould need to assume that labour is the\nonly production factor, and thus all of GDP\ncan be equally divided between workers.\nHowever, this is not the case, as GDP is not\njust a function of labour, but also of capital\nthat workers have at their disposal – all the\nmachines, computer programs, offices, and\nthe like. As displacement is unexpected and\nrefugee status (both legal and intent to stay\nlong term) at first is uncertain, companies\ntake time to increase their stocks of capital\nto the new workers. A more elaborate\nestimate would account for the part of GDP\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nthat is produced by labour alone. This can\nbe estimated by assuming that it is equal\nto the labour compensation share of GDP\n(GDP can be divided into compensation of\nlabour and capital), which in 2022 and 2023\nstood in Poland at 48% according to the\nEuropean Commission’s AMECO database.\nAccounting for that, gives a lower estimate\nof 0.7-1.0% GDP. Such calculations are\nvery abstract, and do not account for other\nphenomena developing simultaneously\nin the economy, like the various effects of\nthe war and energy shock. For this reason,\nwe turn next to formal general equilibrium\nmodelling, where equations of the model\nstate explicitly every assumption about\nthe workings of the economy and allow for\na credible estimation of counter-factual\nscenarios.\n\n\n\nRefugees’ impact on the economy manifests\nin a multi-layered fashion. An influx of\nrefugees means", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "AMECO database", "probe_tag": "keep", "probe_score": 0.9688, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1333, "end": 1347, "key": "sample:jad_paddy_docs:000007:15:0:0", "source": "gold", "luna_reason": null}]}
-{"text": "\n**radically after February 24, 2022.**\nUp until 2021, Ukrainians in Poland were\nmostly men (close to two-thirds), who came\nfor work-related reasons, often leaving their\nfamilies back in Ukraine. The onset of the\nfull-scale conflict in Ukraine triggered the\narrival of individuals displaced by the war.\nThose were primarily women and children,\nwith men in Ukraine being mobilized for\nthe war effort. Social insurance data does\nnot reflect the full extent of the change,\nshowing only workers, without children and\nadults outside of employment.\n\n\n\n**Chart 3. Number of Ukrainians registered in Poland for social insurance by sex**\n\n\n2021 Q4 2022 Q4 2023 Q4 2024 Q2\n\n\n\nNumber of insured\nmen with Ukrainian\ncitizenship\n\n\n\nNumber of insured\nwomen with Ukrainian\ncitizenship\n\n\n\nNumber of insured\nwith Ukrainian\ncitizenship\n\n\n\nSource: Deloitte own elaboration based on ZUS data.\n\n\n3 Employed person is a person, who during the reference week worked for at least 1 hour for pay or profit, including contributing family workers; had a certain job\nattachment; or produced agricultural goods for sale or barter. A definition according to the Labour Force Survey: <u>https://ec.europa.eu/eurostat/statistics-explained/</u>\n<u>index.php?title=Glossary:Employed_person_-_LFS</u>\n\n\n08\n\n\n\nSource: Deloitte own elaboration based on the PESEL database as of September 2024.\n\n\n4 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=eyJrIjoiODhkOGZiMzctZTliMi00NzA5LTgyM2QtZGZh", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 4, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Social insurance data", "probe_tag": "keep", "probe_score": 0.9986, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 400, "end": 421, "key": "sample:jad_paddy_docs:000001:4:2:0", "source": "gold", "luna_reason": null}, {"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.9734, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 862, "end": 870, "key": "sample:jad_paddy_docs:000001:4:2:1", "source": "gold", "luna_reason": "ZUS data underlies the chart on insured Ukrainians by sex.", "usage_type": "evidential", "specificity": "named"}, {"text": "PESEL database", "probe_tag": "keep", "probe_score": 0.9802, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1319, "end": 1333, "key": "sample:jad_paddy_docs:000001:4:2:2", "source": "gold", "luna_reason": null}, {"text": "UNHCR data portal", "probe_tag": "keep", "probe_score": 0.9645, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1471, "end": 1488, "key": "sample:jad_paddy_docs:000001:4:2:3", "source": "gold", "luna_reason": null}]}
-{"text": " elaboration based on Eurostat\n(Labour Force Survey) data.\n\n\n**Occupational downgrading is**\n**widespread among Ukrainian refugees**\n**in Poland.** SEIS data shows that 40% of\nUkrainian refugees aged 25–64 hold a\ntertiary degree – exceeding the share of\nPolish citizens in the same age bracket,\naccording to Eurostat’s 2023 annual\naverage. While ZUS data available as of\nJune 30, 2024, shows occupational groups\nfor less than half of the socially insured\nin Poland, it reflects a visible mismatch\nbetween the refugees’ education and the\njobs they perform. Only 12% of Ukrainian\nrefugees (less than one-third of the share\nin terms of tertiary education) worked in\noccupational groups which require tertiary\neducation, that is managers, specialists,\nand technicians (ISCO 1-3), compared to\n37% of Polish citizens (almost the same\nas the tertiary education share in the\n25-64 age group).\n\n\n\n2022 2023", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 13, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "SEIS data", "probe_tag": "keep", "probe_score": 0.9975, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 148, "end": 157, "key": "sample:jad_paddy_docs:000001:13:2:0", "source": "gold", "luna_reason": null}, {"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.9902, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 346, "end": 354, "key": "sample:jad_paddy_docs:000001:13:2:1", "source": "gold", "luna_reason": null}]}
-{"text": " elaboration based on Polish Border Guard Headquarter and PESEL data.\n\n\n\n\n\n\n\nMost of the refugees from Ukraine\ncurrently living in Poland are women and\nchildren, though over half of the total\npopulation is of working age.\nThe best population data available is the\nactive PESEL database as of 10th October\n2023. According to the registry, 63.7%\nof them are women and 36.3% are men.\nThe database also includes the age of the\nUkrainian PESEL holders, which indicates\nthat over half (56%) are of working age\n(18-64), which amounts to more than 536\nthousand people. More precisely, women\nyounger than 18 make up 19% of the\npopulation, women aged 18-64 account\nfor around 41% of the population, while\nthose aged 65 and above are around 3%\nof total population. The incoming men are\nmostly young, those younger than 18 stand\nfor around 20% of all refugees, men aged\n18-64 make up 15% of the population and\nmen older than 64 account for only 1%.\n\n\nMany of the refugees that settled in Poland\nremain in special needs or otherwise\nprecarious households. According to the\nMSNA Poland 2023 survey, nearly half of all\nrefugee households have a person with a\nchronic illness, while in nearly 10% there is\na disabled person (Washington Group level\n3 disability). In over a third of all households\nis a single parent and over a fifth houses\nan elderly person (10% of households are\ncomprised of exclusively elderly people).\n\n\n\n\n\n\n\n\n\n\n\n\n\nhouseholds with\n\npersons with\n\nchronic ilness\n\n\n\n\n\n\n\nhouseholds\n\nwith a single\n\nparent\n\n\n\nhouseholds with\n\none or more\n\nolder persons\n\n\n\nhouseholds\n\nwith disabled\n\nindividuals\n\n\n\nhouseholds\n\nexclusively\n\nwith elderly\n\n\n\n18  UNHCR data, <u>[https://data2.unhcr.org/en/situations/ukraine](https://data2.unhcr.org/en/situations/ukraine)</u>\n\n\n14\n\n\n\n**Source:*", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 7, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "PESEL data", "probe_tag": "keep", "probe_score": 0.9593227505683899, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 58, "end": 68, "key": "jad_paddy_docs:000007:7:2:0", "source": "camp2", "luna_reason": "PESEL registry data supports refugee demographic estimates and age calculations.", "usage_type": "evidential", "specificity": "named"}, {"text": "PESEL database", "probe_tag": "keep", "probe_score": 0.9803560972213745, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 271, "end": 285, "key": "jad_paddy_docs:000007:7:2:1", "source": "camp2", "luna_reason": "PESEL registry data provides refugee gender and age figures.", "usage_type": "evidential", "specificity": "named"}, {"text": "MSNA Poland 2023 survey", "probe_tag": "keep", "probe_score": 0.9525821805000305, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1060, "end": 1083, "key": "jad_paddy_docs:000007:7:2:2", "source": "camp2", "luna_reason": "Named survey cited for concrete household vulnerability findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "UNHCR data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1644, "end": 1654, "key": "jad_paddy_docs:000007:7:2:3", "source": "camp2", "luna_reason": "Platform source named without shown UNHCR data use or attributed finding.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"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": "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": " banks) further strengthens\nthat effect. In total, general government\nrevenue increased by 2.0% in 2022, 2.75%\nin 2023, and 2.94% in 2024. In monetary\nterms this amounts to PLN 25.0 billion\nin 2022, PLN 39.1 billion in 2023, and\nPLN 47.0 billion in 2024 <sup>22</sup> . In the long term,\nrefugees should increase annual general\ngovernment revenue by around 2.7%.\n\n\n**Ultimately, Ukrainian refugees**\n**generate additional output and**\n**demand.** This results in an increase in real\nGDP, and is especially beneficial for public\nfinance. Although the influx of refugees\nwas costly at the start, the additional\ngeneral government revenue they provided\nwas more than enough to compensate\nfor the expense <sup>23</sup> . Tight labour market\nhelped absorb the increase in labour force,\nmitigating negative impacts of increased\ncompetition on the native workforce. Over\ntime, increased productivity should benefit\nnative workers, as it is the primary driver of\nlong-term wage growth. <sup>24</sup> [^24: For a discussion on the stable long-term relationship between wages and labour productivity, see for example Meager & Speckesser (2011).]\n\n\n\n22 Deloitte own calculations based on <u>Informacja kwartalna o stanie finansów publicznych - Ministerstwo Finansów - Portal Gov.pl for respective years. The general</u>\ngovernment income share in GDP in 2024 was calculated based on the data for Q1–Q3 and based on that total general government income was calculated using\nforecast for GDP from <u>Wytyczne dotyczące wskaźników makroekonomicznych - Ministerstwo Finansów - Portal Gov.pl.</u>\n\n23 Model treats general government sector as a whole, as such cost and income internal structure may differ creating institutions with financial loses while other may\nhave disproportionate increase of income.\n\n24 For", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Informacja kwartalna o stanie finansów publicznych", "probe_tag": "keep", "probe_score": 0.955, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1180, "end": 1230, "key": "sample:jad_paddy_docs:000001:12:1:0", "source": "gold", "luna_reason": null}, {"text": "data for Q1–Q3", "probe_tag": "keep", "probe_score": 0.9504, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1376, "end": 1390, "key": "sample:jad_paddy_docs:000001:12:1:1", "source": "gold", "luna_reason": null}]}
+{"text": " 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.** Cumulative changes in main indicators in 2023\n\n\n**SCENARIO 1** **SCENARIO 2** **SCENARIO 3** **SCENARIO 4**\n\n\n\n**Low employment**\n**conservative**\n**productivity**\n\n\n\n**High employment**\n**conservative**\n**productivity**\n\n\n\n**Low employment**\n**baseline**\n**productivity**\n\n\n\n**High employment**\n**baseline**\n**productivity**\n\n\n\nThe main impact of refugees is in growth\nof the economy. Refugees increase both\nsupply as workers and entrepreneurs as\nwell as demand as consumers. Increase\nin GDP is not directly proportional to the\nincrease in population or employment.\nNet benefits are lowered both due to\na decrease in capital to labour ratio as\nwell as an increase in competition on\nthe labour market. Moreover, increase in\ndemand in tight labour market conditions\nresults in higher inflation and lower\nprice competitiveness of Polish products\nwhich lower its overall positive impact.\nNevertheless, the positive impact of\nrefugees on the economy is significant in\nevery scenario considered.\n\n\nIn 2022 it amounts to real GDP\nbeing higher by 0.5-0.8% and in\n2023 cumulatively by 0.7-1.1%.\nThis corresponds to GDP being\nhigher by 24-36.9 billion PLN in\n2023 <sup>43</sup> .\n\n\nIn the long term, total potential GDP should\nbe higher by around 0.9-1.35% due to\nrefugees contributions. <sup>44</sup>\n\n\nOur results are consistent with the\nprevious, similar studies. In estimating\nGDP impacts we take an approach that", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data from Statistics Poland", "probe_tag": "keep", "probe_score": 0.9998, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 242, "end": 269, "key": "sample:jad_paddy_docs:000007:17:2:0", "source": "gold", "luna_reason": null}]}
+{"text": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n\nnegative perceptions of Ukrainian refugees in some\nhost communities including perceived overuse of\nhealth services and preferential treatment <sup>6</sup> [^6: Kerusauskaite, I., Nimkar, R., Mulloy, L., Slota, A. (2023). Risks to Community Cohesion between Ukrainian Refugees and Host\nCommunities in Central Europe. Community Cohesion in Central Europe project.] . As the\nrefugees stay longer, sustainable solutions to\nmeeting health needs of refugees and host\ncommunities, including sustainable financing,\nrefugee data integration, integration of the refugee\nhealth workforce, and enhanced service delivery\nincluding mental health services, are critical.\n\n\nThrough regional multi-agency collaboration,\nmultisector needs assessments have been\nconducted in refugee-receiving countries since\n2022 to collect information on the needs of\nrefugees, including those related to health, nutrition\nand mental health and psychosocial support. These\nassessments support partners’ understanding of the\nlevel of access to essential services among\nrefugees and outcomes enable governments and\npartners to identify priorities for the response. In\n2024, a social-economic lens was added in\nassessing the needs of refugees in the SocioEconomic Insights Study (SEIS) conducted in ten\ncountries (Bulgaria, Czechia, Estonia, Hungary,\nLatvia, Lithuania, Poland, Republic of Moldova,\nRomania, and Slovakia).\n\n\n# Methodology\n\nThe regional analysis is grounded in consolidated\ndata from the Socio-Economic Insights Survey\n(SEIS), conducted across ten countries: Bulgaria,\nCzechia, Estonia, Hungary, Latvia, Lithuania, Poland,\nRepublic of Moldova, Romania, and Slovakia. Data\nfor the country-specific SEISs were collected\nthrough in-person interviews from May to July 2024.\n\n\nThe total sample size comprises **8,720 households**\nand **19,803 household members**, with respondents\nproviding information on behalf of all individuals\nwithin their households.\n\n\n**COUNTRY** **SAMPLE SIZE 2023** **SAMPLE SIZE 2024**\n\n\n<u>Bulgaria</u> <u>1,054</", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SocioEconomic Insights Study", "probe_tag": "keep", "probe_score": 0.9778, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1286, "end": 1314, "key": "sample:jad_paddy_docs:000004:5:0:0", "source": "gold", "luna_reason": null}, {"text": "Socio-Economic Insights Survey", "probe_tag": "keep", "probe_score": 0.9908, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1540, "end": 1570, "key": "sample:jad_paddy_docs:000004:5:0:1", "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>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": " 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": " <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 the territory of that country.\n\n\n06\n\n\n\n**Chart 2. Ukrainians registered for social insurance**\n\n\nNote: Refugees are identified by PESEL UKR status.\n\nSource: Deloitte own elaboration based on ZUS data.\n\n\n\nUkrainian refugees Pre-war Ukrainians\n\n\n\n07", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 3, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "ZUS data", "probe_tag": "confusion", "probe_score": 0.6506249904632568, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 364, "end": 372, "key": "jad_paddy_docs:000001:3:2:0", "source": "camp2", "luna_reason": "ZUS data underlies the chart of Ukrainians registered for social insurance.", "usage_type": "evidential", "specificity": "named"}]}
 {"text": " 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 refugees finding employment,\ntheir impact grew to 2.3% GDP in 2023,\nand further to 2.7% GDP in 2024. This\ncorresponds to GDP being higher by\nPLN 98.7 billion in 2024. In the long term, as\nthe refugees acquire more country-specific\nskills and firms invest to restore their\ncapital-to-labour ratio, the impact will grow\nto 3.2% GDP by 2030. Refugees contribute\nto the economy by increasing the labour\nsupply as both workers and entrepreneurs,\nand by boosting demand as consumers.\nThe increase in GDP is not directly\n\n\n\nproportional to the increase in population\nor employment. <sup>20</sup> [^20: As outlined in the Appendix on modelling strategy, the total number of refugees was set at 2.6% of the total population, while their share in total employment as\ngrowing from 1.5% in 2022 to 2.4% in 2024.] On the one hand,\nincrease in productivity further boosts\nthe economy, on the other net benefits\nare lowered both due to a decrease in\nthe capital-to-labour ratio, as well as an\nincrease in competition in the labour\nmarket. Moreover, the increase in demand\nin tight labour market conditions work in\nthe direction of higher inflation and lower\nprice competitiveness of Polish products\nwhich decrease its overall positive impact.\n\n\n**The results are in line with the**\n**optimistic scenario from the**\n**previous Deloitte (2024) report.** The\ncurrent report is different from the one\nfrom 2024 in that we account for the\npositive productivity shock reflected in\nthe labour market data, which further\n\n\n\n**The impact of Ukrainian refugees**\n**on the Polish economy is estimated**\n**with the Deloitte D.Climate general**\n**equilibrium model** <sup>", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 11, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "labour market data", "probe_tag": "confusion", "probe_score": 0.0971, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1635, "end": 1653, "key": "sample:jad_paddy_docs:000001:11:3:0", "source": "gold", "luna_reason": "Existing labour market data are used to reflect a productivity shock in the model.", "usage_type": "declaration", "specificity": "vague"}]}
-{"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": "org/en/documents/details/104427 )</u>\n\n\nUrban M. (2022). Refugees will lift economy's potential, but challenges remain,\nResearch Briefing | Poland. Oxford Economics, <u>[https://www.oxfordeconomics.](https://www.oxfordeconomics.com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-potential-but-challenges-remain.pdf)</u>\n<u>[com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-](https://www.oxfordeconomics.com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-potential-but-challenges-remain.pdf)</u>\n<u>[potential-but-challenges-remain.pdf](https://www.oxfordeconomics.com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-potential-but-challenges-remain.pdf)</u>\n\n\n45\n\n\n\nD’Amuri, F., & Peri, G. (2014). Immigration, jobs, and employment protection:\nevidence from Europe before and during the great recession. Journal of the\nEuropean Economic Association, 12(2), 432-464.\n\n\nDeloitte (2023), Ukraine Refugee Pulse report, <u>[https://www2.deloitte.com/pl/pl/](https://www2.deloitte.com/pl/pl/pages/zarzadzania-procesami-i-strategiczne/articles/Ukraine-Refugee-Pulse-report", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 22, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Ukraine Refugee Pulse report", "probe_tag": "confusion", "probe_score": 0.0902, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 945, "end": 973, "key": "sample:jad_paddy_docs:000007:22:3:0", "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": "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": "HELPING HANDS\nTHE ROLE OF \nHOUSING \nSUPPORT AND \nEMPLOYMENT \nFACILITATION IN \nECONOMIC \nVULNERABILITY \nOF REFUGEES \nFROM UKRAINE\nAn inter-agency \nexploration of socio-\neconomic data\nApril 2024", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 0, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "socio-\neconomic data", "probe_tag": "confusion", "probe_score": 0.4913, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 161, "end": 181, "key": "sample:jad_paddy_docs:000000:0:0:0", "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": " Poles. Visible\n\n\n\ndifferences are identified in 15-19 and\n20-24 age groups, with much higher\nemployment rates for Ukrainian refugees\ndue perhaps to the fact that the Ukrainian\nschool system ends at 17 while the Polish\none at 19. <sup>13</sup> [^13: Children in Ukraine start school at 6 years of age, while in Poland at 7. School system lasts for 11 years in Ukraine and 12 years in Poland. After recent reform,\nUkrainian children who started school in or after 2018 will receive 12 years of schooling.] However, employment rates\ndrop for Ukrainian female refugees in the\n25-29, 30-34, and 35-39 age groups when\ncompared to younger and older groups, as\nwell as to Polish women, which may be due\nto insufficient access to childcare services.\nEmployment rates for Ukrainian female\nrefugees are also substantially lower in the\n55-59 age group, perhaps due to the fact\nthat female retirement age in Ukraine has\nonly recently (in 2021) become 60. <sup>14</sup> [^14: <u>https://www.social-protection.org/gimi/gess/Media.action;jsessionid=U1dm6XAPF38pPk5_pzhfaGoS_rOACMDDVv4w5uevMsKBeQEC5-_g!284293951?id=15680</u> 15 Percentage calculated based on GUS average for the economy as a whole in the months of the SEIS survey.]\n\n\n\n**With the current level of integration**\n**of Ukrainian refugees into the labour**\n**market and the jobs they perform,**\n**their median net earnings are about**\n**four-fifths of the national median**\n\n**– although likely lower in terms of**\n**average or gross earnings.** The median\nnet earnings of Ukrainian refugees in\nQ2 2024 were PLN 4,000 in SEIS, and\nPLN 3,767 in NBP (2024) surveys. This\nis 84% and 79% of the national median,\nrespectively. This estimate would be\nmost likely lower, if data allowed us to\nlook at", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "SEIS survey", "probe_tag": "keep", "probe_score": 0.9934, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1204, "end": 1215, "key": "sample:jad_paddy_docs:000001:9:1:0", "source": "gold", "luna_reason": "SEIS survey data underpin reported employment and earnings calculations.", "usage_type": "evidential", "specificity": "named"}, {"text": "NBP (2024) surveys", "probe_tag": "confusion", "probe_score": 0.6828, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1592, "end": 1610, "key": "sample:jad_paddy_docs:000001:9:1:1", "source": "gold", "luna_reason": null}]}
-{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**Table 1.** Ukrainian employment rate in EU.\n\n\n**Employment rate** **Main sectors of employment** **Date** **Source**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Source:** Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023. The calculation methods of employment\nrates vary between the countries, the results for Poland, the United Kingdom, Czech Republic and Italy are based on surveys. Additionally, the\ndifferent statistical offices and organisations may use different employment and working age definitions.\n\n\n\nCurrently, DIW Berlin data shows that the\nemployment of refugees from Ukraine is\nmuch lower in Germany, although many\naspire to find employment. In a weekly\nreport from 12th July 2023 the German\nInstitute for Economic Research (DIW\nBerlin), a survey conducted in the first\nquarter of 2023 finds that only 18% of\nworking age refugees were employed\n(Kollman, 2023). Among the non-employed,\nhowever, as many as 93% declare\nwillingness to begin working, of which\n71% as soon as possible or within a year.\nImportantly, many refugees are currently\nattending language courses in Germany\n\n- 65% in early 2023 with a further 10%\nalready having completed a course. 87%\nalso took part in inclusion courses that\nwere offered. Per the report, since the\nbeginning of the full-scale war,, around one\nmillion people have fled to Germany, while\nEurostat data on beneficiaries of temporary\nprotection show that there were around 1.17\nmillion Ukrainians under such schemes in\nGermany <sup>30</sup> [^30: Eurostat data, <u>https://ec.europa.eu/eurostat/databrowser/view/migr_asytpsm/default/table?lang=en</u>] .\n\n\nAmong working refugees there is a\nsignificant number of entrepreneurs.\nThe high employment rate of refugees in\nPoland covers not", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "OECD International Migration Outlook 2023", "probe_tag": "keep", "probe_score": 0.9999, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 344, "end": 385, "key": "sample:jad_paddy_docs:000007:13:0:0", "source": "gold", "luna_reason": "Named OECD report supplies aggregated employment-rate data presented in the table.", "usage_type": "evidential", "specificity": "named"}, {"text": "DIW Berlin data", "probe_tag": "keep", "probe_score": 0.9881, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 688, "end": 703, "key": "sample:jad_paddy_docs:000007:13:0:1", "source": "gold", "luna_reason": "DIW Berlin data supports the reported employment finding for Ukrainian refugees.", "usage_type": "evidential", "specificity": "named"}, {"text": "survey conducted in the first\nquarter of 2023", "probe_tag": "keep", "probe_score": 0.9396, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 920, "end": 965, "key": "sample:jad_paddy_docs:000007:13:0:2", "source": "gold", "luna_reason": null}, {"text": "Eurostat data on beneficiaries of temporary\nprotection", "probe_tag": "confusion", "probe_score": 0.1036, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1505, "end": 1559, "key": "sample:jad_paddy_docs:000007:13:0:3", "source": "gold", "luna_reason": null}, {"text": "Eurostat data", "probe_tag": "keep", "probe_score": 0.9991, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1662, "end": 1675, "key": "sample:jad_paddy_docs:000007:13:0:4", "source": "gold", "luna_reason": null}]}
-{"text": " those of their\nnative counterparts. Tani (2020) found\nthat in Australia, licensing raised hourly\n\n\n\nvalue to the economy. This estimate may\nunderestimate the potential benefits,\nas the boost in productivity would most\nlikely rise not just employee wages, but\nemployer profits as well. Conversely, the\noverall impact on wages might be lower, if\nincreased worker competition reduced the\naverage individual premium.\n\n\nwages and reduced over-education for\nmigrants working in licensed jobs, while\nproducing worse labour market outcomes\nfor those who did not gain licensure.\nAccording to Peterson et al. (2014), over the\n1973–2010 period, U.S. states with more\nstringent occupational licensing for migrant\nphysicians received fewer new migrant\nphysicians and struggled more with staffing\nshortages in healthcare. Aleksynska and\nTritah (2013) quoted data that migrants\nin France were denied legal access to\napproximately 30% of jobs in the country.\n\n\n\nUkrainian refugees Polish citizens\n\n\nSource: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey\n(Ukrainian refugees’ educational attainment), 2023 Eurostat Labour Force\nSurvey Eurostat (Polish citizens educational attainment), and mid-2024 ZUS\nadministrative data (occupational groups).\n\n\n\nSource: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey\n(Ukrainian refugees’ educational attainment and median net wages),\n2023 Eurostat Labour Force Survey Eurostat (Polish citizens educational\nattainment), and mid-2024 ZUS administrative data (occupational groups).\n\n\n\n**Widespread occupational licensing**\n**is a serious obstacle to an efficient**\n**use of Ukrainian refugees’ human**\n**capital.** Poland has the third highest\nnumber of regulated professions among\nthe 28 European Union member states,\naccording to European Commission’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", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9974, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1035, "end": 1052, "key": "sample:jad_paddy_docs:000001:14:1:0", "source": "gold", "luna_reason": null}, {"text": "2023 Eurostat Labour Force\nSurvey Eurostat", "probe_tag": "keep", "probe_score": 0.999, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1099, "end": 1141, "key": "sample:jad_paddy_docs:000001:14:1:1", "source": "gold", "luna_reason": "Eurostat Labour Force Survey supplies Polish citizens’ educational-attainment data.", "usage_type": "evidential", "specificity": "named"}, {"text": "ZUS\nadministrative data", "probe_tag": "keep", "probe_score": 0.9499, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1197, "end": 1220, "key": "sample:jad_paddy_docs:000001:14:1:2", "source": "gold", "luna_reason": "Named administrative data underpin Deloitte’s occupational-group analysis.", "usage_type": "evidential", "specificity": "named"}, {"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9983, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1298, "end": 1315, "key": "sample:jad_paddy_docs:000001:14:1:3", "source": "gold", "luna_reason": null}, {"text": "Regulated Professions Database", "probe_tag": "confusion", "probe_score": 0.8069, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1800, "end": 1830, "key": "sample:jad_paddy_docs:000001:14:1:4", "source": "gold", "luna_reason": null}]}
-{"text": "## Introduction\n\n##### Nearly two years after the beginning of the full-scale war in Ukraine, the positive impact of the refugees on the Polish economy becomes clearly visible.\n\n\n\nOn their arrival, the impact of refugees\non the economy primarily manifested\nthrough higher consumption, that was\nfinanced mainly by increased governmental\nspending, civil society, international\norganisations, and savings brought\nfrom Ukraine. While these added to a\nsignificant initial increase in consumption,\nmultiple sources of financing and a lack of\naggregated data (particularly on general\ngovernment expenses) make its magnitude\nuncertain. Although in the short term it\nstimulated the economy, drawing just on\nsavings was not sustainable. Over time,\nhowever, refugees started to work as\nemployees and entrepreneurs, adding\nnot only to the demand, but also to the\nsupply of the economy, contributing to its\nlong-term growth. The focus of this report\nis this structural impact of refugees on\nthe economy as consumers, employers,\nentrepreneurs, and taxpayers.\n\n\nThe beginning of the full-scale war in\nUkraine resulted in a large inflow of\nrefugees into Poland outlined in Chapter 1.\nThis cohort differs from the pre-2022\nUkrainian economic migrants, most notably\nin its demographic makeup which primarily\ncomprises children and working age women.\n\n\nThe government quickly granted refugees\nfrom Ukraine access to the labour market,\nhealthcare, and schooling, facilitating the\nprocess of inclusion described in Chapter\n2. Considering their psychological stress\nand needs in terms of child and elderly\ncare, refugees began entering the labour\n\n\n\nmarket surprisingly quickly – attaining\nan employment rate of 28% in May 2022\nand 65% in November 2022 (NBP, 2023).\nBy 30th September 2023 more than\n10 thousand ran their own businesses\naccording to the administrative social\nsecurity ZUS 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", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "aggregated data", "probe_tag": "confusion", "probe_score": 0.612, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 536, "end": 551, "key": "sample:jad_paddy_docs:000007:5:0:0", "source": "gold", "luna_reason": null}, {"text": "administrative social\nsecurity ZUS data", "probe_tag": "keep", "probe_score": 0.9935, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1831, "end": 1870, "key": "sample:jad_paddy_docs:000007:5:0:1", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 19. Tertiary education and corresponding**\n**occupational groups shares**\n\n\n\n**Chart 20. Ukrainian refugees median net wages by**\n**educational attainment**\n\n\n4,300 4,275\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\ncountry-specific knowledge and business\nnetworks) are more difficult to address\nthan others (such as language skills and\noccupational licensing). However, if the gap\nwas narrowed by half, the average wage of\nrefugees would increase by approximately\n10%. Assuming that the productivity\nincrease is equivalent to the wage increase,\nthis would result in PLN 3.5 billion of added\n\n\n\n**Addressing occupational downgrading**\n**could bring macroeconomic benefits.**\nTo demonstrate the potential impact,\na simulation was conducted in which\nthe underrepresentation of refugees in\nhigher-paying occupations was reduced by\nhalf. It was not assumed that there would\nbe no differences between refugees and\nPolish citizens, as some barriers (such as\n\n\n\n40%\n\n\nTertiary education share\n\n25-64 age group\nsurveys\n\n\n\nManagers, professionals,\nand technicians ZUS-insured\n\nemployment share\n\n\n\n\n#### **4.2 Access to regulated professions**\n\n\n\nnatives and this gap was largest for men,\nworkers in the highest education level, and\nnonnaturalized immigrants. This has an\nimportant impact on wages, because, as\nshowed in a seminal work by Kleiner and\nKrueger (2013) and confirmed in several\nanalyses, working in a regulated profession\ncomes with a significant wage premium.\nBrücker et al. (2021), who analysed\nGerman data, found that occupational\nrecognition led to full convergence of\nimmigrants’ earnings to those of their\nnative counterparts. Tani (2020) found\nthat in Australia, licensing raised hourly\n\n\n\nvalue to the economy. This estimate may\nunderestimate the potential benefits,\nas the boost in productivity would most\nlikely rise not just employee wages, but\nemployer profits as well", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "25-64 age group\nsurveys", "probe_tag": "confusion", "probe_score": 0.5821, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1104, "end": 1127, "key": "sample:jad_paddy_docs:000001:14:0:0", "source": "gold", "luna_reason": null}, {"text": "German data", "probe_tag": "keep", "probe_score": 0.9229, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1617, "end": 1628, "key": "sample:jad_paddy_docs:000001:14:0:1", "source": "gold", "luna_reason": "German data supports the finding that occupational recognition equalized immigrant earnings.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"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": " policies in Finland,\nGermany, Ireland, Netherlands, Norway,\nSweden, Switzerland and the UK (no data\nfor Denmark). They find that non-EU15\nrefugees aged 25-64 who arrived when a\ndispersal policy was in place experience\n4.5 percentage points lower employment\nrates than for those not exposed to such\na policy. This may understate the effect,\nas for refugees who arrived 10 or less\nyears before the survey, the effect is\n17.5 percentage points, while it becomes\nstatistically insignificant afterwards.\nFor the six countries for which data on\nresidence is available, non-dispersed\nrefugees show clearly stronger clustering in\neconomically stronger regions (measured\nby GDP per capita).\n\n\n24\n\n\n\n25\n\n\n\nEconomic research on dispersal policies\nand labour market inclusion focuses on\nthe strength of local labour markets and\nsize of local ethnic networks. While some\nscholars find only the strength of local\nlabour markets to be significant and not\nco-national networks (Foged, Hasager, and\nPeri, 2022), or inconsistent results for conational networks (Müller, Pannatier, and\nViarengo, 2022), others find effects only for\nco-national networks (Damm, 2014).\n\n\nMigrants dispersed to weaker labour\nmarkets experience poorer inclusion\noutcomes in subsequent years, and vice\nversa. These outcomes can pertain to\nemployment, earnings, or human capital\naccumulation, and have been shown in\nDenmark (Foged, Hasager, and Peri, 2022;\nAzlor, Damm, and Schiltz-Nielsen, 2020),\nGermany (Aksoy, Giray, Poutvaara, and\nSchikora, 2020), Norway (Godøy, 2017),\nSweden (Åslund, Östh, 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", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on\nresidence", "probe_tag": "confusion", "probe_score": 0.3768, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 532, "end": 549, "key": "sample:jad_paddy_docs:000007:12:1:0", "source": "gold", "luna_reason": null}]}
+{"text": ", 2024 shows that\n38% of Ukrainian refugees worked in\nelementary occupations, much more than\npre-war Ukrainians (25%), non-Ukrainian\nforeigners (18%), and Polish citizens (10%).\n\n\n\n\n\n\n\n\n\n\n\nMSNA Jul-Aug 2023 SEIS May-Jun 2024\n\n\n\n\n\n\n\n\n\nMSNA Jul-Aug 2023 SEIS May-Jun 2024\n\n\n\nSource: Deloitte own elaboration based on MSNA and SEIS UNHCR surveys conducted in July-August 2023 and May-June 2024.\n\n\n\nWhile the share seems least favourable\namong Ukrainian refugees, their situation\nimproved the most in the two years since\nJune 30, 2022 (by 10 pp. compared with\n9 pp. for the pre-war Ukrainians, 2 pp. for\nnon-Ukrainian foreigners and 1 pp. for\nPolish citizens). On the other hand, in\nQ2 2024, managers and specialists, the\ntwo highest paid occupational groups,\ncomprised 8% of both Ukrainian refugees\nand pre-war Ukrainians, 22% of nonUkrainian foreigners (who include many\n\n\n\nIT specialists and executives), and 28% of\nPolish citizens. Their shares increased\nin the past two years by 3 pp. among\nUkrainian refugees and pre-war Ukrainians,\n2 pp. among other foreigners, and 1 pp.\namong Polish citizens – this data shows\nthat though Ukrainian refugees may be\nlargely employed in the less attractive\noccupational groups, they are also the\nfastest to progress toward more attractive\nprofessions. <sup>11</sup> [^11: Since 2021, ZUS has been requesting information about the occupation of non-agricultural workers who first join the social insurance system (most farmers have a\nseparate social insurance system). Unfortunately, this data is not yet comprehensive, as on June 30, 2022, it included 4.8 million people, and June 30, 2024, 7.2 million]\n\n\n\n**Ukrainian refugees in Poland have**\n**clearly improved their economic**\n**situation over the past year.** As\nindicated in chapter 1, the share of\nUkrainian refugee household incomes\nderived from work in Poland has increased\nfrom 74% in the July-August 2023 MSNA\nsurvey to 76% in the May-June 2024", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR surveys", "probe_tag": "keep", "probe_score": 0.9957, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 324, "end": 342, "key": "sample:jad_paddy_docs:000001:7:1:0", "source": "gold", "luna_reason": null}, {"text": "MSNA\nsurvey", "probe_tag": "confusion", "probe_score": 0.645, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1902, "end": 1913, "key": "sample:jad_paddy_docs:000001:7:1:1", "source": "gold", "luna_reason": null}]}
+{"text": " and highest incomes.\nDetails are available in the Online Technical Appendix.\n\n27 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\n28\n\n\n\n28 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\n29", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "GUS (2024) data", "probe_tag": "confusion", "probe_score": 0.2908, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 96, "end": 111, "key": "sample:jad_paddy_docs:000001:14:4:0", "source": "gold", "luna_reason": null}]}
+{"text": " rate of native or other\nimmigrants, except an actual slight positive\nimpact on the wages of native women.\nEven in a conservative scenario that\nassumes negative effects of labour\nmarket competition in the form of higher\nunemployment and slower real wage\ngrowth, an increase in the labour force\ntranslates into larger personal incomes and\nhigher private consumption, which results\nin a larger tax revenue. These effects were\nstrengthened by an influx of capital from\nabroad.\n\n###### In total, the general government revenue increased by 0.8-1.1% in 2022 and 1.05-1.45% in 2023. In monetary terms, this amounts to 10.1-13.7 billion PLN in 2022 and 14.7-19.9 billion PLN in 2023.\n\n\n\nIf estimates quoted by a government offical\nof public expenses on refugees of around\n15 billion PLN in 2022 and 5 billion in 2023 <sup>13</sup> [^13: E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of\nNGOs which was combined with spendings of local governments <u>[Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.](https://www.infor.pl/prawo/nowosci-prawne/5635962,Polska-pomoc-dla-Ukrainy-2022-ile-kosztowala.html)</u>]\nare accurate, we can conclude that they\nwere more than offset by the additional tax\nrevenue. In the long-term, refugees should\nincrease yearly government revenue by\naround 0.85-1.3%.\n\n\n**Unaccounted positive externalities**\nAll our theoretical economic modelling\nresults are conservative lower bound\nestimates, as econometric studies from\nother countries have found immigration\nto have additionally a positive impact\non labour productivity that cannot be\naccounted for using the available data.\nAccording to these econometric studies,\nimmigration can not only raise economic\noutput (i.e., more workers equal more\nproduction), but more importantly labour\nproductivity (i.e., more value added per\nworker)", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 4, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "available data", "probe_tag": "confusion", "probe_score": 0.6607, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1689, "end": 1703, "key": "sample:jad_paddy_docs:000007:4:2:0", "source": "gold", "luna_reason": null}]}
+{"text": " for host country poverty](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)</u>\nassessments\n\n3. Results for the Czech Republic not individually presented due to\nsampling limitations\n\n4. The host country poverty rate was based on <u>[OECD indicators for](https://stats.oecd.org/)</u>\n<u>[2021 that were indexed towards 2023 using consumer price index](https://stats.oecd.org/)</u>\n(CPI) data\n\n\nRefugee households also report having to engage\nin harmful coping strategies to meet basic needs.\nSome 8% and 15% had to resort to emergency\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n5 Belarus, Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, the Republic of Moldova, Poland, Romania, and Slovakia\n\n\n\n6 Defined as the total after-tax income of the household (including wages, transfers, social protection benefits, etc.) divided by the\nsquare root of the household size\n\n\n\n7 Based on <u>[OECD data from 2021, which was indexed by the CPI for 2022 and 2023 for each respective country](https://stats.oecd.org/)</u>\n\n\n\n**4**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 3, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "OECD indicators", "probe_tag": "keep", "probe_score": 0.9908, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 287, "end": 302, "key": "sample:jad_paddy_docs:000000:3:2:0", "source": "gold", "luna_reason": null}, {"text": "OECD data from 2021", "probe_tag": "confusion", "probe_score": 0.8555, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 924, "end": 943, "key": "sample:jad_paddy_docs:000000:3:2:1", "source": "gold", "luna_reason": null}]}
+{"text": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n\nmeasles vaccination coverage for children\nstood at 83%, similar to 84% in 2023, falling\nshort of the 95% target.\n\n\n\n\n\n\n\nInformal support also played a vital role, with\n33% receiving help from family or friends and\n12% accessing spiritual support. Overall, 88%\nof those who received support reported\nimproved wellbeing, though there are notable\ndifferences depending on gender and age.\n\n\nThe recommendations drawn from this analysis\nfocus on addressing the health and mental health\nand psychosocial needs and barriers identified in\nthe SEIS, tailoring them to the specific data and\ncontext of each country. To enhance policy\ndevelopment, it will be crucial to improve monitoring\nof refugees’ health, including sexual and\nreproductive health and mental health, through\ninclusion of disaggregated refugee data into\nnational data systems. This will require effective\ncollaboration among health organizations, statistical\noffices, and partners. Addressing capacity issues in\nnational health systems, such as workforce\nshortages and long wait times, can be supported\nthrough telemedicine and temporarily integrating\nUkrainian healthcare workers. Refugees with\nchronic illnesses and disabilities require targeted\ninterventions to meet their health and MHPSS\nneeds, including through health financing\nmechanisms. Continued efforts are also required to\naddress persistent access barriers through contextspecific strategies, including providing refugees\nwith information on navigating health systems and\npreventive health services such as vaccination.\n\n\nExpanding community-based MHPSS services that\nintegrate formal services and promote the use of\ninformal supports will enhance service delivery.\nPublic awareness campaigns, tailored to both\nrefugees and host communities, should aim to\nreduce stigma and improve knowledge of available\nsupport. Gender-responsive and age-sensitive\napproaches are necessary, particularly for adult men\nand adolescent boys, to encourage help-seeking\nbehaviours and ensure that services are tailored to\nthe specific needs of children and adolescents.\nLastly, further research is required to gain a deeper\nunderstanding of unmet health needs—including\nSRH and MHPSS needs—and the barriers to access", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SEIS", "probe_tag": "confusion", "probe_score": 0.6005, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 608, "end": 612, "key": "sample:jad_paddy_docs:000004:3:0:0", "source": "gold", "luna_reason": "SEIS identifies health needs and barriers underlying the recommendations.", "usage_type": "evidential", "specificity": "named"}, {"text": "disaggregated refugee data", "probe_tag": "confusion", "probe_score": 0.4115, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 853, "end": 879, "key": "sample:jad_paddy_docs:000004:3:0:1", "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\nVocational or lower Secondary Higher\n\n\n\nData is limited, but it appears refugees\nfound work in sectors where the labour\nmarket was particularly tight. Publicly\navailable data does not give the numbers\nof social security registrations of native\nworkers by NACE sector. For this reason,\nin the absence of administrative data,\nto approximate the share of Ukrainian\nworkers in particular sectors it was\nnecessary to use Statistics Poland survey\ndata. The share of workers with Ukrainian\ncitizenship grew more in sectors that were\nexperiencing the highest wage and salaries\ngrowth before refugee displacement. This\neased their entry into the labour market.\nThe refugees were also quick to set-up their\nown businesses or become self-employed.\nAccommodation and food, as a sector,\nhas been experiencing a particularly large\ngrowth in wages and salaries in 2021, as it\nre-opened after the Covid-19 pandemic,\nand subsequently it recorded a particularly\nlarge growth in the share of Ukrainian\nworkers. Transportation has been the only\nsector in which the share and number of\nUkrainian workers declined.\n\n\nA significant number of refugees are\nconcentrated in the urban areas of\nPoland. For one, cities generally record\nlower unemployment rates and higher\nwork productivity, though the costs of\nliving remain higher than in rural areas.\nAccording to the active population in the\nPESEL database, over 30% of all PESEL UKR\nholders had them issued in the country’s\n12 biggest cities. At the same time, the\nresults for the MSNA Poland 2023 survey\nsuggest that these 12 biggest cities are\ninhabited by over 35% of refugees.\n\n\n\nRefugees record higher levels of\nemployment inclusion in European\ncountries that 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", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Statistics Poland survey\ndata", "probe_tag": "keep", "probe_score": 0.9774, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 567, "end": 596, "key": "sample:jad_paddy_docs:000007:10:0:0", "source": "gold", "luna_reason": null}, {"text": "PESEL database", "probe_tag": "confusion", "probe_score": 0.8853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1518, "end": 1532, "key": "sample:jad_paddy_docs:000007:10:0:1", "source": "gold", "luna_reason": null}, {"text": "MSNA Poland 2023 survey", "probe_tag": "keep", "probe_score": 0.9768, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1658, "end": 1681, "key": "sample:jad_paddy_docs:000007:10:0:2", "source": "gold", "luna_reason": null}]}
-{"text": " refugees is for persons with PESEL UKR registered for social security on 30th September 2023. It\nis then compared to the general population by nine main occupational groups from GUS LFS in Q2 2023 and earnings from GUS (2023) “Structure\nof wages and salaries by occupation in October 2022”, and by detailed occupations workers and earnings from GUS (2022) “Structure of wages and\nsalaries by occupations in October 2020”.\n\n\n\n**Note:** Earnings in poviat Lubiński are so high, as it is the site of KGHM, state-owned copper mining corporation.\n\n\n**Source:** Deloitte own elaboration based on ZUS, and Statistics Poland data.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n32\n\n\n\n33", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "ZUS", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 591, "end": 594, "key": "sample:jad_paddy_docs:000007:16:4:0", "source": "gold", "luna_reason": null}, {"text": "Statistics Poland data", "probe_tag": "keep", "probe_score": 0.9696, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 600, "end": 622, "key": "sample:jad_paddy_docs:000007:16:4:1", "source": "gold", "luna_reason": null}]}
-{"text": "unhcr.org/en/situations/ukraine)</u>\n4 According to the active PESEL UKR database.\n5 According to the active PESEL UKR database in October 2023.\n6 Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.\n\n\n06\n\n\n\n7  According to the Labour Force Survey data from Eurostat.\n8  According to the harmonized unemployment rates from Eurostat.\n9  According to the quarterly NBP survey.\n10 According to the UNHCR (2023) survey.\n11 According to the social security data until 30th September 2023.\n12 Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "Labour Force Survey data from Eurostat", "probe_tag": "keep", "probe_score": 0.9701, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 279, "end": 317, "key": "sample:jad_paddy_docs:000007:3:4:0", "source": "gold", "luna_reason": "Existing Eurostat Labour Force Survey data is cited as the basis for a statement.", "usage_type": "declaration", "specificity": "named"}, {"text": "quarterly NBP survey", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 404, "end": 424, "key": "sample:jad_paddy_docs:000007:3:4:1", "source": "gold", "luna_reason": null}, {"text": "social security data until 30th September 2023", "probe_tag": "keep", "probe_score": 0.9598, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 487, "end": 533, "key": "sample:jad_paddy_docs:000007:3:4:2", "source": "gold", "luna_reason": null}, {"text": "Multi-Sector Needs Assessment Poland 2023 survey data", "probe_tag": "keep", "probe_score": 0.9996, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 569, "end": 622, "key": "sample:jad_paddy_docs:000007:3:4:3", "source": "gold", "luna_reason": null}]}
+{"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": " 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\n**Chart 7. Income of Ukrainian refugee households by source**\n\n\n**2%**\n**0.1%**\n\n\n\nWork (regular, part-time, self-employment, remote, other, remote in Ukraine)\n\n\nRemittances from Ukraine\n\n\nPolish social benefits\n\n\nUkrainian social benefits\n\n\nOther (capital, loans, other)\n\n\n\nSource: Deloitte own elaboration based on SEIS (May-June 2024) UNHCR (2024) survey.\n\nNote: Deloitte worked with disaggregated household-level data, ensuring comparability\n(converting all Ukrainian hryvnia incomes into Polish zloty based on daily exchange rates\nin the time of the interview, and 3-month into 1-month remittance incomes).\n\n\n\n**In 2024, Ukrainian refugee households**\n**increasingly sourced their income from**\n**Poland, rather than from Ukraine.** This\ncan be seen when comparing the MSNA\nsurvey conducted in July-August 2023 and\nSEIS in May-June 2024 (UNHCR, 2024, 2023).\n\n\n\nWhile some methodological differences\napply, we can see that incomes earned\nin Poland grew from 81% in 2023 to 90%\nin 2024. Conversely, incomes from Ukraine\ndeclined from 18% to just 9%. This change\ndemonstrates that Ukrainian refugees\n\n\n\ncontinue to integrate economically.\nIt comes as no surprise, given that\nemployment rates and wages of Ukrainian\nrefugees in Poland increased during that\ntime, which is the focus of the next chapter.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**According to academic literature,**\n**better access to host country’s public**\n**services increases the likelihood of**\n**refugees returning to their country of**\n**origin, while labour market integration**\n**decreases it.** Some evidence shows that\nwhen refugees from Ukraine have access to\neducation, healthcare", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SEIS", "probe_tag": "keep", "probe_score": 0.9986, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 392, "end": 396, "key": "sample:jad_paddy_docs:000001:6:0:0", "source": "gold", "luna_reason": null}, {"text": "UNHCR (2024) survey", "probe_tag": "keep", "probe_score": 0.9967, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 413, "end": 432, "key": "sample:jad_paddy_docs:000001:6:0:1", "source": "gold", "luna_reason": null}, {"text": "disaggregated household-level data", "probe_tag": "keep", "probe_score": 0.9675, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 462, "end": 496, "key": "sample:jad_paddy_docs:000001:6:0:2", "source": "gold", "luna_reason": null}, {"text": "MSNA\nsurvey", "probe_tag": "keep", "probe_score": 0.9869, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 849, "end": 860, "key": "sample:jad_paddy_docs:000001:6:0:3", "source": "gold", "luna_reason": null}, {"text": "SEIS", "probe_tag": "drop", "probe_score": 0.0007, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 895, "end": 899, "key": "sample:jad_paddy_docs:000001:6:0:4", "source": "gold", "luna_reason": null}]}
+{"text": " working refugees there is a\nsignificant number of entrepreneurs.\nThe high employment rate of refugees in\nPoland covers not only employees, but\nalso the self-employed. The available data\nalso shows that refugees from Ukraine\nin Poland are likely to start their own\nbusinesses. ZUS (social security) statistics\non insured refugees indicate that around\n5% of them have set up a business or are\nfreelancers. Similar results can be gleaned\nfrom the MSNA Poland 2023 survey results,\nwhich show that slightly more than 5% of\nrespondent households receive income\nfrom self-employment or similar activities.\nThis percentage appears to be slightly\nhigher for men, at over 6%, than women.\n\n\n\n\n\n30  Eurostat data, <u>https://ec.europa.eu/eurostat/databrowser/view/migr_asytpsm/default/table?lang=en</u>\n\n\n\n26 27", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "ZUS (social security) statistics\non insured refugees", "probe_tag": "confusion", "probe_score": 0.4385, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 277, "end": 329, "key": "sample:jad_paddy_docs:000007:13:1:0", "source": "gold", "luna_reason": null}, {"text": "MSNA Poland 2023 survey results", "probe_tag": "confusion", "probe_score": 0.7324, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 445, "end": 476, "key": "sample:jad_paddy_docs:000007:13:1:1", "source": "gold", "luna_reason": null}, {"text": "Eurostat data", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 688, "end": 701, "key": "sample:jad_paddy_docs:000007:13:1:2", "source": "gold", "luna_reason": null}]}
 {"text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n10. **While the situation remains fluid, the recent reduction in armed conflict may facilitate**\n**substantial population movement.** About 1.3 million people have returned from displacement within or\noutside South Sudan since 2016. Of these, 644,174 returned in the short period between the signing of\nthe revitalized peace agreement in September 2018 until June 2019. <sup>26</sup> [^26: IOM DTM, Round 6 (op cit.).] The largest number of returns were\nto Jonglei (191,052), Upper Nile (164,068), and Western Bahr Ghazal (162,770). <sup>27</sup> [^27: Ibid.] These figures indicate\nan accelerating pace of return since the agreement was signed. According to recent intention surveys by\nboth the United Nations High Commission for Refugees and IOM, the main pull factors for return are\nimproved security, family reunification, access to basic services, and livelihood opportunities. About 30\npercent of refugees in neighboring countries consider returning, with IDPs being slightly more willing to\nreturn over the next 12 months. Yet, illegal land occupations remain an issue for the displaced, who\nsometimes will illegally occupy land in place of their own inaccessible properties during return processes.\nIntercommunal conflict continues to create new displacement in locations such as Unity, Warrap, Lakes,\nWestern Bahr-el-Ghazal, Central Equatoria, and Jonglei. <sup>28</sup> [^28: United Nations Mission in South Sudan (UNMISS) (August 2019) ( _Mimeo_ ).] Such factors created at least 167,979 new\ndisplacements in 2019, for instance. <sup>29</sup> [^29: UNOCHA Humanitarian Needs Overview, p.13 and IOM DTM, p.4] Up until 2019, 67 percent of displacements were estimated to have\nbeen driven by", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000058", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "IOM DTM, Round 6", "probe_tag": "keep", "probe_score": 0.9010196924209595, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 493, "end": 509, "key": "jdc_operational:000058:6:0:0", "source": "camp2", "luna_reason": "Named IOM displacement dataset cited for return figures.", "usage_type": "evidential", "specificity": "named"}, {"text": "intention surveys", "probe_tag": "keep", "probe_score": 0.9156019687652588, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 769, "end": 786, "key": "jdc_operational:000058:6:0:1", "source": "camp2", "luna_reason": "Named organizations’ intention surveys support reported return preferences and pull factors.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "36. **Business environment.** Jordan has a very poor track record of implementing business climate\nreforms.This is reflected in poor performance in Doing Business measures such as distance to the frontier\nand the World Economic Forum Competitiveness Index. The reasons for this poor performance relate to a\nlack of systematic processes to identify and implement reforms. Often, reforms are donor driven rather than\ndeveloped organically and, as a result, there is very little buy-in from stakeholders and poor implementation\nof regulations. Processes to ensure implementation of reforms are also weak. **Businesses face a**\n**constraining regulatory environment in Jordan, limiting the potential for formal entrepreneurship**\n**and job creation, including home-based enterprises** . The objective behind the proposed reforms is to\ncreate momentum and address regulatory areas that are important impediments to business growth.\n\n\n37. **This Program aims to institutionalize a systematic ‘home-grown’ process that will improve**\n**the business climate.** This includes (a) establishment of a deliberative and consultative process that\nprovides a menu of reforms; (b) predictability measures to ensure any new reforms are subject to a public\nnotice and consultation process; (c) development of a measurement system to assess implementation\nprogress; and (d) articulation of clear targets. The menu may contain reforms identified at the start of\nimplementation of the PforR as well as those identified through a consultative process during the Program\nlifetime.\n\n\n38. **In approaching the investment climate area, a multipronged approach has been developed.**\n\n\n    - The first prong addresses the medium- to long-term challenge of developing a predictable,\nsystematic approach to regulatory reform. The actions will be identified in consultation with\nthe private sector. A measurement system and a baseline will be put in place.\n\n\n    - The second prong aims to provide immediate impetus to implementing reform by focusing on\none regulatory area highly relevant to the business environment that can", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "World Economic Forum Competitiveness Index", "probe_tag": "keep", "probe_score": 0.9391920566558838, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 213, "end": 255, "key": "jdc_operational:000045:20:0:0", "source": "camp2", "luna_reason": "Named index used to evidence Jordan’s poor business environment performance", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "sup>, in contrast with the UN Broadband Commission’s target of 2 percent,\nmaking it prohibitively expensive for many Ugandans. Based on a survey by Research ICT Africa in 2018 <sup>34</sup>,\nInternet use among individuals earning more than US$ 1,000 per month is very high (almost 100 percent),\nbut it drops significantly in lower income brackets: among people earning less than US$ 100 per month,\nonly 11 percent use the Internet <sup>35</sup> . Affordability of mobile devices also appears to be a key barrier: 89\npercent of respondents of a NITA-U survey who do not own a mobile phone cite its cost as the main\nbarrier. <sup>36</sup>\n\n\n**10.** **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\nnetworks (2G), mobile broadband (3G and 4G) geographic coverage is only at 50 percent, with sharp\nregional disparities, particularly between the Northern and Western regions (which host most refugees)\nand the Central region. <sup>37</sup> For instance, the geographic coverage for mobile telephony is still low at 44\npercent as of 2018. <sup>38</sup> As a result of limited broadband access, the use of the Internet by enterprises and\nthe public sector remains very low. The quality of service also remains problematic: according to Ookla <sup>39</sup>,\nmobile download speeds in Uganda ranked only 115 <sup>th</sup> in the world (June 2019).\n\n\n**11.** **The situation among the refugee population is even more dire.** To-date, 68", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000033", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NITA-U survey", "probe_tag": "keep", "probe_score": 0.9617089033126831, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 544, "end": 557, "key": "jdc_operational:000033:6:1:0", "source": "camp2", "luna_reason": "Survey provides the cited 89-percent finding on mobile-phone affordability.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nUganda Electricity Access Scale-up Project (EASP) (P166685)\n\n\nproviding Tier 1 level access and above. The Uganda Solar Energy Association (USEA) reports over 210 solar\ncompanies operating in the Ugandan market as at end-December 2020, with most sales coming from a few\ninternational companies (for example, Fenix, M-Kopa, Solar Today, Village Power <sup>8</sup> [^8: USEA, Uganda Solar Market Report. Annual Sales and Impact Data. January-December 2019; GOGLA Global Off-Grid Solar\nMarket Reports. Sales and Impact Data for H1 2020.] ). These companies sold over\n482,100 off-grid solar products in 2019 and 128,242 off-grid solar products in the first half of 2019, positioning\nUganda as the third largest market in East Africa behind Kenya and Ethiopia.\n\n11. **About 58 percent of the population live without electricity.** The main access deficit is exhibited in rural\nareas, where 80 percent of the population resides and less than 40 percent has access to electricity. As reported\nin the Poverty Maps of Uganda Technical Report (World Bank, November 2019), the districts with the highest\naccess deficits below 10 percent, also correspond to the poorest ones, as visualized in the maps in figure 2. At the\nnational level, Uganda has one of the lowest electricity consumptions per capita in the world, estimated at an\naverage of 80 kWh per year in 2017, which is far below its peers (for example Kenya at 155 kWh per year, Ghana\nat 300 kWh per year). Such trends contribute to Uganda’s “adaptation deficit”, which limits the opportunity of\ncommunities to be resilient to external shocks, including those caused by disease or climate change.\n\n12. **The outcomes in clean cooking are even more dire with about 95 percent of Ugandans using solid**\n**biomass fuels for their meals** . The SDG7 tracking report <sup>9</sup> identified Uganda as one", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000040", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "GOGLA Global Off-Grid Solar\nMarket Reports", "probe_tag": "keep", "probe_score": 0.9066358208656311, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 474, "end": 516, "key": "jdc_operational:000040:6:0:0", "source": "camp2", "luna_reason": "Named market reports provide sales and impact data cited for product sales.", "usage_type": "evidential", "specificity": "named"}, {"text": "Poverty Maps of Uganda", "probe_tag": "keep", "probe_score": 0.9015596508979797, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1012, "end": 1034, "key": "jdc_operational:000040:6:0:1", "source": "camp2", "luna_reason": "Named technical report cited as evidence for district poverty and access-deficit findings.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\nsecondary teachers indicates that they do not have sufficient content knowledge while other studies have shown\nthey do not have sufficient pedagogical skills to teach. The learning assessment found that only 66 percent of\nteachers were proficient in English, 70 percent in mathematics and 17 percent in biology. Teacher training and\ncontinuous professional development is inadequate.\n\n\n22. **The combination of issues discussed above leads to an overall low performance of the education system**\n**including poor learning outcomes.** Results of the national assessment of progress in education (NAPE) conducted\nsince 2008 targeting Senior Two (S2) show that student learning in math, biology and English is on a declining\ntrend. Further analysis of these data indicate that differentials also persist across gender especially in biology and\nmath and across urban and rural schools. The persistent decline in performance points to an urgent need to\naddress the quality of education at this level. An analysis of Uganda Certificate of Education (UCE) results for Olevel in 2015 and in 2016 showed over 52 percent and 58 percent, respectively, of the candidates failed to pass in\nat least division 3 and therefore have dim prospects for further education and employment. Students perform\nworst in the science subjects where approximately half of those who sit do not pass mathematics, physics,\nchemistry, and biology. The performance at the Uganda Advance Certificate of Education (UACE) A-level is slightly\nbetter given that only the best performing O-level students proceed to A-level. This not only weakens the\nfoundation for further learning, but also undermines the country’s potential to tackle poverty.\n\n23. **The MoES is in the process of preparing the new Education Strategic Plan for 2020-2025.** The Plan will\nbe focused on resolving key issues in the education sector and will target improvements in learning outcomes.\nThe Plan is being developed in an inclusive manner with participation of", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "national assessment of progress in education", "probe_tag": "keep", "probe_score": 0.9272812604904175, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 625, "end": 669, "key": "jdc_operational:000018:20:0:0", "source": "camp2", "luna_reason": "Existing national assessment results show declining student learning outcomes.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " pedagogical training at all.\n\n\n13. There are several proximate causes that help to explain these results.\n\n\n  - **The school network is not fully accessible.** Among children enrolled in public or community schools, 20 percent\nare one or more kilometers from the school; 5 percent are three or more kilometers distant. Roughly 3 percent\nof children who drop-out cite distance as the key factor. In addition, based on the 2019 administrative data, only\n60 percent of primary schools were full cycle, the remaining were incomplete.\n\n  - **Classrooms are overcrowded, underequipped and in poor condition** . The overall pupil-teacher ratio was 55:1 in\n2020, ranging from 33 in Borkou to 95 in Kanem; and was generally much higher in rural areas (59:1) than urban\nareas (50:1). If one considers a pupil-teacher ratio of 50:1 as a ceiling beyond which pedagogical effectiveness is\nnot possible, then _over_ _half of all students are in classrooms where learning cannot take place. In fact, learning_\n_could only be effective in 4 provinces: Borkou, Ennedi Est, Ennedi Ouest and Mayo-Kebbi_ . On average, there are 55\npupils per classroom, ranging from 27 children per classroom in Borkou, to 79 children per classroom in Lac\nProvince. In classrooms with more than 55 students, that is in roughly half of the system’s classrooms, space\nconstraints would not allow one to fit in sufficient furniture, even if it were available. Combining table-benches\nand benches without table, there was only one seating place for every three students; if one considers only\navailable table-benches (which are the state norm for student furniture), then there was only one seating place\nfor every four students. Approximately one fifth of available furniture was in poor condition.\n\n  - **Learning environments are in poor physical state and often", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2019 administrative data", "probe_tag": "keep", "probe_score": 0.9317038059234619, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 422, "end": 446, "key": "jdc_operational:000009:6:1:0", "source": "camp2", "luna_reason": "Administrative data supports the reported share of primary schools that were full cycle.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " risks, and absorb financial shocks.\n\n\n[1] United Nations Higher Commissioner for Refugees (UNCHR) estimates there are approximately 655,496 Syrian\nrefugees in Jordan as of January 2017.\n\n\n[2] The World Bank, Jordan Economic Monitor, Fall 2016.\n\n\n[3] Average for the first three quarters of 2016. Jordan Department of Statistics.\n\n\n[4] IMF Working Paper WP/15/22, “Identifying Constraints to Financial Inclusion and Their Impact on GDP and\nInequality: A Structural Framework for Policy”, Era Dabla-Norris, Yan Ji, Robert Townsend, and D. Filiz Unsal. January\n2015, http://www.imf.org/external/pubs/ft/wp/2015/wp1522.pdf. - See more at:\nhttp://mastercardcenter.org/insights/imf-mit-study-shows-financial-inclusion-drives-economicgrowth/#sthash.r5T59cZ1.dpuf\n\n\nSectoral and Institutional Context\n**Existing datasets on financial inclusion suggest that there is a great potential to deepen financial inclusion in Jordan:**\n\n\n   - **With only one-fourth of adults having a bank account, Jordan is lagging behind its peers.** The recent Findex\n\nfigures for 2014 estimate that only 24.6 percent of the population (15 years and above) have formal bank\naccounts, i.e. 13 percentage points below countries with similar GDP per capita; and contrary to most countries\nin the developing world, this share has been stagnant since 2011.\n\n   - **Jordan lags behind other countries in terms of access to credit from formal financial institutions.** Only 14\n\npercent of the adult population reported that they have borrowed from a financial institution (World Bank\nGlobal Findex).\n\n\nApr 05, 2017 Page 3 of 11", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 2, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Findex\n\nfigures", "probe_tag": "keep", "probe_score": 0.9159215688705444, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1032, "end": 1047, "key": "jdc_operational:000013:2:1:0", "source": "camp2", "luna_reason": "Findex figures provide the cited 2014 bank-account estimate.", "usage_type": "evidential", "specificity": "named"}, {"text": "Findex", "probe_tag": "confusion", "probe_score": 0.8359279632568359, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1555, "end": 1561, "key": "jdc_operational:000013:2:1:1", "source": "camp2", "luna_reason": "World Bank Global Findex provides the cited borrowing statistic.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\n60. **Subcomponent 4A: Project management support for high-quality implementation.** This subcomponent will\nfinance the Project Implementation Teams (PITs) at the MGLSD and the PSFU. it will finance capacity building activities,\nincluding (a) of the national, district, subcounty, parish, refugee settlement stakeholders and implementation support\nteams. It will finance the development of key partnerships including of quarterly review meetings for all stakeholders\ninvolved in the project at the regional and district levels. The project as part of its Monitoring and Evaluation (M&E)\nactivities will design and develop an MIS that collects and stores detailed data from project applicants during the\nregistration process (i.e.,, before beneficiaries have accessed any project-financed activities). As indicated in component\n1, the MIS is expected to assign a unique identifier to each registered applicant (GROW_ID) that will be shared with the\napplicant. The MIS will collect information from applicants during registration, such as (a) key contact information,\ngender, age, marital status, education status, refugee status, employment; (b) business level outcomes such as business\npartners, business age, monthly profits, number of employees; and (c) access to other programs and loans. The MIS\ndatabase will be updated as program applicants make use of specific components. The GROW_ID can be entered to\nupdate the database with any additional information on services received to ensure the applicant is only registered once.\nFor example, dates of business trainings, service provider, or amount of funds will all be entered into the MIS. This\ndatabase will help support operations through feedback loops as it can track who is accessing which services in real time.\nThe MIS will also be important in being able to establish a sample of study participants to draw on for an impact\nevaluation", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MIS\ndatabase", "probe_tag": "confusion", "probe_score": 0.5231879353523254, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1413, "end": 1425, "key": "jdc_operational:000025:30:0:0", "source": "camp2", "luna_reason": "The project will develop and update this MIS database with applicant data.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": " growth rate to reach $335\nbillion in 2024. <sup>11</sup> [^11: Business Process Outsourcing (BPO) Services Market Research Report - Global Forecast till 2024 by Market Research Future] Jordan enjoys a unique blend of qualities, making it an attractive destination for BPO/ITO\nservices. Global giants such as Cisco, Expedia, Amazon, Microsoft, Webhelp, Teleperformance, and Oracle\nhave already established operations in Jordan. Local BPO/ITO players such as Aspire, Crystel, and Extensya are\nexperiencing organic growth, <sup>12</sup> [^12: Aspire is specialized in ITO services and targets the US market (retains 275 Jordanian employees), Extensya provides contact center support\nto Vodaphone, Saudi Airline, MBC, and others (retains 1700 Jordanian employees in Amman and Irbid), and Crystal provides contact center\nsupport to local and regional clients (retains 1000 Jordanian employees in Amman and Karak).] targeting global and regional markets. Some of the critical success factors that\nhelp position Jordan as an ideal BPO/ITO destination include availability of affordable technical and nontechnical talents, neutral Arabic speaking dialect, geopolitical stability, good infrastructure, liberalized\ntelecom sector, proximity to key target markets in GCC, and government support. However, critical gaps\nremain such as a mismatch between the workforce and job market requirements, limited domestic market\nand access to export opportunities, and limited access to funding necessary for business development and\nexpansion.\n\n**9.** **Although Jordan is well-known for its growing number of university graduates in computer science,**\n**math and engineering fields, it remains ill-equipped with specialized skills to thrive in a digital economy.**\nThe findings of a 2016 Labor Market Study conducted by the Jordanian ICT Association, Intaj revealed five core\nweaknesses underlying the skills mismatch: (i) an outdated university curriculum, (ii) lack of soft skills, (iii) lack\nof awareness and experience with global technology trends, (iv)", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000044", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2016 Labor Market Study", "probe_tag": "confusion", "probe_score": 0.8863385915756226, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1767, "end": 1790, "key": "jdc_operational:000044:4:1:0", "source": "camp2", "luna_reason": "Study findings identify five core weaknesses underlying the skills mismatch.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda (P176747)\n\n\n\n|Col1|including childcare and<br>those community and<br>household members.|Col3|Col4|the infrastructure<br>facilities.|Col6|\n|---|---|---|---|---|---|\n|Women beneficiaries (percentage)|<br>|||<br>||\n|Women in RHD||||||\n|Refugee women||||<br>||\n|Value of credit provided to women<br>enterprises (Amount)|This indicator measures the<br>value of credit provided by<br>the PFIs under the project,<br>disaggregated by refugee<br>status, district, age, and<br>disability status.|Continuous.<br>|PFI data.<br>|The PFIs will maintain<br>databases of the value<br>of the credit disbursed,<br>disaggregated by<br>refugee status, district,<br>age, and disability<br>status.<br>|The MGLSD to collect<br>the data from the PFIs<br>each month, and<br>compile and report it.<br>|\n|Women enterprises in RHDs||||<br>||\n|Refugee-owned enterprises||<br>||||\n|Beneficiaries of job-focused interventions||Enterprise<br>baseline<br>survey,<br>annual<br>surveys from<br>year 2.<br>|Surveys of<br>enterprises.<br>|This indicator measures<br>", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 50, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PFI data", "probe_tag": "confusion", "probe_score": 0.15660575032234192, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 599, "end": 607, "key": "jdc_operational:000025:50:0:0", "source": "camp2", "luna_reason": "Span is a data-source cell within a project indicator table.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "data from the PFIs", "probe_tag": "confusion", "probe_score": 0.5401945114135742, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 805, "end": 823, "key": "jdc_operational:000025:50:0:1", "source": "camp2", "luna_reason": "MGLSD plans to collect and compile this project monitoring data monthly.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\ngovernment subsidies and grew to represent about 59 percent of the schools offering secondary education and\nslightly above half of the total students enrolled. Still, the Uganda secondary enrollment rate stands at a level\nwhich is significantly below that of regional comparators.\n\n7. **The issue of insufficient resources is compounded by an array of inefficiencies that undermine the**\n**performance and productivity of the entire system.** These include, inter alia:\n\n\na) **An insufficient number and inadequate distribution of free of charge public secondary schools**\n\nthroughout Uganda to address the existing and growing demand generated by the projected population\ngrowth, the rise in primary school completion, and the recent significant inflow of refugees.\n\n\nb) **Low internal efficiency due to very low survival rate throughout the education cycles** . In 2017, the\n\nprimary survival rate stood at 56 percent, which is considerably below the primary survival rate in Kenya\nat close to 100 percent, Ethiopia at 72 percent, and Rwanda at 68 percent (Figure 3). <sup>7</sup> [^7: End of primary education here refers to 6th grade for the ease of cross-country comparison.] As a result of this\nlow overall productivity, it takes almost twice as many years of schooling than normal to produce a\ngraduate in primary and secondary education. For instance, on average it took 12.6 years for a primary\nschool student to graduate the cycle in 2013 (primary cycle in Uganda is seven years), which is only\nmarginally better than the 14 years it took in 2008. The inefficiencies persist through secondary school,\nlargely as a consequence of low volumes of students progressing through primary grades and later to\nlower secondary. As a result, the cost of service provision at the secondary level in 2013 was 2.3 times\nhigher than what it should have been. <sup>8</sup>\n\nFigure 3: Survival Rates", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "primary survival rate", "probe_tag": "confusion", "probe_score": 0.22408068180084229, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 954, "end": 975, "key": "jdc_operational:000018:13:0:0", "source": "camp2", "luna_reason": "Bare rate phrase without a named or generic data source.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"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": " inequalities persist. School enrollment and retention rates\namong girls in the refugees hosting districts are exceptionally low, a result of their domestic\nresponsibilities, child marriage, teenage pregnancy, long distances to schools, and lack of sanitation\n\n\n9 This index reflects gender-based inequalities in three dimensions – reproductive health, empowerment, and economic\n[activity. http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/UGA.pdf.](http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/UGA.pdf)\n10 Uganda Demographic and Health Survey (2016).\n11 Uganda Violence Against Children Survey (2015).\n12 UNICEF: Situation Analysis of Children in Uganda, 2015\n13 Government of Uganda: Violence Against Children Survey (VACS) Report, 2018\n14 UDHS, 2016\n15 UNHCR, 2016, 5-Year Interagency SGBV Strategy, Uganda\n_16_ <u>http://ug.one.un.org/sites/default/files/documents/UNAC-</u>\n<u>[Northern%20Uganda%20and%20West%20Nile%20Humanitarian%20and%20Development%20Report%20-January-](http://ug.one.un.org/sites/default/files/documents/UNAC-Northern%20Uganda%20and%20West%20Nile%20Humanitarian%20and%20Development%20Report%20-January-February%202018.pdf)</u>\n<u>[February%202018.pdf](http://ug.one.un.org/sites/default/files/documents/UNAC-Northern%20Uganda%20and%20West%20N", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000001", "page": 5, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Uganda Demographic and Health Survey", "probe_tag": "confusion", "probe_score": 0.8688366413116455, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 534, "end": 570, "key": "jdc_operational:000001:5:2:0", "source": "camp2", "luna_reason": "Named survey cited as evidence for preceding education and gender findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "Uganda Violence Against Children Survey", "probe_tag": "confusion", "probe_score": 0.8201774954795837, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 582, "end": 621, "key": "jdc_operational:000001:5:2:1", "source": "camp2", "luna_reason": "Named survey cited as an existing source in the reference list.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "**The World Bank**\nEnhancing Community Resilience and Local Governance Project Phase II (P177093)\n\n\n**I.** **STRATEGIC CONTEXT**\n\n\n**A. Country Context**\n\n\n1. **South Sudan has been beset by decades of armed conflicts and ranks as one of the least**\n**developed countries in the world today.** Southern Sudan, as the region was called before independence,\nhas been marred by conflict since 1955, just a year before Sudan attained its independence from British\ncolonial rule. The region experienced systematic marginalization and underdevelopment under both\nBritish and Sudanese rule, inhibiting it from developing its physical and human capital. Consequently, at\nits independence in July 2011, South Sudan ranked near the bottom of global development indicators,\nwith little infrastructure, basic services provided almost entirely through humanitarian aid, and an\neconomy completely dependent on oil.\n\n\n2. **Renewed civil conflict broke out in December 2013 and has only recently subsided** with the\nformation of the Transitional Government of National Unity in February 2020, pursuant to the terms of\nthe September 2018 Revitalized Agreement on the Resolution of the Conflict in South Sudan (R-ARCSS). <sup>1</sup>\nPeace remains fragile, and implementation of several key provisions of the R-ARCSS—such as the\nunification of armed forces of different factions, disarmament, demobilization and reintegration of excombatants, and transitional justice, remains stalled. While the national-level ceasefire is largely holding,\nviolence in South Sudan remains high. Inter-communal violence, which often has links to national actors\nand dynamics, is widespread. <sup>2</sup> [^2: World Bank. 2021. _South Sudan Risk and Resilience Assessment_ .] <mark>After decades of insecurity, ab</mark> out 7.2 million people (60 percent of the\npopulation) are in ‘Crisis’ (IPC <sup>3</sup> Phase", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "global development indicators", "probe_tag": "confusion", "probe_score": 0.7986257076263428, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 732, "end": 761, "key": "jdc_operational:000028:13:0:0", "source": "camp2", "luna_reason": "Indicators support the concrete claim that South Sudan ranked near the global bottom.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "**The World Bank**\nRoads and Employment Project (P160223)\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|municipalities consulted on<br>road priorities||||||meetings from/to union of<br>municipalities.<br>||\n|<br>Description:This  indicators measure consultations with local authorities, and indirectly with the public, on their road rehabilitation priorities.|<br>Description:This  indicators measure consultations with local authorities, and indirectly with the public, on their road rehabilitation priorities.|<br>Description:This  indicators measure consultations with local authorities, and indirectly with the public, on their road rehabilitation priorities.|<br>Description:This  indicators measure consultations with local authorities, and indirectly with the public, on their road rehabilitation priorities.|<br>Description:This  indicators measure consultations with local authorities, and indirectly with the public, on their road rehabilitation priorities.|<br>Description:This  indicators measure consultations with local authorities, and indirectly with ", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 51, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Roads and Employment Project", "probe_tag": "confusion", "probe_score": 0.08959637582302094, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 47, "key": "jdc_operational:000008:51:0:0", "source": "camp2", "luna_reason": "Project title, not a data resource or data-use mention.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": " evaluation\nof NDP-1 in Uganda, March 2019. State of Uganda Population Report 2018.\n4 World Bank World Development Indicators (2017).\n5 Uganda National Household Survey, Uganda Bureau of Statistics, 2017.\n6 World Bank World Development Indicators (2013).\n7 Uganda’s economy slowed from an average of 7% annual GDP growth in the early 2000s to 4.5% in the 5 years leading up to 2017.\n8 Uganda: Driving inclusive socio-economic progress through mobile-enabled digital transformation, GSMA, 2019.\n9 Ibid.\n\n\nJul 22, 2019 Page 3 of 28", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000063", "page": 2, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "State of Uganda Population Report 2018", "probe_tag": "keep", "probe_score": 0.9324547052383423, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 44, "end": 82, "key": "jdc_operational:000063:2:2:0", "source": "camp2", "luna_reason": "Named existing population report cited as a source.", "usage_type": "declaration", "specificity": "named"}, {"text": "World Bank World Development Indicators", "probe_tag": "confusion", "probe_score": 0.889045000076294, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 86, "end": 125, "key": "jdc_operational:000063:2:2:1", "source": "camp2", "luna_reason": "Named World Bank indicator dataset cited as an existing statistical source.", "usage_type": "declaration", "specificity": "named"}]}
-{"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": "**The World Bank**\nPromoting Financial Inclusion Policies and Regulations in Jordan ( P163719 )\n\n\nand evaluation studies.\n\n\nThis component will be conducted in close coordination with GIZ.\n\n\n**Component 2: Developing a country-specific program of peer-learning and knowledge sharing (US$400,000).**\n\n\n   - The project through partnership with AFI, AMF and WB will facilitate full engagement and peer learning among\n\nregulators and policymakers in Jordan by involving them in the broad array of services and offerings, with a\nspecial focus on the policy areas of priority that have been identified by the country based on the Financial\nInclusion Market Diagnostic results. Specifically, this component will finance the following sub-components:\n\n\n**Sub-component 2.1:** The Jordanian AFI membership during project duration will be funded under this\ncomponent and will engage Jordan in the following member services, which are designed to address the\nnational objectives of policymakers and regulators and will be modified to also address the national objectives\nof Jordan:\n\n\n   - Working Groups: These groups of 15-40 member institutions focus on specific policy areas, including: Digital\n\nFinancial Services; Consumer Protection and Market Conduct; Financial Inclusion Strategy; Financial Inclusion\nData; and SME Finance. The working groups are chaired by members and have led to important reforms in\nmany of the countries involved and facilitated the production of policy guidelines and tools that have practical\nrelevance.\n\n   - Participation in AFI's Global Policy Forum (GPF): The GPF is regarded as the leading global knowledge exchange\n\nevent on financial inclusion policymaking. Most sessions are hosted by members who share ‘on the ground’\nexperiences.\n\n   - Peer Learning Initiative with Standard Setting Bodies (SSBs): This will provide opportunities for Jordan to\n\nparticipate in shaping and influencing the global agenda through knowledge sharing with SSBs, which can have\na significant impact on how the global financial system helps or hinders financial inclusion.\n\n   - **Sub-component 2.2:** Organizing", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Financial\nInclusion Market Diagnostic results", "probe_tag": "confusion", "probe_score": 0.39546725153923035, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 625, "end": 670, "key": "jdc_operational:000013:7:0:0", "source": "camp2", "luna_reason": "Diagnostic results inform identification of priority policy areas.", "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": "**The World Bank**\nEnhancing Community Resilience and Local Governance Project Phase II (P177093)\n\n\nmembers as mechanics, and trained the water user committees to collect user fees to pay for spare parts\nand mechanics’ services. The project team participates regularly in relevant cluster working groups such\nas protection, WASH, camp coordination and camp management, community communication, and\nengagement to follow the ongoing dialogue on external assistance. The team also engages regularly with\nUNOCHA, United Nations Mission in South Sudan, relevant donors, and CSOs. Through these engagements,\nthe project will continue to coordinate with other programs.\n\n\n67. **The proposed project will coordinate closely with and complement other World Bank-financed**\n**projects.** ECRP-II will have a shared PMU with the planned PFMIS Project. Further, the two projects will\nwork in a complementary manner to lay the foundation for transparent and accountable\nintergovernmental fiscal transfers for local service delivery. ECPR-II and the ongoing South Sudan Safety\nNet Project (SSSNP) (P169274) follow the same community institutional structure of BDCs and PDCs, and\nwhere target sites overlap, the two projects will use the same community structures. ECRP-II and the\nongoing Provision of Essential Health Services Project ( <mark>P168926)</mark> will coordinate so that where ECRP-II\nbuilds/rehabilitates health clinics, the Health Project can provide the software.\n\n\n68. **ECRP-II will continue to coordinate closely with development and humanitarian agencies on**\n**DRM.** As part of the 2020 Flood Damage Needs Assessment, <sup>71</sup> [^71: World Bank/GFDRR. 2021 _. South Sudan Floods 2020. Remote Flood Damage and Needs Assessment,_ September 2021] the project team coordinated with key\nagencies (for example, FAO, World Food Programme, REACH Initiative, IOM, and UNHCR) and donors (for\nexample, GIZ, Swiss Agency for Development and Cooperation, Dutch Embassy, USAID) to obtain data", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 38, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2020 Flood Damage Needs Assessment", "probe_tag": "confusion", "probe_score": 0.8864630460739136, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1589, "end": 1623, "key": "jdc_operational:000028:38:0:0", "source": "camp2", "luna_reason": "Named external assessment cited as the basis for coordinating data collection.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "**The World Bank**\nLebanon Emergency Health Project (P163476)\n\n\n**VII. RESULTS FRAMEWORK AND MONITORING**\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n||**Name:**Primary care<br>beneficiaries||Number|280000.00|715000.00|Bi-annual<br>|HIS<br>|PMU<br>|PMU<br>|\n||Poor Lebanese||Number|150000.00|340000.00|||||\n|||||||||||\n||<br>Displaced Syrians||Number|130000.00|375000.00|||||\n||Description:Number of beneficiaries who will have access to the essential healthcare services package.|Description:Number of beneficiaries who will have access to the essential healthcare services package.|Description:Number of beneficiaries who will have access to the essential healthcare services package.|Description:Number of beneficiaries who will have access to the essential healthcare services package.|Description:Number of beneficiaries who will have access to the essential healthcare services package.|Description:Number of beneficiaries who will have access to the essential healthcare services package.|Description:Number of beneficiaries who will have access to the essential healthcare services package.|Description:Number of beneficiaries who will have access to the essential healthcare services package.||\n\n\n|Col1|Name: % female of total<br>beneficiaries|Col", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 42, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Lebanon Emergency Health Project", "probe_tag": "confusion", "probe_score": 0.09379251301288605, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 51, "key": "jdc_operational:000032:42:0:0", "source": "camp2", "luna_reason": "Project title, not an existing data resource or data-use mention.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": "**The World Bank**\nChad Rural Mobility and Connectivity Project (P164747)\n\n\n**ANNEX 3: Climate Change Impact Study**\n\n\nRural Mobility and Connectivity Project in Chad:\nAssessing the Vulnerability to and Cost of Climate Change Impacts on a Road Rehabilitation Project\n\nusing IPSS\n\n\n**Overview and Background**\n\n\n1. The assessment of this road rehabilitation project included in its evaluation an engineering-based\nanalysis tool called the IPSS <sup>12</sup> to further understand the vulnerabilities of the road segments to the impacts\nof climate change. IPSS, developed by researchers out of the University of Colorado, has been used to\nidentify vulnerabilities in the road under study, to help better manage the risk associated with climate\nchange and to help better inform specific adaptation investment options for the road.\n\n\n2. IPSS utilizes stressor-response engineering data coupled with IPCC-approved climate change data\nto estimate the potential impacts from specific climate stressors, in this case flooding and precipitation.\nThe tool is then used to assess the cost of reactively addressing the impacts of climate change (fixing\ndamages) versus proactively mitigating the impacts of climate change (through upgrades in the\nconstruction process of the roads). The tool will shed light on the cost incurred by changing climate in\nterms of keeping the road maintained and will inform decisions regarding investment strategy. IPSS was\nrun for the first phase (75 km) of the Chad Rural Mobility and Connectivity Project and will be utilized to\nanalyze the remaining 325 km stretch of road as well. It is important to note that the analysis does not\nsupport any one of the climate models or support that any outcome is more likely than another. The\nresults displayed in the following paragraph show the predictions of the median model, as noted.\n\n\n3. The climate-induced hazards threatening the project include flooding and change in precipitation.\nThese pose a threat to mobility, accessibility, and thus economic growth. Flooding has the potential to\nin", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 58, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "stressor-response engineering data", "probe_tag": "confusion", "probe_score": 0.2518046200275421, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 847, "end": 881, "key": "jdc_operational:000048:58:0:0", "source": "camp2", "luna_reason": "Existing engineering data are used to estimate climate-stressor impacts.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "IPCC-approved climate change data", "probe_tag": "confusion", "probe_score": 0.8431960344314575, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 895, "end": 928, "key": "jdc_operational:000048:58:0:1", "source": "camp2", "luna_reason": "IPCC-approved data are used by IPSS to estimate climate impacts.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nUganda COVID-19 Education Response Project (P174033)\n\n\n\n|Col1|learning materials.<br>Disaggregated by gender|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|% of children supported with<br>distance/home-based learning<br>interventions|% of children supported<br>with distance/home-based<br>learning interventions|once<br>|Project<br>implementati<br>on<br>documents<br>|Data will be collected<br>by MoES and District<br>Educaiton Officers.<br>|MoES, PCU<br>|\n|PDO Indicator 3. Number of children<br>previously enrolled in grant-supported<br>schools who return to school once the<br>school system is reopened.|Number of children<br>previously enrolled in grant-<br>supported schools who<br>return to school once the<br>school system is reopened|Annual<br>|EMIS Data<br>|EMIS data at school<br>level.<br> <br>|Uganda Beareau of<br>Statistics, MoES<br>|\n|% children previously enrolled in<br>grant-supported schools who return<br>to school once the school system is<br>reopened<br>|% of children previously<br>enrolled in grant-supported<br>schools who return to<br>school once the school<br>system is reopened|Annual<br>|The<br>enrollment<br>will be<br>monitored<br>through the<br>EMIS data.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 35, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "EMIS Data", "probe_tag": "confusion", "probe_score": 0.11649195104837418, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 773, "end": 782, "key": "jdc_operational:000034:35:0:0", "source": "camp2", "luna_reason": "EMIS monitoring is planned for future project indicator verification.", "drop_reason": "promissory", "specificity": "named"}]}
-{"text": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n|Location|Male (%)|Female (%)|All (%)|\n|---|---|---|---|\n|<br>Poorer<br>|<br>0.22<br>|<br>0.01<br>|<br>0.18<br>|\n|<br>Middle<br>|<br>0.54<br>|<br>0.05<br>|<br>0.46<br>|\n|<br>Richer<br>|<br>1.52<br>|<br>1.52<br>|<br>1.52<br>|\n|<br>Richest<br>|<br>40.86<br>|<br>29.79|<br>38.50|\n\n\n\n3. **Access to electricity for cooking.** Most households in Chad rely on wood for cooking (87.8\npercent) followed by charcoal (6.5 percent of all households). Only 2.9 percent of households use\nelectricity, LPG, or natural gas as their main fuel for cooking. About 3.1 percent of male-headed\nhouseholds rely on either of these fuels compared to 2.1 percent of female-headed households.\n\n4. **Income and productive asset ownership.** Women see their productive activities constrained due\nto high fertility and limited agency and access to resources. Chad has one of the highest fertility rates in\nthe world (5.8 births per women), which severely affects women’s capacity to participate in the labor\nmarket. <sup>44</sup> Women also lack agency for personal decisions; only 23 percent of women were", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 77, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Chad Energy Access Scale Up Project", "probe_tag": "confusion", "probe_score": 0.8981017470359802, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 54, "key": "jdc_operational:000051:77:0:0", "source": "camp2", "luna_reason": "Names a project, not a data resource or evidence used in analysis.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n**23.** **Disbursements and Flow of Funds.** Funds will be channeled directly from the World Bank to the UN-Habitat\nbank account in US dollars outside Lebanon. UN-Habitat will submit withdrawal applications to the World Bank to\nrequest funds using the report-based disbursement method (i.e., based on IFRs for a six month expenditure\nprojection). The format and content of the IFRs is provided in the Disbursement and Financial Information Letter\n(DFIL). The amount of the advance will be based on a projection of six months expenditures. The disbursement\ncategories, allocations, and percentage of expenditures to be financed are shown in the table below.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Category|Amount of the Grant<br>Allocated (expressed in USD)|Percentage of Expenditures to be<br>Financed<br>(inclusive of Taxes)|\n|---|---|---|\n|(1) Goods, works, non-consulting<br>services, and consulting services<br>under Part 1 of the Project|8,275,520|100%|\n|(2)<br>Consulting<br>services,<br>non-<br>consulting services and CCI Grants<br>under Part 2 of the Project|1,951,857|100%|\n|(3) (a) Indirect Cost under Part 3 of<br>the project (5%)<br> <br>(3) (b) Direct Cost under Part 3 of the<br>Project|607,143<br> <br> <br> <br>1,915,480|100%|\n|**TOTAL AMOUNT**|", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 52, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "IFRs", "probe_tag": "confusion", "probe_score": 0.09230616688728333, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 408, "end": 412, "key": "jdc_operational:000012:52:0:0", "source": "camp2", "luna_reason": "Financial reports used for disbursement administration, not substantive data analysis.", "drop_reason": "bookkeeping", "specificity": "descriptive"}, {"text": "IFRs", "probe_tag": "drop", "probe_score": 0.026097137480974197, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 408, "end": 412, "key": "jdc_operational:000012:52:0:1", "source": "camp2", "luna_reason": "Interim financial reports used for project disbursement administration", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "include a section to report on the accountability of funds utilized and a section to access funds\nusing the report based method of disbursement. The reporting section of the IFRs should include\n(a) Statement of Sources and Uses of Funds; (b) Statement of Uses of Funds by Project\nActivity/Component; and (c) budgets compared to actual, and list of assets. The disbursement\nsection should include (a) Designated Account Activity Statement; (b) bank statements for DA\nand related bank reconciliation statements; (c) Summary Statement of DA expenditures for\ncontracts subject to prior review; and (d) Summary statement of DA expenditures not subject to\nprior review.\n\n\n25. **Designated Account:** CVDB will open a segregated DA at CBJ in US Dollars to cover\nthe Grant' shares of eligible expenditures. The Ceiling of the DA will be based on the forecast for\ntwo (2) quarters as provided in the quarterly IFR. CVDB will be responsible for submitting\nquarterly replenishing applications with appropriate supporting documentation.\n\n\n26. **Sub-Accounts:** Each participating municipality will be required to open a sub-account at\nCVDB for receiving the grant funds in local currency. The Grants will be provided annually to\nparticipating municipalities in two tranches: (i) the first tranche would be in the form of an\nadvance equal to 50 percent of the total annual allocated amount, and (ii) the second tranche\nwould be released only after submitting the progress reports and FM reports with bank\nreconciliations to CVDB for review and verification that funds were disbursed according to the\nsubsidiary agreements and positive list of expenditures.\n\n\n27. **E-Disbursement:** The World Bank has introduced e-disbursement for all projects in\nJordan. Under e-Disbursement, all transactions will be conducted and associated supporting\ndocuments and IFRs scanned and transmitted online through the World Bank’s Client", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000026", "page": 51, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "quarterly IFR", "probe_tag": "drop", "probe_score": 0.045932333916425705, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 891, "end": 904, "key": "jdc_operational:000026:51:0:0", "source": "camp2", "luna_reason": "Quarterly IFR is project financial reporting, merely functioning as bookkeeping documentation.", "drop_reason": "plays_role", "specificity": "vague"}]}
-{"text": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Sr.<br>No.|Description|Cost|Bank<br>financing|GoU<br>financing|\n|---|---|---|---|---|\n|14|Consultancy to study mobility patterns and barriers for<br>women in the refugee hosting districts and the design of<br>potential pilots for refugees to benefit from road upgrading|0.5|0.5|0|\n|15|Strengthen the skills in handling climate change and natural<br>disasters risks in refugee hosting areas, improve contingency<br>planning and the climate resilience of local communities, and<br>update of the Road Design Manuals and Specifications for<br>civil works to account for climate change parameters|0.5|0.5|0|\n|**Component 3: Road Safety**|**Component 3: Road Safety**|**2 **|**2 **|**0 **|\n|16|Completion of development and operationalization of a<br>Road Accident Database Management System|1|1|0|\n|17|Training and awareness campaigns in the Project area<br>(including a communication specialist)|1|1|0|\n|**Component 4: Contingent Emergency Response**|**Component 4: Contingent Emergency Response**|**0 **|**0 **|**0 **|\n\n\n61. **Financing Instrument.** The lending instrument for the Project is Investment Project Financing. The Project\nwill be funded by a grant from the IDA Window for Host Communities and Refugees and the National IDA.\n\n\n62. **Readiness for Implementation.** Steps have been", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Road Accident Database Management System", "probe_tag": "drop", "probe_score": 0.024172689765691757, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 855, "end": 895, "key": "jdc_operational:000050:31:0:0", "source": "camp2", "luna_reason": "Table activity entry, not evidence of data use.", "drop_reason": "table_artifact", "specificity": "named"}]}
+{"text": "**The World Bank**\nLebanon Electricity Transmission Project (P170769)\n\n\nDeposit inflows have decelerated sharply since 2011, and annual foreign direct investment (FDI)\ndecreased by an average of US$1 billion, increasing uncertainty on the economy's ability to meet its\nfinancing needs. The limited financing did not go into productive areas, resulting in sub-par\ninfrastructure which is not conducive to job creation and productivity, further perpetuating the cycle of\nlow growth. Lebanon’s quality in overall infrastructure ranks 130 out of 137 countries. <sup>3</sup> [^3: World Economic Forum, Global Competitiveness Index 2017-2018.]\n\n4. **Lebanon is a fragile country, with challenges further exacerbated by a large influx of**\n**refugees.** In addition to being a proxy for many international influences, the country also suffers from\nfrequent internal sectarian tensions which in the past have led to extended episodes of violence and\nconflicts along confessional lines. The security concern in the region has affected the tourism industry\non which the economy depends. Government institutions are captured by political parties, with informal\npower sharing that often results in frequent coalitions, parliamentary blocs, and national unity\ngovernment. The social contract is undermined by poor infrastructure and service delivery, particularly\nelectricity supply. On the other hand, Lebanon enjoys a high level of human capital as the quality of\n(private) education and health facilities is high. Most of Lebanon’s resilience has come from a strong\nprivate sector despite a challenging political environment. Since the Syrian crisis in 2011, Lebanon\nhas been hosting displaced Syrians with the number estimated at 1-1.5 million by 2015, which\nrepresents the largest concentration of refugees per capita in the world, in addition to the existing\n300,000 Palestinian refugees. The country, with large international aid, has managed to provide the\nrefugees with basic services, but this no doubt adds a tremendous pressure on the already weak public\nservice system, especially as the refugees tend to concentrate in already", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000010", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Global Competitiveness Index", "probe_tag": "keep", "probe_score": 0.9375889301300049, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 597, "end": 625, "key": "jdc_operational:000010:3:0:0", "source": "camp2", "luna_reason": "Named index cited as the source for Lebanon’s infrastructure ranking.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "> With a strong reliance on subsistence farming and pastoralism, rural\ncommunities are particularly affected by extreme weather events and natural disasters, including the\nrecent desert locust invasion. Historical records show a large year-to-year variability in precipitation, but\ndroughts have become more frequent and widespread since the 1960s. <sup>3</sup> The seasonality and intensity of\nthe rainy season are also changing, resulting in more frequent and extreme flooding in many parts of the\ncountry. More intense and variable weather events are predicted for the future. <sup>4</sup> The consequences of\nclimate volatility are intensifying intercommunal conflict over natural resources, ongoing population\ndisplacement, and worsening food insecurity. The 2019 exceptionally intense seasonal flood, with 900,000\n\n\n1 UNOCHA (United Nations Office for Coordination of Humanitarian Affairs). 2020. _Humanitarian Needs Overview 2020_, p. 3\n2 Germanwatch. 2019. _Global Climate Risk Index 2020_, p. 42.\n3 United States Agency for International Development (USAID) (2019 _), South Sudan Climate Vulnerability Profile_, p. 2.\n4 ThinkHazard (2019). South Sudan.\n\n\nJune 22, 2020 Page 3 of 23", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000058", "page": 2, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Historical records", "probe_tag": "keep", "probe_score": 0.9171906113624573, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 203, "end": 221, "key": "jdc_operational:000058:2:1:0", "source": "camp2", "luna_reason": "Existing historical records support the stated precipitation variability finding.", "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": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\nprofessional artists.\n\n\n**47.** The model results show that the project benefit-cost ratio (BCR) is expected to exceed the poverty rate, i.e., the\nmost natural alternative to compare with a uniform (random) cash distribution. <sup>49</sup> According to this model, the BCR is\n0.92. This outperforms by a factor of 3.7 the threshold of 25%, i.e., the poverty rate in Lebanon <sup>50</sup> . The proposed\napproach is therefore expected to reach vulnerable households more effectively, compared to a random distribution\nof cash to the poor.\n\n\n**48.** **Cultural and creative industries are key drivers of the creative economy and represent important sources of**\n**employment, economic growth, and innovation, thus contributing to city competitiveness and sustainability.** <sup>51</sup>\nAccording to the Cities, Culture and Creativity report, in 2013 the revenues of cultural and creative industries were\nestimated to be around $2.25 trillion, i.e., three percent of global GDP. <sup>52</sup> In 2015, it was estimated that CCI in Lebanon\ncontributed almost five percent to Lebanon’s GDP and 4.5 percent to national employment, with an average annual\ngrowth rate of over eight percent. <sup>53</sup> Approximately 20 percent of the economically active population (362,000 people)\nare estimated to be working in the sector, including both formal and informal professionals. <sup>54</sup> Many CCIs also generate\na large number of non-creative jobs. A preliminary calculation using UNESCO data suggests that overall for every\ncreative job in a CCI, 1.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 26, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNESCO data", "probe_tag": "keep", "probe_score": 0.9510562419891357, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1585, "end": 1596, "key": "jdc_operational:000012:26:0:0", "source": "camp2", "luna_reason": "UNESCO data supports a preliminary calculation about creative-sector employment.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " secondary schooling from households in underserved areas? When parents are asked in\nsurveys about the reasons why their children do not pursue their education beyond a certain level, the distance\nto school does not come up strongly, but this is deceptive because the effect of distance may be felt through\nhigher costs, and cost is often cited as a constraint for schooling. To measure the impact of the distance to schools\non enrollment and completion, regression analysis was conducted with national household surveys. Results are\nshown in Table 5.1. While effects are not always statistically significant, there is clear evidence that longer\ndistances to schools in terms of the time needed to reach schools leads to lower enrollment at the primary level,\nand lower completion rates at the junior secondary levels were effects are large (a coefficient of -0.16 suggests a\nnegative impact on the likelihood of completing of up to 16 percentage points versus the reference category of a\nschool located within 15 minutes of the community).\n\n**<u>Table 5.1: Marginal Impact of Time Needed to Reach Schools on Enrollment and Completion by Cycle</u>**\n\n\n\n<u>Starting</u>\nprimary\n\n\n\n<u>Complete primary</u>\n\nconditional\n<u>on starting primary</u>\n\n\n\n<u>Starting junior</u>\nsecondary conditional\n<u>on completing primary</u>\n\n\n\n<u>Completing junior</u>\nsecondary conditional\n\n\n\n<u>school</u> <u>on starting primary</u> <u>on completing primary</u> <u>on starting junior sec.</u>\n\n<u>Aged 9-12</u> <u>Aged 12-15</u> <u>Aged 15-18</u> <u>Aged 18-21</u>\nLess than 15 minutes <u>Reference</u> <u>Reference<", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 92, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "national household surveys", "probe_tag": "keep", "probe_score": 0.9387670159339905, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 494, "end": 520, "key": "jdc_operational:000018:92:1:0", "source": "camp2", "luna_reason": "Regression analysis used existing national household surveys to estimate enrollment impacts.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "_Procedures for preparing and approving RAP_\n\n54. _Project Screening_ . Once the subprojects are identified by unions or municipalities, the PMU\nwill obtain all permits/approvals related to the Project. Thereafter, they will cooperate with unions or\nmunicipalities to carry out social screening to determine whether or not the subprojects will result in\nany resettlement impact. The PMU will then decide on the need for the preparation of a Resettlement\nAction Plan (RAP) or an abbreviated RAP.\n\n55. _Socioeconomic and Inventory Survey_ . Following the identification of the subprojects that\nmay involve involuntary resettlement, the PMU in cooperation with unions and municipalities will\ncarry out a socio-economic study and census survey, in which baseline data within the subproject’s\ntarget areas is collected. This information shall include the PAPs and related household members or\ndependents, total land holdings, and affected assets. This information will be put in writing and shall\nbe used in determining the appropriate compensation and assistance for each affected\nindividual/household.\n\n56. _RAP preparation, review and approval._ Once the census survey is completed, the PMU will\nwork with relevant unions and municipalities to prepare the RAP. The RAP, including the proposed\nmitigation measures within the plan, will be reviewed and approved by CDR’s Board and\nsubsequently sent to the World Bank for final review and approval.\n\n57. _RAP disclosure and implementation_ . Once the RAP is approved by the Bank, it will be\ntranslated into Arabic and disclosed locally as well as in InfoShop at the Bank. The PMU and unions\nand municipalities are responsible for the implementation of the RAP.\n\n_Grievance Redress Mechanisms_\n\n58. A multi-level grievance redress mechanism has been established for the proposed Project.\nThe procedures for handling grievances are as follows:\n\n- The affected person should file his/her grievance in writing to the relevant municipality. The\nmunicipality should respond within 14 days.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 54, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "socio-economic study and census survey", "probe_tag": "confusion", "probe_score": 0.588322639465332, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 701, "end": 739, "key": "jdc_operational:000003:54:0:0", "source": "camp2", "luna_reason": "Planned survey and study will be carried out to collect baseline data.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "census survey", "probe_tag": "confusion", "probe_score": 0.7160173654556274, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1153, "end": 1166, "key": "jdc_operational:000003:54:0:1", "source": "camp2", "luna_reason": "The census survey will be carried out for future project resettlement planning.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nBeirut Critical Environment Recovery, Restoration and Waste Management Program (P176635)\n\n\nurgent action as identified in the RDNA. Lack of containment is also likely cause for site contamination and an\nadditional challenge for port restoration planning.\n\n9. **The institutional responsibility to address these impacts and overall environment management in Lebanon rests**\n**with the Ministry of Environment (MoE).** However, significant weaknesses exist both in terms of technical\ncapacity and with the overall regulatory framework in the country. While there are regulations for handling,\nstorage, and management of hazardous waste (Decree No. 5606 of 2019) and health care waste management\n(Decree No. 13389 of 2004), the capacity of MoE to enforce and monitor implementation of these regulations is\nweak. In addition, there are no specific regulations for the management of chemical substances and stockpiles in\nLebanon, which is regarded as an important factor for the disaster at PoB.\n\n10. **Infrastructure for the treatment and disposal of hazardous and chemical waste is absent in Lebanon, which is**\n**critical for the management of waste generated due to the explosion.** While the country has limited capacity for\nthe collection and temporary storage of hazardous waste, there are no facilities for their treatment or final\ndisposal. As a consequence, hazardous materials including electronic waste is mixed with municipal solid waste\nand disposed in the existing municipal solid waste facilities. Development of adequate facilities is essential for the\nmanagement of hazardous waste generated due to PoB explosion, as well as for the overall needs of Lebanon. In\ncase of healthcare waste, infectious waste is adequately treated at dedicated treatment facilities and segregated\ncytotoxic waste is being shipped abroad under the Basel Convention requirements <mark>on the Control of</mark>\n<mark>Transboundary Movements of Hazardous Wastes and their Disposal (1992)</mark> <sup>5</sup>", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000042", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "RDNA", "probe_tag": "confusion", "probe_score": 0.08390740305185318, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 145, "end": 149, "key": "jdc_operational:000042:4:0:0", "source": "camp2", "luna_reason": "Named assessment cited as identifying urgent environmental action", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\nby snow resulting in large economic losses.\n\n\n39. This component is therefore aimed at improving the capacity of the MPWT to deal with road\nemergency works, especially those induced by snow and climate extremes. This component will finance\nthe purchase of road vehicles and equipment, particularly those needed for snow removal and landslides\nrepairs. This component will finance the purchase of 15 wheel loaders, 10 snow blowers, 5 salt spreaders,\nand 10 four wheel drive vehicles. This component will also assist in revising the existing emergency\nprocedures of MPWT, and its capacity to plan for extreme weather event, including the timely and proper\nmobilization and dispatching of its equipment. Given its strong linkages to the climate change agenda, this\ncomponent could also benefit at later stages from support from disaster risk management and climate\nadaptation funds.\n\n\n**Component 3: Capacity Building and Implementation Support (US$7.5 million)**\n\n\n40. This component is aimed at building the capacity of the Lebanese agencies in the planning and\nmanagement of the road sector. It will also contribute to the training and capacity building of contractors\nand workers on new and improved road construction and maintenance techniques. This component will\nfinance consultancy services and related software and IT equipment, to support the following\nsubcomponents:\n\n\n41. **Subcomponent 1.** Strengthen national road asset management (US$2 million). This\nsubcomponent will finance the creation of a road asset database for the trunk network in Lebanon, the\ncollection of the basic information for the database (such as road condition visual surveys, IRAP\nassessment of road safety, and traffic counts on select road sections), and the revision of design and\nmaintenance standards to reflect changing climate conditions, particularly related to drainage and slope\nprotection/stabilization. This subcomponent will also finance the preparation of bidding documents and\ntraining on performance‐based contracts for road maintenance.\n\n\n42. **Sub", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "road asset database", "probe_tag": "confusion", "probe_score": 0.06317541003227234, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1568, "end": 1587, "key": "jdc_operational:000008:27:0:0", "source": "camp2", "luna_reason": "Database creation and associated data collection are planned project activities.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "road condition visual surveys", "probe_tag": "confusion", "probe_score": 0.11051909625530243, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1688, "end": 1717, "key": "jdc_operational:000008:27:0:1", "source": "camp2", "luna_reason": "Surveys are planned for collection as part of creating the road asset database.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "IRAP\nassessment of road safety", "probe_tag": "confusion", "probe_score": 0.7302994132041931, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1719, "end": 1749, "key": "jdc_operational:000008:27:0:2", "source": "camp2", "luna_reason": "Assessment data will be collected for the road asset database.", "drop_reason": "production", "specificity": "named"}, {"text": "traffic counts", "probe_tag": "confusion", "probe_score": 0.3006365895271301, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1755, "end": 1769, "key": "jdc_operational:000008:27:0:3", "source": "camp2", "luna_reason": "Traffic counts are planned for collection to create a road asset database.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\nlearning agenda. For further details see Annex 4. The Results Framework also includes an indicator relating to the\nadoption of energy efficient and climate resilience infrastructure under Component 3.\n\n64. **Citizen engagement.** The project will work on strengthening citizen engagement, and all beneficiaries, including\nrefugees are key partners in its implementation. Specifically, the project will utilize the following citizen engagement\nmechanisms: (a) participatory decision-making and mobilization of women entrepreneurs through support to existing\nand new women platforms at the village, district, and refugee settlement levels; (b) participatory planning in the design\nof infrastructure for women; and (c) implementation of a grievance redress mechanism (GRM). The GRM will ensure that\nqueries or clarifications about the project are responded to in a timely manner, and that grievances are addressed\nefficiently and effectively. The proposed project will further solicit periodic feedback from beneficiaries through\nbeneficiary satisfaction surveys as well as spot checks and includes a results indicator on the percentage of the project’s\ngrievance redress systems that are addressed.\n\n**C. Project Costs and Financing**\n\n65. **The total project costs are US$217 million, which is to be financed through an IDA grant including US$36 million**\n**from the IDA19 WHR** **for host communities and refugees matched with $4 million from Uganda’s PBA.** See Table 4 for\ndetails.\n\n\n**Table 4: Project Costs by Component**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Project Component|Cost (US$<br>millions)|Of which WHR<br>(US$ millions)|\n|---|---|---|\n|1. Support for Women Empowerment and Enterprise Development<br>Services, including in host and refugee communities<br>|<br>42.0<", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "beneficiary satisfaction surveys", "probe_tag": "confusion", "probe_score": 0.547711968421936, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1144, "end": 1176, "key": "jdc_operational:000025:31:0:0", "source": "camp2", "luna_reason": "Future project surveys are planned to solicit beneficiary feedback.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n\n\n\n\n\nOther Decision (as needed)\n\n\n**B. Introduction and Context**\n\n\nCountry Context\n\n\n1. **South Sudan was beset by decades of armed conflicts even prior to its independence in 2011,**\n**and these have only become increasingly complex in the years since.** Southern Sudan, as the region was\ncalled before independence, has been marred by conflict since 1955, just a year before Sudan attained its\nindependence from British colonial rule. The region experienced systematic marginalization and\nunderdevelopment under both British and Sudanese rule, inhibiting it from developing its physical and\nhuman capital. Consequently, at its independence in July 2011, South Sudan ranked almost at the bottom\nof the global development indicators with little infrastructure, basic services provided almost entirely\nthrough humanitarian aid, and an economy completely dependent on oil. Renewed civil conflict broke out\nin December 2013 and has only recently subsided with the formation of a new government in February\n2020, pursuant to the terms of the September 2018 Revitalized Peace Agreement. <mark>As a result of decades</mark>\n<mark>of violence, nearly 7.5 million people of the estimated 14 million total population rely on some type of</mark>\n<mark>humanitarian assistance or protection.</mark> <sup>1</sup> [^1: UNOCHA (United Nations Office for Coordination of Humanitarian Affairs). 2020. _Humanitarian Needs Overview 2020_, p. 3]\n\n\n2. **The country is highly vulnerable to climate change and natural disasters, and increased stress**\n**on natural resources is fueling local conflicts** . The Global Climate Risk Index ranked the country 125 out\nof 171 between 1998 and 2018. <sup>2</sup> [^2: Germanwatch. 2019. _Global Climate Risk Index 2020_, p. 42.] With a strong reliance on subsistence farming and pastoralism, rural", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000058", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "global development indicators", "probe_tag": "confusion", "probe_score": 0.8837147951126099, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 807, "end": 836, "key": "jdc_operational:000058:2:0:0", "source": "camp2", "luna_reason": "Indicators support South Sudan’s near-bottom global development ranking.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "**Annex 7. Economic Analysis**\n\n\n1. The net effect of the Program at the individual’s level is calculated as the additional benefit that\na representative child obtains as a result of the Program. This effect is estimated from a present\ndiscounted value (PDV) calculation. This approach estimates the stream of benefits and costs of schooling\nover a lifetime in the labor market with and without the Program.\n\n2. Data for this analysis are obtained mainly from the 2010 _Income and Expenditure Survey_, a\nhousehold survey of the labor force, and from the 2015 Population and Housing Census conducted by the\nDepartment of Statistics. This representative information accounts for the entire population of Jordan of\nall ages. It is worth noting that the estimates below are considered under estimates as they do not account\nfor the social benefits of more and better education.\n\n_Estimation of expected economic benefits_\n\n3. The private benefits (returns to schooling) are measured following the standard literature on cost‐\nbenefit analysis for investments in education and by calculating the earnings over the course of the\nworking life. Age‐earnings profiles are built based on the education levels of the Jordan, namely: (i)\nincomplete primary (0‐2 grades completed); (ii) incomplete lower secondary (3‐9 grades completed); (iii)\nincomplete upper secondary school (10 grades completed); (iv) completed upper secondary but not post‐\nsecondary (11‐12 grades completed); and (v) post‐secondary (13 grades completed and above).\n\n4. These age‐earnings profiles are constructed separately for two population groups which differ\nsignificantly in their education and labor market experiences, namely (i) men; and; (ii) women. These are\nenriched by incorporating: (1) the probability of employment in three types of employment (wage\nemployment, self‐employment, and unpaid employment); (2) the probability of employment in the public\nsector; (", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 61, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2010 _Income and Expenditure Survey_", "probe_tag": "confusion", "probe_score": 0.897545576095581, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 464, "end": 500, "key": "jdc_operational:000041:61:0:0", "source": "camp2", "luna_reason": "Survey data are used as the main basis for economic analysis.", "usage_type": "evidential", "specificity": "named"}, {"text": "household survey of the labor force", "probe_tag": "confusion", "probe_score": 0.34258925914764404, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 504, "end": 539, "key": "jdc_operational:000041:61:0:1", "source": "camp2", "luna_reason": "Existing labor-force survey is identified as a primary data source for economic analysis.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "2015 Population and Housing Census", "probe_tag": "keep", "probe_score": 0.9282529354095459, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 554, "end": 588, "key": "jdc_operational:000041:61:0:2", "source": "camp2", "luna_reason": "Census data are used for the program's economic analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\nand distribution of basic commodities (e.g. rice, cooking oil, milk powder, sugar), including with private sector\nparticipation <sup>30</sup> ; (ii) assessing options for the regional food security coordination role that Jordan can play, focusing\non regional risk management instruments, including for addressing climate related risks, and Jordan’s potential to\nhost a regional commodities market; (iii) evaluation of food policy options to smooth future supply shocks in a\nfiscally sustainable way; and (iv) support ongoing efforts to realign public support to the livestock sub-sector\ntowards more sustainable resource use and effective targeting of the most vulnerable. Activities (i, ii and iv) would\nsupport potential reductions in food loss and waste, with corresponding greenhouse gas emission reductions.\nGender differentiated assessments will be considered to help identify more inclusive policies related to food\nsecurity, including the participation of women-owned/led enterprises as key informants.\n\n**38.** **While the monitoring of wheat distribution along the value chain is salient, access to bread can be better**\n**assessed** . There are well established control systems in place to ensure that grains are efficiently transformed into\nwheat and distributed to end users. Better understanding the characteristics of end users may enable better\ntargeting of policies focusing on the consumption of basic commodities in the country <sup>31</sup> . With that in mind, the\nproject will support the development of a “bread map” <sup>32</sup> where location of bakeries and other points of sale of\nbread will be visualized and correlated with population density to inform on the distributional aspects of food and\nguide the more equitable access of basic food by the population of Jordan. The map will be made available online,\nto the public <sup>33</sup>", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 23, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "bread map", "probe_tag": "confusion", "probe_score": 0.06568266451358795, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1592, "end": 1601, "key": "jdc_operational:000024:23:0:0", "source": "camp2", "luna_reason": "Project will develop a future map visualizing bakery and bread-sale locations.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "--|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **<br>|**Responsibility for Data**<br>**Collection **|\n|Students benefiting from direct<br>interventions to enhance learning||Midterm and<br>project end.<br>|EMIS, project<br>reports<br>|<br>The indicator includes:<br>Students benefiting<br>from teachers trained<br>and supported under<br>the project* - 2,358,000<br>Students receiving<br>scholarships - 86,000<br>AEP - 6,600<br>* 2017 EMIS data.<br>Annual enrollment of<br>students includes all<br>public school students|<br>MoES<br>|\n\n\nPage 50 of 96", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 55, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "EMIS data", "probe_tag": "confusion", "probe_score": 0.8280574083328247, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 515, "end": 524, "key": "jdc_operational:000018:55:1:0", "source": "camp2", "luna_reason": "2017 EMIS data supports concrete student enrollment figures.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\nCrescent Societies, which will confirm that the bakeries service areas that include poor and vulnerable groups are\nreceiving the flour as per Framework Agreement. In addition, the project will finance high frequency ‘Listening to\nPoor and Vulnerable Household Surveys’, entailing data collection on bread prices and consumption for the poor\nand vulnerable households, by collecting random sampling and surveying (biweekly) using UNHCR and WFP\nbeneficiary lists. This information will be triangulated at MOET level with information consolidated from the\nconsumer protection agency, GM, and price monitoring system, and used to adopt appropriate remedies, such as\nincluding in the Framework Agreement a preferential distribution clause for bakeries located in areas where most\nof the poor and vulnerable groups are located. Additional social risks are associated with the consultancy services\nand technical assistance under Component 2 that will help MOET’s planned transition from the current wheat\nsubsidy system to a more market-oriented system. Such risks will be mitigated through recommendations in the\nstudy to ensure linkages with the social safety net programs like ESSN, a clear communication campaign, and an\neffective and widespread dissemination of the grievance mechanism. All the mitigation measures will be covered\nin the Environmental and Social Management Plan (ESMP), which will be prepared before signing Framework\nAgreements with local importers and as a disbursement condition.\n\n80. The Environmental risk rating is Moderate. The project is limited to procurement of wheat to maintain\nthe supply during the market disruptions caused by the war in Ukraine. The project finance will not involve any\ncivil works nor any other activities after the vessels deliver the shipment at the ports of Beirut and/or Tripoli.\nThere are some associated activities, which are not directly financed by the project but are directly and\nsignificantly related to the project; will be carried out contemporaneously with the project; and necessary for the\nproject to be viable and would not have been conducted if the project did", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Listening to\nPoor and Vulnerable Household Surveys", "probe_tag": "confusion", "probe_score": 0.38338759541511536, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 297, "end": 347, "key": "jdc_operational:000019:33:0:0", "source": "camp2", "luna_reason": "Project-financed surveys entail future data collection.", "drop_reason": "production", "specificity": "named"}, {"text": "UNHCR and WFP\nbeneficiary lists", "probe_tag": "confusion", "probe_score": 0.7232257723808289, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 509, "end": 540, "key": "jdc_operational:000019:33:0:1", "source": "camp2", "luna_reason": "Existing UNHCR and WFP lists are used to draw the survey sample.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " and\ndeceleration in private consumption. The pandemic has also stalled telecommunications infrastructure\ninvestments and dampened consumer demand because of the falling purchasing power. For poor and vulnerable\nhouseholds in Uganda, the impact of COVID-19 is especially severe. Since the COVID-19 outbreak, 91 percent of\n\n\n1 2020. _Uganda Economic Update_, _Strengthening Social Protection to Reduce Vulnerability and Promote Inclusive Growth_, 2020. World\nBank.\n2 Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat. 2015. _The_, _World Population_\n_Prospects: The 2015 Revision_ .\n3 2020. Uganda Economic Update, Strengthening Social Protection to Reduce Vulnerability and Promote Inclusive Growth, 2020. World\nBank.\n4 World Bank. 2016. _The Uganda Poverty Assessment Report 2016_ . Washington, DC: World Bank.\nhttp://pubdocs.worldbank.org/en/381951474255092375/pdf/Uganda-Poverty-Assessment-Report-2016.pdf\n5 World Bank Data.\n6 World Bank Data.\n7 World Bank. 2020. _Uganda Economic Update_, _Strengthening Social Protection to Reduce Vulnerability and Promote Inclusive Growth_,\n2020. World Bank.\n8 World Bank. 2020. _Uganda Economic Update, 1_ 6 _th Edition, December 2020:_ Investing in Uganda’s Youth. December 2020.\n\n\nPage 1 of 76", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 13, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "World Bank Data", "probe_tag": "confusion", "probe_score": 0.11067483574151993, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 964, "end": 979, "key": "jdc_operational:000023:13:2:0", "source": "camp2", "luna_reason": "Standalone numbered reference entry without shown data use.", "drop_reason": "ref_list", "specificity": "vague"}]}
+{"text": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n**Box 2. Lebanon Emergency Primary Healthcare Restoration Project (EPHRP)**\n**Objective**\nThe objective of the EPHRP is to assist the GoL in reducing the social, economic, and health impacts of the Syrian\ncrisis on poor Lebanese by subsidizing a package of essential health care services.\n**Beneficiaries**\nThis project targets 150,000 of the 340,000 poor Lebanese identified by the NPTP as living below the poverty\nline, using a proxy means testing targeting mechanism.\n**Essential Health Care Package**\nThe project provides beneficiaries with a package of essential health care services comprising the following:\n(i) three age- and gender-specific wellness packages (age 0-18, females 19 years and above, males 19 years and\nabove); (ii) two care packages for the most common non-communicable diseases in Lebanon, diabetes and\nhypertension; and (iii) an antenatal package.\n**Providers**\nServices are provided to beneficiaries through 75 of the 204 MoPH network centers. Network facilities are\nmanaged by NGOs (67 percent), local municipalities (20 percent), MoPH (11 percent), and MoSA (2 percent).\nProvider participation is voluntary and is governed by the legal agreement between the MoPH and the managing\nentity.\n**Quality of Care**\nQuality of care is monitored through the PHCC accreditation program implemented by the MoPH in collaboration\nwith Accreditation Canada International. Currently, all 75 PHCCs are within the accreditation program. The\nquality of clinical care is also monitored by the MoPH through clinical indicators captured in the Health\nInformation System.\n**Contracting and Provider Payment Mechanism**\nThe MoPH purchases the package of services for the beneficiary population from PHCCs. Provider payment is\nbased on capitation and is output-based. The average per", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Health\nInformation System", "probe_tag": "confusion", "probe_score": 0.5563758611679077, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1617, "end": 1642, "key": "jdc_operational:000032:16:0:0", "source": "camp2", "luna_reason": "System indicators are used to monitor clinical care quality.", "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": " by i)\na series of conducive Government policies <sup>18</sup>, and ii) the significant uptake of mobile phone subscribers, which grew\nfrom 14.7 million in 2010 to 21.7 million in 2018, representing an increasing penetration rate that has reached 56%\nof the total population. <sup>19</sup> Developing digital infrastructure fosters growth. Based on recent analysis <sup>20</sup> by the World\nBank Africa Chief Economist’s Office, closing the digital infrastructure gap <sup>21</sup> in the East and Southern Africa region\ncould result in 1.5 percentage point growth increase in economic growth per capita. If complemented by expansion\nin human capital development, the growth effect could increase to 3.87 percentage points. Indirectly, the digital\nsector contributes to enhancing productivity, facilitating information exchange, and improving service delivery across\nthe economy.\n\n5. **The substantial increase in mobile phone ownership (71% of the population) is laying the foundation for Uganda’s**\n**digital transformation and enabling the rapid take-up of various e-services.** According to the 2017/2018 survey by\n\n\n10 The Horn of Africa sub-region is defined as Djibouti, Eritrea, Somalia, Sudan, Kenya, Uganda and South Sudan.\n[11 United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) 2018. https://www.unocha.org/southern-and-](https://www.unocha.org/southern-and-eastern-africa-rosea/uganda)\n<u>[eastern-africa-rosea/uganda](https://www.unocha.org/southern-and-eastern-africa-rosea/uganda)</u>\n[12 UNHCR, 2018. https://www.un.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000063", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2017/2018 survey", "probe_tag": "confusion", "probe_score": 0.5173022747039795, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1100, "end": 1116, "key": "jdc_operational:000063:3:1:0", "source": "camp2", "luna_reason": "Survey supports the stated 71% mobile-phone ownership finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "22. **Moreover, investments in strengthening data systems (both technical and financial) need to**\n**continue to deepen the use of data for evidence‐based decision making in the sector and further**\n**improve resource allocation.** The MOE has successfully deployed an education management\ninformation system (EMIS), which is now hosting data on all schools and students in the system.\nAdditional investments in a geographical information system (GIS) are ongoing and will allow MOE to\nbetter plan for expansion of access across all regions in the country. Leveraging the data available\nthrough the EMIS for decision making in the sector is a key opportunity for the MOE which will require\nadditional technical assistance and capacity building to materialize. In addition, the collection,\nanalysis, and use of student learning data and disaggregated and gender‐sensitive data are essential\nfor monitoring, targeting pedagogical interventions, and improving teacher practices in the classroom.\n\n\n**C.** **Relationship to the Country Partnership Framework and Rationale for Use of**\n**Instrument**\n\n23. **_Relationship to the CPF._** The proposed operation is fully aligned with the Jordan Country\nPartnership Framework (CPF) discussed by the World Bank Group Board on July 14, 2016. The CPF\ncovers the period FY17–22 and highlights the economic, geopolitical, and social challenges that Jordan\nhas been facing, particularly with the Syrian refugee crisis. The CPF also acknowledges Jordan’s\ncommitment to reforms for a more sustainable growth path with stronger job creation, better service\ndelivery, a more conducive investment climate, and a larger involvement of citizens in the decision‐\nmaking process. In this respect, it is fully aligned with the government’s Vision Jordan 2025. The\nproposed operation directly supports the second pillar of the CPF, which aims to improve the quality\nand equity of service delivery, particularly its objective 2.2. “Improved delivery of education services.”\nThe proposed", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "student learning data", "probe_tag": "confusion", "probe_score": 0.2374759018421173, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 810, "end": 831, "key": "jdc_operational:000041:14:0:0", "source": "camp2", "luna_reason": "Generic data is mentioned for intended monitoring, without an attributed finding or figure.", "drop_reason": "bare_stat", "specificity": "vague"}, {"text": "disaggregated and gender‐sensitive data", "probe_tag": "confusion", "probe_score": 0.124959796667099, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 836, "end": 875, "key": "jdc_operational:000041:14:0:1", "source": "camp2", "luna_reason": "Data collection is presented as an essential activity, not existing data use.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n19. **Subcomponent 4.** Support training activities (US$0.5 million). This subcomponent will support\ntraining activities to build the technical skills of MPWT and CDR staff, as well as workers and small\ncontractors. It will support training on soft skills as well as technical skills related to the work to be\ncarried out at selected project sites. In particular, this subcomponent will also support the training of\nsmall local contractors and their workers on proper routine maintenance requirements and\ntechniques, environmental and social aspects, and health and safety aspects. The implementation of\nthis subcomponent could be in collaboration with other interested donors such as the ILO. This\nsubcomponent could benefit from grants from interested donors. A technical supervision manual for\nCDR and MPWT regional offices will be prepared to improve their monitoring and supervision efforts\nof road condition.\n\n\n20. **Subcomponent 5.** Support for Project Implementation (US$1 million). This subcomponent will finance\nthe hiring of required experts by the implementing agency (CDR) to properly undertake the\nimplementation and monitoring of the project.\n\n\n**Table 1.5. Road Safety Fatalities and Injuries in Lebanon** <sup>**16**</sup> [^16: Lebanese ISF.]\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Year|Total<br>Number of<br>Fatalities|Number of<br>Syrian<br>fatalities|Percentage of<br>Syrian<br>Fatalities|Total<br>Number of<br>Injuries|Number of<br>Syrian<br>Injuries|Percentage of<br>Syrian Injuries|\n|---|---|---|---|---|---|---|\n|2011|508|52|10.2|6050|418|", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 58, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Road Safety Fatalities and Injuries in Lebanon", "probe_tag": "confusion", "probe_score": 0.12874919176101685, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1234, "end": 1280, "key": "jdc_operational:000008:58:0:0", "source": "camp2", "luna_reason": "Standalone table caption, not an independent data-use mention.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
+{"text": "/PR/PM/MEPD/SE/SG/DGEP/2017 dated September 23, 2017 and it is the first step\ntoward building a Unified Social Registry (USR). Currently the Government, through the _Cellule Filets Sociaux_, is moving towards\nfinalizing the USR manual and procuring all necessary hardware (servers, mainframes) and software to establish the registry. It is\nenvisaged that a USR unit will eventually be created within the Government.\n\n\nPage 13", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 17, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Unified Social Registry", "probe_tag": "confusion", "probe_score": 0.37818413972854614, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 96, "end": 119, "key": "jdc_operational:000035:17:2:0", "source": "camp2", "luna_reason": "Registry is being built, with procurement and establishment still planned.", "drop_reason": "promissory", "specificity": "named"}]}
 {"text": " covering, _inter alia_, the following: i) Information systems used to\nidentify best available offers of products and terms of trade (affecting prices, quality, availability and transportation of products); ii) Process\nmaps of procurement processes (identifying number of transaction steps, and potential time and cost savings derived from undertaking\nprocedural streamlining and automation); iii) Level of contestability and transparency of procurement systems as well as perceptions by\nstakeholders.\n31 While the scope of this project is not on targeting (access) consumption of bread, but rather on ensuring availability of grains, project\nmonitoring will be carried out with focus on grain purchases and also the availability of bread at points of sale.\n32 A consultative approach will be used for the development of the “bread maps” and “animal feed maps”. Including beneficiaries will help\ngain a better understanding of the characteristics of end users and enable better, tailored policies. Beneficiaries can provide valuable\nfeedback on the accessibility of bakeries and bread sale points, as well as grain distribution centres. Visualization of the maps would be\ndisability-inclusive and consider the needs of people with limited literacy.\n33 Digitally, the map could be delivered through a Food Citizen Platform that serves as an interactive tool, is accessible through mobile\nphones, allows real-time feedback and provides information on food and nutrition beyond the scope of wheat and barley.\n\n\nPage 19 of 54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 23, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "bread maps", "probe_tag": "drop", "probe_score": 0.024127816781401634, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 826, "end": 836, "key": "jdc_operational:000024:23:2:0", "source": "camp2", "luna_reason": "Maps are planned for future development, not existing data used in analysis.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "animal feed maps", "probe_tag": "confusion", "probe_score": 0.14068707823753357, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 843, "end": 859, "key": "jdc_operational:000024:23:2:1", "source": "camp2", "luna_reason": "Maps are planned outputs being developed, not existing data used for analysis.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "**Annex 7: Map IBRD 33385**\n\n\n68", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 77, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Map IBRD 33385", "probe_tag": "drop", "probe_score": 0.01701207272708416, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 11, "end": 25, "key": "jdc_operational:000007:77:0:0", "source": "camp2", "luna_reason": "Standalone annex map title, not a cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": ":<br>Fadi Yarak<br>  Title:<br>Director General|Contact:<br>Fadi Yarak<br>  Title:<br>Director General|Contact:<br>Fadi Yarak<br>  Title:<br>Director General|Contact:<br>Fadi Yarak<br>  Title:<br>Director General|Contact:<br>Fadi Yarak<br>  Title:<br>Director General|\n|Telephone No.:961-1-772-110<br>  Email:FYarak@MEHE.gov.lb|Telephone No.:961-1-772-110<br>  Email:FYarak@MEHE.gov.lb|Telephone No.:961-1-772-110<br>  Email:FYarak@MEHE.gov.lb|Telephone No.:961-1-772-110<br>  Email:FYarak@MEHE.gov.lb|Telephone No.:961-1-772-110<br>  Email:FYarak@MEHE.gov.lb|Telephone No.:961-1-772-110<br>  Email:FYarak@MEHE.gov.lb|Telephone No.:961-1-772-110<br>  Email:FYarak@MEHE.gov.lb|\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)**|\n|[   ]", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 4, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "Project Financing Data", "probe_tag": "drop", "probe_score": 0.028415339067578316, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 680, "end": 702, "key": "jdc_operational:000030:4:5:0", "source": "camp2", "luna_reason": "Standalone table header, not a substantive data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"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": " (b) the capacity of Uganda National Roads Authority to manage environmental, social and road safety\nrisks.\n\n\nKey Results\n\n\n25. The PDO level indicators are:\n\n(a) enhance road transport connectivity in select refugee hosting districts of Uganda\n\n(i) Travel time on the Project road corridor dis-aggregated by buses, motorbikes, and trucks\n\n(modes used by refugees/hosts and for trade)\n(ii) Vehicle Operating Costs on the Project road corridor dis-aggregated by buses, motorbikes,\n\ncars, 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\n(iv) Percentage increase in trade volumes using the Project road (dis-aggregated by refugees,\n\nhosts)\n\n\n(b) enhance the capacity of Uganda National Roads Authority to manage environmental, social and\nroad safety risks\n\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\n(vii) Annual number of fatalities or serious injuries involving construction vehicles or at\n\n\n39 Includes 13 permanent staff, 20 contract staff, and 6 technical advisors\n\n\nApr 07, 2020 Page 12 of 16", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000001", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Crash data", "probe_tag": "drop", "probe_score": 0.024797827005386353, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 922, "end": 932, "key": "jdc_operational:000001:11:1:0", "source": "camp2", "luna_reason": "PDO indicator describes planned crash-data reporting and decision use, not existing evidence.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"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:000062", "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:000062:71:0:0", "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**\nLebanon Health Resilience Project (P163476)\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|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|**Name:**Health personnel<br>receiving training||Number|0.00|1000.00|Bi-annual<br>|PMU<br>|PMU<br>|\n|Description:Number of health personnel receiving training through the project|Description:Number of health personnel receiving training through the project|Description:Number of health personnel receiving training through the project|Description:Number of health personnel receiving training through the project|Description:Number of health personnel receiving training through the project|Description:Number of health personnel receiving training through the project|Description:Number of health personnel receiving training through the project|Description:Number of health personnel receiving training through the project|\n|||||||||\n|**Name:**Maintain Client<br>Satisfaction (PHCCs &<br>Hospitals)||Percentage|75.00|75.00|Annual<br>|Client satisfaction survey<br>|PMU<br>|\n|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 45, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Client satisfaction survey", "probe_tag": "drop", "probe_score": 0.03337932378053665, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1099, "end": 1125, "key": "jdc_operational:000032:45:0:0", "source": "camp2", "luna_reason": "Planned annual project monitoring survey, not an existing data source used for analysis.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": "*Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|\n|[ X ]|Loan|[ ]|Grant|Grant|Grant|[x ]|[x ]|Other|Other|Other|Other|Other|Other|\n|[ X ]|Credit|||||||||||||\n|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|\n|", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 5, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Program Financing Data", "probe_tag": "drop", "probe_score": 0.018062889575958252, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1, "end": 23, "key": "jdc_operational:000045:5:3:0", "source": "camp2", "luna_reason": "Standalone table header, not a substantive data resource or data use.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n**23.** **Disbursements and Flow of Funds.** Funds will be channeled directly from the World Bank to the UN-Habitat\nbank account in US dollars outside Lebanon. UN-Habitat will submit withdrawal applications to the World Bank to\nrequest funds using the report-based disbursement method (i.e., based on IFRs for a six month expenditure\nprojection). The format and content of the IFRs is provided in the Disbursement and Financial Information Letter\n(DFIL). The amount of the advance will be based on a projection of six months expenditures. The disbursement\ncategories, allocations, and percentage of expenditures to be financed are shown in the table below.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Category|Amount of the Grant<br>Allocated (expressed in USD)|Percentage of Expenditures to be<br>Financed<br>(inclusive of Taxes)|\n|---|---|---|\n|(1) Goods, works, non-consulting<br>services, and consulting services<br>under Part 1 of the Project|8,275,520|100%|\n|(2)<br>Consulting<br>services,<br>non-<br>consulting services and CCI Grants<br>under Part 2 of the Project|1,951,857|100%|\n|(3) (a) Indirect Cost under Part 3 of<br>the project (5%)<br> <br>(3) (b) Direct Cost under Part 3 of the<br>Project|607,143<br> <br> <br> <br>1,915,480|100%|\n|**TOTAL AMOUNT**|", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 52, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "IFRs", "probe_tag": "confusion", "probe_score": 0.09230616688728333, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 408, "end": 412, "key": "jdc_operational:000012:52:0:0", "source": "camp2", "luna_reason": "Financial reports used for disbursement administration, not substantive data analysis.", "drop_reason": "bookkeeping", "specificity": "descriptive"}, {"text": "IFRs", "probe_tag": "drop", "probe_score": 0.026097137480974197, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 408, "end": 412, "key": "jdc_operational:000012:52:0:1", "source": "camp2", "luna_reason": "Interim financial reports used for project disbursement administration", "drop_reason": "bookkeeping", "specificity": "vague"}]}
+{"text": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n\n\n\n\n\nPage 6 of 54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 8, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Lebanon Health Resilience Project", "probe_tag": "drop", "probe_score": 0.04027361050248146, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 52, "key": "jdc_operational:000032:8:0:0", "source": "camp2", "luna_reason": "Names a project, not an existing data resource or data use.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": " emergency crew as part of the maintenance activities are key Project<br>features. Enhancement of skills in handling environmental risks, road safety awareness, and<br>safety data management are part of contingency planning.<br>Component 2: Institutional Strengthening will entail the enhancement of institutional skills in<br>handling natural hazards and environmental risks in the project corridor areas and will lead to<br>better contingency planning to help improve climate resilience.<br>Component 3: Road Safety – Road safety awareness campaigns in the Project area, and road<br>safety data collection and management system are part of contingency planning and help<br>improve climate resilience and adaptation through the information gathering which will inform<br>decision making and gear key strategies.<br>Component 4: Contingent Emergency Response – The ability to support emergencies in the wake<br>of natural disasters will help climate resilience of the road network and communities.|\n|---|---|\n|**Link to**<br>**project**<br>**activities**|This project will enhance resilience of the road network and of the communities served by the<br>Koboko, Yumbe and Moyo (KYM) road corridor. This will be done through four project<br>components, as follows:<br>Component 1: Road Upgrading Works - This project component will support civil works for<br>widening and upgrading of the approximately 105 km-long KYM road corridor from the gravel<br>weather prone surface to bituminous paved road standards. The unpaved laterite road which is<br>the current state is vulnerable to extreme weather conditions and climate change risks,<br>especially the projected increase in precipitation levels that can lead to more frequent and<br>intense flooding and erosion. Paving the surface of the road is therefore a good climate change<br>adaptation measure.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 77, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "safety data collection and management system", "probe_tag": "drop", "probe_score": 0.0361877866089344, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 585, "end": 629, "key": "jdc_operational:000050:77:1:0", "source": "camp2", "luna_reason": "Project data collection system is planned to gather information for future decisions.", "drop_reason": "production", "specificity": "descriptive"}]}
 {"text": "br>trained in Child Friendly<br>School Program<br>Component 2: all staff<br>trained in AEP<br>Component 3: all<br>teachers, headteachers<br>and cluster staff<br>trained<br>|MoES<br>|\n|Grievances registered and addressed in<br>line with Grievance Redress Mechanism<br>|Data source: Grievance Log<br>Books, Grievance Redress<br>System Data Base, Quarterly<br>Grievance Redress Status<br>Reports|<br>Semi-<br>annually<br>|PCU/MoES<br>|<br>Administrative Data<br>|PCU/MoES<br>|\n\n\nPage 56 of 96", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 61, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Grievance Log", "probe_tag": "drop", "probe_score": 0.041625577956438065, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 281, "end": 294, "key": "jdc_operational:000018:61:1:0", "source": "camp2", "luna_reason": "Routine grievance-administration log used for project monitoring", "drop_reason": "bookkeeping", "specificity": "named"}, {"text": "System Data Base", "probe_tag": "drop", "probe_score": 0.02710389532148838, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 326, "end": 342, "key": "jdc_operational:000018:61:1:1", "source": "camp2", "luna_reason": "System database is cited as a data source for registered and addressed grievances.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "Administrative Data", "probe_tag": "drop", "probe_score": 0.009150476194918156, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 436, "end": 455, "key": "jdc_operational:000018:61:1:2", "source": "camp2", "luna_reason": "Standalone table cell naming an administrative data category, not a cited data use.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 3 of 54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Lebanon Health Resilience Project", "probe_tag": "drop", "probe_score": 0.04073747992515564, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 52, "key": "jdc_operational:000032:5:0:0", "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\n|New electricity connections<br>(predominantly energized by solar PV and<br>battery storage) in 12 secondary cities|Col2|Quarterly|Reports of<br>SNE, progres<br>s reports of<br>PIU|Data provided by SNE<br>operational units and<br>Owner's Engineer|PIU of SNE|\n|---|---|---|---|---|---|\n|Electricity connections (predominantly<br>energized by solar PV and battery storage)<br>in new cities and towns, out of which|<br>|Quarterly<br>|<br>Progress<br>reports of<br>the PIU of<br>the Ministry<br>of Petroleum<br>and Energy<br> <br>|Data will be collected<br>by M&E specialists of<br>the PIU of Ministry of<br>Petroleum and Energy<br>from progress reports<br>made by private<br>operators and checked<br>through site visits.<br>|PIU of the Ministry of<br>Petroleum and Energy<br>|\n|In cities housing host communities||Quarterly<br>|Reports of<br>SNE, progres<br>s reports of<br>PIU<br> <br>|<br>Data provided by SNE<br>operational units and<br>Owner's Engineer<br>|PIU of SNE<br>|\n|Female-headed households electrified<br>under subcomponents 1.1 - 1.3||Quarterly<br>|<", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 59, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data provided by SNE", "probe_tag": "drop", "probe_score": 0.04813060536980629, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 249, "end": 269, "key": "jdc_operational:000051:59:0:1", "source": "camp2", "luna_reason": "Planned monitoring data source in a project results table, not existing data use.", "drop_reason": "promissory", "specificity": "named"}]}
+{"text": ">sanitation service delivery and support long-term<br>investments in infrastructure development, in RHDs<br>in the West Nile and Northern region.<br>Locations targeted for solar based water pumping<br>have already been identified in Arua, Yumbe, Moyo,<br>Adjumani, Lamwo, and Kiryandongo<br>|Provide digital enabling environment for<br>remove water monitoring and strengthen<br>efficiencies and effectiveness of water<br>management systems.<br> <br> <br> <br> <br>|\n|**Gender Based Violence**<br>**and Violence Against**<br>**Children Prevention and**<br>**Response Services in**<br>**Uganda’s Refugee-**<br>**Hosting Districts Report**<br> <br>_Status: Analysis_<br>_completed,_|Total<br>0.5<br> <br> <br>RSW/<br>WHR<br>N/A|To mitigate GBV and prevent violence against children<br>through engagement in productive activities in 4<br>RHDs.|Increased<br>access<br>to<br>more<br>affordable<br>connectivity will also increase likelihood of GB<br>online risks. Project will support the project<br>objective indirectly by including awareness<br>and mitigation measures in digital skills<br>training.<br> <br>Digital connectivity will strengthen case<br>management for GBV and violence against|\n\n\nPage 64 of 76", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 76, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Hosting Districts Report", "probe_tag": "drop", "probe_score": 0.027639077976346016, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 610, "end": 634, "key": "jdc_operational:000023:76:3:0", "source": "camp2", "luna_reason": "Fragment of a table title, not an independently used data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n|Col1|installment of livelihood<br>grant.|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Number of beneficiaries receiving<br>Economic Opportunities who are female<br>youth|Number of beneficiaries<br>receiving economic<br>opportunities under<br>Component 2, in accordance<br>with the Project Operations<br>Manual, of which are youth<br>and female, defined as<br>women between the ages of<br>18 and 35 years, and have<br>received at least 1<br>installment of livelihood<br>grant.<br>|<br> <br>This<br>indicator<br>will be<br>measured,<br>at a<br>minimum,<br>on a<br>quarterly<br>basis<br>|SNSOP MIS<br>|Beneficiary data will be<br>collected during<br>registration and<br>updated during project<br>implementation.<br>Payment data will be<br>regularly updated in the<br>SNSOP MIS<br>|The Implementing<br>Partner in charge of<br>Component 2 will be<br>responsible for data<br>collection.<br>|\n|Percentage of grievances resolved<br>through the GRM|Number of all grievances<br>which are lodged, processed<br>and resolved through the<br>SNSOP GRM divided by all<br>complaints which are<br>lodged, processed and/or<br>resolved, expressed as a<br", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 63, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SNSOP MIS", "probe_tag": "drop", "probe_score": 0.02833188883960247, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 685, "end": 694, "key": "jdc_operational:000057:63:0:0", "source": "camp2", "luna_reason": "Project MIS data will be collected and updated for future indicator monitoring.", "drop_reason": "promissory", "specificity": "named"}, {"text": "SNSOP MIS", "probe_tag": "drop", "probe_score": 0.018197588622570038, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 685, "end": 694, "key": "jdc_operational:000057:63:0:1", "source": "camp2", "luna_reason": "MIS data collection and updates are planned project monitoring activities.", "drop_reason": "promissory", "specificity": "named"}]}
+{"text": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 3 of 54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Emergency Food Security Project", "probe_tag": "drop", "probe_score": 0.022284748032689095, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 50, "key": "jdc_operational:000024:7:0:0", "source": "camp2", "luna_reason": "Project title, not a cited or used data resource", "drop_reason": "ref_list", "specificity": "named"}]}
 {"text": "**The World Bank**\nChad - Refugees and Host Communities Support Project (P164748)\n\n\n\n\n\n\n\n\n\n\n|for Performance Based Financing|Col2|Col3|Health|by region on level of<br>utilization of the<br>standard forms<br>Performance Based<br>Financing introduced by<br>the P148052 Mother<br>and Child Health<br>Services Strengthening<br>Project. Information is<br>based on<br>representative surveys.|Col6|\n|---|---|---|---|---|---|\n|Cash transfer beneficiaries (households)||Quarterly<br>|Baseline data<br>collected<br>from UNHCR<br>and WFP on<br>number<br>of refugees<br>receiving<br>cash<br>transfers  in<br>target areas.<br>The CFS is<br>launching a<br>baseline<br>study which<br>will help to<br>confirm<br>baseline<br>numbers, to<br>be reviewed<br>at MTR.|CFS local offices<br>produce simple reports<br>by region on number of<br>households receiving<br>the transfer.  This<br>number is than<br>multiplied by 5 since<br>the average size of<br>families is of five<br>member. The reports<br>are then consolidated<br>by the CFS. Data are<br>non-cumulative by<br>cohort.<br>|CFS<br>|\n\n\n\nPage 52", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 56, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "representative surveys", "probe_tag": "drop", "probe_score": 0.025918155908584595, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 362, "end": 384, "key": "jdc_operational:000035:56:0:0", "source": "camp2", "luna_reason": "Generic surveys are named without an attributed finding or concrete claim.", "drop_reason": "bare_stat", "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": "refugee_pads", "corpus_id": "refugee_pads:000041", "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:000041:38:1:0", "source": "camp2", "luna_reason": "Survey data supports reported enrollment-rate differences 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:000041:38:1:1", "source": "camp2", "luna_reason": "Survey data supports reported enrollment-rate disparities.", "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:000041:38:1:2", "source": "camp2", "luna_reason": "Household Survey data support the finding that parents withdraw girls from school.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nAgricultural Employment Support for Refugees and Turkish Citizens through Enhanced Market Linkages (P171543)\n\n\nlow-skilled workers in agriculture, and the average monthly wage is TL 1,101.00 (with a median TL\n1,000.00), far below the current 2018 net minimum wage of TL <mark>1.603,12.</mark> Figure 4.1. displays the\ndistribution of monthly wages for formal and informal workers. As evidenced in the figure, workers in the\nagricultural sector, particularly workers who are employed informally, are currently paid way below the\nminimum wage. The gap between the minimum wage, the legally mandated wage for all agricultural\nworkers, and the median wage of informal agricultural workers, is close to TL 1,200, which is about 30\npercent less than the 2018 net minimum wage. This reflects either very low levels of labor productivity\nfor those workers, or farmers paying workers below their marginal productivity level. For the bulk of\ninformal workers whose monthly wage is 40 percent lower than the minimum wage, formalization is not\nan achievable objective in the short term.\n\n\nFigure 4.1. Wage distribution among low-skilled workers in agriculture\n\n\n_Source:_ Turkey Labor Force Survey 2018.\n_Note:_ The vertical red bar represents the net minimum wage as of 2018.\n\n\n183. **To estimates the costs and benefits of the project, the analysis breaks down the group of**\n**potential beneficiary workers in three groups** : (a) the already employed in agriculture that are currently\ninformal and may become formal; (b) informal workers that would remain informally employed but would\nincrease their productivity through skill training; and (c) workers not currently employed who would\nbecome employed as a result of additional job creation. It is also assumed that a small proportion of the\nworkers in (b) would become formal in the long term thanks to increased labor productivity and other\ninterventions", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000114", "page": 77, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Turkey Labor Force Survey", "probe_tag": "keep", "probe_score": 0.9652908444404602, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1179, "end": 1204, "key": "refugee_pads:000114:77:0:0", "source": "camp2", "luna_reason": "Source survey supports the wage-distribution analysis and cited labor findings.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "\nCameroon accounts for 44 percent of the total gross domestic product (GDP) in the Central African\nEconomic and Monetary Community (CEMAC). More than half of goods bound for Central Africa\npass through the port of Douala, while exports and imports to the Central African Republic, Chad\nand the Republic of Congo all flow through Cameroon’s national network of roads and rail.\n\n\n3. **However, recent economic growth has not been driven by structural transformation**\n**and is susceptible to various risks, including climate variability and change.** Despite a gloomy\noverall economic environment in the CEMAC region and lower oil prices, economic developments\nin 2016 have remained positive with a growth rate of 4.7 percent (compared to 5.8 percent in\n2015). However, economic growth has primarily been spurred by large public investments instead\nof structural reforms. Natural resource rents have helped finance a centralized governance system\nwith a state-led development model, which weighs down the economy with monopolies, an\nunfavorable business environment, and weak governance. The country’s debt situation has also\nrecently deteriorated due to lower revenues from commodities, increasing macro-economic\nuncertainty. The public debt-to-GDP ratio reached 34.1 percent in 2016 (compared to 15.6 percent\nin 2013) and the risk of debt distress was raised from medium to high in the joint International\nMonetary Fund/World Bank 2015 Debt Sustainability Assessment, reflecting the collapse in the\nvalue of exports and the rapid growth in non-concessional borrowing. Moreover, the increases in\nclimate variability and extreme events (such as droughts and floods) pose threats to economic\ngrowth. Finally, it is important to note that presidential, legislative, and municipal elections are\nscheduled for 2018.\n\n\n4. **Insecurity, internal displacement, refugees, and climate change exacerbate the**\n**widening north-south gap in economic and social terms.** Impoverished communities in the\nNorth are particularly", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2015 Debt Sustainability Assessment", "probe_tag": "keep", "probe_score": 0.9205523729324341, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1431, "end": 1466, "key": "refugee_pads:000144:14:1:0", "source": "camp2", "luna_reason": "Named assessment supports the reported change in Cameroon’s debt-distress risk.", "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": "refugee_pads", "corpus_id": "refugee_pads:000022", "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:000022:38:1:0", "source": "camp2", "luna_reason": "Survey data supports concrete 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:000022:38:1:1", "source": "camp2", "luna_reason": "Survey data supports reported enrollment-rate disparities.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": " . Prepared by Banyan Global.\n17 56 percent of children under 5 years of age in Burundi are stunted, with 61 percent in Ngozi, 66 percent in Muyinga, 59 percent in\nCankuzo, and 52 percent in Ruyigi: DHS 2016-17\n18 Data as of 2017. See _[https://data.worldbank.org/indicator/sp.dyn.tfrt.in](https://data.worldbank.org/indicator/sp.dyn.tfrt.in)_\n\n\nPage 10 of 86", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000110", "page": 15, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "DHS 2016-17", "probe_tag": "keep", "probe_score": 0.920405924320221, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 199, "end": 210, "key": "refugee_pads:000110:15:2:0", "source": "camp2", "luna_reason": "DHS data support reported stunting percentages across Burundi provinces.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nEnhancing Connectivity and Resilience in the Far North of Cameroon for Inclusiveness Project (P178207)\n\n\n16. **In the Far North region of Cameroon, refugee-hosting areas need special attention due to the increased**\n**demands of hosting displaced populations, and the resulting pressures on public service delivery systems and**\n**infrastructure.** This poor region of Cameroon is greatly impacted by large flows of incoming refugees. According\nto UNHCR statistics, 78,722 refugees, 16.4 percent of Cameroon’s refugee population, are in the Minawao camp\nin Mayo Tsanaga, <sup>27</sup> and the highest number of refugees outside of the Minawao camp are located around Mora\non the axis of the MDK road.\n\n\n17. **Among refugee and host populations in the Far North region of Cameroon, women and young people are the**\n**most vulnerable, and poor connectivity is exacerbating the challenges they are facing.** The proportion of young\npeople in refugee camps without access to education remains high, and women’s literacy is a particularly thorny\nissue. Twenty-one percent of the refugees registered in the Far North them are women between the ages of 18\nand 59, and more than 48 percent of refugees are school-aged children. <sup>28</sup> Climate-resilient infrastructures are\nimportant for supplying various camps with core relief resources and improving refugee and host communities’\naccess to the basic socioeconomic infrastructure. The absence of reliable means of transport and financial\nsupport for families—maternal and child support—are the two main challenges for the refugees and host\ncommunities in the Far North of Cameroon. These challenges prevent them from attending and completing\neducation or accessing health centers, even when school and health infrastructure is available. In addition,\nwater, sanitation, and hygiene infrastructure is needed in schools, and", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000003", "page": 18, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR statistics", "probe_tag": "keep", "probe_score": 0.9508150815963745, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 467, "end": 483, "key": "refugee_pads:000003:18:0:0", "source": "camp2", "luna_reason": "UNHCR statistics support the reported refugee population figures.", "usage_type": "evidential", "specificity": "named"}]}
 {"text": " access to credit, learns about new market opportunities,\nand acquires the skills needed to successfully operate their businesses. <sup>22</sup> Studies of women entrepreneurs in Uganda find\nthat women who work closely with a mentor—often male, and usually a family member—are more likely to transition\ninto higher-profit sectors. <sup>23</sup> <sup>24</sup>\n\n15. **Additional factors that block women from developing growth-oriented enterprises in profitable sectors are**\n**related to the failure of existing business development services to address the needs of women-owned firms** .\nAccording to an enterprise survey conducted in 2014, MSMEs lacked key skills needed for business growth. Only 28\npercent of firms surveyed said they do book-keeping to track revenues and expenses; a mere 10 percent had invested in\ntraining for employees; and just 36 percent had access to the internet. Female-owned firms appear to be particularly\nlacking when it comes to the use of standard business practices. A recent microenterprise survey showed a gender gap\nof 24 percentage points on an index of adoption of good business practices. Few training courses address the specific\nchallenges of formalizing a business, including meeting tax obligations, preparing proper records, fulfilling reporting\nrequirements, and obtaining licenses. Training tends to focus on limited topics, such as financial or computer literacy,\nbut leaves out training in life skills and support for network. Yet, global evidence demonstrates that developing socioemotional skills, through psychology-based trainings, are as important to enterprise success as strengthening business\nskills. <sup>25</sup> Finally, many business development services continue to train women for sectors where women-owned firms are\nover-represented, such as small trade or food service, rather than where they could diversify their business and earn\nhigher profits.\n\n\n19 Delecourt, S. and Fitzpatrick, A. 2021.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000088", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "enterprise survey", "probe_tag": "keep", "probe_score": 0.9434184432029724, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 603, "end": 620, "key": "refugee_pads:000088:14:1:0", "source": "camp2", "luna_reason": "Existing 2014 survey supports the finding that MSMEs lacked key business skills.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "microenterprise survey", "probe_tag": "keep", "probe_score": 0.9146700501441956, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1009, "end": 1031, "key": "refugee_pads:000088:14:1:1", "source": "camp2", "luna_reason": "Survey provides the attributed 24-point gender gap finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "</u>_ .\nAccording to the latest Annual School Census, public schools enroll 30 thousand refugee students (in 1,681 schools)\nand 280 thousand IDPs (in 1,852 schools). While IDP children are concentrated in three Darfur states (68 percent of\n\n\nPage 14 of 40", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000024", "page": 18, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Annual School Census", "probe_tag": "keep", "probe_score": 0.9861, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 32, "end": 52, "key": "sample:refugee_pads:000024:18:2:0", "source": "gold", "luna_reason": "Census data support enrollment figures for refugee students.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " to become self-sufficient.\n\n\n8. **The economic inclusion package would benefit ten to 20 percent of** **_Tekavoul_** **beneficiary**\n**households**, which would exit the program on an annual basis. The average cost of the economic inclusion\npackage would be US$470 per beneficiary. In terms of the benefits, facilitating access to wage employment\nor likely more productive self-employment opportunities, is estimated to yield a four percent increase in\nearnings per beneficiary. The EPCV data has baseline annual earnings for the not in employment, education,\nor training at US$1,764. If a working life of 25 years were assumed (given that some beneficiaries will be\nexiting the program at a young age and others closer to retirement), this would equate to net gains of\nUS$3,145 per beneficiary over a working life. Under these assumptions, the IRR of 16 percent for the economic\ninclusion package would exceed the discount rate of 10 percent.\n\n\n**Strengthening the shock response system for households vulnerable to climate-shocks**\n\n\n9. T **he** **_Elmaouna_** **program and accompanying EWS represent potentially significant benefits at the**\n\n\nPage **53** of **61**", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000045", "page": 58, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "EPCV data", "probe_tag": "keep", "probe_score": 0.9183592200279236, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 484, "end": 493, "key": "refugee_pads:000045:58:2:0", "source": "camp2", "luna_reason": "EPCV data provides baseline annual earnings used in the economic analysis.", "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": "refugee_pads", "corpus_id": "refugee_pads:000086", "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": "refugee_pads:000086:31:0:1", "source": "camp2", "luna_reason": "Names administrative data as a verification source without showing data 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": "refugee_pads:000086:31:0:2", "source": "camp2", "luna_reason": "Administrative data is listed without a concrete finding or demonstrated analytical use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "> <br>|<br>**Responsible: Implementing agencies**<br>**/Bank**|<br>**Responsible: Implementing agencies**<br>**/Bank**|<br>**Responsible: Implementing agencies**<br>**/Bank**|**Stage: Throughout**|**Due Date :**<br>**Ongoing**|**Status:**<br>**Ongoing**|\n|**Capacity**|**Capacity**|**Rating:**|**SUBSTANTIAL**|**SUBSTANTIAL**|**SUBSTANTIAL**|**SUBSTANTIAL**|**SUBSTANTIAL**|\n|**Description:**Lack of institutional capacity of the Project<br>Coordination Unit (PCU) located in DGE to carry out Project<br>management,<br>monitoring<br>and<br>evaluation,<br>including<br>procurement,<br>disbursement,<br>financial<br>management<br>and<br>safeguards could slow project implementation.<br> <br>This risk is compounded by extremely long national<br>**_procurement procedures_** which affect the speed of project<br>implementation. The delays result from the low threshold for<br>prior review and the centralization of notices and results<br>publication at DGMP. A survey conducted in 2010 showed that<br>the procurement process could take anywhere between nine to<br>fourteen months.|**Description:**Lack of institutional capacity of the Project<br>Co", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000136", "page": 69, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "survey conducted in 2010", "probe_tag": "confusion", "probe_score": 0.6560235619544983, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 958, "end": 982, "key": "refugee_pads:000136:69:2:0", "source": "camp2", "luna_reason": "Past survey provides a concrete finding about procurement duration.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " phase of the program that will look into extending the BRT lines to the southern\nand eastern suburbs of Beirut. This ambitious project will be the first mass transit and regular transport\nsystem in Lebanon in over 50 years, in a complex political-economy context in the country and the sector\n(alignment, informal operators, behavioral change, institutional). It is a vital project in tackling traffic\ncongestion, contributing to growth and connectivity between various Lebanese regions, and in providing\naffordable and reliable transport.\n\n\n14. **The proposed project will provide clean, affordable, and reliable transportation to middle- and**\n**low-income Lebanese and Syrians.** Currently, only the very poor Lebanese and Syrians use the existing\npublic transport system due to lack of alternatives. The planned system is designed to attract middle- and\nlow-income Lebanese and Syrians by substantially upgrading the quality of services to achieve modal shift\nwhile keeping prices affordable. Traffic surveys have shown that Syrians also rely significantly on public\ntransportation to meet their transportation needs and already represent between 30 percent and 40\npercent of users of the existing public transport system and are expected to significantly benefit from the\nnew improved services. The planned BRT project with its associated feeder network will cover about half\nof the country and will reach over 50 percent of all Lebanese and Syrians in Lebanon.\n\n\n15. **In addition, the project will create short-term jobs in the construction sector that has historically**\n**been a major employer for the low-skilled Lebanese and Syrians in Lebanon.** Before the Syria conflict,\nthe construction sector employed more than 100,000 workers (approximately 10 percent of the labor\nforce). The construction sector is also the second largest employer of Syrian refugees in Lebanon (24.1\npercent), after household work (26.5 percent). The employment of Syrians in the construction sector does\nnot displace the Lebanese labor force since over the past decade, the skilled labor force in construction\nhas been", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000074", "page": 16, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Traffic surveys", "probe_tag": "confusion", "probe_score": 0.4189385771751404, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 998, "end": 1013, "key": "refugee_pads:000074:16:1:0", "source": "camp2", "luna_reason": "Past traffic surveys support a concrete finding about Syrian public-transport use.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "<br>supervisors. MOE will then evaluate teachers against this<br>framework to identify teacher professional development needs<br>and to determine teachers’ placement on the career path<br>(certification level). Data should be disaggregated by gender.|MOE Teacher<br>evaluation records|Third Party|The verification agency will verify<br>teacher evaluation records.|\n|**DLR#4.4.**Number of K‐12<br>teachers trained and certified <br>|In‐service training for grade 4 to 10 teachers to be delivered<br>with the aim of aligning teacher skills and competencies with<br>the new Teacher Standards. The training would also place<br>emphasis on the application of targeted instruction strategies<br>and the use of student assessments (formative and<br>summative). Instructional support materials, whether paper or<br>technology based, that are closely aligned with the curriculum<br>and that teachers will be trained on, will be introduced as<br>supplementary means for fostering improved teaching<br>practices. Successful completion of the training by the<br>awarding of a teacher certificate will serve ", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 45, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "evaluation records", "probe_tag": "confusion", "probe_score": 0.5041353702545166, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 266, "end": 284, "key": "refugee_pads:000127:45:2:0", "source": "camp2", "luna_reason": "Future third-party verification of records is planned monitoring machinery.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "teacher evaluation records", "probe_tag": "confusion", "probe_score": 0.5041353702545166, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 336, "end": 362, "key": "refugee_pads:000127:45:2:1", "source": "camp2", "luna_reason": "Future verification of records is planned monitoring machinery, not existing data use.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "_Sierra Leone_\n\n\nPRICES and GOVERNMENT FINANCE\n\n1981 1991 2000 2001 Inflation (%)\n_Domest)c_ _pHces_\n_(% change)_ c 1\nConsumer prices 16 7 102 7 -0.9 3 0 30 _< _\nImplicit GDP deflator 8 7 128 8 6 2 6 1 20\n\n_Govemment finance_ _10_\n_(% of GDP,_ _includes curent_ grants) 0\nCurrentrevenue .. 112 182 178 .10. 98 97 93 99 00 01\nCurrent budget balance .. -5 8 -4.5 -7 1 - GDP deflator _ CPI\nOverall surplus/deficit -10 4 -10.6 -12 3\n\n\nTRADE\n\n1981 1991 2000 2001 Export and Import levels (USS mnIll.)\n_(US$ millions)_\nTotal exports (fob) 147 176 75 78 400\nRutile . 72\nDiamonds (recorded) 32 10 21 300\nManufactures\nTotal imports (cHf) 317 158 161 303 20\nFood . 53 66 72 100\nFuel and energy 26 29 3d _ _8_\nCaptal goods .. 38 18 22  - __\n96 D6 97 9o 99 00 01\nExport price index _(1995=100)_ 90 86 87\nImport price Index (1995=100) 93 93 92 mExports ***Mrrports**\nTerms of trade (1995-100) 97 93 94\n\n\n\nBALANCE of PAYMENTS\n\n\n\n1981 1991 2000 2001 Curmnt account balance to GDP _(%)_\n_(US$_ _millions)_\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\n\n\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\nNet income -28 -60 -18 -20\nNet current", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000052", "page": 61, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Import price Index", "probe_tag": "confusion", "probe_score": 0.10835491865873337, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 792, "end": 810, "key": "refugee_pads:000052:61:0:1", "source": "camp2", "luna_reason": "Standalone table index label with figures, not an independent data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "Financial Management**\n\n69. **The project will be implemented by the** **_Cellule Filets Sociaux_** **, which is currently**\n**implementing the PFS** . Fiduciary compliance for that project is deemed satisfactory, and the\nunaudited interim financial reports (IFRs) for the project have been submitted on time and found\nacceptable. In addition, CFS has adequate and qualified staff to handle the financial management\n(FM) tasks of the proposed project, although some additional support will be required. Its current\nfinancial management team consists of a specialist on administrative and financial transactions\nand a senior accountant at the central level, as well as two assistant accountants at the regional\nlevel. CFS is also in the process of hiring an internal auditor.\n\n70. **For the proposed project, CFS will hire an additional accountant to be based in**\n**N’djamena.** She or he will perform day-to-day accounting activities and record transactions in the\ncentral MIS and database. In the new regional offices, assistant accountants will be hired to\nperform day-to-day financial transactions.\n\n\n33 A review of the emergency cash transfer project in Niger (Safety Nets Project, Niger P123399) shows that cash transfers were\nused primarily for better and more diverse food (67–90 percent), drinkable water (urban settings), reinvestment (animals) and debt\nrelief.\n34 Data collected in Sri Lanka on start-up costs for 2,019 urban microenterprises show that 10 percent of firms started with US$100\nor less and 23 percent with US$500 or less. Previous work on Mexican microenterprises, find a similar range of starting capital\nlevels for Mexican microenterprises, with many starting with low amounts. Several studies, including randomized experiments\nthat give one-time grants of US$100 or US$200 to microenterprise owners, find high", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000112", "page": 35, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Data collected in Sri Lanka", "probe_tag": "confusion", "probe_score": 0.8441522121429443, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1375, "end": 1402, "key": "refugee_pads:000112:35:1:0", "source": "camp2", "luna_reason": "Existing Sri Lankan data supports concrete start-up cost findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for Data<br>Collection|Monitoring project implementation including reporting from beneficiaries. BDF data fed to MINEMA.|\n|Responsibility for Data<br>Collection|BDF and MINEMA|\n|**Beneficiaries of matching grant that are still operational one year after intervention (Percentage)**|**Beneficiaries of matching grant that are still operational one year after intervention (Percentage)**|\n|Description|Quantitative indicator counting number of beneficiaires that received matching grants and that are<br>operational 1 year after the intervention.|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for Data<br>Collection|Monitoring project implementation including reporting from beneficiaries. BRD data fed to MINEMA.|\n|Responsibility for Data<br>Collection|BRD and MINEMA.|\n|**Households benefiting from graduation programming (Number)**|**Households benefiting from graduation programming (Number)**|\n|Description|Quantitative indicator counting number of households that benefit from graduation programming.|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for Data<br>Collection|Monitoring project implementation.|\n|Responsibility for Data<br>Collection|MINEMA.|\n|**Businesses that benefit from partial credit guarantee scheme (Number)**|**Businesses that benefit from partial credit guarantee scheme (Number)**|\n|Description|Quantitative indicator counting number of businesses that benefit from the BDF partial credit guarantee<br>scheme.|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Method", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000188", "page": 47, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "BDF data fed to MINEMA", "probe_tag": "confusion", "probe_score": 0.6196142435073853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 189, "end": 211, "key": "refugee_pads:000188:47:1:0", "source": "camp2", "luna_reason": "Project monitoring data flow, not an existing dataset used for analysis.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "BRD data fed to MINEMA", "probe_tag": "confusion", "probe_score": 0.6440773010253906, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 826, "end": 848, "key": "refugee_pads:000188:47:1:1", "source": "camp2", "luna_reason": "Project monitoring data transfer is named without substantive analytical use.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "; sulfate (SO42); and total dissolved solids (TDS). The LRA then uses a simple Water Quality\nIndex (WQI), which presents the advantage of communicating water quality information in an\nunderstandable way for all stakeholders. The WQI summarizes a large amount of water quality data in\nscores reported as a total number between 1 and 100, with (a) 90–100 as excellent, (b) 75–90 as good,\n(c) 60–75 as fair, (d) 40–60 as marginal, and (e) 0–40 as poor. Under this component, the number of\nlocations will be increased to 20 and support will be mainly in the form of water quality measurement\nequipment, which could also expand the water quality indicator measured (such as BOD <sup>52</sup> ).\n\n\n116. **Improving water resources modeling** . Over time, the LRA will need to develop a systemwide modeling of the upper-catchment (hydrology, water quality, and so on), which will support\nmonitoring progress during the implementation of the MoE’s Business Plan for Combating Pollution\nin Qaraoun Lake. The LRA has already existing surface and groundwater flow models (such as HECRAS and Modflow) and these will be a good basis to expand to the wider upper catchment modeling.\nUnder this component, a water expert will be hired to support in assessing existing models, current,\nand projected water balance and integrate as possible current models to a wider upper catchment\nmodeling. The TOR of the water expert was discussed and is in advanced stage of preparation.\n\n\n117. **Raise awareness** . The LRA will continue to raise awareness about the need to clean up the\nLitani River by undertaking awareness and clean-up campaigns. It is important to involve all\nstakeholders in order to change the behavior of water users. The impact of awareness should be to the", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000036", "page": 39, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "water quality data", "probe_tag": "confusion", "probe_score": 0.3260340988636017, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 262, "end": 280, "key": "refugee_pads:000036:39:1:0", "source": "camp2", "luna_reason": "Existing water quality data are summarized into WQI scores and categories.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "\nUgandan research institutions will be a key partner in implementing the M&E framework building on existing data\nreports and in partnership with local research institutions. The PSFU PIU will work closely with Ugandan research\ninstitutions for three reasons. First, to coordinate the various data collections so as to be more efficient in utilizing\nall existing firm-level data. Second to identify and collect additional data with respect to jobs and firm productivity.\nThird, to use the data collected on an ongoing basis make suggestions to the PSC to improve the project impact. <sup>48</sup> [^48: 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.]\nAll data will be disaggregated by gender, refugee, host community, and non-host community nations to ensure\nadequate targeting and collection of results for targeted populations.\n\n\n**C. Sustainability**\n\n\n79. In principle, the project components are based on implementing interventions that are fully financially\nsustainable while generating the largest possible impact. Although the rebates offered to borrowers under\nWindow 1 of Component 1 are not recoverable, from a cost-benefit perspective the extension of the amortization\nperiod of MSME loans is consistent with the BoU policy and will contribute to a reduced probability of default of\nMSMEs and to the stability of the financial sector by reducing NPLs and also to preserving functioning MSMEs and\njobs that might otherwise get impaired. It will also support revival of otherwise viable enterprises and therefore,\ncontribute to growth and to protecting institutional, social and financial capital, that might otherwise have been\nlost. Windows 2 and 3 of Component 1 are financially self-sustaining: Tier 3 and 4 institutions (MFDs, MFIs, and\nSACCOs) will be provided with access to concessional credit lines. These credit lines will be limited 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", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000073", "page": 36, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "firm-level data", "probe_tag": "confusion", "probe_score": 0.3304522633552551, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 362, "end": 377, "key": "refugee_pads:000073:36:1:0", "source": "camp2", "luna_reason": "Existing firm-level data are used to coordinate collections and improve project impact.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nSouth Sudan Health Sector Transformation Project (HSTP) (P181385)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Frequency|Quarterly|\n|---|---|\n|Data source|Quarterly Health Facility Assessment|\n|Methodology for Data<br>Collection|TPM report|\n|Responsibility for Data<br>Collection|TPM / PMU|\n|**Percentage of general service availability score for refugees.**|**Percentage of general service availability score for refugees.**|\n|Description|Service availability is described by an index using the three areas of tracer indicators (infrastructure, workforce, and<br>utilization). This is made possible by expressing the indicators as a percentage score un-weighted average of the<br>three areas|\n|Frequency|Quarterly|\n|Data source|Quarterly Health Facility Assessment|\n|Methodology for Data<br>Collection|TPM report|\n|Responsibility for Data<br>Collection|TPM / PMU|\n\n\n\n**Monitoring & Evaluation Plan: Intermediate Results Indicators by Components**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Component 1: Provision of Basic Health Services Nationwide|Col2|\n|---|---|\n|**Percentage of Gender-Based Violence Services provided (Percentage) **|**Percentage of Gender-Based Violence Services provided (Percentage) **|\n|Description|Percentage of SGBV survivors who treated for assault + SGBV cases provided with emergency contraceptives +<br>SGBV cases referred out + SGBV survivors given PEP + Clinical management of rape + OPD Rape and GBV services|\n|Frequency|Quarterly|\n|Data source|DHIS|\n|Methodology for Data<br>Collection|DHIS2|\n|Responsibility for Data<br>Collection|MoH and UNICEF; Measures subcomponents 1.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000006", "page": 46, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Quarterly Health Facility Assessment", "probe_tag": "confusion", "probe_score": 0.2195861041545868, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 148, "end": 184, "key": "refugee_pads:000006:46:0:0", "source": "camp2", "luna_reason": "Named assessment declared as the data source for a quarterly health-service indicator.", "usage_type": "declaration", "specificity": "named"}, {"text": "DHIS", "probe_tag": "confusion", "probe_score": 0.45181700587272644, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1450, "end": 1454, "key": "refugee_pads:000006:46:0:1", "source": "camp2", "luna_reason": "DHIS is identified as the data source for a reported GBV services indicator.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "**The World Bank**\nMauritania Social Safety Net System Project II (P171125)\n\n\nwill be published in the UNDB online, on the World Bank’s external website, and in at least one newspaper of\nnational circulation in the Borrower’s country, or in the official gazette, or a widely used website or electronic\nportal with free national and international access. SPNs for goods and non-consulting services will be procured\nusing National Competitive Bidding (NCB). Expressions of Interest for all consulting services with a cost less\nthan US$500,000 will be published in at least one newspaper of national circulation in the Borrower’s country.\n\n\n23. **Fraud and corruption.** All procurement entities as well as bidders and service providers (that is,\nsuppliers, service providers, and consultants) shall observe the highest standard of ethics during the\nprocurement and execution of contracts financed under the project in accordance with paragraphs 1.16 and\n1.17 (Fraud and Corruption) of the Procurement Guidelines and paragraph 1.23 and 1.24 (Fraud and\nCorruption) of the Consultants Guidelines, and the _‘Guidelines on Preventing and Combating Fraud and_\n_Corruption in Projects Financed by IBRD Loans and IDA Credits and Grants’_, dated July 1, 2016 in addition to\nthe relevant articles of the national public procurement legislation.\n\n\n**_Procurement Arrangements_**\n\n\n24. The project must use procurement methods for all activities in accordance with the World Bank’s\n‘Procurement Regulations for IPF Borrowers’ (Procurement Regulations) dated July 2016 and revised in\nNovember 2017 and August 2018 under the NPF.\n\n\n**_Assessment of Procurement Capacity of the Implementing Agency and Risks_**\n\n\n25. **The procurement capacity is considered moderately satisfactory** . The _Tadamoun_ Procurement team\nhave carried out procurement activities for the first phase project (P150430", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000045", "page": 51, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNDB online", "probe_tag": "confusion", "probe_score": 0.8125324845314026, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 103, "end": 114, "key": "refugee_pads:000045:51:0:0", "source": "camp2", "luna_reason": "Procurement publication venue, not a data resource used for analysis or evidence.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": ">144 76 68 34|Col11|Col12|Col13|TOTAL<br>79,668<br>29,133<br>23,091<br>12,954<br>4,534<br>1,316|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|**_Total_**|**_8,186_**<br>|**_14,022_**<br>|**_23,155_**<br>|**_22,698_**<br>|**_21,491_**<br>|**_10,724_**<br>|**_8,099_**<br>|**_4,275_**<br>|**_18,551_**<br>|**_9,069_**<br>|**_6,798_**<br>|**_3,628_**<br>|**_150,696_**<br>|\n\n\n\n_Source: NPTP Database, Ministry of Social Affairs_\n\n**Essential Healthcare Package (EHCP)**\n\n5. The project will provide beneficiaries with a package of essential healthcare services\ncomprising of the following: (i) three age specific and gender wellness packages (ages 0-18,\nfemales 19 years and above, males 19 years and above); (ii) two care packages for the two\ncommon NCDs in Lebanon; diabetes and hypertension; and (iii) a", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 35, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "NPTP Database", "probe_tag": "confusion", "probe_score": 0.6819568276405334, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 397, "end": 410, "key": "refugee_pads:000020:35:1:0", "source": "camp2", "luna_reason": "Named database cited as the source for the table's presented figures.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "\nrange of secondary and tertiary care facilities. However, continuity and sustainability of health\nservice delivery in Jordan is at risk of being severely compromised as a result of the upsurge in\ndemand for healthcare by the influx of the Syrian refugees.\n\n\n7. The healthcare needs of the Syrian refugees are different from those of the settled\npopulations because of the different demographic mix, living conditions and vulnerabilities,\nrequiring therefore a different mix of services and mode of health system response to respond to\ntheir needs. Such an upsurge both in demand and the mix of healthcare needs could easily\noverwhelm the existing facilities especially in Jordan where the absorptive capacity is relatively\nlow given its own population size relative to the size of the refugee population. According to\nUNHCR data, 78 percent of the Syrian refugees are vulnerable requiring additional assistance.\nThis include women (49 percent), children under the age of 12 (40 percent), and elderly (2.1\npercent). In addition, 23 percent of Syrian refugees have chronic diseases or serious medical\nconditions that require medical follow up. Comparative morbidity data show a different disease\nprofile with increased levels of morbidity for Syrian refugees than Jordanians which may affect\nthe disease burden in the future. According to Jordan’s national cancer statistics, Syrian refugees\npresenting with cancer at health facilities rose from 134 in 2011 to 169 in the first quarter of\n2013, representing 14 percent increase in Jordan’s total cancer disease burden. Similarly, MOH\nmorbidity data show a rise in selected communicable diseases. For example, TB case notification\nincreased from 5/100,000 among Jordanians in 2009 to 13/100,000 among Syrian refugees in\n2013. While no measles cases have been reported in Jordan since 2009, recent MOH data show\nthat 18 Jordanians and 23 Syrians have been diagnosed with the disease in 2013. Polio which had\nbeen eradicated since 1999 was also detected in two cases in 2013. With this higher demand for\n\n\n1414 World Health Organization Statistics, 2013\n\n\n34", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000064", "page": 33, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "national cancer statistics", "probe_tag": "keep", "probe_score": 0.9172952175140381, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1347, "end": 1373, "key": "refugee_pads:000064:33:1:2", "source": "camp2", "luna_reason": "Statistics support reported cancer increases among Syrian refugees.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "MOH\nmorbidity data", "probe_tag": "confusion", "probe_score": 0.864539623260498, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1579, "end": 1597, "key": "refugee_pads:000064:33:1:3", "source": "camp2", "luna_reason": "MOH morbidity data support a concrete finding about rising communicable diseases.", "usage_type": "evidential", "specificity": "named"}, {"text": "MOH data", "probe_tag": "keep", "probe_score": 0.938871443271637, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1845, "end": 1853, "key": "refugee_pads:000064:33:1:4", "source": "camp2", "luna_reason": "MOH data support reported measles diagnoses among Jordanians and Syrians in 2013.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "decentralized \"partnership\" approach to governance that involves line ministnes, NGOs, CBOs, <sup>and</sup> <sup>civil</sup>\nsociety. NCRRR/NaCSA has been supported by the African Development Bank, UNDP, DflD, and IDA.\nIt has provided assistance for more than 500,000 displaced persons, shelter rehabilitation, vocational\ntraining, trauma healing, and micro-finance programs. It has financed 275 community-based sub-projects\nin the areas of health, education, water and sanitation, agriculture and capacity building. These <sup>tasks</sup>\nhave been carried out with considerable support from the 260 NGOs registered in Sierra Leone, of which\n68 are international. These NGOs have been instrumental in ensuring service delivery to remote <sup>areas</sup>\nwhere public services were absent.\n\n\n**3.** **Sector** **issues** **to be** **addressed** **by the** **project and strategic choices:**\n\n**Poverty in a Post-Conflict** **Environment.** Section 2 above outlines the principal characteristics\nof poverty in Sierra Leone and the condition of the country at the close of the civil war. <sup>Access</sup> <sup>of the</sup>\npoor majority to food, shelter, employment opportunities and social services are among the <sup>principal</sup>\n\n\n\nconstraints to post-conflict reconstruction, economic recovery and poverty reduction. District recovery\nassessments reveal that over 340,000 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", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000176", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "District recovery\nassessments", "probe_tag": "confusion", "probe_score": 0.2696845233440399, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1323, "end": 1352, "key": "refugee_pads:000176:9:0:0", "source": "camp2", "luna_reason": "Assessments provide a concrete finding on war-destroyed and rebuilt houses.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "\nComponent 2).\n\n10. Quality of Care will be monitored and maintained through the MoPH PHCC accreditation\nprogram. The PHC accreditation program was initiated in 2009 by the MoPH in collaboration\nwith Accreditation Canada International (ACI). With support of local experts, the program was\ndeveloped, piloted and implemented in a phased approach in PHC network facilities. Currently,\n34 out of the 75 PHCCs are accredited and the other 42 are preparing for accreditation in 2015.\nMoreover, quality of clinical care will be monitored by the MoPH through the EHCP clinical\nindicators listed in Annex V.\n\n**Enrollment**\n\n11. Contracted PHCCs will receive from CMU of PCM through the MoPH the list of\nbeneficiaries in their catchment area and will be responsible for enrolling those beneficiaries\nthrough marketing and outreach campaigns. Once enrolled, individuals will be exempted from\npayment for EHCP services as they will be fully subsidized by the government. A nominal fee of\naround US$12 will be paid by each household for registration. Upon enrollment, each member of\nthe household will receive a photo identification enrollment card which will be saved in the\nsystem for proper verification of beneficiaries.\n\n\n37", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 36, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "EHCP clinical\nindicators", "probe_tag": "confusion", "probe_score": 0.1874558925628662, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 556, "end": 580, "key": "refugee_pads:000020:36:1:0", "source": "camp2", "luna_reason": "Future monitoring through indicators is planned, not existing data use.", "drop_reason": "promissory", "specificity": "named"}]}
-{"text": " index.\nb) Middle East and North Africa, World Bank classification\nc) High-income countries (HICs), according to the World Bank FY22 classification\nd) Djibouti, Eritrea, Ethiopia, and Somalia\ne) For consistency across countries, this table employs nutrition estimates from the UNICEF-WHO-WB Joint Child\nMalnutrition Estimates, which indicate a substantially higher rate of stunting than found by the Djibouti 2019\nSMART survey.\n\n\nPage 13 of 64", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000131", "page": 17, "chunk": 7, "split": "holdout_annotate", "spans": [{"text": "UNICEF-WHO-WB Joint Child\nMalnutrition Estimates", "probe_tag": "keep", "probe_score": 0.9220291972160339, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 277, "end": 325, "key": "refugee_pads:000131:17:7:0", "source": "camp2", "luna_reason": "Named estimates support a tabled comparison of stunting rates.", "usage_type": "evidential", "specificity": "named"}, {"text": "Djibouti 2019\nSMART survey", "probe_tag": "confusion", "probe_score": 0.8483895659446716, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 400, "end": 426, "key": "refugee_pads:000131:17:7:1", "source": "camp2", "luna_reason": "Named survey provides the comparison basis for stunting estimates.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nSPF: Improved Livelihoods for Internally Displaced Persons in Azerbaijan (P178125)\n\n\napproximately 45 students per round of participants.\n\n20. Criteria for selection of participants will include IDPs who are considered vulnerable as\nmeasured by: a) housing status, b) income level, c) level of education, d) access to services, e)\nemployment status, and f) disability. Selection of participants will also aim to include a balance of men\nand women, with at least 50% of beneficiaries being women. Applicants who are seeking training in\nskills that have been determined in the needs survey as being in high demand will also be preferred\nover those proposing training in areas where there is more limited labor market demand. Skills areas\nmay include, among others: business/trade, agri-business, vocational activities (i.e., carpenter, cook,\nhairdresser), use of digital technology, among others, with a focus on employment potential and to\nthe extent possible avoiding gender stereotypes. A Selection Committee will be formed to review and\nendorse the list of approved applicants and the most appropriate training institute or apprenticeship\nfor each applicant. As it is expected that the majority but not all participants will successfully complete\nthe training courses, a modest oversubscription will be planned with the aim of reaching or exceeding\nthe target of 520 total beneficiaries.\n\n21. To understand better the real opportunities for IDPs, particularly about the types of\nprofessions that are most in demand in the project areas, the project will ask IDPs (as part of the\napplication process) to fill out a basic labor market assessment form. The process for this will be a day\nwhere the mentors work with potential project participants and explain to them how they can find\nout more about the kinds of opportunities they have in their communities and how to find out about\npotential income from different activities. In addition to the information collected by IDPs from local\nemployers, the State Employment Agency and", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000007", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "needs survey", "probe_tag": "confusion", "probe_score": 0.7521653771400452, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 594, "end": 606, "key": "refugee_pads:000007:15:0:0", "source": "camp2", "luna_reason": "Survey finding on high-demand skills informs participant selection.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": " participation in decisions to make education\nservice delivery more effective and accountable.\n\n\n51 GoP and WHO (World Health Organization). 2019. _Review of Essential Health Services in Pakistan Based on DPC3._\n52 World Bank. 2009. _Protecting Pro‐Poor Health Services during Financial Crises. Lessons from Experience._\n53 World Bank. 2018. _Health Financing Systems Assessment Pakistan using WHO Data._\n54 Ministry of Federal Education and Professional Training. 2018. _National Education Policy Framework._\n55 ASER Pakistan. 2018. _Annual Status of Education Report ‐ National._\n\n\nPage 23 of 47", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000085", "page": 27, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "WHO Data", "probe_tag": "confusion", "probe_score": 0.6816293001174927, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 394, "end": 402, "key": "refugee_pads:000085:27:2:0", "source": "camp2", "luna_reason": "Bibliography title fragment, not evidence of data being used.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": " SEP, in their\ncapacity of coordinators and regulators for social protection. Based on the needs identified under the Merankabandi\nProject, training and technical support will be provided, as well as assistance with coordination costs. A special focus will\nbe put in strengthening SEP-CNPS capacity to manage the Social Registry and to coordinate its roll out with partners.\n\n85. This sub-component will also support some basic analytical services to build the evidence base which the Technical\nCommittee and the SEP could use for policy and program design.\n\n\n**Sub-component 5.2: Monitoring, Evaluation and Capacity Building (US$5 million)**\n\n\n<mark>86.</mark> <mark>The project will support strong monitoring practices to ensure the scaling up of safety nets interventions under</mark>\n<mark>the Merankabandi project and the expansion of coverage and delivery of payments in accordance to the key project</mark>\n<mark>results indicators to achieve the intended outcomes.</mark> <mark>This subcomponent would support the development of social</mark>\n<mark>accountability and citizen engagement mechanisms with the support of local-level institutions and stakeholders. The</mark>\n<mark>project will introduce monitoring mechanisms to prevent errors, fraud, and corruption in delivery through monitoring</mark>\n<mark>and validation of payments. The project will provide support to process assessments and evaluations during</mark>\n<mark>implementation. IBM mechanisms will be put in place to assess satisfaction of beneficiaries on project performance and</mark>\n<mark>to collect real time data on the evolving vulnerability context.</mark>\n\n<mark>87.</mark> <mark>This subcomponent will support a wide range of capacity-building activities including a range of training modules</mark>\n<mark>on technical and operational aspects required for the implementation of the safety nets and", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 32, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Social Registry", "probe_tag": "confusion", "probe_score": 0.08348707854747772, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 313, "end": 328, "key": "refugee_pads:000130:32:1:0", "source": "camp2", "luna_reason": "Registry is named, but its data are not shown informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "real time data", "probe_tag": "drop", "probe_score": 0.014520137570798397, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1579, "end": 1593, "key": "refugee_pads:000130:32:1:1", "source": "camp2", "luna_reason": "Project will collect this data during future monitoring activities.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": ".....................................64**\n\n**Annex 5: Economic and Financial Analysis ..............................................................................69**\n\n**Annex 6: Major Related Projects Financed by the World Bank and/or other Agencies ......81**\n\n**Map IBRD 43032**\n\n\nvi", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Map IBRD 43032", "probe_tag": "drop", "probe_score": 0.03682317957282066, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 267, "end": 281, "key": "refugee_pads:000144:5:1:0", "source": "camp2", "luna_reason": "Standalone map label, not a cited or used data resource.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": " on sub-project choices –<br>Water, Education, Health, Infrastructure)<br> <br>|\n|12-48 months| <br>Implementation of all components’<br>activities<br> <br>Community consultation and<br>inclusion<br> <br>Capacity building of project staff<br> <br>Technical quality control<br> <br>Selection of investments according to<br>selection criteria<br> <br>Collection of M&E data<br> <br>Adherence to fiduciary procedures<br> <br>Policy dialogue with government<br> <br>Information sharing and coordination<br>with other donors/agencies<br>supporting NGOs<br> <br>|As above<br>|\n|48 – 60<br>months| <br>Finalization of component activities<br> <br>Collection of end-line M&E data<br> <br>Final technical audit|As above|\n\n\n71", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000071", "page": 81, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "M&E data", "probe_tag": "drop", "probe_score": 0.01219255942851305, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 369, "end": 377, "key": "refugee_pads:000071:81:1:0", "source": "camp2", "luna_reason": "Planned project monitoring data collection, not use of existing data.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": " ToRs for the recruitment of an independent external\nauditor, acceptable to IDA/IBRD, based on acceptable ToRs – who will audit both agencies based on a single contract ; and\n(f) completing the recruitment of an experienced FM specialist officer and an accountant (for the MASS component).\n\n\n**Table 1.2. Risks and Mitigating Measure**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Risks|Risk<br>Rating|Risk Mitigating Measures|Residual<br>Risk<br>Rating|Conditions for<br>Effectiveness<br>(Y/N)|\n|---|---|---|---|---|\n|**Inherent Risk**|**Inherent Risk**|**Inherent Risk**|**Inherent Risk**||\n|**Country level**: Poor<br>governance and slow<br>pace of<br>implementation of<br>public financial<br>management (PFM)<br>reforms that might<br>hamper the overall<br>PFM environment.|H|In the wake of the 2023 PEFA assessment, the PFM<br>bottlenecks identified by the 2023 PEFA informed the<br>design of a PFM reform strategy. A specific TA, with<br>the support of the World Bank and other donors, was<br>implemented to assist the government in developing<br>a coherent PFM strategy based on the PEFA<br>recommendations.<br> <br>The government, with the support of the World Bank<br>and other donors, has since developed a public<br>finance reform roadmap for the period 2024-2027. A<br>PFM reform strategy and associated action plan<br>", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000180", "page": 45, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2023 PEFA assessment", "probe_tag": "keep", "probe_score": 0.9149467945098877, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 770, "end": 790, "key": "refugee_pads:000180:45:1:0", "source": "camp2", "luna_reason": "Existing PEFA assessment identified bottlenecks informing PFM reform strategy.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "W) losses affect the financial performance of WSS service providers as energy costs\naccount for around 30–40 percent of their minimal budgets for operational expenses. While reduction of\nenergy consumption by water utilities may not lead to significant reduction in GHG emissions, as the\ncountry is reliant on hydropower for almost 95 percent of electricity generation, optimizing energy use\nfor water service provision will simultaneously improve financial performance of utilities and overcome\nseasonal constraints in availability of electricity which affects operation of the systems.\n\n\n11. **The burden of deficient water supply is especially affecting the poor.** In rural areas, house\nconnections are available to 34 percent of the poorest households compared to 80 percent in urban areas,\nwhich demonstrates that the gap in services is largely correlated with location rather than income of\nhouseholds. However, the gap between rich and poor in drinking water service provision is much less\npronounced than is commonly seen in other low-income countries. Most of the gap is the result of\nlocation, as most poor people reside in rural areas. In urban areas, about 80 percent of the poorest\npopulation use house connections (compared to 99 percent of the richest households). Data from the\n\n\n20 TajStat. 2020. Population Census Data.\n\n\nPage 10 of 89", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000162", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Population Census Data", "probe_tag": "keep", "probe_score": 0.9220527410507202, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1315, "end": 1337, "key": "refugee_pads:000162:13:1:0", "source": "camp2", "luna_reason": "TajStat 2020 census data source the preceding household-access findings.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " or more pilot agencies; and (d) introducing, where appropriate, mechanisms to enhance oversight\nand monitoring of procurement, including the participation of communities and nongovernmental\nbodies, to enhance performance.\n\n\n**Component 4. Enhancing the use of statistics for policy making**\n\n\n38. The end goal of any statistical system is to produce high-quality data to inform policies and\nmake them publicly available. Achieving this goal requires an investment not only in the production of\nmicro-data (censuses and surveys) and routine statistics (prices, national account, external trade, and so\non) but also in data processing, analyzing, archiving, and dissemination. Given the large demand of the\nnational statistical system, the choice is made to focus either on the areas where the World Bank clearly\nhas a comparative advantage among the donors or areas not supported by the other donors, namely,\nhousehold survey, population census, national account, and archiving and dissemination. At the core of\nall this are two aspects: data collection and capacity building. The philosophy underlying data collection\nis to improve the design of the surveys to take into account the most recent methodological approaches.\nAs for capacity building, the preference is given either to train staff locally or to use the learning-bydoing approach. Three subcomponents are distinguished as follows:\n\n\n**<mark>Subcomponent 4.1. Improving poverty-related data</mark>**\n\n\n39. **Objective** . The objective of this subcomponent is to improve the poverty related data\nproduction and analysis.\n\n\n40. **Current status.** INS has implemented living conditions surveys in 1996, 2001, 2007, and 2014.\nThe last three surveys have used very close methodologies and poverty indicators are comparable over\n\n\nPage 54 of 93", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 57, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household survey", "probe_tag": "confusion", "probe_score": 0.4212111234664917, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 909, "end": 925, "key": "refugee_pads:000044:57:1:0", "source": "camp2", "luna_reason": "Listed as a planned statistical production focus, not existing survey data used.", "drop_reason": "production", "specificity": "vague"}, {"text": "national account", "probe_tag": "confusion", "probe_score": 0.290707528591156, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 946, "end": 962, "key": "refugee_pads:000044:57:1:2", "source": "camp2", "luna_reason": "Listed as an area for statistical production, not existing data use.", "drop_reason": "production", "specificity": "vague"}, {"text": "living conditions surveys", "probe_tag": "confusion", "probe_score": 0.758538007736206, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1629, "end": 1654, "key": "refugee_pads:000044:57:1:3", "source": "camp2", "luna_reason": "Existing survey rounds support comparison of methodologies and poverty indicators.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "\nframework advance the integration of refugees and foster an enabling environment for them to live in safety and\nwith dignity. Uganda is also implementing the Comprehensive Refugee Response Framework (CRRF) in accordance\nwith the New York Declaration for Refugees and Migrants that is guiding and framing all refugee-related activities.\nThese, combine with the aim to ensure that the refugee response provides support to both refugees and RHDs,\nputting them on a path to self-reliance and by bridging humanitarian and development ways of working. Uganda\nhas reiterated its ongoing commitments to refugee protection in the context of COVID-19 in Uganda’s Strategy\nNote on Support to Refugees and RHDs. Since initial eligibility for WHR resources, Uganda has been implementing\nRefugee and Host Community Sector Response Plans for: education; health; water and environment; and jobs and\n\n\n36 Based on the Uganda Refugee Protection Assessment Update August 2-18, 2021.\n\n\nPage 18 of 92", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000073", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Uganda Refugee Protection Assessment Update", "probe_tag": "confusion", "probe_score": 0.8663803339004517, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 902, "end": 945, "key": "refugee_pads:000073:23:1:0", "source": "camp2", "luna_reason": "Named assessment cited as the basis for the surrounding refugee-protection analysis.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "|No system|System functional|\n|Number of workers registered in the employment database<br>(Number)||0.00|30,000.00|\n|Number of employers formalized (Number)||0.00|500.00|\n|Number of beneficiaries enrolled in training database (Number)||0.00|45,000.00|\n|Number of refugee beneficiaries enroled in training database<br>(Number)||0.00|22,500.00|\n|Number of employers receiving technical assistance (Number)||0.00|10,000.00|\n|Proportion of trainees satisfied with the training received<br>(Percentage)||0.00|75.00|\n|Proportion of farmers satisfied with the program (Percentage)||0.00|75.00|\n|Beneficiaries of job-focused interventions (CRI, Number)||0.00|38,000.00|\n\n\nPage 43 of 85", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000114", "page": 46, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "employment database", "probe_tag": "confusion", "probe_score": 0.5755578279495239, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 67, "end": 86, "key": "refugee_pads:000114:46:1:0", "source": "camp2", "luna_reason": "Database is merely named as an indicator source, with no shown data use.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": " a reduction in the poverty rate (headcount poverty)\nand reduction of the poverty gap – as well as to reinforce systems that should allow for such reduction to continue after\nthe project. Currently, a substantial share of the population in Djibouti remains poor (21.1 percent poverty rate in 2017).\nAs for human capital, Djibouti has one of the lowest rankings in MENA and ranks 172 among 188 countries in the HDI.\nNotable challenges include some of the highest rates of stunting and wasting for children under five. Although poverty\nreduction (though hard to attribute without an expensive impact evaluation) is expected to be the main effect of the\nprogram’s expansion, as a second order effect, the project may have an impact on overall human development outcomes\n(although limited given the scope of the proposed conditionalities).\n\n63. **Simulating the impact of PNSF expansion on headcount poverty in Djibouti** . The proposed project aims to expand\nPNSF to cover 5,000 of the poorest and most vulnerable households in Djibouti, providing critical consumption smoothing\nto selected beneficiaries. Based on the latest plans for the expansion of the program and using the latest available\nhousehold survey in Djibouti (Enquête Djiboutienne Auprès de Ménages, EDAM 4), this economic analysis aims to\ncalculate the impact of the proposed cash transfer program on head count poverty. The simulation approximates a US$56\nper month transfer to 5,000 households. The total allocation of the program is simulated through a three-step process.\nFirst, 5,000 households are selected randomly in regions of the interior based on the percentage of poor population\n(excluding Djibouti Ville). Second, the benefits are distributed only to households in these areas. Finally, households are\nrandomly assigned to receive benefits so that their consumption levels are increased, until the target of 5,000 households\nis reached.\n\n\nPage 21 of 44", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 25, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household survey in Djibouti", "probe_tag": "confusion", "probe_score": 0.5144079327583313, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1193, "end": 1221, "key": "refugee_pads:000154:25:1:0", "source": "camp2", "luna_reason": "Existing survey data are used to calculate simulated poverty impacts.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "EDAM 4", "probe_tag": "keep", "probe_score": 0.9406355023384094, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1263, "end": 1269, "key": "refugee_pads:000154:25:1:2", "source": "camp2", "luna_reason": "Named household survey used to simulate cash-transfer impacts on poverty.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " audits and financial verification). The\ntotal loan amount subject to the modified provisions is estimated at between US$38-50 million,\nof which up to US$21 million represent contracts subject to retroactive financing. To mitigate\nthe risk of some international firms not learning of the opportunities on time, packages above\nUS$500,000, which are still to be procured, will additionally have timely notification in UNDB\nonline and the JPD website would include the English version of the advertisement (see Annex 3\nfor further details). All project procurement above the US$5 million threshold will remain\nsubject to standard Bank terms, conditions and policies, including the application of the ACGs.\n\n\n58. Regarding application of Anti-Corruption Guidelines, it should be noted that the JPD\ncontracts do not explicitly contain clauses related to fraud and corruption, but are governed by\nthe national anti-corruption rules providing for the exclusive jurisdiction of the ACC, an\nindependent agency, in cases of fraud and corruption. Therefore, a waiver of some provisions of\nthe World Bank Anti-Corruption Guidelines is sought to rely on the Borrower’s national ACC to\ninvestigate cases of fraud and corruption in the use of project funds for the aforementioned\ncontracts (under US$5 million). The waiver specifically proposes the modification of paragraph\n9 and the deletion of paragraph 10, which currently provide, among others, for the right of the\nBank to inspect accounts, records and all other documents of the Borrower or other recipients of\nloan proceeds relating to the Project. These paragraphs will be substituted with modified\nprovisions stating the obligation of the Borrower to undertake investigations in case of allegation\nof fraud and corruption and provide related reports to the Bank (Modified Anti-Corruption\nProvisions; see Annex 3). This approach is similar and along the lines adopted in Program-forResults Financing (PforR) projects. All other procurement for contracts for goods and services\n\n\n28", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000064", "page": 27, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "UNDB\nonline", "probe_tag": "confusion", "probe_score": 0.6278200745582581, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 416, "end": 427, "key": "refugee_pads:000064:27:1:0", "source": "camp2", "luna_reason": "Procurement notification platform is mentioned without data being used.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": " all of its food requirements <sup>4</sup> [^4: The country recently leased tracts of land in Ethiopia to grow food in an attempt to lower its import bill. Facts in paragraph 2 are also from the same\nsource.] . Therefore, the economy is quite dependent on the service\nsector, specifically the commercial activities that supports the trade sector given the country’s strategic location\nas a Red Sea transit point with about two-thirds of the port’s activities supporting imports and exports to and from\nEthiopia. The country is home to about a million individuals and is multiethnic in nature with Somalis, Afar and\nArabs. Djibouti city accounts for about 70 percent of the country’s population, with the remaining population\nspread across the five regions. In these administrative regions, the rural share varies quite a bit ranging from 40\npercent of the population in Ali Sabieh to 77 percent in Tadjourah. On aggregate about 15 percent of the\npopulation live in rural areas, with the rest residing in the country’s cities and towns.\n\n3. **Djibouti's stability in an otherwise unstable region has made the country a destination for refugees**\n**from neighboring countries** .  The fragile, conflict and violence (FCV) context in countries surrounding Djibouti,\nheightens the need for the country to respond to the needs of refugees and host communities and prepare for\nlikely future refugee flows, asylum seekers and migrants. Unrest in neighboring countries has forced refugees to\nseek shelter in Djibouti since the mid-seventies. United Nations High Commissioner for Refugees (UNHCR) update\non refugees and asylum seekers in Djibouti as of January 31, 2022, states that there are 34,810 such individuals in\nthe country. These populations are concentrated in three regions - Djibouti City (7111), Ali Sabieh (24886) and\nObock (2813). There are two locations within Ali Sabieh - Ali-Addeh (17018) and Holl-Holl (7868). These numbers\nrepresent the total number of refugees and asylum seekers", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000195", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "update\non refugees and asylum seekers in Djibouti", "probe_tag": "confusion", "probe_score": 0.8956204652786255, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1588, "end": 1637, "key": "refugee_pads:000195:11:1:0", "source": "camp2", "luna_reason": "UNHCR update supports the reported refugee and asylum-seeker count.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "CURRENCY EQUIVALENTS\n\n\nExchange Rate Effective Date: January 26, 2004\n\n\nCurrency Unit = I L S 1 = 0.224\n\nUS$1 = 4.461 I L S\n\n\nFISCAL YEAR\nJanuary 1      - December 31\n\n\n\nABBREVIATIONS _AND_ ACRONYMS\n\n\n\n~ _ - **\"_-I-** - - _ _ - _ _ I\n\n\n\n~ _ - **\"_-I-**                                                                                                                                                                                                                                                      -                                                                                                                                                                                                                                                      - _ _ I\n\nBP BankProce&re -- **I** - - - - MOH _ x I _2_ Ministry \" of Health - __ \" .\nMOPT {Ministry of Post and Telecommunication\n\n\n\nCFAA -1Country Financial Accountability Assessment :MOSA 1Ministry of Social Affars\n\nCPAR Country Procurement Assessment Review NGO INon-Govemmental Organization\nDepartment for Intemational Development\nDFID- _ _ -_ (UnlteEl*%&?d I I ~ I \" I _ _ OM \" 9peratlonal Map! **!** \" __\nDGAA Directorate General for Admnistration of Aid OP,Operational Policy\n\nEC European Comssion PA Palestine Authority\nEmergency Municipal Services Rehabilitation\n\nE PEJ?'?, - - - **IPA?** - p r - p APpFus_al pocpmen! - - \n\n\nSecondary Emergency Services Support Project lPCBS\n\n\n\nPalestine Central Bureau of Statistics\n\n\n\nESSP Secondary Emergency Services Support Project lPCBS Palestine Central Bureau of Statistics\nESSR Emergency Services Support Project ;PCT Project Coordination Team\nFIS Financial Information System,PHECS 'Palestine Expenditure and Consumption Survey\nFMIS $Financial and Management Information System **bLCS** !Palestine Living Conditions Survey\nFMIS Manj+gemcnt I;fo-Fatiqn System ~ ~ P F \" _ iProject Prpration Facilgy\n\n\n\n$Financial and Management Information System **bLCS** !", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Palestine Expenditure and Consumption Survey", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1682, "end": 1726, "key": "refugee_pads:000047:1:0:0", "source": "camp2", "luna_reason": "Survey is merely defined in an abbreviation list, with no data use or finding.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "Palestine Living Conditions Survey", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1787, "end": 1821, "key": "refugee_pads:000047:1:0:1", "source": "camp2", "luna_reason": "Survey is only defined in an acronym list; no data use or finding is shown.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": " respective city\ncontract. The TLUs in Yaoundé and Douala will be composed of dedicated staff drawn from the\nCTD and include: a project manager, a civil engineer, a social specialist, an accountant and a junior\nassistant (recent graduate). The TLU personnel will benefit from an additional premium, indexed\non performance and results. In the other cities, the TLUs will mobilize municipal staff in parallel\nto their usual activities due to the scarcity of management staff. In the CUs, the TLUs will bring\ntogether staff from both levels of local government (CU and CA). There will be annual audits of\nthe TLUs.\n\n\n50. The project’s intervention in the northern cities (Maroua and Kousséri) will require\nconflict-sensitive approaches, specific implementation arrangements and possibly adapted project\nactivities. These will be further defined in coordination with other donors intervening in these areas\n(particularly AFD) and based on the findings of the RPBA (expected to be available in Fall 2017).\n\n\n**B.** **Results Monitoring and Evaluation**\n\n\n51. Continuous M&E will be an integral part of project implementation under the overall\nresponsibility of the PCU. Each TLU will be responsible for day-to-day monitoring of project\nactivities at the city level and providing regular updates to the PCU on the implementation of the\nCity Contract. Project monitoring will be based on biannually progress reports, including updates\non the results framework included in the Project Appraisal Document. At mid-term review (MTR)\nand before project closing, a beneficiary assessment will be undertaken. In addition to the Results\nFramework indicators, the project M&E system will also capture sector data defined by the GoC\n(MINEPAT, MINHDU, and so on) to inform policy and progress in implementation of national\nstrategies. The M&E manual will provide further details on the results framework, social/gender", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 27, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "MINEPAT", "probe_tag": "confusion", "probe_score": 0.2954710125923157, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1717, "end": 1724, "key": "refugee_pads:000144:27:1:1", "source": "camp2", "luna_reason": "Institution name alone is not a cited or used data resource.", "drop_reason": "bare_stat", "specificity": "named"}]}
+{"text": " secondhand clothes, or have established restaurants and kiosks and engage in petty trading.\nThese are mostly conducted on an informal basis, as the costs of obtaining official work and business permits are high.\n\n\n13. **Zambia is taking a more progressive approach to refugee inclusion.** There is a general recognition in Government\nthat a shift to self-reliance and a move away from humanitarian support is required. Zambia’s Eighth National\nDevelopment Plan (8NDP) has a vision for a more decentralized approach to economic and social development, which will\nsupport the greater inclusion of approximately 101,837 <sup>15</sup> [^15: Zambia National Statistical Report, Ministry of Home Affairs and Internal Security, May 2024.] refugees, asylum seekers, and former refugees that currently\nreside in the country.\n\n\n14. **In August 2023, the GRZ endorsed a new National Refugee Policy, approved by the Cabinet in November 2023.**\nThe Office of the Commissioner for Refugees, in close cooperation with the MoHAIS and the United Nations High\nCommissioner for Refugees (UNHCR), developed the new policy to address existing legal gaps and enhance coordination\nwithin government. Its implementation is expected to ease reservations to the 1951 Convention and harmonize the 2017\nRefugee Act with other national legislation (for example, the Immigration and Deportation Act of 2010) that will enhance\nopportunities for protection and solutions for self-reliance. <sup>16</sup> [^16: They include, among others _,_ the Immigration and Deportation Act, Refugees Act No.1 of 2017 and amendments to other legislation, such as the\nLands Act CAP 184, Higher Education Bursaries and Scholarships Act no.31 of 2016, Birth and Death Registration Act CAP 51, Citizenship Act of No] To assist policy delivery, the Government has established an\ninteragency National Steering Committee chaired by the Office of the Vice President. In March 2023, the MoHAIS launched\na plan for the Modernization of Refugee and Host Community Settlement Areas (MORHCSA)", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000187", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Zambia National Statistical Report", "probe_tag": "confusion", "probe_score": 0.6526820063591003, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 638, "end": 672, "key": "refugee_pads:000187:14:1:0", "source": "camp2", "luna_reason": "Named statistical report cited as source for refugee population figure.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "ficiaries satisfied with the<br>community infrastructures financed by<br>the project<br>Percentage of direct<br>beneficiaries of community<br>infrastructures that are<br>globally satisfied with the<br>infrastructures<br>Once<br> <br>Survey<br> <br>Survey at end of project<br> <br>SEAS<br>|Beneficiaries satisfied with the<br>community infrastructures financed by<br>the project<br>Percentage of direct<br>beneficiaries of community<br>infrastructures that are<br>globally satisfied with the<br>infrastructures<br>Once<br> <br>Survey<br> <br>Survey at end of project<br> <br>SEAS<br>|Beneficiaries satisfied with the<br>community infrastructures financed by<br>the project<br>Percentage of direct<br>beneficiaries of community<br>infrastructures that are<br>globally satisfied with the<br>infrastructures<br>Once<br> <br>Survey<br> <br>Survey at end of project<br> <br>SEAS<br>|Beneficiaries satisfied with the<br>community infrastructures financed by<br>the project<br>Percentage of direct<br>beneficiaries of community<br>infrastructures that are<br>globally satisfied with the<br>infrastructures<br>Once<br> <br>Survey<br> <br>Survey at end of project<br> <br>SEAS<br>|Beneficiaries satisfied with the<br>community infrastructures financed by<br>the project<br>Percentage of direct<br>beneficiaries of community", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 37, "chunk": 7, "split": "holdout_annotate", "spans": [{"text": "Survey at end of project", "probe_tag": "confusion", "probe_score": 0.11902756989002228, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 248, "end": 272, "key": "refugee_pads:000154:37:7:0", "source": "camp2", "luna_reason": "Planned end-of-project survey, not existing data used for analysis.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "Survey at end of project", "probe_tag": "confusion", "probe_score": 0.10709517449140549, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 248, "end": 272, "key": "refugee_pads:000154:37:7:1", "source": "camp2", "luna_reason": "Planned end-of-project survey, not an existing dataset used for analysis.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": " of the post-harvest\nlosses resulting from investments into climate-smart market infrastructure. In the model for\nmaize/groundnut/sesame storage, the WOP considers that beneficiaries will be able to store their production in\ntraditional storage infrastructures, while the investment in the WP will materialize into modern storage (two\nwarehouses of a capacity of 1,000 tons each) and drying equipment, leading to a sensible reduction of post-harvest\nlosses from 16 to 8 percent. In the case of fish-related infrastructure, a group of 560 fish vendors <sup>58</sup> will benefit from\naccess to cold-storage, resulting in a reduction of losses from 25 to 15 percent.\n\n\n20. **Access to inputs** : To estimate the benefits of access to inputs, two crop models have been developed reacted\nto the cultivation of maize and groundnut. It has been assumed that maize production will benefit from\n“intensification kit”, defined as one-year support with improved seeds and fertilizer, while groundnut production\nonly benefits from improved seeds. In these, the WOP situation is characterized by the cultivation of maize and\ngroundnuts, each on 1 ha and 1 cycle per year, with low access to inputs and low yields (yields estimated at 1200\nkg/hectare in the case of maize and 500 kg/hectare in the case of groundnut). Access to inputs in the WP situation\nand capacity building will result in yield improvements, reaching 2,500 kg/ hectare in the case of maize and 650\nkg/hectare in the case of groundnuts.\n\n\n58 The number of vendors has been estimated based on data collected during the field mission, January 2023.\n\n\n**Page 65 of 88**", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000183", "page": 69, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data collected during the field mission", "probe_tag": "confusion", "probe_score": 0.6725601553916931, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1548, "end": 1587, "key": "refugee_pads:000183:69:2:0", "source": "camp2", "luna_reason": "Existing field-mission data supports the vendor-number estimate.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nIraq COVID-19 Vaccination Project (P177038)\n\n\ni) The PMU uses a register “spreadsheet” to record the details of purchased vaccines under the project,\nincluding among others, description, reference to contract, quantity, location, and the Governorate in\nwhich the vaccines were deployed;\nii) The PMU will prepare a detailed distribution plan, which will include among others the description of\nall vaccines and beneficiary governorate;\niii) All items will be traceable;\niv) Special conditioned warehouse register will be used for the received vaccines;\nv) Special committees will be established to receive the purchased vaccines. The committee will be\nresponsible for vaccine inception upon delivery at the location to confirm quantity and quality as per\nthe signed contract;\nvi) Items will be stored in a designated area that would be easy to differentiate from all other inventory\n(vaccines) items;\nvii) Warehouses will be maintained to provide the necessary conditions to protect the vaccines from\nweather, heat, theft, damaged, etc.); and\nviii) Annual stocktaking will be performed by Directorates of Health, and the PMU will compare to its own\nregister of assets.\n\n\n14. **Financial audit** : The project’s financial statements will be audited annually by an independent auditor\nacceptable to the World Bank, in accordance with internationally accepted auditing standards and terms of\nreference cleared by the World Bank. The PMU will be responsible for preparing the TORs for the auditor and will\nsubmit them to the World Bank for clearance. The audit scope will cover the activities of the project implemented\nby the PMU. The audit report will be sent to the Bank no later than 6 months following the end of the project’s\nfiscal year. The report will include an opinion on the project’s financial statement. The auditor will also be\nrequested to provide an opinion on the project’s effectiveness of internal control system including the vaccines\nsafeguard", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000058", "page": 57, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "register of assets", "probe_tag": "confusion", "probe_score": 0.44569456577301025, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1167, "end": 1185, "key": "refugee_pads:000058:57:0:0", "source": "camp2", "luna_reason": "Routine asset-register reconciliation and stocktaking, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
+{"text": " sensitive to the choice of the discount rate. The use\nof a higher discount rate of 10.2 percent would produce economic returns just equivalent to the\ntotal amount of the project (US$5.6 million). There are many benefits that are difficult to\nquantify, particularly associated with the recreation areas. This is thus a conservative rate that\nshows that the project is economically justified.\n\n53. **The assessment is based on the characteristics of the households and property of Q7.**\nThe determinants of consumption levels and real estate values in Q7 are based on the 2012\nhousehold survey for the city of Djibouti (EDAM 3) and the Population and Housing Census of\n2009 (RGPH) and take into account the impact of neighborhood characteristics such as the\noverall unemployment rate. The improvement of the residents’ health is measured through the\nnumber of Disability-Adjusted Life Years (DALYs) saved due to lower rates of diarrhea,\nrespiratory infections and paratyphoid fever. The estimate of the opportunity cost of flood is\nbased on an international benchmark.\n\n54. Activities surrounding street rehabilitation will use labor-intensive techniques and locally\nproduced materials. Overall, the implementation of the project should therefore generate demand\nin Djibouti for labor, goods, and services amounting to US$3.57 million. In addition to\nstrengthening households’ resilience to flooding, the project’s success will depend on its capacity\nto trigger economic growth in the neighborhood, expected to generate an additional impact of\nabout US$2.43 million in Quartier 7. Easier and quicker access to enter or exit the neighborhood\nwill increase the population’s overall economic opportunities, efficiency, and security. If the\nnumber of jobs in the retail and catering sectors expands—like in other neighborhoods where\n\n\n15 This includes DRM partners: Djibouti Center for Research Studies (CERD), Civil Defense, and Executive Secretariat for Disaster\nManagement, Meteorology Agency.\n\n\n15", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000067", "page": 24, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2012\nhousehold survey for the city of Djibouti", "probe_tag": "confusion", "probe_score": 0.6403886079788208, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 571, "end": 617, "key": "refugee_pads:000067:24:1:0", "source": "camp2", "luna_reason": "Survey data underpin consumption and real estate value calculations.", "usage_type": "evidential", "specificity": "named"}, {"text": "EDAM 3", "probe_tag": "confusion", "probe_score": 0.8594664335250854, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 619, "end": 625, "key": "refugee_pads:000067:24:1:1", "source": "camp2", "luna_reason": "Named household survey used to estimate consumption and real estate values.", "usage_type": "evidential", "specificity": "named"}, {"text": "Population and Housing Census of\n2009", "probe_tag": "confusion", "probe_score": 0.7162066698074341, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 635, "end": 672, "key": "refugee_pads:000067:24:1:2", "source": "camp2", "luna_reason": "Census data inform property values and household consumption analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**Box A.2.1: National ID card in Burundi**\n\n\nThe information on the present ID card includes: last and first names, names of\nparents, birth date, civil status, occupation, a black and white picture of the bearer\nand his/her signature. It also includes an ID number and the places of residence.\nTo obtain an ID card, one must present a birth certificate and proof of residence\nsigned by the _chef de colline_ and the commune administrator. Cost in 2016 is BIF\n2,500.00 (US$ 1.61).\n\nBurundi has piloted a biometric ID card. This card would include: first and last\nname, sex, birth date, province, commune, current residence, parents’ names and\nchildren’s names, CAM card number, Social Security National Institute number,\n_Mutuelle de la Fonction Publique_ number, profession, place of birth, picture,\nfingerprint, profession. It would be machine-readable per the requirements of the\nEAC.\n\n\n32. T **he sub-component will support the background analysis for the implementation of**\n**the database and its implementation.** These include:\n\n(a) Design and implementation of key tools: updated poverty and malnutrition maps,\n\ndevelopment of community-based targeting criteria and processes, development of\nregistration questionnaire, construction of proxy-means test score, the organization of the\ndifferent committees involved in the registration, the implementation of the PMT survey,\nstoring and analysis of the data as well as the preparation of beneficiary lists for the cash\ntransfer program and its complementary activities. It will also support the acquisition of\nkey equipment (hardware, software, back-up equipment).\n\n(b) Implementation of the targeting and registration in selected areas including the organization\n\nand support of the targeting committees, the implementation and processing of\nquestionnaires and the preparation of the list of registered households as well as eligible\nhouseholds for the cash", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 57, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PMT survey", "probe_tag": "confusion", "probe_score": 0.3144630491733551, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1369, "end": 1379, "key": "refugee_pads:000157:57:0:0", "source": "camp2", "luna_reason": "The project will implement the PMT survey as part of targeting activities.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"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:000052", "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": "refugee_pads:000052:36:0:1", "source": "camp2", "luna_reason": "Planned incorporation into future monitoring surveys, not citation of existing used data.", "drop_reason": "promissory", "specificity": "descriptive"}]}
+{"text": " gender norms and household dynamics play a critical role in causing these gaps.\nAccording to a 2022 study by Access to Finance Rwanda, deeply ingrained societal expectations shape how women\nparticipate in economic life and influence their capacity to leverage assets—particularly land and property—as\ncollateral. <sup>_34_</sup> One pervasive norm is that women should prioritize family and caregiving responsibilities over business\nactivities. This norm restricts their time and engagement in income-generating pursuits and weakens their\nperceived legitimacy as entrepreneurs, reducing their chances of qualifying for credit. Additionally, women are\noften expected to rely on family support, especially from spouses, instead of seeking independent financial\nsolutions, distancing them from formal financial institutions and financial products.\n\n\n31 Baseline failure rates by segment are extremely difficult to assess. As such, the analysis uses conservative assumptions based on extensive\ndiscussions with key stakeholders and potential beneficiaries. These assumptions have been tested for sensitivity.\n32 CEIC data\n33 In the absence of available survey data, the analysis uses proxies for these losses and repair costs from survey data from neighboring\nBurundi. Based on this data, annual flooding losses amount to ~US$89 per household and repair costs amount to US$25.60 per household.\n34 <u>[Gendered Social Norms Diagnostic and their Impact on Women’s Financial Inclusion in Rwanda, 2022, Access to Finance Rwanda](https://afr.rw/downloads/gendered-social-norms-diagnostic-and-their-impact-on-womens-financial-inclusion-in-rwanda/)</u>\n\n\nPage 18", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000188", "page": 33, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "survey data", "probe_tag": "confusion", "probe_score": 0.736857533454895, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1150, "end": 1161, "key": "refugee_pads:000188:33:2:0", "source": "camp2", "luna_reason": "Unavailable survey data motivates substitute proxy estimates.", "usage_type": "declaration", "specificity": "vague"}, {"text": "survey data from neighboring\nBurundi", "probe_tag": "keep", "probe_score": 0.9535335898399353, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1228, "end": 1264, "key": "refugee_pads:000188:33:2:1", "source": "camp2", "luna_reason": "Existing Burundi survey data are used as proxies for losses and repair costs.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " attirer d'importants investissements étrangers directs\n(IED). En 2006, les entrées d'IED ont connu une forte accélération suite à la construction du\nterminal à conteneurs de Doraleh et la zone franche du port de Djibouti. Entre 2006 et 2010,\nles entrées d'IED se chiffraient en moyenne à plus de 14 pourcent du produit intérieur brut\n(PIB), et la formation brute de capital a atteint 31 pourcent du PIB (Graphique 1). Par\nconséquent, le taux de croissance s'est accéléré en 2002-2012 pour atteindre une moyenne\nd'environ quatre pourcent par an. L'inflation est restée assez bien maîtrisée au cours de cette\npériode. Elle s'est stabilisée à environ 3,8 pourcent au cours des quatre dernières années,\naprès avoir culminé au plus fort du choc de la hausse des prix de la nourriture et du carburant\nde 2007 à 2008, en raison de la dépendance quasi totale du pays sur les denrées alimentaires\nimportées.\n\n3.\nDjibouti est un pays à revenu intermédiaire-faible, avec un PIB par\nhabitant en 2011 de 1430 et 2500 dollars EU en parité de pouvoir d'achat (PPA). Entre 2002\net 2012, la croissance du PIB a atteint en moyenne environ 4 pourcent par an (Graphique 1).\nToutefois, le niveau de pauvreté reste élevé même s’il a légèrement diminué au cours de la\ndernière décennie. Selon les statistiques du Gouvernement, la", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000134", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "statistiques du Gouvernement", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1275, "end": 1303, "key": "refugee_pads:000134:5:1:0", "source": "camp2", "luna_reason": "Government statistics are cited as evidence for the poverty assessment.", "usage_type": "evidential", "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": "refugee_pads", "corpus_id": "refugee_pads:000176", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1188, "end": 1214, "key": "refugee_pads:000176:31:0:2", "source": "camp2", "luna_reason": "Existing NaCSA administrative data is listed as a verification source for program awareness results.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nAdvancing Sustainability in Performance, Infrastructure, and Reliability of the Energy Sector in the West Bank and\nGaza (P170928)\n\n\n\n\n\n\n|Indicator Name|DLI|Baseline|Intermediate Targets|End Target|\n|---|---|---|---|---|\n||||**1 **||\n|PENRA publishes on its website results of citizen<br>engagement survey (Number)||0.00|1.00|2.00|\n|Grievances registered related to delivery of<br>project benefits that are actually addressed<br>(Percentage)<br>||0.00|90.00|90.00|\n\n\n\n\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|Non-technical losses West Bank|Average based on non-<br>technical losses recorded<br>for each distribution<br>company in West Bank|Annual<br>|Non-technical<br>losses<br>reported by<br>each<br>distribution<br>company<br>individually<br>|Primary data<br>|PENRA PMU<br>|\n|Non-technical losses Gaza|Non-technical losses as per<br>Gaza Distribution Company<br>(GEDCO)", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000133", "page": 47, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "engagement survey", "probe_tag": "confusion", "probe_score": 0.1281181275844574, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 306, "end": 323, "key": "refugee_pads:000133:47:0:0", "source": "camp2", "luna_reason": "Survey phrase appears within a project indicator table.", "drop_reason": "table_artifact", "specificity": "descriptive"}, {"text": "PENRA PMU", "probe_tag": "drop", "probe_score": 0.0406012088060379, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1020, "end": 1029, "key": "refugee_pads:000133:47:0:1", "source": "camp2", "luna_reason": "Identifies the project unit responsible for producing primary monitoring data.", "drop_reason": "production", "specificity": "named"}]}
+{"text": "<br>Collection|MoH / TPM|\n|**Percentage of complaints to Grievance Redress Mechanisms satisfactorily addressed in a timely manner**|**Percentage of complaints to Grievance Redress Mechanisms satisfactorily addressed in a timely manner**|\n|Description|Percentage of complaints submitted to the GRM addressed according to the protocol and within agreed time<br>period.|\n|Frequency|Quarterly|\n|Data source|UNICEF|\n|Methodology for Data<br>Collection|UNICEF to provide data / TPM to verify|\n|Responsibility for Data<br>Collection|UNICEF; PMU|\n|**Percentage of completeness of reporting by facilities**|**Percentage of completeness of reporting by facilities**|\n|Description|Percentage of facilities that submit complete reports within the required deadline.|\n|Frequency|Quarterly|\n|Data source|DHIS2|\n|Methodology for Data<br>Collection|DHIS2|\n|Responsibility for Data<br>Collection|MoH/ PMU|\n|**Percentage of states that conducted quarterly coordination meetings with a review of data and documented with minutes including**<br>**action items and follow-up**|**Percentage of states that conducted quarterly coordination meetings with a review of data and documented with minutes including**<br>**action items and follow-up**|\n|Description|Percentage of State’s quarterly health service delivery coordination meetings for the health sector held with a<br>review of data included in the meeting and documented with minutes which include action items and follow-up<br>on action items. Meetings are to be held quarterly in each state. Four meetings are expected each year per<br>state. CHDs and implementing partners will be participated in the review|\n|Frequency", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000006", "page": 54, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "DHIS2", "probe_tag": "drop", "probe_score": 0.04972269758582115, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 790, "end": 795, "key": "refugee_pads:000006:54:1:1", "source": "camp2", "luna_reason": "Names DHIS2 as a reporting source without showing its data being analyzed or used.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "Jobs-focused interventions contribute to the jobs agenda and have an explicitly stated and substantive link to creating<br>more, better, and/or inclusive jobs. Beneficiaries include individuals, workers, microenterprises, SMEs, and so on. The<br>indicator captures the number of beneficiaries supported through the following job-focused interventions of the project:<br>productive infrastructure (1.1), matching grants (1.2), supplier development/linkage programs (1.3), and weather-index<br>insurance program and PPCG fund (2.2).|\n|Responsibility for Data<br>Collection <br>PPCG Fund Manager, implementing partners, and productive infrastructure providers. Data will be aggregated by the PIU.|Responsibility for Data<br>Collection <br>PPCG Fund Manager, implementing partners, and productive infrastructure providers. Data will be aggregated by the PIU.|\n|**Beneficiaries of job-focused interventions - women (Number)CRI**|**Beneficiaries of job-focused interventions - women (Number)CRI**|\n|Description <br>Number of female beneficiaries reached by interventions that contribute to the jobs agenda in operations supported by<br>the World Bank.|Description <br>Number of female beneficiaries reached by interventions that contribute to the jobs agenda in operations supported by<br>the World Bank.|\n|Frequency<br>Semi-annually|Frequency<br>Semi-annually|\n|Data Source|Implementing partners and project records: Consolidation of project records from PPCG Fund Manager, implementing|\n\n\n\n~~Page 35 of 55~~", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000004", "page": 38, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "Implementing partners and project records", "probe_tag": "drop", "probe_score": 0.023233206942677498, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1369, "end": 1410, "key": "refugee_pads:000004:38:4:0", "source": "camp2", "luna_reason": "Project records are routine administrative monitoring paperwork, not external data reuse.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nUganda Development Response to Displacement Impacts Project Phase II\n(P510476)\n\n\n\nPROJECT APPRAISAL\n\nDOCUMENT\n\n\n\n\n\n\n\n\n\n|Frequency|Quarterly|\n|---|---|\n|Data source|Project MIS and Project Progress Reports|\n|Methodology for<br>Data Collection|Monitoring project implementation, including through regular phone surveys to project-supported groups and<br>monitoring by project-trained Community Resource Persons|\n|Responsibility for<br>Data Collection|IA<br>|\n|**Project-supported institutions that access formal finance (Number)**|**Project-supported institutions that access formal finance (Number)**|\n|Description|Quantitative indicator on project supported institutions under component 3 that successfully access formal<br>finance. This would be an indication of advancement and sustainability.|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports|\n|Methodology for<br>Data Collection|Monitoring project implementation.|\n|Responsibility for<br>Data Collection|IA|\n|**Project Management, Accountability Systems and Coordination**|**Project Management, Accountability Systems and Coordination**|\n|**Complaints received through the grievance redress mechanism that are resolved (Percentage)**|**Complaints received through the grievance redress mechanism that are resolved (Percentage)**|\n|Description|Quantitative indicator counting number of grievances registered, addressed and resolved.|\n|Frequency|Quarterly|\n|Data source|Project GRM|\n|Methodology for<br>Data Collection|Monitoring of grievances addressed project GRM|\n|Responsibility for<br>Data Collection|AI, including Inspectorate of Government|\n|**Actions identified in the Community Score Card that have been addressed by the project (Percentage)**", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000186", "page": 48, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Project MIS and Project Progress Reports", "probe_tag": "confusion", "probe_score": 0.2258799821138382, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 183, "end": 223, "key": "refugee_pads:000186:48:0:0", "source": "camp2", "luna_reason": "Project monitoring source cell inside an M&E table", "drop_reason": "table_artifact", "specificity": "descriptive"}, {"text": "Project GRM", "probe_tag": "drop", "probe_score": 0.03287842869758606, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1468, "end": 1479, "key": "refugee_pads:000186:48:0:1", "source": "camp2", "luna_reason": "Project grievance mechanism is named without showing actual data use.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "OPRC Operational Procurement Review Committee\nPAD Project Appraisal Document\nPDO Project Development Objective\nPFS Project Financial Statement(s)\nPIU Project Implementation Unit\nPLM Person with Limited Mobility\nPIM Project Implementation Manual\nPPP Public-Private Partnership\nPPSD Project Procurement Strategy Development\nQCBS Quality- and Cost-Based Selection\nRAP Resettlement Action Plan\nROW Right-of-Way\nRPA Regional Procurement Adviser\nRPTA Railways and Public Transport Authority\nSOE Statement of Expenditure\nSPS Stated Preference Survey(s)\nSTEP Systematic Tracking of Exchanges in Procurement\nUIFR Unaudited Interim Financial Report\nUN United Nations\nUTDP Urban Transport Development Project\nVAT Value Added Tax\nWA Withdrawal Application", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000074", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "SPS Stated Preference Survey", "probe_tag": "drop", "probe_score": 0.04722153767943382, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 514, "end": 542, "key": "refugee_pads:000074:3:0:0", "source": "camp2", "luna_reason": "Glossary definition only; no survey data are cited, analyzed, or used.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 5 of 54", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000078", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Emergency Food Security Project", "probe_tag": "drop", "probe_score": 0.02151625044643879, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 50, "key": "refugee_pads:000078:9:0:0", "source": "camp2", "luna_reason": "Project title only; it does not cite or use an existing data resource.", "drop_reason": "ref_list", "specificity": "named"}]}
 {"text": "br>beneficiaries affected by climate change to existing social<br>programs|**Sub-component 3.2:**<br>**Development of a**<br>**National**<br>**Social**<br>**Registry**<br>**(US$2**<br>**million)**<br> <br>Registration of beneficiaries<br>and<br>referral<br>to<br>social<br>programs<br>- <br>The Social Registry will collect socio-economic data from<br>beneficiaries that can help determine households’<br>vulnerability to climate change based on 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|**Sub-component 3.2:**<br>**Development of a**<br>**National**<br>**Social**<br>**Registry**<br>**(US$2**<br>**million)**<br> <br>Registration of beneficiaries<br>and<br>referral<br>to<br>social<br>programs<br>- <br>The Social Registry will collect socio-economic data from<br>beneficiaries that can help determine households’<br>vulnerability to climate change based on 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", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 88, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "socio-economic data", "probe_tag": "confusion", "probe_score": 0.07672742009162903, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 324, "end": 343, "key": "refugee_pads:000130:88:3:0", "source": "camp2", "luna_reason": "The registry will collect this data, making it future project-produced information.", "drop_reason": "production", "specificity": "vague"}, {"text": "socio-economic data", "probe_tag": "drop", "probe_score": 0.04576203599572182, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 324, "end": 343, "key": "refugee_pads:000130:88:3:1", "source": "camp2", "luna_reason": "The Social Registry will collect this data; it is planned project data production.", "drop_reason": "production", "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": "refugee_pads", "corpus_id": "refugee_pads:000088", "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": "refugee_pads:000088:3:0:0", "source": "camp2", "luna_reason": "Glossary expansion only; no survey data are cited, analyzed, or used.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": " BAEC, PITE, Bureau of Curriculum and Extension Center, DoS, and BISE.\n41 It includes (a) allocating DDO code to the cluster head; (b) LECs preparing cluster plans and budgets; and (c) organizing\ntrainings of head teachers at the cluster head level on participatory planning, school‐based budgeting, cluster‐level\nprocurements, and conducting of summative and formative student assessments; and (d) EMIS cells gathering cluster data and\nsubmitting to the District Education Authority (DEA) and SED.\n\n\nPage 16 of 47", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000085", "page": 20, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "cluster data", "probe_tag": "drop", "probe_score": 0.0288, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 420, "end": 432, "key": "sample:refugee_pads:000085:20:2:0", "source": "gold", "luna_reason": "EMIS cells are gathering the data, so it is being produced rather than used.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": " boxes at the _colline_ -level in the\ncare of a civil society organization, possibly a hotline at central-level. Complaints received through\nSMS, phone or boxes will be logged in the MIS. A results indicator to track the progress of the\nimplementation of the GRM system has been included in the results framework.\n\n\n**_Subcomponent 2.3: Monitoring and evaluation (US$2.8 million equivalent)_**\n\n43. **Since the project is supporting new interventions and processes in Burundi, and in**\n**order to ensure transparency, the third sub-component will support process evaluations of**\n**the key program processes and an impact evaluation including beneficiary surveys** . The\nprocess evaluations will focus on the core operational processes: targeting, payment, delivery of\ncomplementary activities. The process evaluation in the first phase communes will inform the\nexpansion in the second phase but also provide key input in the design of the operating processes.\nThe process evaluations will continue in the second phase to provide real-time information about\nscale-up and implementation in different provinces. The process evaluation will be complemented\nby regular beneficiary surveys to help map out implementation successes and issues, externalities,\nand community dynamics and contribute to the establishment of the grievance redress mechanism.\n\n44. **The impact evaluation will focus on key poverty, welfare, and human development**\n**indicators at the household and community-levels for the cash transfers** . The random\nselection at the _colline_ -level will support a randomized control trial design based on a sample of\nparticipating and non-participating _collines_ . Baseline data will be collected prior to the first\ntransfer. A mid-term data collection will take place at 24 months. To evaluate the sustainability of\nimpacts, the end-line data collection will take place six months after the end of the program\nactivities (at 42 months).\n\n\n13", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "beneficiary surveys", "probe_tag": "confusion", "probe_score": 0.33407673239707947, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 643, "end": 662, "key": "refugee_pads:000157:23:1:0", "source": "camp2", "luna_reason": "Beneficiary surveys are planned as part of the project’s future impact evaluation.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "beneficiary surveys", "probe_tag": "confusion", "probe_score": 0.6031164526939392, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 643, "end": 662, "key": "refugee_pads:000157:23:1:1", "source": "camp2", "luna_reason": "Planned beneficiary surveys are project-generated evaluation data, not existing data use.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "Baseline data", "probe_tag": "drop", "probe_score": 0.029786886647343636, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1677, "end": 1690, "key": "refugee_pads:000157:23:1:2", "source": "camp2", "luna_reason": "Baseline data will be collected in the future as part of the project.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": " the situation that was agreed upon with\nthe Borrower.\n\nSigned by:\nFinancial Management v I _N_\n##### Specialist K {dO'.i1, O0\n\n(FMS-OPR) Rafika Chaouali, MNSHD Date\n\n\n**Part II:** **Procurement/Contract Management** System\n\nI have reviewed the procurement/contract management system relating to this project, including\nthe format and content of the section on Project Management Reports (PMRs) on procurement\n\nmonitoring. The objective of the review was to determine whether the procurement/contract\nmanagement system adopted by the project conforms to IDA's guidelines for procurement in\ninvestment projects. My review was based on the \"Assessment of Agency's Capacity to\nImplement Project Procurement, Setting of Prior Review Thresholds and Procurement\nSupervision Plan\" guidelines issued by IDA.\n\nI confirm that the project satisfies IDA's minimum procurement management requirements.\nHowever, in my opinion, the project does not have in place an adequate procurement/contract\nmanagement system that can provide the appropriate data on major procurement and contract\nmanagement (PMR - Section 3) as required by IDA.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000090", "page": 54, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on major procurement and contract\nmanagement", "probe_tag": "drop", "probe_score": 0.02957168221473694, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1032, "end": 1081, "key": "refugee_pads:000090:54:1:0", "source": "camp2", "luna_reason": "Routine procurement and contract-management reporting, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000012", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on social development issues", "probe_tag": "drop", "probe_score": 0.022581301629543304, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1670, "end": 1703, "key": "refugee_pads:000012:24:0:0", "source": "camp2", "luna_reason": "Data will be collected and analyzed during the project.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "ary means for fostering improved teaching<br>practices. Successful completion of the training by the<br>awarding of a teacher certificate will serve as the verification<br>means. Data should be disaggregated by gender.|MOE Training and<br>certification records|Third Party|The verification agency will verify<br>training records for teachers'<br>training and will check teacher<br>certification records. The<br>certification mechanism will need<br>to be compliant with the<br>requirements agreed upon with the<br>WB as specified in the Program<br>Operations Manual.|\n\n\n38", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 45, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "certification records", "probe_tag": "drop", "probe_score": 0.004437553230673075, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 239, "end": 260, "key": "refugee_pads:000127:45:3:0", "source": "camp2", "luna_reason": "Future verification of certification records is planned, not actual data use.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "training records", "probe_tag": "drop", "probe_score": 0.004437553230673075, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 312, "end": 328, "key": "refugee_pads:000127:45:3:1", "source": "camp2", "luna_reason": "Future verification of training records is planned monitoring machinery.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": "**The World Bank**\nUganda Investing in Forests and Protected Areas for Climate-Smart Development Project (P170466)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|allow new private sector<br>concessions be established<br>and operate.<br>This indicator measures<br>transformative capacity of<br>resilience.|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<br>transformative capacity of<br>resilience through<br>enhancing economic<br>opportunities for<br>communities.<br>Annual<br> <br>Reports from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA<br>|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<br>transformative capacity of<br>resilience through<br>enhancing economic<br>opportunities for<br>communities.<br>Annual<br> <br>Reports from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000043", "page": 58, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "activity reports", "probe_tag": "drop", "probe_score": 0.03423101827502251, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 779, "end": 795, "key": "refugee_pads:000043:58:0:0", "source": "camp2", "luna_reason": "Future project indicator reporting based on activity reports is promissory monitoring.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": "**Improving organizational and institutional capacity for managing refugees**|\n|Strengthened mechanism for<br>management of information<br>across participating entities<br>(Text)|DLI 2|No automated system for<br>monitoring and evaluating<br>data on refugees.|<br>CCAR jointly with the<br>CAR have defined<br>system specifications<br>and agreed on data<br>integration<br>arrangements.|CCAR (Islamabad) has<br>established a functioning<br>MIS system.|<br>CCAR (Islamabad) and,<br>at least, one (1)<br>provincial CAR has a<br>functioning MIS system.<br> <br> <br> <br>|CCAR (Islamabad) and, at<br>least, two (2) provincial<br>CARs have a functioning<br>MIS system.|<br>CCAR (Islamabad) and,<br>three (3) provincial CARs<br>have a functioning MIS<br>system.|\n|Improved knowledge and skills<br>of professional staff of<br>organizations responsible for<br>refugee management (female)<br>(Text)|DLI 5|There is no requirement<br>for ongoing professional<br>training and no program<br>to support continuous<br>learning.|At least 20 percent of<br>selected professional<br>cohort has completed at<br>least one course in the<br>Refugee Learning<br>Program.|At least 35 percent of<br>selected professional<br>cohort has completed<br>the Refugee Learning<br>Program|At least 50 percent of<br>selected professional<br>cohor", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000009", "page": 26, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on refugees", "probe_tag": "drop", "probe_score": 0.021278008818626404, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 241, "end": 257, "key": "refugee_pads:000009:26:1:0", "source": "camp2", "luna_reason": "Generic data reference names an absent monitoring system, with no demonstrated data use.", "drop_reason": "system_registry", "specificity": "vague"}]}
-{"text": "-19.pdf)</u>\nby the OECD in collaboration with UNHCR, and\nin which participation was on a voluntary basis. <sup>**23**</sup>\nFurther information on the survey, including the list of\nparticipants, is provided in the note on data sources\nand methodology at the end of this report.\n\n\n**The total volume of bilateral official**\n**assistance to refugee situations**\n**increased between 2016 and 2019**\n\n\nAccording to the 2020 OECD survey data, donors\ncontributed a cumulative total of USD 22.8 billion in\nbilateral Official Development Assistance (ODA) to\nrefugee situations in countries with lower incomes\nover 2018 and 2019. <sup>**24**</sup> This total is USD 24.2 billion\n\n\n\nwhen core contributions to refugee-mandated\nagencies (USD 1.44 billion), such as UNHCR and\nUNRWA, are included. The total amount of ODA\nincreased by 9 per cent (or 8 per cent when the core\ncontributions are included) from USD 10.9 billion\nin 2018 to USD 11.9 billion in 2019. <sup>**25**</sup> This growth in\nbilateral ODA to refugee situations (Figure 8) in host\ncountries with lower incomes continues the positive\ntrend observed in the previous survey conducted\nby the OECD in 2018. <sup>**26**</sup> Despite comparability\nlimitations between the two surveys (with several\nmethodological improvements made in the 2020\nsurvey), the data previously collected by the OECD\nrevealed an increase in bilateral ODA to refugee\nsituations of 23 per cent between 2015 and 2017. <sup>**27**</sup>\n\n\n**Figure 8:** Bilateral ODA to refugee situations, by\n\ntype of recipient, 2018 – 2019 (OECD Financing\n\nfor Refugee Situations Survey 2020, gross\ndisbursement, 2019 constant prices, US dollars)\n\n\n\n12", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000803", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2020 OECD survey data", "probe_tag": "keep", "probe_score": 0.972926676273346, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 416, "end": 437, "key": "reliefweb:000803:11:1:0", "source": "camp2", "luna_reason": "OECD survey data supports reported bilateral ODA totals.", "usage_type": "evidential", "specificity": "named"}, {"text": "data previously collected by the OECD", "probe_tag": "keep", "probe_score": 0.9156764149665833, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1307, "end": 1344, "key": "reliefweb:000803:11:1:1", "source": "camp2", "luna_reason": "OECD-collected data supports the reported increase in bilateral ODA.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " number of serious\nfactors, including: risks, threats and potential trauma faced by those who come forward; significant\ngaps in available services; restrictions on movement; shame, fear, stigma and discrimination; risks of\nretaliations and “honor killings”; impunity for perpetrators; and the existence of mandatory\nreporting of sexual violence by government health staff. Feedback from communities and service\nproviders indicate an increase of sexual violence within communities, directly related to the crisis\nand mass displacement. However, when reporting of GBV does happen, it is untimely, with only 9%\nof GBV cases reporting within three days of the incident. <sup>16</sup> [^16: GBVIMS, July 2015 – February 2016. This statistic represents all GBV cases, not just sexual violence.] Timely reporting is critical for addressing\nthe mental and physical health needs, including preventing long-lasting psychological effects of\ntrauma and providing lifesaving HIV post-exposure prophylaxis ad other immediate medical care.\n\nGaps in humanitarian aid have increased risks of violence and heightened the likelihood of women\nand girls being forced to engage in negative coping strategies (like survival sex or early and forced\nmarriage) to meet basic needs. Displaced women, especially widows and female-headed\nhouseholds, are particularly vulnerable to GBV. Safety audits in IDP and refugee sites identified\nsecurity risks for women and girls, including long distances to collect water, poor lighting at\nsanitation facilities, and overcrowded living. A recent study among IDPs living in critical shelters and\ncamps found that 64% of latrines surveyed were both unsegregated and without locks, representing\na significant risk of violence for women and girls. <sup>17</sup> [^17: GBV risks amongst IDPs Living in Critical Shelters and Camps, International Organization for Migration (IOM), September\n2015] Threats to their physical safety and security and\non-going harassment are part of the daily reality for many IDP women and girls.\n\n12 GBVIMS, July 2015 – February 2016. Data is only from reported cases and is in no way representative of", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000831", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "GBVIMS", "probe_tag": "keep", "probe_score": 0.9643412828445435, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 686, "end": 692, "key": "reliefweb:000831:6:1:0", "source": "camp2", "luna_reason": "GBVIMS data supports the reported 9% timely-reporting statistic.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**WESTERN BALKANS** REGULAR ECONOMIC REPORT NO.18\n\n\nMontenegro must now deal with the deepest\nrecession in decades…\n\n\n\n...mainly because the COVID-crisis has halted\ntourism.\n\n\n\nReal GDP growth, percent International tourists overnight stays, in thousands\n10 1,000\n\n\n900\n\n\n\n5\n\n\n0\n\n\n-5\n\n\n-10\n\n\n-15\n\n\n\n800\n\n\n700\n\n\n600\n\n\n500\n\n\n400\n\n\n300\n\n\n200\n\n\n100\n\n\n0\n\n\n\nJ <u>2015–19 average</u> J <u>2020</u>\n\n\n_Source:_ MONSTAT data, World Bank staff calculations. _Source:_ MONSTAT data, World Bank staff calculations.\nEmployment fell in all sectors... ...and inflation plunged into negative territory.\n\n\n\nAdministrative data, thousands, Jan 2015–Jul 2020 Administrative data, Jan 2014–Jul/Aug 2020\n220 55 12\n\n\n\n600\n\n\n500\n\n\n400\n\n\n300\n\n\n200\n\n\n100\n\n\n0\n\n\n\n55\n\n\n\n12\n\n\n10\n\n\n8\n\n\n6\n\n\n4\n\n\n2\n\n\n0\n\n\n-2\n\n\n-4\n\n\n\n200\n\n\n190\n\n\n180\n\n\n170\n\n\n160\n\n\n\n50\n\n\n45\n\n\n40\n\n\n35\n\n\n30\n\n\n25\n\n\n20\n\n\n\n\n- Employment - Employment_tc - PPI, percent - CPI, percent - Real net wage (EUR 2015), rhs\n\n<u>▬</u> <u>Unemployment, rhs</u> <u>▬</u> <u>Unemployment_tc, rhs</u>\n\n\n_Source:_ MONSTAT data, tc = trend cycle. _Source:_ MONSTAT data, World Bank staff calculations. Last obs. (CPI and\nPPI - Aug 2020, Real net wage - Jul 2020)\nBank lending is still solid… ...but the fiscal position has deteriorated.\n\n\n\nOutstanding loans, Jan 2012–Jul 2020, in millions 2015–20, percent of GDP\n3.5 60\n\n\n\n0\n\n\n-2\n\n\n-4\n\n\n-6\n\n\n-8\n\n\n-10\n\n\n-12\n\n\n-14\n\n\n\n3.0\n\n\n2.5\n\n\n2.0\n\n\n1.5\n\n\n1.0\n\n\n0.5\n\n\n0\n\n\n\n50\n\n\n40\n\n\n30\n\n\n20\n\n\n10\n\n\n0\n\n\n\nJ Private", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000814", "page": 74, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MONSTAT data", "probe_tag": "keep", "probe_score": 0.9424273371696472, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 403, "end": 415, "key": "reliefweb:000814:74:0:0", "source": "camp2", "luna_reason": "MONSTAT data support the report's economic indicators and World Bank calculations.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " to sampling constraints and the\nnon-probabilistic selection of respondents, the\nresults may not fully represent the entire refugee\npopulation from Ukraine. Additionally, the choice of\nsampling locations may have introduced a bias\ntoward more vulnerable segments of the\npopulation. Variations in sampling approaches and\ndata collection periods across countries can also\naffect comparability.\n\n\n\n**Net enrolment rates.** The questionnaire of the\n2024 SEIS contained more detailed questions on\neducation of refugee household members than the\n2023 MSNA, but needs to be interpreted with care\nknowing that any data on enrolment of children\nstemming from the survey needs to be contrasted\nto net enrolment rates as calculated according to\ninternationally accepted standard methods used by\nUNESCO and the World Bank. <sup>15</sup>\n\n\nEnrolment rates represent the ratio of refugee\nchildren and youth from Ukraine who are of school\nage and who are enrolled in a host country’s\neducation system. <sup>16</sup> The 2023 MSNA and SEIS data\nallows for a calculation of enrolment rates based on\nwhat households reply to the surveys with respect\nto the enrolment status of individual children and\nyouth. However, this calculation differs from the\nglobal standard method of calculating a net\nenrolment rate. The global standard mostly relies on\nadministrative data and household surveys of\nschool age population and corresponds to\nenrolment in the relevant level of education. The\n2023 MSNA and the 2024 SEIS have a slightly\ndifferent focus and gauge whether or not children\nand youth are enrolled in education in host\ncountries, and whether or not children are engaged\nin different types of remote or online learning\nwithout collecting detailed information relating the\nenrolment at different levels of education. An\nadditional limitation is that SEIS is only available for\nten countries. Compulsory school age brackets also\nvary across Europe, making comparison of\nenrolment rates complex.\n\n\n**Refugee population data.** The data used to\nestimate the child and youth refugee populations\nhas limitations related to disaggregation and\npotential double counting across", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001564", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2023 MSNA", "probe_tag": "keep", "probe_score": 0.9576025605201721, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1005, "end": 1014, "key": "reliefweb:001564:4:1:1", "source": "camp2", "luna_reason": "Named survey data used to calculate refugee enrolment rates.", "usage_type": "evidential", "specificity": "named"}, {"text": "SEIS data", "probe_tag": "keep", "probe_score": 0.9684779047966003, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1019, "end": 1028, "key": "reliefweb:001564:4:1:2", "source": "camp2", "luna_reason": "SEIS data are used to calculate refugee enrolment rates.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "a refugee haven” (Chatelard, 2010). This small state – one of the most water\nscarce in the world – has been home to the Palestinian refugees (and their descendants) who\nfled their homes in 1948 and 1967 as well as those who were expelled from Kuwait in 1991.\nEstimates vary greatly but it is believed that the Palestinians constitute at least 50% of the\npopulation. People fleeing violence in Iraq have come to Jordan at various junctures over the\npast three decades. And the recent Syrian crisis has brought refugees in numbers that exceed\neven the original influx of Palestinians in the mid-20 <sup>th</sup> Century. Thus any analysis of the\nJordanian Government’s response to the Iraqis who have entered the country since 2003 must\ntake into account the massive influx of refugees – both in volume and in relation to the size of\nthe citizenry. <sup>4</sup> [^4: According to the UNHCR 2012 Statistical Yearbook (the last available), in that year Jordan hosted the eighth\nlargest number of refugees in the world. When the number of refugees is considered in relation to the size of the\nhost country population Jordan came out number one. These figures do not reflect the continued influx of Syrian\n[and Iraqi refugees since December 2012. See http://www.unhcr.org/pages/4a02afce6.html](http://www.unhcr.org/pages/4a02afce6.html)] It is inconceivable that the leaders of European and other developed countries,\nparticularly at a time of rising popular opposition to immigration, would admit even a\nfraction of the number allowed to remain by the Jordanian authorities.\n\nWhilst acknowledging the hospitality of the authorities under very challenging conditions, it\nis also important to note that Jordan has received significant benefits through its role as a host\ncountry (Chatelard, 2010). It has been argued that the Iraqis have contributed significantly to\nthe growth of the economy. According to Human Rights Watch, in", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000556", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "UNHCR 2012 Statistical Yearbook", "probe_tag": "keep", "probe_score": 0.9650992751121521, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 882, "end": 913, "key": "reliefweb:000556:20:1:0", "source": "camp2", "luna_reason": "Named UNHCR yearbook supports refugee-hosting rankings and population comparisons.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "/000</u>\n76 Resolutions no. 26/07 and 33/07, National Assembly (DR, 27.8.2007 and 10.9.2007) -https://www.lexlink.eu/legislacao/geral/14793/\nia-serie/por-tipo-de-documentolegal/2007/000\n77 Angonotícias/Novo Jornal, 12.12.2011: <u>“Ministra da Justiça manda suspender Lei da Nacionalidade”</u>\n78 <u>Decreto nº 37/99 de 26 de Novembro (1999), que anulou uma regra portuguesa de que todos os nascidos nas colónias que</u>\ntinham o seu registo de nascimento transcrito no registo português em Lisboa tiveram os seus registos angolanos anulados,\nperdendo a sua prova de nascimento em Angola.\n\n\n\nOs cidadãos portugueses foram o maior grupo a obter a nacionalidade angolana em 2017 e 2019, cerca de\nmetade de todos, seguidos pelos nacionais de São-Tomé: 20% em 2017 e 15% em 2019. Os números totais de\ncidadãos angolanos naturalizados não impressionam - como é o caso na maioria dos outros estados africanos\n(embora seja frequentemente difícil encontrar números precisos). As 202 aquisições de nacionalidade angolana\nem 2017 correspondem a 0,001% da população total de 31 milhões.\n\n\n_A África do Sul fez uma excepção com 14.108 naturalizações em 2001", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000443", "page": 15, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "registo português em Lisboa", "probe_tag": "keep", "probe_score": 0.9602658748626709, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 469, "end": 496, "key": "reliefweb:000443:15:3:0", "source": "camp2", "luna_reason": "Names a registration record without showing its data being used for analysis or a decision.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "br>Q3<br>Q4<br>Total<br>Q2-Q1<br>Q3-Q2<br>Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1<br>Q3-Q2<br>Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1<br>Q3-Q2<br>Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 20, "chunk": 11, "split": "holdout_annotate", "spans": [{"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.7617231011390686, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 210, "end": 222, "key": "reliefweb:000427:20:11:0", "source": "camp2", "luna_reason": "Existing monthly data supplied to UNHCR underlies the presented asylum-applicant table.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.7753190398216248, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 210, "end": 222, "key": "reliefweb:000427:20:11:1", "source": "camp2", "luna_reason": "Existing monthly data supplied by countries underlies the presented asylum-applicant table.", "usage_type": "declaration", "specificity": "vague"}]}
-{"text": " son**\n**mucho más dados a remitir solicitudes de asilo afirmativas a través**\n**del Departamento de Seguridad Nacional (96% del total de solici-**\n**tudes), que reportan a ACNUR solicitudes de casos que a menudo**\n**engloban a más de una persona, en lugar de solicitudes defensivas**\n**mediante el Departamento de Justicia, que se reportan por individuo.**\n**Frente a ello, se remiten a través del Departamento de Seguridad**\n**Nacional el 23% de las nuevas solicitudes de asilo de salvadoreños,**\n**el 29% de las de guatemaltecos y el 23% de las de hondureños.**\n\n\n\nTurquía siguió recibiendo solicitudes de asilo desde\notros países distintos a Siria, cuyos nacionales reciben\napoyo por el régimen de protección temporal. Turquía\nse convirtió debido a ello en el quinto país que más\nsolicitudes de asilo recibió con 83.800 en 2018.\n(Estas cifras tienen en cuenta las solicitudes remitidas\na ACNUR hasta el 10 de septiembre de 2018, el día\nque ACNUR Turquía terminó su labor de registro de\nextranjeros que buscaban protección internacional\ny el Gobierno turco estableció un procedimiento\ndescentralizado para todos los solicitantes). Los\nsolicitantes de asilo afganos siguieron remitiendo\nla mayor parte de solicitudes en 2018 con 53.000,\nfrente a las 67.400 de 2017. De igual forma", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000519", "page": 21, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "registro de\nextranjeros", "probe_tag": "confusion", "probe_score": 0.2932921350002289, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 978, "end": 1001, "key": "reliefweb:000519:21:5:0", "source": "camp2", "luna_reason": "Registration activity, not an existing dataset used for analysis", "drop_reason": "production", "specificity": "vague"}]}
-{"text": " recently started working as a refugee doctor in order to support the COVID-19 response._\n_“I’ve waited for this opportunity for years. It now feels that the seven years I spent at medical school in Yemen we’re finally worth it.”_\n_© UNHCR/Lilly Carlisle_\n\n\nmore on the complementarity of approaches, with resettlement serving as a priority\nto many refugees in the region, including as alternative to dangerous onward\njourneys, given the lack of other solutions available to refugees in the region.\nInvesting in protection linked with durable solutions, with ongoing attention to\nefficient case processing and management towards resettlement, complementary\npathways and voluntary return, will remain a priority of the Strategy.\n\n\nMENA operations will seek to strengthen their capacity and efficiency further towards\nachieving resettlement targets at the levels of the pre-pandemic era while ensuring\nthe integration of integrity safeguards, as reflected in the Bureau’s risk register.\nMENA will strive to additionally encourage swift departures, as much as possible, to\nensure the essential protection that resettlement offers refugees is realized.\n\n\nIn 2023, resettlement will continue being used strategically and as a foundation for\ndialogue with host States. Resettlement remains crucial in today’s regional landscape\nas it promotes international responsibility sharing as reflected in the Global Compact\non Refugees and is a tangible demonstration of solidarity. Nevertheless, with annual\nopportunities for resettlement only meeting five per cent of refugee protection needs\nin MENA, the expansion of opportunities will remain one of the main objectives for\nthe year to come.\n\n\nAn important outlook for 2023 is to refine and ensure the continuation of innovative\nand creative solutions in MENA that will help drive the upscaling of resettlement,\n\n\n\n86 87", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000214", "page": 43, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Bureau’s risk register", "probe_tag": "confusion", "probe_score": 0.5218762159347534, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 961, "end": 983, "key": "reliefweb:000214:43:2:0", "source": "camp2", "luna_reason": "Names a risk register without showing substantive data analysis or use.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": " and \n discussions \n with \n SWG \n members, \n the \n Senior \n Gender \n Capacity \n Advisor \n and\nthe \n Sector \n Gender \n Focal \n Points \n Network, \n the \n SGBV \n SWG \n identified \n engaging \n with \n men \n & \n boys \n as \n one \n of\nthe \n priorities \n for \n 2015 \n and \n this \n is \n reflected \n in \n the \n 2015 \n SGBV \n SWG \n Work \n Plan \n as \n one \n of \n the \n specific\nobjectives. \n For \n the \n SGBV \n SWG, \n it \n is \n important \n to \n ensure \n that \n SGBV \n service \n providers \n are \n aware \n of \n tools\nand \n strategies \n to \n effectively \n include \n and \n engage \n men \n and \n boys \n to:\n\n\n- Deepen \n understanding \n about \n the \n importance \n of \n engaging \n men \n and \n boys \n in \n SGBV \n prevention \n work\nand \n meet \n the \n needs \n of \n male \n survivors \n in \n SGBV \n response;\n\n- Share \n strategies \n and \n tools \n for \n inclusion \n of \n men \n and \n boys \n in \n SGBV \n response \n and \n prevention \n activities.\n\n- Identify \n actions \n to \n enhance \n the \n engagement \n of \n men \n and \n boys \n in \n SGBV \n programming \n at\norganizational \n and \n working \n group \n levels.\n\n\n**Summary \n of \n the \n Workshop**\n\n\nIn \n discussions \n about \n gender \n roles \n and \n cultural \n contexts, \n workshop \n participants \n discussed \n the \n following\nquestions:\n\n1 \n Evidence \n for \n the \n need \n for \n this \n workshop \n comes \n from \n two \n primary \n sources: \n Regular \n sex \n and \n age \n disaggregated \n data \n collection\nand \n analysis \n of \n provision \n of \n services \n through \n the \n UNHCR \n Refugee \n Coordination \n Portal \n (ActivityInfo) \n and \n the \n GBVIMS \n End \n of \n Year\nReport \n 2014 \n including \n data \n from \n SGBV \n case \n management.\n\n\n**<mark>Workshop: Engaging Men and Boys in Sexual and Gender-</mark>** **­‐** **<mark>Based Violence (SGBV) programming</mark>**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000868", "page": 0, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "sex \n and \n age \n disaggregated \n data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1363, "end": 1401, "key": "reliefweb:000868:0:1:0", "source": "camp2", "luna_reason": "Existing disaggregated data are declared as evidence informing workshop needs.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "UNHCR \n Refugee \n Coordination \n Portal", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1481, "end": 1520, "key": "reliefweb:000868:0:1:1", "source": "camp2", "luna_reason": "Portal data supported workshop need analysis through service data.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "<mark>TABLE 4</mark> **Origin of asylum applications lodged in Europe \u0003** | 2012 - 2013 **(1)**\n\n\nCovering 38 European countries which provided monthly data to UNHCR.\n\n\n\n\n\nOrigin\n\n\n\n\n\nAnnual\nchange\n\n\n\n|Share|Col2|Col3|Rank|Col5|\n|---|---|---|---|---|\n|2012<br>6.5<br>5.8<br>5.3<br>11.9<br>6.6<br>5.5<br>4.9<br>3.2<br>4.6<br>2.7<br>1.9<br>1.0<br>2.9<br>1.8<br>1.6<br>2.2<br>2.2<br>0.7<br>1.8<br>1.3<br>1.1<br>0.8<br>1.6<br>1.5<br>1.6<br>1.3<br>1.2<br>0.8<br>0.6<br>0.7<br>0.9<br>0.7<br>0.7<br>0.6<br>0.6<br>0.5<br>0.4<br>0.3<br>0.5<br>0.4<br>9.0|2013<br>11.1<br>8.0<br>7.4<br>7.3<br>7.1<br>4.6<br>4.6<br>4.4<br>3", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001462", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.803321897983551, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 144, "end": 156, "key": "reliefweb:001462:25:0:0", "source": "camp2", "luna_reason": "Monthly UNHCR data underpin the presented asylum-application table.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": " públicas; buscar alternativas a la detención.\n\n\n**Sector Trabajo.-** transversalizar el tema de migración general en los ministerios de trabajo; crear\nmecanismos de coordinación en cada país; establecer y promover convenios con los países\nbuscando la migración ordenada y segura bajo acuerdos establecidos; establecer un sistema\nformal para las personas que migran irregularmente; Ministerios del Trabajo deben aprovechar\nlos programas de desarrollo; directorio institucional entre consulados, migración y ministerios\nde trabajo; simplificar los trámites y costo de los trámites de migración y de obtención de\ndocumentación; implementación de los protocolos regionales existentes y evaluarlos para incluir\nsituaciones no previstas en ellos, sobre todo respecto a niñez laboral; capacitar y sensibilizar a\nlos funcionarios públicos, sobre todo en materia de trabajo; crear mecanismos efectivos para la\nniñez indígena específicamente.\n\n\n**Sector Migración.-** Implementación de políticas públicas de prevención de la migración y\npromover la migración documentada; crear sistemas de información integrales y con conexiones\ninterinstitucionales; homologación de formularios únicos y protocolos de actuación; necesaria la\nrevisión y adecuación de procedimientos actuales sobre los sistemas de registro de nacimientos\npara garantizar el derecho a la identidad; capacitación para un formulario único; armonización\nde legislaciones migratorias en estándares internacionales; armonizar los datos", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000894", "page": 90, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "sistemas de registro de nacimientos", "probe_tag": "confusion", "probe_score": 0.1614680290222168, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1277, "end": 1312, "key": "reliefweb:000894:90:1:0", "source": "camp2", "luna_reason": "Names birth-registration systems without showing their data being used.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"text": "Integrated GbV and SRH\nSectoral Impact and Needs Analysis\nHeavy monsoon floods in the northern parts of Bangladesh have caused substantial damage and suffering\nacross many districts. Flood damage, prolonged inundation together with COVID-19 distress has severe and\ndisproportionate impact on the safety and security, i.e.- protection of women, adolescent girls and other\nmarginalized groups. Demographic data is showing out of the affected people, around 1.47 million are\nwomen, almost 50,000 pregnant mothers, and that 160,000 are adolescent girls and children aged 5-18. Loss\nof houses, livelihoods, restricted mobility, lack of privacy, disrupted services and inaccessibility - weaken\nprotection measures and resilience of individuals. Around 40% female responded insecurity as one of the\nsufferings due to the flood. Earlier studies on COVID 19 already indicate an increasing trend of early marriage\nand this prolonged distress can further intensify such negative coping mechanisms. Possession of essential\npersonal items including clothes, GBV and SRH awareness and information can enhance confidence of\nadolescent girls, women and other gender diverse group to protect themselves and adopt GBV risk mitigation\nmeasures. At a household level, increasing food insecurity will impact the female headed households,\nadolescent girls and pregnant mothers the most – around 80% of the unions indicates irregular food intake or\nskipping meal, particularly as key sufferings for women and girls. Additionally, the loss of livelihood due to\nflood will differently impact women – taking away their fundamental rights including decision making and\naccess to services. In rural Bangladesh lifetime partner violence of any form is around 74% (VAW 2015),\ntherefore such distress can potentially lead to domestic violence against women and girls.\nSexual and Reproductive Health (SRH) needs during crisis situations are many times overlooked. For women\nand girls, this can result in life-threatening complications and even death. Primary data shows that health care\nservices and antenatal and neonatal care services have been disrupted in 251 (75%) and 215 (64%", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001664", "page": 34, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Demographic data", "probe_tag": "confusion", "probe_score": 0.7292742729187012, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 392, "end": 408, "key": "reliefweb:001664:34:0:0", "source": "camp2", "luna_reason": "Data is attributed to concrete demographic counts of affected people.", "usage_type": "evidential", "specificity": "vague"}, {"text": "Primary data", "probe_tag": "confusion", "probe_score": 0.7666497826576233, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 2019, "end": 2031, "key": "reliefweb:001664:34:0:1", "source": "camp2", "luna_reason": "Primary data supports concrete findings on disrupted healthcare services.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "/docid/61f3a52e4.html)</u>\nAvailable at: <u>[https://www.refworld.org/docid/64c2748c4.html](https://www.refworld.org/docid/64c2748c4.html)</u>\n\n\n7.  The numbers of the dead and missing in this factsheet relate to incidents that took place on the three Mediterranean routes for which IOM and UNHCR\nhas received a sufficient level of detail. Because data on deaths during sea crossings are highly incomplete, these figures are rounded to reflect the fact that\nthe true number of lives lost in the Mediterranean Sea is not known. To explore data, see IOM <u>[Missing Migrants Project and UNHCR Dead and](https://missingmigrants.iom.int/)</u> <u>[Missing at Sea](https://data.unhcr.org/en/dataviz/95?sv=0&geo=0&_ga=2.195999276.18342678.1696230784-1487407682.1601492413)</u>\n<u>[dashboard.](https://data.unhcr.org/en/dataviz/95?sv=0&geo=0&_ga=2.195999276.18342678.1696230784-1487407682.1601492413)</u>\n\n\n8.  IOM attributes the incident that took place off Pylos, Greece, where more than 500 individuals lost their lives on 14 June 2023, while en route from Libya\nto Italy, to the central Mediterranean Sea.\n\n\nJoint Press Release: UNHCR and IOM call for coordinated action and safe pathways, 14 June 2023, available at", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000246", "page": 8, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data on deaths during sea crossings", "probe_tag": "confusion", "probe_score": 0.10630938410758972, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 348, "end": 383, "key": "reliefweb:000246:8:2:0", "source": "camp2", "luna_reason": "Existing death data inform rounded figures despite acknowledged incompleteness.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " former refugees returning home prior to the\napplication of cessation clauses – the process to\nformally end refugee status – which came into effect\non 30 June 2022. The cessation of refugee status\nfollowed the peaceful resolution of two decades of\nintermittent civil conflict and political instability.\n\n\nOther sizeable refugee returns were observed in\nNigeria (13,300) and Burundi (12,500). While some\ndata on movements back to Ukraine is available,\nwith the fluid security situation it is not possible\nto determine if people who have returned have\nremained.\n\n\n\nFigure 10 **| Major refugee return flows | Jan-Jun 2021 and Jan-Jun 2022**\n\n\nSouth Sudanese refugees from Uganda\n\n\nSyrian refugees from Türkiye\n\n\nIvorian refugees from Liberia\n\n\nSouth Sudanese refugees from Sudan\n\n\nNigerian refugees from Niger\n\n\nSouth Sudanese refugees from Ethiopia\n\n\nBurundian refugees from Rwanda\n\n\n\n\n\nBurundian refugees from United Rep. of\n\nTanzania\n\n\n0 20,000 40,000 60,000 80,000\n\n\n**49** For example, UNHCR supports local communities receiving returnees through concrete and practical interventions in areas such as\nshelter, legal aid and civil documentation, distribution of relief items, livelihoods and repairs to schools, health facilities and other civilian\n[infrastructure. See the UNHCR statement on the return of displaced Syrians.](https://www.unhcr.org/news/latest/2021/7/60fefeff4/unhcr-statement-return-displaced-syrians.html)\n**50** It is likely that many of the returns to Côte d’Ivoire were former asylum-seekers.\n\n\n24 UNHCR > **MID-YEAR TRENDS 2022**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000857", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on movements back to Ukraine", "probe_tag": "confusion", "probe_score": 0.2667640447616577, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 403, "end": 436, "key": "reliefweb:000857:23:1:0", "source": "camp2", "luna_reason": "States data availability without citing an analyzed finding or substantive use.", "drop_reason": "availability", "specificity": "descriptive"}]}
-{"text": "Adult (15+) literacy rate [%]|ND|57.7|52.8|62.8|98.4|57.4|54.9|91.2|\n|Percentage of women (15+) in<br>labour force|15.7|57.3|66.4|28.8|55.9|54.3|24.4|35|\n|Percentage of men (15+) in<br>labour force|79.7|84.1|76.9|80.9|77.1|63.2|82.9|76.4|\n|Average household size17|7.3|4.68â|4.6|4.8â|7.4|4.9â|6.6|3.9â|\n\n\n_Source: World Bank Data and UNDP_\n\n\n**Table 3:** Comparative country level data: carbon dioxide emissions per capita\n\n\n\n|Col1|Afghanistan|Bangladesh|Bhutan|India|Maldives|Nepal|Pakistan|Sri Lanka|\n|---|---|---|---|---|---|---|---|---|\n|Carbon dioxide emission per<br>capita (tonnes)|0.29|0.37|0.66|1.67|3.3|0.14|0.93|0.62|\n\n\n_Source: UNDP_\n\n\n\n\n\n17 Variety of sources: UNFPA, 2012, <u>http://goo.gl/JY6Yyd; DGHS,2012,</u> <u>http://goo.gl/OJwnA9; Bhutan Multiple Indicator Survey 2010;</u>\nCMIE, 2011, <u", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001169", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "World Bank Data", "probe_tag": "keep", "probe_score": 0.9090189933776855, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 314, "end": 329, "key": "reliefweb:001169:14:2:0", "source": "camp2", "luna_reason": "Source line identifies World Bank data underlying presented comparative indicators.", "usage_type": "declaration", "specificity": "named"}, {"text": "Bhutan Multiple Indicator Survey", "probe_tag": "confusion", "probe_score": 0.7815672159194946, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 752, "end": 784, "key": "reliefweb:001169:14:2:1", "source": "camp2", "luna_reason": "Named survey cited as a source for comparative country-level data.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "-SEEKERS\n\n\n\nWERE CHILDREN\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**PEOPLE OF CONCERN**\n\n\n\n\n\n\n\n\n\n**8.5 million** people of concern in 2020\n0 **9%** of the global population of concern 91.9 million\n\n\n**People of concern | 2015-2020**\n\n\n\n**$207.5 million** funds available in 2020\n\n\n\n**Monthly evolution of funding | 2020**\n\nUnearmarked Softly earmarked Earmarked Tightly earmarked\n\n\n250\n\n\n\n**REGIONAL FUNDING OVERVIEW**\n**AND EARMARKING**\n\n\n\n0 **64%** funded $324.7 millionrequired\n\n\n\n**64%** funded $324.7 millionrequired\n\n\n\nRefugees\n\nStateless persons*\n\n10\n\n\n8\n\n\n6\n\n\n4\n\n\n2\n\n\n\nAsylum-seekers IDPs\n\nReturnees (refugees and IDPs) Others of concern\n\n\n\nJan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec\n\n\n\n\n\n\n\n200\n\n\n150\n\n\n100\n\n\n50\n\n\n0\n\n\n\n0\n\n\n\n2015 2016 2017 2018 2019 2020\n\n\n\n**4%**\n\n\n\n_*Data on stateless persons in Southern Africa not available._\n\n\n\n**94** UNHCR GLOBAL REPORT 2020 UNHCR GLOBAL REPORT 2020 **95**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001216", "page": 1, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Data on stateless persons in Southern Africa", "probe_tag": "confusion", "probe_score": 0.3288133442401886, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 757, "end": 801, "key": "reliefweb:001216:1:1:0", "source": "camp2", "luna_reason": "Pure statement that data are unavailable, without analysis or substitute estimates.", "drop_reason": "availability", "specificity": "descriptive"}]}
-{"text": "\nThose households were likely to be dissatisfied about the\nreduction and were unwilling to participate in the followup survey. Reduced participation resulted in a lower\nrepresentation among those two groups of households,\nparticularly when disaggregated by camp. Because of this,\nthe panel analysis was only conducted on the whole sample,\nwhile the disaggregation of panel findings by camp and\neligibility group was impossible. However, sample panel\ndata was adequate to conduct statistical analysis on relevant\noutcome indicators. Findings of the surveyed panel sample\ncannot be applied to the reference population, limiting the\ngeneralizability of the findings to the broader population.\n\n\n\n**Table 4: Panel household sample distribution by**\n\n**eligibility groups**\n\n\n\n|Eligibility Group|Total|\n|---|---|\n|Full food ration|757|\n|Half food ration|61|\n|No food assistance|74|\n|**Total**|**892**|\n\n\nThe changes in the outcome indicators were observed at\nthe same time as seasonal price changes of some food\nitems and seasonal variability in livelihood opportunities.\nSuch contextual changes – including the closure of Gihembe\ncamp shortly after data collection in September 2021 which\nled to a significant increase in population size in Mahama\ncamp - might have impacted JPDM results, so further\nmonitoring rounds are required to validate the observed\ntrends.\n\nFor more details on the methodology, the sampling method,\netc. please refer to the Annex.", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001368", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "panel\ndata", "probe_tag": "confusion", "probe_score": 0.058796025812625885, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 444, "end": 454, "key": "reliefweb:001368:14:1:0", "source": "camp2", "luna_reason": "Existing panel data supported statistical analysis of outcome indicators.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "The sampling approach for\nMyanmarese refugees entailed two\nsteps. Firstly, we used UNHCR’s\nregistration database (proGRES)\nand a population proportional to size\n(PPS) strategy to randomly select\n20 enumeration areas out of the 30\nmapped Sample Sites <sup>9</sup> . PPS is useful\nwhen sampling units vary in size\nbecause it assures that households in\ndenser enumeration areas have the\nsame probability of getting into the\nsample as those in smaller sites, and\nvice versa. Secondly, we randomly\nselected 20 households in each of the\n20 Sample Sites, for a total sample\nof 400. This selection occurred by\nrandomly selecting 6-7 apartment\nbuildings in each enumeration area,\nthen going to these locations and\nrandomly selecting the nearest 3-4\ndwellings with refugees from Myanmar\nplus 2-3 Indian/non-refugee dwellings\nfor interviews. Our final sample of\nMyanmarese totalled 434 households.\n\n\nThe sampling approach for Somali\nrefugees entailed enumeration. In view\nof the very limited number of Somali\nrefugees living in Delhi (around 200\nindividuals in total) we targeted all of\nthem. We identified their addresses\n\n\n\nusing UNHCR’s registration database,\nbeneficiaries’ lists of implementing\npartners and field visits with key\ninformants. We ended up with a\ntotal of 64 Somali households.\n\n\nThe sampling strategy for the Afghan\ncommunities had to address the\nvery low densities in Delhi’s wards.\nWe randomly identified addresses\nfrom UNHCR’s registration database\n(using a random number generator).\nDuring the field visits, if no Afghan\nnationals were living in the selected\napartment building, the enumerators\nselected up to two replacements from\nneighbouring blocks or buildings.\n\n\nOnce an Afghan household was\nidentified, enumerators used a\n‘snowball’ technique (often used\nin hidden populations which are\ndifficult to access) by asking the\nidentified Afghan respondent to\npoint us to other Afghans in the\nneighbourhood. In order to limit bias\nwe only selected up to four households\nthrough snowballing to complete the\ndesired sample. Indian households\nwere", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000087", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR’s registration database", "probe_tag": "keep", "probe_score": 0.9664838314056396, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1121, "end": 1150, "key": "reliefweb:000087:19:0:4", "source": "camp2", "luna_reason": "Existing UNHCR database used to identify addresses for refugee sampling.", "usage_type": "declaration", "specificity": "named"}, {"text": "beneficiaries’ lists of implementing\npartners", "probe_tag": "confusion", "probe_score": 0.7498599290847778, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1152, "end": 1197, "key": "reliefweb:000087:19:0:3", "source": "camp2", "luna_reason": "Existing beneficiary lists were used to identify addresses for refugee sampling.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "-seekers \nwaiting to register claims. As a consequence, the number of applicants registered rose sharply in 2007, \nmaking Greece the sixth most important receiving country during that year (25,100 claims). Since then, \nthe number has decreased continuously and stood at 10,300 applications in 2010. As a consequence, Greece \ndropped to 11th place.14 \nThe number of Iraqi asylum applications lodged in Sweden dropped from 18,600 in 2007 to 2,300 in 2009. It \nis believed that a change in Swedish decision-making on Iraqi asylum claims and an active return policy led \n13\tThe figure for Belgium includes 3,400 repeat claims.\n14\tSee Annex Table 1 for the number of asylum claims submitted in those countries.\nIncrease and decrease\nof asylum claims\nIncrease         over 100%\nIncrease     50% to 100%\nIncrease       1% to   50%\nDecrease      1% to  50%\nDecrease    50% to 100%\nDecrease        over 100%\nLess than 10 claims in 2010\n+7,630\n-1,890\n-7,160\n-9,410\n-10 +250\n+90\n+170\n-5,650\n-2,240\n+10\n+270\n+5,670\n+2,760\n-970\n-180\n+13,680\n-8,590\n-1,570\n-340\n+1,390\n-\n-4,800\n+30\n+140\n-2,220\n-280\n+20\n-270\n-890\n+20\n-4,050\n+20\n-750\n+1,150\n+160\n+10\n-180\n+100\n-10\n+2,040\n-10,090\n+6,510\nTrends in asylum claims lodged in 44 industrialized countries:\nAbsolute and relative increase/decrease 2010 compared to 2009\nMap 1\nNote: This map is limited to the 44 countries which provide monthly asylum statistics to UNHCR. All figures are rounded off to the closest ten.", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000381", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "monthly asylum statistics", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1361, "end": 1386, "key": "reliefweb:000381:7:1:0", "source": "camp2", "luna_reason": "Map presents asylum trends using monthly statistics provided to UNHCR.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " million refugees were granted citizenship by their asylum country. The\nUnited States of America alone accounted for two thirds of them, even though their 2008\nnumbers are not yet available. Azerbaijan and Armenia also granted citizenship to a significant\nnumber of refugees during the same period (188,400 and 65,800 respectively). For 2008,\nUNHCR was informed of refugees being granted citizenship in Belgium (4,200), Ireland (1,000),\nArmenia (730), and the United Republic of Tanzania (490).\n\n22 Data for the United States of America refers to US Fiscal Year (1 October – 30 September) and may include people resettled\nfor the purpose of family reunification.\n\n\n\n**Fig 5: UNHCR-assisted resettlement**\n\n\n\n**departures of refugees, 1993-2008**\n\n\n\n70,000\n60,000\n50,000\n40,000\n30,000\n20,000\n10,000\n0\n\n\n\n'92 '94 '96 '98 '00 '02 '04 '06 '08\n\n\n\n**_12_**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000784", "page": 11, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Data for the United States of America", "probe_tag": "confusion", "probe_score": 0.4329369068145752, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 499, "end": 536, "key": "reliefweb:000784:11:2:0", "source": "camp2", "luna_reason": "Defines data coverage without presenting or analyzing a finding.", "drop_reason": "availability", "specificity": "descriptive"}]}
-{"text": "U N H C R / S . R I C H\nIX\nD\nATA COVERAGE ON \nATA COVERAGE ON \ndemographic information \ndemographic information \ngenerally differs among \ngenerally differs among \nthe various population cat-\nthe various population cat-\negories, with coverage for \negories, with coverage for \nrefugees traditionally being among \nrefugees traditionally being among \nthe highest. This can be explained \nthe highest. This can be explained \nby the fact that UNHCR has in place \nby the fact that UNHCR has in place \na dedicated refugee registration sys-\na dedicated refugee registration sys-\ntem and mechanism for collecting \ntem and mechanism for collecting \ninformation on refugees, as opposed \ninformation on refugees, as opposed \nto for the other population categories. \nto for the other population categories. \nPopulation data on refugees is often \nPopulation data on refugees is often \ndisaggregated by sex and age, as well \ndisaggregated by sex and age, as well \nas by location. It is important to em-\nas by location. It is important to em-\nphasize that demographic and loca-\nphasize that demographic and loca-\ntion information improves needs as-\ntion information improves needs as-\nsessment and monitoring, while also \nsessment and monitoring, while also \nenhancing mechanisms for identify-\nenhancing mechanisms for identify-\ning gaps in effective protection.\ning gaps in effective protection.\nDEMOGRAPHIC \nCHARACTERISTICS\nThe total number of countries or \nThe total number of countries or \nterritories that provide demographic \nterritories that provide demographic \ninformation disaggregated by sex \ninformation disaggregated by sex \nhas decreased slightly, from \nhas decreased slightly, from 165\n165 in \n in \n2012\n2012 to \n to 157\n157 a year later. While over-\n a year later. While over-\nall data coverage increased slightly \nall data coverage increased slightly \nin \nin 2013\n2013 in absolute terms, a further \n in absolute terms, a further \ndeterioration in relative terms has \ndeterioration in relative terms has \nbeen observed. This is primar-\nbeen observed. This is primar-\nily explained by a continuation of \nily explained by a continuation", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001229", "page": 34, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Population data on refugees", "probe_tag": "confusion", "probe_score": 0.8291587233543396, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 793, "end": 820, "key": "reliefweb:001229:34:0:0", "source": "camp2", "luna_reason": "Existing refugee population data is described as supporting needs assessment and monitoring.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "Population data on refugees", "probe_tag": "confusion", "probe_score": 0.47461292147636414, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 793, "end": 820, "key": "reliefweb:001229:34:0:1", "source": "camp2", "luna_reason": "Generic population data is mentioned without an attributed finding or concrete data use.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": " please see here.](https://dtm.iom.int/europe/arrivals)\n\n12. References to Kosovo shall be understood to be in the context of United Nations Security Council\nresolution 1244 (1999).\n\n13. The list of indicators considered included is: Having worked without getting the expected payment; Being forced to work; Offers of an arranged marriage; Being kept at a certain location\nagainst their will; Experienced some form of physical violence; Observed threats with sexual\nviolence.\n\n14. European Union Member States + Iceland, Liechtenstein, Norway and Switzerland.\n\n15. Data extracted on 11 July 2023.\n\n16. A first-time applicant is a person who lodge an application for asylum for the first time in a given\nEuropean country.\n\nMaps in this file are for illustration purposes only. The boundaries and names shown\nand the designations used do not imply official endorsement or acceptance by\nUNHCR, UNICEF and IOM.\n\n\n\nUNICEF:\n**Deepak Kumar Dey**\ndkdey@unicef.org\n\n\n\nIOM:\n**Ivona Zakoska Todorovska**\ndtmmediterranean@iom.int\n\n\n\nFor further information or any\nquestions concerning this\nfactsheet, please contact:\n\n\n\nUNHCR:\n**Javed Khan**\nkhanjav@unhcr.org\n\n\n\n_8_", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000370", "page": 7, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "Data extracted on 11 July 2023", "probe_tag": "confusion", "probe_score": 0.07284197956323624, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 565, "end": 595, "key": "reliefweb:000370:7:5:0", "source": "camp2", "luna_reason": "Bare date-qualified data reference without a named source or demonstrated use.", "drop_reason": "ref_list", "specificity": "vague"}]}
-{"text": "Furthermore, more than 2 million asylum applications were lodged in 38 European countries in 2015\n\n     - almost three times the 2014 figure (709,800). It\nshould be noted, however, that the recording of statistical information in Europe in 2015 includes considerable instances of double counting. According\nto European government statistics, the main countries of origin of applicants were the Syrian Arab\n\n\n\nRepublic (675,700), Afghanistan (406,300) and Iraq\n(253,600). European Union (EU) Member States received more than 1.2 million asylum applications,\nwith Germany and Sweden receiving close to 50\nper cent of applications launched in the EU. ●\n\n\nData Source:\nhttp://data.unhcr.org/mediterranean/regional.php\n\n\n\n**Fig.15** **Monthly Mediterranean Arrivals in 2015**\n\n***** Figures include sea arrivals to Malta, Italy and Greece and sea and land arrivals to Spain\n\n\n**250,000**\n\n\n**200,000**\n\n\n**150,000**\n\n\n**100,000**\n\n\n**50,000**\n\n\n**0**\n**JAN** **FEB** **MAR** **APR** **MAY** **JUN** **JUL** **AUG** **SEP** **OCT** **NOV** **DEC**\n\n\nUNHCR Global Trends 2015 **35**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001367", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR Global Trends 2015", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1044, "end": 1068, "key": "reliefweb:001367:33:0:1", "source": "camp2", "luna_reason": "Named UNHCR report cited as source for asylum application statistics.", "usage_type": "evidential", "specificity": "named"}]}
-{"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": "**Population Data Analysis** Mid-Year Review Regional Bureau for Southern Africa | June 2024 11", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001265", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Population Data", "probe_tag": "drop", "probe_score": 0.017070390284061432, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 2, "end": 17, "key": "reliefweb:001265:10:0:0", "source": "camp2", "luna_reason": "Document title fragment, not an identified data source or actual data use.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "unhcr > **Global trends 2017** 11", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000669", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Global trends 2017", "probe_tag": "drop", "probe_score": 0.03141952306032181, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 10, "end": 28, "key": "reliefweb:000669:10:0:0", "source": "camp2", "luna_reason": "Named UNHCR report is explicitly referenced.", "usage_type": "declaration", "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": "* **allocation:** [persons granted refugee status 2015, 2016, 2017; persons granted subsidiary/temporary](http://ec.europa.eu/eurostat/documents/2995521/7233417/3-20042016-AP-EN.pdf/)\n[protection 2015, 2016, 2017; number of asylum applications: 2015-17; number of resettled persons 2015, 2016, 2017 (no](http://ec.europa.eu/eurostat/documents/2995521/7233417/3-20042016-AP-EN.pdf/)\ndata available for number of persons being resettled, as specified in the AMF distribution key).\n**Integration** **& legal migration allocation:** [total number of legally residing TCNs 2015-2017 (data filtered to include permits](http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_resvalid&lang=en)\nof 12 months or longer duration and exclude permits related to education); number of TCNs obtaining a first residence\n[permit (data filtered to exclude students or permits of less than 12 months duration) 2015-17.](http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_resfirst&lang=en)\n**Countering irregular migration** **allocation:** [number of TCNs subject to a return decision 2015-2017; number of TCNs who](http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_eiord&lang=en)\n[have left the territory as a result of an order to leave (voluntary", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001185", "page": 47, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "migr_resvalid", "probe_tag": "drop", "probe_score": 0.04793050140142441, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 669, "end": 682, "key": "reliefweb:001185:47:1:0", "source": "camp2", "luna_reason": "Eurostat dataset supplies legally residing TCN counts for allocation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "Idem as**1.3’’’’ a** <br>Idem as**1.3’’’’ a** <br>Idem as**1.3’’’’ a** <br>Idem as**1.3’’’’ a**<br> <br>Idem as**1.3’’’’ a** <br>Idem as**1.3’’’’ a** <br>Idem as**1.3’’’’ a**|**1.3’’’’**Income from<br>agricultural production<br>facilitated <br>**1.3’’’’ a:**% of targeted<br>PoC who self-report<br>increased/maintained/d<br>ecreased income<br>compared to previous<br>year (for livestock and<br>fisheries)<br>i.e., Targeted PoC =<br>PoC targeted with non-<br>farming agricultural<br>intervention (only<br>livestock or fisheries)<br> <br>(# of targeted PoC<br>who self-report<br>increased/maintaine<br>d/decreased income<br>compared to last<br>year / # of targeted<br>PoC surveyed) x<br>100<br> <br>Idem <br>Idem<br>**Beneficiary**<br>**midline and end**<br>**line Survey (1st **<br>**cycle)** will be<br>administered by<br>partner and this<br", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001259", "page": 96, "chunk": 13, "split": "holdout_annotate", "spans": [{"text": "line Survey", "probe_tag": "drop", "probe_score": 0.04360790550708771, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 758, "end": 769, "key": "reliefweb:001259:96:13:0", "source": "camp2", "luna_reason": "Survey is planned for administration by the partner.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nSouth Sudan Health Sector Transformation Project (HSTP) (P181385)\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|age-specific mortality rates of that period, expressed per 1000 live births|\n|---|---|\n|Frequency|Annually|\n|Data source|Survey|\n|Methodology for Data<br>Collection|Survey|\n|Responsibility for Data<br>Collection|Third Party Monitor / PMU|\n|**Under ive years’ mortality rate (per 1000 live births) for refugees**|**Under ive years’ mortality rate (per 1000 live births) for refugees**|\n|Description|The probability of a child born in a specific year or period dying before reaching the age of 5 years, if subject to<br>age-specific mortality rates of that period, expressed per 1000 live births|\n|Frequency|Annually|\n|Data source|Survey|\n|Methodology for Data<br>Collection|Survey|\n|Responsibility for Data<br>Collection|Third Party Monitor / PMU|\n|** ntermittent prevention o malaria during pregnancy (  p≥3)**|** ntermittent prevention o malaria during pregnancy (  p≥3)**|\n|Description|Percentage of women who received three or more doses of intermittent preventive treatment during antenatal<br>care visits during their last pregnancy|\n|Frequency|Quarterly|\n|Data source|DHIS2|\n|Methodology for Data<br>Collection|DHIS2|\n|Responsibility for Data<br>Collection|MoH and UNICEF; Measures subcomponent 1.1 Under UNICEF|\n|**Maternal mortality ratio**|**Maternal mortality ratio**|\n|Description|Number of maternal deaths from any cause related to or aggravated by pregnancy or its management (excluding", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000006", "page": 51, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "DHIS2", "probe_tag": "drop", "probe_score": 0.029331916943192482, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1196, "end": 1201, "key": "refugee_pads:000006:51:0:1", "source": "camp2", "luna_reason": "Names DHIS2 as a data source without showing its data being used.", "drop_reason": "system_registry", "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": "refugee_pads", "corpus_id": "refugee_pads:000170", "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:000170:62:2:0", "source": "camp2", "luna_reason": "Bare date-qualified data phrase without an identified source or substantive finding.", "drop_reason": "ref_list", "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": "|Col1|ABBREVIATIONS AND ACRONYMS|\n|---|---|\n|AIP|Annual Investment Plan|\n|ACLED|Armed Conflict Location and Event Data|\n|AERMW|Agency for the Execution of Road Maintenance Works|\n|CBO|Community-based Organizations|\n|CEC|Citizen Engagement Committee|\n|CEDP|Casamance Economic Development Project|\n|CERC|Contingent Emergency Response Component|\n|COVID-19|Coronavirus Disease|\n|CPF|Country Partnership Framework|\n|CSO|Civil Society Organization|\n|DDP|Department Development Plan|\n|DFIL|Disbursement Financial Information Letter|\n|ESCP|Environmental and Social Commitment Plan|\n|ESRS|Environmental and Social Review Summary|\n|ESP|_Emerging Senegal Plan (Plan Senegal Emergent)_|\n|ESMF|Environmental and Social Management Framework|\n|ESMP|Environmental and Social Management Plan|\n|FCV|Fragility Conflict and Violence|\n|FI|Financial Intermediaries|\n|FM|Financial Management|\n|FP|Facilitating Partners|\n|FY|Fiscal Year|\n|GBV|Gender-based Violence|\n|GDP|Gross Domestic Product|\n|GII|Gender Inequality Index|\n|GoS|Government of Senegal|\n|GRM|Grievance Redress Mechanism|\n|IFC|International Finance Corporation|\n|IFR|Interim Financial Report|\n|IPF|Investment Project Financing|\n|IRR|Internal Rate of Return|\n|LDP|Local Development Plan|\n|LIW|Labor Intensive Work|\n|LMIC|Lower Middle-income Country|\n|LMP|Labor Management Procedure|\n|M&E|Monitoring and Evaluation|\n|MIS|Management Information System|\n|MPI|Multi-dimensional Poverty Index|\n|MTR|Mid-term Review|\n|NGO|Non-governmental", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000116", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Armed Conflict Location and Event Data", "probe_tag": "drop", "probe_score": 0.03317582979798317, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 80, "end": 118, "key": "refugee_pads:000116:2:0:0", "source": "camp2", "luna_reason": "Glossary definition names ACLED without showing its data being used.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"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": "refugee_pads", "corpus_id": "refugee_pads:000029", "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": "refugee_pads:000029:16:0:0", "source": "camp2", "luna_reason": "The Planning unit currently generates this data, so it is project-produced rather than reused.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "**PROTECTION BRIEF III SLOVAKIA**\n\n**July 2023 – March 2024**\n\n\nsubsidies, and only newly arrived refugees and those with certain vulnerabilities are targeted by the\nsupport. <sup>32</sup>\n\n#### Inclusion in the Social Protection System\n\n\nThe Government of Slovakia has enabled Temporary Protection holders to access significant portions of\nthe public social protection system on par with Slovak nationals. Notably, refugees can avail themselves\nof numerous State-provided social protection benefits, primarily channeled through the Offices of\nLabour, Social Affairs and Family. A key instrument is the Material Need Assistance, <sup>33</sup> designed for\nindividuals whose household income falls below the national subsistence minimum threshold. <sup>34</sup> This\nassistance is particularly relevant for older persons, single mothers with children, persons with disabilities\nor serious medical condition, or newly arrived refugees. According to official data, more than 12,000\nrefugees received the Material Need Assistance in January 2024. <sup>35</sup> Another vital social protection\ninstrument is the Disability Allowance for Refugees, <sup>36</sup> available to refugees with two different degrees\nof severe disability. The Offices of Labour, Social Affairs and Family conduct individual assessments to\ndetermine eligibility and the amount of the assistance. According to official data, more than 1,400\nrefugees received the Disability Allowance for Refugees in September 2023. <sup>37</sup> Other important\ninstruments available to Temporary Protection holders include the Childcare Allowance, <sup>38</sup> Subsidy to\nSupport Child’s Nutrition Habits, <sup>39</sup> Subsidy to Support Child’s Education, <sup>40</sup> and the Substitute Care\nAllowance. <sup>41</sup> Moreover, the State-supported accommodation system for refugees", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000476", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "official data", "probe_tag": "keep", "probe_score": 0.9232162833213806, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 947, "end": 960, "key": "reliefweb:000476:4:0:0", "source": "camp2", "luna_reason": "Official data supports the reported number of refugees receiving assistance.", "usage_type": "evidential", "specificity": "vague"}, {"text": "official data", "probe_tag": "keep", "probe_score": 0.9318990111351013, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 947, "end": 960, "key": "reliefweb:000476:4:0:1", "source": "camp2", "luna_reason": "Official data supports the reported count of refugees receiving assistance.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "**<u>2007 Global Trends</u>**\n\n\nUNHCR assistance departed from Thailand (14,600), Kenya (6,500), the United Republic of\nTanzania (6,200), Malaysia (5,600), and Turkey (2,700). These five UNHCR offices together\naccounted for 7 out of every 10 UNHCR-assisted resettlement departures in 2007.\n\nA total of 75,300 refugees were admitted by 14\nresettlement countries, including the United\nStates of America (48,300) <sup>20</sup> [^20: Resettlement statistics for the United States of America may also include persons resettled for the purpose of family\nreunification.], Canada (11,200),\nAustralia (9,600), Sweden (1,800), Norway\n(1,100), and New Zealand (740). Overall, this\nwas 5 per cent above the total for 2006 (71,700).\nOver the last few years, States in Latin America\nhave emerged as new resettlement countries,\nalbeit at a lower scale, offering a durable\nsolution for refugees primarily from Colombia.\n\n\n_A US-bound refugee from Bhutan bids her friends and relatives_\n\n<u>Local integration</u> _goodbye in eastern Nepal’s Sanischare camp. UNHCR/ V. Tan_\n\nWhile the degree and nature of local integration is difficult to measure in quantitative terms,\nsome countries document the acquisition of nationality, the final and crucial step towards\nobtaining the full protection of the asylum country. Even in those cases where refugees acquire\nthe citizenship through naturalization, statistical data is usually very limited as the countries\nconcerned generally do not distinguish between refugees and others who have been naturalized.\nMoreover, national laws in many countries do not permit refugees to become naturalized. The\nnaturalization of refugees is both restricted and under-reported.\n\nThe limited data on naturalization of refugees available to UNHCR show that during the past\ndecade, more than 1 million refugees were granted citizenship by their asylum country. The", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000651", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Resettlement statistics for the United States of America", "probe_tag": "keep", "probe_score": 0.9072957634925842, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 430, "end": 486, "key": "reliefweb:000651:10:0:0", "source": "camp2", "luna_reason": "Statistics qualify the reported U.S. refugee resettlement figure.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "*\n\n\n\n**Housing (dwelling, sharing, evictions, rent**\n**costs)**\n\n\n\n**Livelihoods strategies (income sources,**\n**expenditure, debts, coping strategies, assets)**\n\n\n\n**Mobility (migration history, future**\n**intentions, return)**\n\n\n\nFor the area-based analysis, these areas are\ngrouped into three different geographical strata\nthat are analysed comparatively (a description\nof each area’s characteristics is provided in the\nfollowing section):\n\n\n\n**The Sulaymaniyah District Centre, being the**\n**district hosting the largest number of IDPs and**\n**refugees;**\n\n\n\n**Periphery district centres, which encompass**\n**all the district centres surrounding the**\n**Sulaymaniyah centre with a relevant population**\n**of IDPs or refugees;**\n\n\n\nThe sample drawn from each of the targeted\nsubdistricts was proportionate to the size of\neach population group in that subdistrict (Table\n1). Population figures for the host community\nand IDPs were facilitated by the Sulaymaniyah\nStatistics Office based on an internal census\ncarried out in 2015, which included IDPs pre- and\npost-2014; figures for refugees were facilitated by\nUNHCR. Population weights were subsequently\napplied during the analysis in order to obtain\nresults applicable to all urban areas at the\ngovernorate level.\n\n\nThe sample size used allows for an extrapolation\nof statistically significant results with a 5% margin\nof error for each geographical stratum, except\nfor the Kalar and Kifri segment (results are\nsignificant with a 10% margin of error due to a\nsmaller sample size available). The results are also\nrepresentative for each population group with a\n5% margin of error.\n\n\n\n**Kalar and Kifri district centres, which**\n**are areas that hold special relevance for the**\n**humanitarian partners", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000440", "page": 8, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "internal census", "probe_tag": "keep", "probe_score": 0.9191617369651794, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 995, "end": 1010, "key": "reliefweb:000440:8:1:0", "source": "camp2", "luna_reason": "Existing 2015 census supplied population figures used for sampling and analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "a\n\ninstancia”. Las 189.000 solicitudes restantes se cursaron en segunda instancia,\n\n\n\nincluidas las presentadas ante tribunales y otros órganos de apelación.\n\n\n\n**(36)**\n\nincluidas las presentadas ante tribunales y otros órganos de apelación.\n\n\nl deterioro de la situación humanitaria en manera justa o eficiente, ACNUR puede realizar la\nvarios países a lo largo del año se refleja determinación de la condición de refugiado en virtud\nclaramente en los datos estadísticos sobre de su mandato. En los últimos años, ACNUR ha\nlas personas que presentan solicitudes de registrado un aumento del número de solicitudes\nasilo durante el periodo abarcado en este de asilo individuales, pero el máximo histórico se\ninforme. En 2014 se presentaron ante los Estados o alcanzó en 2014, año en el que la organización registró\n# **E**\n\n\n\nl deterioro de la situación humanitaria en\nvarios países a lo largo del año se refleja\nclaramente en los datos estadísticos sobre\nlas personas que presentan solicitudes de\nasilo durante el periodo abarcado en este\ninforme. En 2014 se presentaron ante los Estados o\n# **E**\nante ACNUR más de 1,66 millones de solicitudes\nindividuales de asilo o de la condición de refugiado\nen 157 países o territorios, el nivel más alto del que\nse tiene constancia. Aunque la cifra provisional\nde 2014 representó un aumento del 54% de las\nsolicitudes de asilo en el mundo con respecto a\n2013 (1,08 millones)", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000206", "page": 26, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "datos estadísticos", "probe_tag": "keep", "probe_score": 0.9089224338531494, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 453, "end": 471, "key": "reliefweb:000206:26:1:0", "source": "camp2", "luna_reason": "Statistical data support concrete asylum-application figures and year-on-year comparison.", "usage_type": "evidential", "specificity": "vague"}, {"text": "datos estadísticos", "probe_tag": "keep", "probe_score": 0.9322575330734253, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 453, "end": 471, "key": "reliefweb:000206:26:1:1", "source": "camp2", "luna_reason": "Estadísticas sustentan hallazgos cuantificados sobre solicitudes de asilo", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "% es rural\n(Ortega y Ospina, 2012: 39). Aquí es importante tener en cuenta que si bien el conflicto armado\nha golpeado fuertemente a las zonas rurales del país, actualmente ciudades de la periferia como\nTumaco se encuentran gravemente amenazadas. En este mismo sentido es importante tener en cuenta\nque a pesar de que se reconozca a ciudades como Tumaco y Puerto Asís como zonas urbanas estas\ntienen características muy diferentes a las ciudades del interior, los procesos de descentralización\nde las últimas décadas si bien han dado mayor presencia a las municipalidades, los procesos de\nurbanización y desarrollo económico de estas son todavía insipientes.\n#### **1.2 Crecimiento progresivo del refugio en los últimos años**\n\nDe manera coincidente con estudios como el de Quito y de Guayaquil vemos que el ingreso de la\npoblación colombiana refugiada hacia Ecuador ha aumentado progresivamente.\n\n\nDe 420 casos encuestados, el 17,6% están en Ecuador desde el 2011; entre el 2008-2010\ningresaron el 43,6%; entre el 2000 y el 2007 ingresaron el 28,6%; las personas que ingresaron\nhasta 1999 representan el 3,9%, y para marzo del 2012 fecha en que fue levantada la encuesta se\nencontraron 25 casos de personas que recientemente entraron al Ecuador (ver gráfico 2).\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n(54,3%) seguido de Nariño con el 12,1%\ny Caquetá 9,3%.\n\nEstos resultados indican que la pro", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000895", "page": 6, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "encuesta", "probe_tag": "keep", "probe_score": 0.9089784622192383, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1163, "end": 1171, "key": "reliefweb:000895:6:2:0", "source": "camp2", "luna_reason": "Encuesta de 2012 sustenta los porcentajes y casos reportados.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "To estimate the causal effect of refugee arrivals on host communities’ attitudes\n\ntowards immigrants and income, the authors: (a) compare attitudes and income at the\n\nregional level four years before and four years after large, sudden arrivals of refugees;\n\n(b) compare regions that experienced large increases in refugees with those that did\n\nnot within the same country; and (c) compare effects across different hosting situations\n\n(i.e., by employment and encampment policies).\n\n\nThe analysis is based on data covering the period from 2005 to 2018, including: (i)\n\ndata on attitudes and income from Gallup World Poll (GWP) and 12 additional public\n\nopinion surveys; (ii) refugee populations at the sub-national level from UNHCR; and\n\n(iii) data on policies on camps from UNHCR and on _de jure_ access to the labor market\n\n[from Blair et al. (2021).](https://doi.org/10.1017/S0020818321000369)\n\n\nPreliminary findings:\n\n - **Across all regions, large and sudden arrivals of refugees do not have a**\n\n**negative effect on average attitudes towards immigrants or income.** On\n\naverage, there is little effect in the periods immediately following a large wave of\n\nrefugees across affected regions in lower- and middle-income countries.\n\n - **There is little evidence that attitudes towards immigrants or income vary**\n\n**across camp and non-camp settings or across environments with progressive**\n\n**and restrictive labor market policies.**\n\n\nThe authors conclude that, “while restrictive policies are often justified to benefit host\n\ncommunities, there is little evidence to support the argument.”\n\n\n**The Economic Effects of Immigration Pardons: Evidence from**\n**Venezuelan Entrepreneurs**\n\n\n_Dany Bahar, Bo Cowgill, and Jorge Guzman (2022)_\n_Working Paper_\n_<u>[http://dx", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001300", "page": 20, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on policies on camps from UNHCR", "probe_tag": "keep", "probe_score": 0.9471192955970764, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 743, "end": 779, "key": "reliefweb:001300:20:0:2", "source": "camp2", "luna_reason": "UNHCR data on camp policies informs analysis of refugee-hosting situations.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "MONITOREO DE PROTECCIÓN\n\n\n##### **6. Acceso a Documentación**\n\n\n\n76%\n\n\n\n\n\n\n\nSolicitante de la\n\ncondición de\n\nrefugiado\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nRefugiado\nreconocido\n\n\n\nSolicitud ha sido\n\nrechazada\n\n\n\nRetiró solicitud Intenciones de\nsolicitar refugio\n\nen Panamá\n\n\n\nIntenciones de\nsolicitar refugio\n\nen otro país\n\n\n\nNo tiene\nintenciones de\nsolicitar refugio /\n\n\n\nNo sabe / No ha\n\n\n\n_Fuente: PMT, HFS1, HFS2, HFS3_ decidido*\n_*Sólo se preguntó \"No sabe /no ha decidido solicitar refugio\" en PMT 2%. Se agrega a 2% \"No tiene intenciones de solicitar refugio.\"_\n\n\n\ndecidido*\n\n\n\nUNHCR / Febrero 2022 23", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001181", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "PMT", "probe_tag": "confusion", "probe_score": 0.31963199377059937, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 383, "end": 386, "key": "reliefweb:001181:21:0:0", "source": "camp2", "luna_reason": "Source-line cites PMT as the resource underlying presented protection-monitoring figures.", "usage_type": "declaration", "specificity": "named"}, {"text": "HFS2", "probe_tag": "confusion", "probe_score": 0.4817606806755066, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 394, "end": 398, "key": "reliefweb:001181:21:0:2", "source": "camp2", "luna_reason": "Named source cited for the table’s documented protection-access finding.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "<br>Pas de contre-vérification ni de triangulation parmi les différentes<br>sources concernant le même thème. Exécution d’une analyse<br>quantitative des données qualitatives.<br> <br> <br>  eux de disposer de plus de données.<br>Pas de prise en compte de la limite de saturation alors que les<br>données supplémentaires ne fournissent pas de nouvelles<br>informations ni de différents types d’informations.|\n|Les notes prises sur le terrain sont faciles à analyser.<br>Le guide d’interview doit être respecté à la lettre.<br>Il est (toujours) mieux de disposer de plus d’informateurs.<br>|Les notes prises sur le terrain sont faciles à analyser.<br>Le guide d’interview doit être respecté à la lettre.<br>Il est (toujours) mieux de disposer de plus d’informateurs.<br>|Les notes prises sur le terrain sont faciles à analyser.<br>Le guide d’interview doit être respecté à la lettre.<br>Il est (toujours) mieux de disposer de plus d’informateurs.<br>|Pas d’organisation chronologique ni d’organisation par mots clés<br>le jour même de leur rédaction.<br>Pas d’adaptation des questions en fonction des situations et des<br>individus.<br>Pas de sélection des informateurs les plus instruits, des<br>informateurs les plus au courant des probl", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001477", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "données qualitatives", "probe_tag": "confusion", "probe_score": 0.090755395591259, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 154, "end": 174, "key": "reliefweb:001477:23:1:0", "source": "camp2", "luna_reason": "Qualitative data are explicitly analyzed, indicating existing data use.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "### RECOMMENDATIONS\n\n**The following recommendations are based on the findings from this study, including suggestions made by the**\n**UNHCR offices themselves in the online survey.**\n\n\n\nInstitutional Level\n\n\nĐ CwC activities need to be scaled up and\n\n**mainstreamed** at the corporate level to go beyond\nthe current random approach that is based on the\nknow-how and commitment of individual staff\nmembers. UNHCR needs a CwC policy that prescribes\nobligatory measures and secures adequate resources.\nA feedback mechanism to measure the impact of\nCwC activities should also be created.\n\n\nĐ Communicating with audiences spread thousands\n\nof kilometres apart, from countries of origin to\ndiaspora communities in Europe, is a highly complex\nform of communication. UNHCR as an organisation\nhas considerable experience in CwC, but it is\ndistributed erratically. The organisation therefore\nneeds to **build staff capacities** as widely as possible,\nin all operations and at all levels. The best way to\ndo so is to develop an **advanced programme for**\n**CwC trainers** who would instruct and guide less\nexperienced staff members, thus evening out the\ninconsistencies between offices.\n\n\nCentral Mediterranean Route\n\n\nĐ Current UNHCR and TRS **awareness activities** are\n\n**no match for the flood of disinformation** PoC\nare exposed to. In order to enable PoC to make\ninformed decisions, UNHCR needs to **expand the**\n**TRS approach** . The characteristics of the TRS\napproach include engagement with the communities\nin the countries of origin and the diaspora, the\nuse of testimonials from community members,\nand consistent messaging through a multitude of\nchannels. TRS-styled campaigns should be developed\nfor all major groups using the Central Mediterranean\nRoute.\n\n\nĐ As digital platforms are accessible across borders,\n\nUNHCR offices can create synergies by **using**\n**the same platforms along the entire Central**\n**Mediterranean Route** .", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001467", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "online survey", "probe_tag": "confusion", "probe_score": 0.5670039653778076, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 166, "end": 179, "key": "reliefweb:001467:7:0:0", "source": "camp2", "luna_reason": "Existing online survey findings inform the study's recommendations.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "1\nOVERVIEW\nThis report is the eleventh in the series of Protection \nTrends reports prepared by the South Sudan Protection \nCluster, with inputs from Child Protection, Sexual and \nGender Based Violence (SGBV), and Mine Action \nsub-clusters.1 This paper is a departure from previous \nTrends reports, instead providing an overview of the \nprotection trends for the entire year. The paper provides \nan overview of the protection situation followed by a \ndiscussion of trends based on data collected during \nreporting period for general protection trends, child \nprotection, GBV, and mine action. This includes an \noverview of the context, access to basic services, forced \ndisplacement and population movement patterns, \nfamily tracing and reunification, grave violations of child \nrights, sexual and gender based violence (SGBV), and \nexplosive hazards. \nThis report is not an exhaustive overview of the context \nin South Sudan in 2017, rather it highlights trends \nand observations of the serious protection trends \nimpacting the civilian population in South Sudan to \ninform the response of both humanitarian and political \nactors. For more detail on protection trends relating \nto specific periods, please refer to previous quarterly \ntrends reports. To contextualize the reporting period, \nthe paper uses data going back to 2013, to understand \nthe progressive impact of conflict and insecurity on \nprotection concerns. The information presented in \nthe report is based on a broad range of sources. The \noperational environment currently limits the availability \nof data on some key protection concerns. Furthermore, \nlack of humanitarian presence and reliance on remote \ndata collection for some locations present major \nchallenges in providing an accurate and comprehensive \ndepiction of the protection situation in some areas.\nCONTEXT OVERVIEW\nThe continued armed conflict in South Sudan in 2017 \nhas dire consequences for civilians resulting in civilian \ndeaths, separation, and conflict related sexual \nviolence. These issues are compounded by growing \nfood insecurity, limited basic services, widespread \nhealth issues, and exacerbated by heavy rains and \nflooding. There was little improvement in the overall \nprotection environment and civilians continued to \nflee from active conflict and reports of fighting across", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001475", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data collected during \nreporting period", "probe_tag": "confusion", "probe_score": 0.24963800609111786, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 480, "end": 519, "key": "reliefweb:001475:1:0:0", "source": "camp2", "luna_reason": "Existing reporting-period data supports discussion of protection trends.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "data going back to 2013", "probe_tag": "confusion", "probe_score": 0.21318423748016357, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1306, "end": 1329, "key": "reliefweb:001475:1:0:1", "source": "camp2", "luna_reason": "Existing historical data is used to contextualize conflict impacts.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "social and cultural importance of such locations, contrasted with primary and capital cities. Secondary cities can\nbe intermediary cities and vice versa. This study uses all of these terms but seeks to do so in their appropriate\ncontexts, linking them to their usage by stakeholders. When presenting data from secondary research or\ninterviews, it adopts these terms as used by their original source.\n\n\nThe term “ **urban initiative** ” is used to refer to the full range of urban programmes and activities, implemented\nby protection stakeholders in collaboration with cities and municipalities. Urban initiatives can be international\nand involve multiple partners, as is the case with International Centre for Migration Policy Development’s\n(ICMPD) MC2CM project, implemented in partnership with UCLG and UN-Habitat. At the same time, initiatives\ncan also describe single programme activities, for instance a counselling service run by a municipality with\ntechnical inputs from an external stakeholder such as UNHCR.\n\n\n[UNHCR defines the](https://www.unhcr.org/glossary) **protection of vulnerable people on the move** as “all activities aimed at achieving\nfull respect for the rights of the individual in accordance with the letter and spirit of international human\nrights, refugee and humanitarian law. Protection involves creating an environment conducive to respect for\nhuman beings, preventing and/or alleviating the immediate effects of a specific pattern of abuse, and restoring\ndignified conditions of life through reparation, restitution and rehabilitation.” Targeting **vulnerable migrant**\n**populations** [, the International Organization for Migration’s (IOM’s)](https://www.iom.int/protection) **protection interventions** include, amongst\nothers, “child protection, risk mitigation, response to and prevention of gender-based violence, countertrafficking, alternatives to detention, mental health and psychosocial support, land property and reparations and\n[inclusion of", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001416", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data from secondary research or\ninterviews", "probe_tag": "confusion", "probe_score": 0.055398229509592056, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 300, "end": 342, "key": "reliefweb:001416:3:0:0", "source": "camp2", "luna_reason": "Generic data source is named without an attributed finding or concrete claim.", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
+{"text": "**22** UNHCR Mid-Year Trends 2014", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000565", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR Mid-Year Trends 2014", "probe_tag": "confusion", "probe_score": 0.32699480652809143, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 7, "end": 33, "key": "reliefweb:000565:21:0:0", "source": "camp2", "luna_reason": "Standalone report title with no shown data use or cited finding.", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": "%**~~<br>~~**1%**~~|\n\n\n\nDISCLAIMER: figures do not add up to 100 per cent due to rounding.\n\n\n**24** [The international migrant dataset includes refugees and asylum-seekers in specific countries. Source: https://www.un.org/en/development/](https://www.un.org/en/development/desa/population/migration/data/estimates2/data/UN_MigrantStockByAgeAndSex_2019.xlsx)\n[desa/population/migration/data/estimates2/data/UN_MigrantStockByAgeAndSex_2019.xlsx](https://www.un.org/en/development/desa/population/migration/data/estimates2/data/UN_MigrantStockByAgeAndSex_2019.xlsx)\n**25** [Source: https://population.un.org/wpp2019/Download/Standard/Population/](https://population.un.org/wpp2019/Download/Standard/Population/)\n**26** Demographic data is available for 80 per cent of refugees globally. For the remainder, UNHCR has estimated the demographics based on the\nrefugee data available in host countries and other countries in the same region. This figure excludes Venezuelans displaced abroad.\n**27** To enable the comparison, data for the 5-19 and 20-24 age ranges in the world population and international migrant data was apportioned to\nUNHCR’s 5-11, 12-17 and 18-24 ranges.\n**28** [https://www.unhcr.org/steppingup/](https://www.unhcr.org/steppingup/)\n\n\nUNHCR > **GLOBAL", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001657", "page": 18, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "Demographic data", "probe_tag": "confusion", "probe_score": 0.2600899636745453, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 716, "end": 732, "key": "reliefweb:001657:18:5:0", "source": "camp2", "luna_reason": "Generic demographic data supports the concrete 80-percent availability finding.", "usage_type": "evidential", "specificity": "vague"}, {"text": "refugee data", "probe_tag": "confusion", "probe_score": 0.4284474551677704, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 853, "end": 865, "key": "reliefweb:001657:18:5:1", "source": "camp2", "luna_reason": "Existing refugee data underpins UNHCR demographic estimates for countries lacking complete data.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " the Shona population report being able to\nread and write in at least one language, 93 percent of urban nationals can do so. Male Shonas report\na slightly higher literacy rate at 93 percent, compared to 85 percent of women. In contrast, urban\nnational rates are 95 percent and 91 percent for men and women, respectively. Considering the two\nofficial languages in Kenya, English and Swahili, more than 75 percent of the Shona community population can read and write in at least one of them: English (74 percent) and Swahili (87 percent).\n\n\n**The employment rate of the Shona community is higher than for urban nationals, although this does**\n**not translate into lower poverty rates; most of the employed Shona are self-employed.** Most of the\nworking-age Shona population is employed, which is slightly higher than the urban Kenyan average\n(73 percent vs. 69 percent). However, the Shona poverty rate remains higher than for nationals. Moreover, nearly 8 in 10 Shona employed are self-employed compared to only 3 in 10 among nationals.\nSuch a differing trend may be explained by the lack of identity documents needed to access the formal\nemployment market, which may force most of the Shona community to engage in self-employment to\nearn a living. Only 2 percent of the Shona report being unemployed, which is in line with the 4 percent\nof urban Kenyans, whereas 24 percent are outside the labor force (OLF) compared to the national\nurban average of 27 percent.\n\n\n**The findings from the Shona SES also reflect differences in intra-household bargaining power among**\n**men and women.** Overall, Shona community women are less likely to be involved in decision making,\nbe less educated, and have lower labor force participation. Women and girls in the Shona community\nhave lower overall educational attainment, attendance, and literacy rates than Shona men and boys.\nIn addition, when the two official languages in Kenya", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001424", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Shona SES", "probe_tag": "confusion", "probe_score": 0.7977429628372192, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1488, "end": 1497, "key": "reliefweb:001424:12:1:0", "source": "camp2", "luna_reason": "Findings from the named Shona SES support household bargaining-power analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " Durante la mayor parte del\npasado decenio, las cifras de desplazamiento oscilaron\nentre 38 millones y 43 millones de personas al año.\nSin embargo, a partir de 2011, cuando era de 42,5\nmillones, la cifra ha aumentado hasta llegar a la actual\nde 59,5 millones, lo que representa un incremento\ndel 40% en tan solo tres años. Este crecimiento\nplantea dificultades para encontrar respuestas\nadecuadas a estas crisis, que de forma creciente son\ncausa del desplazamiento múltiple de personas o de\nmovimientos secundarios en busca de seguridad.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**(3)** Esta cifra incluye a 19,5 millones de refugiados: 14,4 millones bajo el mandato de ACNUR y 5,1 millones de refugiados palestinos inscritos en el Organismo de Obras\n\nPúblicas y Socorro de las Naciones Unidas para los Refugiados de Palestina en el Cercano Oriente (UNRWA). La cifra global también incluye a 38,2 millones de\ndesplazados internos (fuente: IDMC) y a casi 1,8 millones de personas cuyas solicitudes de asilo no se habían resuelto al final del periodo del informe.\n\n\n\n**(4)** Fuente para las poblaciones nacionales: Naciones Unidas, División de Población, Perspectivas de la población mundial: La revisión de 2012, Nueva York, 2013. A los fines\n\nde este análisis, se ha tenido en cuenta la población de variante media de fertilidad de 2014.\n\n\n\nACNUR Tendencias Globales 2014 **5**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000206", "page": 4, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "IDMC", "probe_tag": "confusion", "probe_score": 0.6815088391304016, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 915, "end": 919, "key": "reliefweb:000206:4:2:0", "source": "camp2", "luna_reason": "IDMC is cited as the source for the displaced-person population figure.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**Endnotes**\n\n1. These figures represent the total number of migrants and refugees who arrived in Italy and Malta through the Central Mediterranean Sea after departing\nfrom Algeria, Libya, and Tunisia in 2022. The numbers may include migrants and refugees who made more than one attempt to cross the sea from these\ncountries. These figures also include those who were intercepted or rescued by the authorities of Algeria, Libya and Tunisia and disembarked in these\ncountries in 2022.\n\n\nData on disembarkation in the three North African countries is sourced from a variety of channels, including official reports shared by national authorities,\nand media monitoring, and data gathered at the disembarkation points where UNHCR and IOM partners were present.\n\n\nData on arrivals in Italy and Malta is received from the Ministry of Interior of both countries.\n\n\n2. Central Mediterranean Route refers to sea departures from Algeria, Libya, and Tunisia, and to sea arrivals to Italy and Malta through the Mediterranean\nSea.\n\n\n3. Sources: UNHCR, IOM, UNDSS, Italian MoI, Official website of the Tunisian Ministry of Interior and the social media pages of the Tunisian Ministry of\nInterior and Tunisian National Guard, media and social media monitoring.\n\n\n4. Arrivals from Algeria were also recorded in Spain, but these fall outside the scope of this factsheet.\n\n\n5. See IOM <u>[Missing Migrants Project and UNHCR](https://missingmigrants.iom.int/)</u> <u>[Dead and Missing at Sea dashboard to explore data. The numbers of dead and missing in this factsheet](https://data2.unhcr.org/en/dataviz/95?sv=0&geo=0&_gl=1*1ju2cm2*_rup_ga*MTQ0ODMwODQ4Ny4xNjgzNjQxNzc2*_rup_ga_EVDQT", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000791", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data on arrivals in Italy and Malta", "probe_tag": "confusion", "probe_score": 0.8585852384567261, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 758, "end": 793, "key": "reliefweb:000791:5:0:1", "source": "camp2", "luna_reason": "Existing arrival data is sourced from both countries’ Ministries of Interior.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "Dead and Missing at Sea dashboard", "probe_tag": "confusion", "probe_score": 0.8064855933189392, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1448, "end": 1481, "key": "reliefweb:000791:5:0:2", "source": "camp2", "luna_reason": "Dashboard data underlies the factsheet’s reported dead and missing figures.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**PILLAR II. MULTISECTORAL**\n**RESPONSE**\n\n\nSince the development of the five-year strategy for the\neffective fight against SGBV, UNHCR and partners have\nexerted much effort in the camps despite the financial\nand material challenges as well as the lack of qualified\nmanpower. Still, there has been a clear improvement in\nthe quality and access to available services.\n\n\nin the treatment and handling of victims of sexual and\ngender-based violence UNHCR and partners in Chad\nimplemented a holistic and multisectoral approach. This\napproach consists of five concurrent responses: clinical\nmanagement of rape and other gender-based violence,\npsychosocial support, legal support, material support,\nsecurity and safety.\n\n\nIn 2016, some 78.9% of the victims received\npsychosocial support and treatment. In addition, 39.6%\nof victims had access to medical services, 30.1% were\nsupported materially, 6.4% legally, 26.6% with security\narrangements, 16.19% supported with incomegenerating activities and 1.2% had access to a safe\nenvironment.\n\n\nOverall, the statistical data analysis on access to and use\nof services available in 2016 indicates that psychosocial\ncare remains the most solicited service once again,\nfollowed by medical care.\n\n\n1. Access to medical services\n\n\nThe clinical management of SGBV cases in general and\nof rape in particular (as per the WHO standard\nprotocol) remains a major problem in Chad and by\nextension in the refugee population (lack of qualified\nmanpower, scarcity of inputs (pep kit), ignorance of the\nneed to arrive within 72 hours of an incident to a\nmedical structure on the part of the refugees, etc.)\n\n\nUNHCR, CNARR and humanitarian partner\norganizations elaborated SOPs for SGBV that also\naddress the challenges of medical management of\nSGBV in the camps. A free treatment service is\navailable in the health centers in refugee camps (trauma\ninjury management, STI treatment, pregnancy\nprevention, voluntary testing and pep", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001383", "page": 18, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "statistical data", "probe_tag": "confusion", "probe_score": 0.18183422088623047, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1047, "end": 1063, "key": "reliefweb:001383:18:0:0", "source": "camp2", "luna_reason": "Statistical data supports the 2016 analysis of service access and use.", "usage_type": "evidential", "specificity": "vague"}]}
+{"text": "|1969|\n|Republic of**KAZAKHSTAN**|6,121|Unknown|15,844|9|1999|1999|1995|\n|State of**KUWAIT**|398|-|1,519|157|-|-|1969|\n|**KYRGHYZ** Republic|3,292|Unknown|3,753|453|1996|1996|1992|\n\n\n222 United Nations Office of the High Commissioner for Refugees, 17 April 2006, (as of 1 January 2005) at www.unhcr.org.\n223 Internal Displacement Monitoring Centre (as of 24 July 2006) at www.globalidpproject.org.\n224 United Nations Office of the High Commissioner for Refugees, 17 April 2006, (as of 1 January 2005) at www.unhcr.org.\n225 United Nations Office of the High Commissioner for Refugees, 17 April 2006, (as of 1 January 2005) at www.unhcr.org.\n226 United Nations Office of the High Commissioner for Refugees, September 2005.\n227 European Union, 2002.\n228 Norwegian Refugee Council, December 2005.\n229 Norwegian Refugee Council, 2002.\n230 United Nations, March 2006.\n231 United Nations Humanitarian Coordinator, 27 April 2006.\n232 Norwegian Refugee Council, April 2002.\n233 Internal Displacement Monitoring Centre, July 2006.\n234 United Nations Assistance Mission for Iraq, June 2006 based on a 2001 UNHABITAT survey.", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000351", "page": 37, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "2001 UNHABITAT survey", "probe_tag": "confusion", "probe_score": 0.5213293433189392, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1090, "end": 1111, "key": "reliefweb:000351:37:3:0", "source": "camp2", "luna_reason": "Existing named survey provides the basis for the cited information.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "Blueprint Initiative: Social protection systems for children in Libya Report – 2022\n\n\n<mark>Furthermore, some KIs from the MoSA, as well as social workers (15/53), reported that children of Libyan</mark>\n<mark>mothers and non-Libyan fathers could not be identified by this database. Indeed, these families must</mark>\n<mark>first be registered with the ‘Database for Foreigners’ within the CRA, which is meant to provide each</mark>\n<mark>family with a unique identification number. However, according to a senior KI at the Wife’s and Children’s</mark>\n<mark>Grant project, the database did not include any households at the time of data collection, reportedly</mark>\n<mark>due to a lack of awareness among the population about the requirement to do so, as well as how to</mark>\n<mark>register.</mark>\n\n\nThe SSolF’s system\n\n\n<mark>The SSolF’s information management system appears to be widely paper-based. The majority of</mark>\n<mark>employee KIs reported that the Information and Documentation Department within the SSolF is in</mark>\n<mark>charge of storing beneficiaries' files at the municipal level (15/22). It was also reported that, although</mark>\n<mark>digital databases exist (on Excel), most of the departments and offices work on hard copies. According</mark>\n<mark>to these KIs, this is mostly due to computer illiteracy of staff and a lack of funding to buy the necessary</mark>\n<mark>devices, including computers. Moreover, KIs from offices in Sebha also reported frequent power cuts as</mark>\n<mark>a reason for working with paper-based systems. As for the Emergency Assistance;", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001686", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Database for Foreigners", "probe_tag": "confusion", "probe_score": 0.2443784475326538, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 354, "end": 377, "key": "reliefweb:001686:31:0:0", "source": "camp2", "luna_reason": "Named database cited to explain identification failures and absence of registered households.", "usage_type": "declaration", "specificity": "named"}, {"text": "digital databases", "probe_tag": "confusion", "probe_score": 0.686317503452301, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1164, "end": 1181, "key": "reliefweb:001686:31:0:1", "source": "camp2", "luna_reason": "Names databases without showing their data informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": "|Asylum Levels and Trends in Industrialized Countries 2007|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|Col13|Col14|Col15|Col16|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|**Table 6. Annual asylum applications lodged in industrialized countries by origin, 2007**<br>Covering 29 major asylum countries which provided monthly data to UNHCR. Values between 1 and 4 have been replaced with an asterisk.<br>See Annex I for country codes used.<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|**Table 6. Annual asylum applications lodged in industrialized countries by origin, 2007**<br>Covering 29 major asylum countries which provided monthly data to UNHCR. Values between 1 and 4 have been replaced with an asterisk.<br>See Annex I for country codes used.<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|**Table 6. Annual asylum applications lodged in industrialized countries by origin, 2007**<br>Covering 29 major asylum countries which provided monthly data to UNHCR. Values between 1 and 4 have been replaced with an asterisk.<br", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.0846036747097969, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 353, "end": 365, "key": "reliefweb:001058:17:0:1", "source": "camp2", "luna_reason": "Fragment appears within a table caption and is not independently usable.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " experience during the trainings. In some cases, this was a result of lack of access to\ncomputers or the internet during training sessions. In other cases, participants criticized the curriculum,\nwhich felt overly focused on theoretical principles, rather than real-life examples of how they may\napply their learnings.\n\n\n**Financial barriers and time restrictions prevent some from taking advantage of training**\n**opportunities.** Although many workshop participants shared their appreciation for comprehensive,\nlong-term training programs, they likewise noted that it can be difficult to balance these programs\nwith the ongoing need to earn money and support their families. This was especially pronounced in\nurban areas where the pressures of rent, utilities, food and transportation were more top of mind than\nthey are for those living in refugee camps. The reality of having to forgo work in favor of training was\nrestrictive.\n\n\n\n\n\n**Despite the growing prevalence of smartphones, many refugees perceive access to computers**\n**as essential to conducting digital work.** Without a doubt, smartphone penetration is increasing\nin nearly all areas of the seven countries in this study. Smartphones, and associated mobile data,\nprovide access to the internet and especially to social media services, of which many were\npopular with participants including Facebook, Instagram, WhatsApp, and Telegram. Nevertheless,\nmany workshop participants indicated that their devices are not sufficient for digital work and\nperceive that digital work can only be completed on computers.\n\n\n\nprovide access to the internet and especially to social media services, of which many were\n\n**Soft skills and English language training were consistently among the most desired components**\n\npopular with participants including Facebook, Instagram, WhatsApp, and Telegram. Nevertheless,\n\n**of training programs.** Participants across multiple countries emphasized the importance of soft skills\n\nmany workshop participants indicated that their devices are not sufficient for digital work and\n\ndevelopment, including effective communication, negotiation, critical thinking and problem-solving.\n\nperceive that digital work can only be completed on computers", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001358", "page": 9, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "mobile data", "probe_tag": "confusion", "probe_score": 0.5965668559074402, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1216, "end": 1227, "key": "reliefweb:001358:9:2:0", "source": "camp2", "luna_reason": "Names an infrastructure resource without showing data used for analysis or a finding.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": "SUMMARY OF KEY SECTORS / THEMATIC AREAS ASSOCIATED KEY DATA SETS IN RWANDA\n\n\n\n\n\n\n\n\n\nRecommendations to improve data on refugees in Rwanda include a concerted effort to invest\n\nin standalone data production activities, and to leverage on existing avenues. Some of the\n\nexamples includes:\n\n\n       - Inclusion of refugees in the next Integrated Household Living Conditions Survey (EICV)\n\nnational household survey.\n\n       - A standalone skills’ survey of refugees.\n\n       - Population and Housing Census: While ensuring that the POCs are included in the\n\nAugust 2022 Census, UNHCR Rwanda to take steps by reinforcing contacts with NISR,\n\nand collaborating with MINEMA and NISR to obtain the POCs data and/or study the\n\nresults of the Census data on POCs.\n\n       - An ongoing self-reliance study, with a planned two rounds of panel survey, will produce\n\ndimensions and indicators on self-reliance of refugees.\n\n       - UNHCR Flagship Survey: UNHCR Rwanda has been offered the opportunity to explore\n\na UNHCR financed comprehensive modules of surveys on a representative sample of\n\nrefugees. The UNHCR Rwanda Operation to proactively take steps to bring this activity\n\nonboard.\n\n       - Statelessness: The ongoing activity of stateless population verification exercise in\n\nRwanda could be leveraged to undertake a study on the stateless population.\n\n       - Potential linkages between proGres and other data systems could yield fruit.\n\n\nUNHCR / June 2022 / Version 1\n\n\n\n19", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001182", "page": 18, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "POCs data", "probe_tag": "confusion", "probe_score": 0.5456476211547852, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 691, "end": 700, "key": "reliefweb:001182:18:0:4", "source": "camp2", "luna_reason": "Planned acquisition and study of census data, not already-used evidence.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "panel survey", "probe_tag": "confusion", "probe_score": 0.5867941975593567, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 826, "end": 838, "key": "reliefweb:001182:18:0:6", "source": "camp2", "luna_reason": "Planned panel survey will produce new indicators, so it is future data production.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": " de**\n**empezar una nueva vida.**\n\n**El reasentamiento beneficia a un**\n**número relativamente pequeño de re-**\n**fugiados: en 2012, menos del 1% de los**\n**refugiados del mundo se beneficiaron**\n**de esta solución duradera. En los últi-**\n**mos diez años, se reasentaron unos**\n**836.500 refugiados, frente a 7,2 mi-**\n**llones de refugiados repatriados. En**\n**los últimos años, ACNUR y los Esta-**\n**dos trabajan para aumentar el uso del**\n\n\n\n**reasentamiento como solución dura-**\n**dera estratégica.**\n\n**La integración local es un proceso**\n**complejo y gradual que incluye dimen-**\n**siones económicas, sociales y culturales,**\n**distintas, aunque relacionadas. Para**\n**muchos, adquirir la nacionalidad del**\n**país de asilo es la culminación de este**\n**proceso. El análisis de los datos sobre**\n**integración local que aparecen en este**\n**informe está limitado a las estadísticas**\n**disponibles sobre naturalización de**\n**refugiados en países de acogida.**\n\n\n\n**Estrategias para soluciones integrales**\n\n\n\n**cuelas, y el conflicto armado que volvió a**\n**desenc", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001451", "page": 16, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "estadísticas", "probe_tag": "confusion", "probe_score": 0.20322319865226746, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 878, "end": 890, "key": "reliefweb:001451:16:1:0", "source": "camp2", "luna_reason": "Only states analysis is limited to available statistics, without an attributed finding.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": "jados\n\n- abandonados por motivos de violencia, que busca\nestablecer un mecanismo de protección jurídica de\nbienes de las personas desplazadas por violencia\natendidas por la SEDH. La ruta inicia desde el momento\nde la solicitud de protección ante de la Dirección de\nProtección a Personas Desplazadas Internamente por\nla Violencia (DIPPDIV) de la SEDH, en donde se aplica\nuna ficha de identificación de bienes, posteriormente se\n\n\n\nrealiza un cruce de información con el Registro Unificado\nde Registros de la Propiedad del IP, se dictamina el caso\ny finalmente se procede a la inscripción del bien en\nun módulo que se creará en el sistema de información\ndel IP. En 2021, se continuará el proceso de revisión,\nsocialización y validación del instrumento, con el fin de\ndesarrollar ejercicios de pilotaje en 2022.\n\nLa Dirección de la Infancia, Niñez, Adolescencia y Familia\n(DINAF) como garante de derechos de la niñez y la\nadolescencia, con el apoyo del ACNUR y World Vision\nHonduras (WVH) han realizado diferentes actividades de\nfortalecimiento en el Programa de Antenas de Protección\nen las oficinas de Tegucigalpa, San Pedro Sula, Olancho\n\n\n**EL ARTE COMUNITARIO COMO ESTRATEGIA**\n**PARA FORTALECER LA PARTICIPACIÓN**\n**E INCLUSIÓN DE LAS COMUNIDADES EN**\n**RIESGO EN SAN PEDRO SULA**\n\nArte Comunitario es una estrategia de intervención\ncomunitaria liderada", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000936", "page": 39, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "sistema de información\ndel IP", "probe_tag": "confusion", "probe_score": 0.6511688232421875, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 629, "end": 658, "key": "reliefweb:000936:39:2:0", "source": "camp2", "luna_reason": "Future system module will be created; data resource does not yet exist.", "drop_reason": "production", "specificity": "named"}]}
 {"text": "CHAPTER **8**\n\n\nFigure 21 **\u0003|** **Demographic characteristics available on UNHCR’s population of concern** **|** 2006-2016\n\n\n70\n\n\n60\n\n\n50\n\n\n40\n\n\n30\n\n\n20\n\n\n10\n\n\n0\n\n\n2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016\n\n\nTotal pop. of concern Sex-disaggregated data available Age-disaggregated data available\n\n\n\nIn 2014 and 2015, 164 countries provided at least\nsome sex-disaggregated data on populations of\nconcern. But in 2016, this number declined to 147\ncountries, representing 59 per cent of the entire\npopulation of concern. Some of this decline can be\naccounted for by changes in how the data are\nreported (Figure 21). <sup>70</sup> From the available data, men\naccounted for 20.4 million and women for 19.3 million\npeople out of the total population of concern.\n\n\nIn 2016, 140 countries reported any data\ndisaggregated by age, compared with 141 in 2015.\nEven though the total population covered increased,\nthe proportion covered was still only 35 per cent. Of\nthe 23.9 million people covered in 2016, 12.7 million\nwere children below the age of 18, or 53 per cent, a\nsmall increase in the proportion of the population of\nconcern from 2015.\n\n\nThe coverage of disaggregated data by population\ngroup varied. Refugees and asylum-seekers tended to\nhave the best coverage, and IDPs and stateless people\nthe least. In 2016, sex-disaggregated data were\navailable for 10.7 million refugees, and agedisaggregated data were available for 9.7 million (out of\nthe 17.2 million total population), representing 62 per\ncent and 56 per cent of the refugee population,\nrespectively. Among IDPs, 56 per cent of the\npopulation was covered by sex-disaggregated data,\nwhile only 26 per cent was covered by agedisaggregated data. For asylum-seekers,", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000712", "page": 53, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Sex-disaggregated data", "probe_tag": "drop", "probe_score": 0.045009639114141464, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 244, "end": 266, "key": "reliefweb:000712:53:0:0", "source": "camp2", "luna_reason": "Existing sex-disaggregated data support reported population coverage findings.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "Age-disaggregated data", "probe_tag": "drop", "probe_score": 0.021646983921527863, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 277, "end": 299, "key": "reliefweb:000712:53:0:1", "source": "camp2", "luna_reason": "Age-disaggregated data support the reported coverage and population findings.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "sex-disaggregated data", "probe_tag": "confusion", "probe_score": 0.683610200881958, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 368, "end": 390, "key": "reliefweb:000712:53:0:3", "source": "camp2", "luna_reason": "Disaggregated data support reported country coverage and population figures.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "### Nutrition & Food Security\n###### 2017 ANNUAL GLOBAL OVERVIEW\n\n**<mark>N U T R I T I O N</mark>** **<mark>N U T R I T I O N S U R V E YS</mark>**\n\n\n\n_Proportion of surveyed sites_\n\n\n\n\n\n_Number of sites with nutrition survey conducted_", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000453", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "nutrition survey", "probe_tag": "drop", "probe_score": 0.016156669706106186, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 210, "end": 226, "key": "reliefweb:000453:7:0:0", "source": "camp2", "luna_reason": "Metric label in a table, not an independently used data source.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
-{"text": "UNHCR headquarters, regional bureaux and operations\nrelied on diverse sources, tools and approaches to\ncollect data that was disaggregated by age, gender and\nother diversity characteristics. **This data was generated**\n**through a variety of interventions, such as registration,**\n**sectoral programme monitoring, protection monitoring,**\n**targeted interventions for specific groups and**\n**assessments to inform strategic planning** .\n\n\nUNHCR held the **biometric records**\nof **9.2 million** individuals of age 5 and\nabove in its Population Registration and\nIdentity Management EcoSystem, PRIMES\n(compared with 8.8 million in 2019).\n\n\nIn **Kenya,** UNHCR collected AGD data through individual\nassessments, protection incidents reported through the\nUNHCR Helpline, information provided by community\nleadership structures, community-based organizations\nactive in refugee communities, and community workers\nor volunteers. The social and vulnerability assessments\nconducted jointly by UNHCR and its partners\nthroughout the year were also a valuable source of\nAGD-disaggregated data. These assessments engaged\nall groups at heightened protection risks, including\nwomen and children, persons with disabilities, LGBTIQ+\npeople, and older persons.\n\n\nIn **Syria,** UNHCR collected AGD-disaggregated data\nthrough its registration activities for refugees and\nasylum-seekers, as well as through the wide network of\ncommunity centres supported by UNHCR. UNHCR’s data\nmanagement tool targets refugees, internally displaced\npersons, returnees and host communities. Furthermore,\nUNHCR also coordinated the work of the <u>[Inclusion](https://www.humanitarianresponse.info/en/operations/stima/inclusion-technical-working-group)</u>\n<u>[Technical Working Group, in particular their assessment](https://www.humanitarianresponse.info/en/operations/stima/inclusion-technical-working-", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000271", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "AGD-disaggregated data", "probe_tag": "drop", "probe_score": 0.015035430900752544, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1058, "end": 1080, "key": "reliefweb:000271:14:0:2", "source": "camp2", "luna_reason": "Names generated data without showing analysis, targeting, or an attributed finding.", "drop_reason": "bare_stat", "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": ",221,181|224,718|20,445,899|4,149,853|317,207|43,503,362|5,343,793|4,161,979|6,140,688|3,582,203|86,531,669|\n\n\n76 UNHCR > **GLOBAL TRENDS 2019**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001657", "page": 75, "chunk": 8, "split": "holdout_annotate", "spans": [{"text": "GLOBAL TRENDS 2019", "probe_tag": "drop", "probe_score": 0.04355302080512047, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 124, "end": 142, "key": "reliefweb:001657:75:8:0", "source": "camp2", "luna_reason": "Standalone report heading with no demonstrated data use.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": "An example was shared from Dadaab, where only annual funding has been available, which makes it very\n\ndifficult to plan for long term challenges associated with climate change related displacement. Predictability and\n\na forward-looking approach across both Compacts are needed to be better prepared and anticipate how climate\n\nchange will impact people’s resilience, ability to maintain livelihoods, and their protection needs.\n\n\n**Meeting joint commitments to refugees and migrants**\n\n\n_“In the absence of regular mobility, human smugglers have become vectors of irregular migration. They_\n_shape who moves, how they move, and in what quantity they move. Those with responsibilities to better_\n\n_manage migration and to implement systems for international protection, need to be more sensitive to the_\n\n_vector and drivers of human mobility that smugglers are.”_\n\n\nTuesday Reitano, Global Initiative Against Transitional Organized Crime\n\n\n_“The CRRF gives us the opportunity to look at refugee protection from a whole-of-society approach. This_\n\n\n_includes consultations directly with children and youth. “_\n\n\nRez Gardi, Empower Youth Trust\n\n\nThe New York declaration specifically acknowledges that, though their treatment is governed by separate legal\n\nframeworks, refugees and migrants have the same universal human rights and fundamental freedoms. They\n\nalso face many common challenges and have similar vulnerabilities, including in the context of large movements.\n\nThus seven joint commitments were established in the New York declaration, including commitments to tackle\n\nxenophobia, smuggling and trafficking, to protect children and improve data on mixed flows. The discussion\n\nwas structured to take participants along the shared journey of a refugee or migrant. In doing so, this session\n\nused UNHCR’s 10 Point Plan of Action on Refugee Protection and Mixed Migration to highlight good practices\n\nof successfully responding to the common needs of persons in mixed flows at various points in that journey and\n\nreflected on ways in which States can meet the aforementioned joint commitments to refugees and migrants.\n\n\nThe New York declaration also foresees the development of two global", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000146", "page": 52, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on mixed flows", "probe_tag": "drop", "probe_score": 0.028252173215150833, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1650, "end": 1669, "key": "reliefweb:000146:52:0:0", "source": "camp2", "luna_reason": "Commitment describes improving future data, not using an existing dataset.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "*5 Conclusions**\n\nCountries do not export; firms do (Leighton, 1970). Likewise, economic growth is\ngenerated at the level of individual firms. Against this backdrop and drawing on a\nrepresentative sample of firms, this paper presented some microeconomic evidence on the\nproductivity growth process in Croatia in the period since the onset of recession. Four sets of\nresults can be highlighted.\n\nFirst, there is a persistent (and increasing) heterogeneity of firm performance in\nCroatia along different outcome measures: evidence showed that the degree of concentration\nhas been always high - in terms of labor productivity, followed by capital productivity and\nunit labor cost – and is getting even higher from 2008 to 2012. When exploring firm\nheterogeneity across different analytical criteria – as region, size, export orientation and\nownership – and controlling for sector-level differences, results showed that: i) Adriatic\nregion firms fare worse that Continental firms; ii) trade integrated firms have better\nperformance than partially or non-trade integrated companies; iii) small firms perform better\nthan large companies, with higher labor productivity and lower unit labor cost; and iv) SOEs\nhave lower productivity ( labor and capital) when compared to private firms and this gap is\nincreasing over time.\n\nSecond, Croatia lags behind its regional peers in terms of entrepreneurship measures,\nwhich suggests a comparative lower economic dynamism. The entry density is below what\nwould be predicted by its income level, and its rates of high growth firms and gazelles are\nalso below those of its ECA peers.\n\nThird, the lack of dynamism of Croatian economy is confirmed when looking at firm\nentry and exit process. Evidence for developed economies suggests that healthy market\neconomies exhibit a high pace of firm churning (see Bartelsman et al. (2009) for a recent\ncross country analysis). Results presented here for the Croatian economy pointed to a reduced\nfirm dynamism when compared with ECA peers. In Croatia, only 5.5 percent of all firms are\nnew to the market on", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006093", "page": 27, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "representative sample of firms", "probe_tag": "confusion", "probe_score": 0.35360854864120483, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 182, "end": 212, "key": "prwp:006093:27:4:0", "source": "camp2", "luna_reason": "Sample underpins reported microeconomic evidence on Croatian firm productivity.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "#### **Appendix A**\n\n**Number of observations by country used to compute the “procyclicality” of REER for the**\n**entire period**\n\n\nOur dataset has 63 countries. Data series go, at best, from 1975q1 to 2013q1 (for quarterly data\nseries), and from 1975 to 2013 (for annual data series). The criterion for the choice of countries is\navailability of real GDP (in quarterly data).\n\n\n**Table A1: Countries included in the data and the data availability**\n\n\n<u>Quarterly NEER data</u> <u>Quarterly</u> <u>REER</u> <u>data</u> <u>Quarterly</u> <u>GDP</u> <u>data</u>\n<u>(from when to when)</u> <u>(from when to when)</u> <u>(from when to when)</u>\n\n<u>Argentina</u> <u>1994q1-2013q1</u> <u>1994q1-2013q1</u> <u>1990q1-2012q4</u>\nAustralia 1979q1-2013q1 1980q1-2013q1 1975q1-2012q4\nAustria 1975q1-2013q1 1975q1-2013q1 1975q1-2012q4\nBelgium 1975q1-2013q1 1975q1-2013q1 1980q1-2012q4\nBelize 1975q1-2013q1 1980q1-2013q1 2000q1-2012q4\nBolivia 1975q1-2013q1 1980q1-2013q1 1990q1-2010q4\nBrazil 1975q1-2013q", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006196", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "quarterly data", "probe_tag": "confusion", "probe_score": 0.5782432556152344, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 360, "end": 374, "key": "prwp:006196:25:0:1", "source": "camp2", "luna_reason": "Only qualifies quarterly data availability; no data use or finding is shown.", "drop_reason": "availability", "specificity": "vague"}]}
-{"text": "/sup> The RTA's impact on its members' exports to and imports from\nthe ROW are estimated to be negative and sometimes decreasing, a result suggesting an\noverall ambiguous trade effect of the CACM.\n\n\nThe Andean Community (CAN) is a preferential agreement signed in 1988 by\nBolivia, Colombia, Ecuador, Peru and Venezuela. Except for Venezuela included as\nimporter only, all the other CAN members are both exporter and importer in the database\nused for the estimations. Figure 4 of Appendix 4 plots the estimated trade residuals\nagainst the number of years of CAN members' participation. Intra-CAN exports seem to\nhave started increasing three years before the official date of entry into force of this RTA.\nIt remained positive and increasing over the estimation period. However, the RTA's\neffects on imports from and exports to the ROW are estimated to be negative or neutral.\n\n\nThe Economic Community of West African States (ECOWAS) is a political\nassociation created in 1975 by fifteen members (Mauritania withdrew in 1999): Benin,\nBurkina Faso, Cape Verde, Côte d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau,\nLiberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, Togo. Except for Burkina Faso,\nCôte d'Ivoire, Liberia, Nigeria, Senegal and Togo that are included as exporter and\n\n\n5In fact, the CACM collapsed in 1969 after a five-day war that had been known as the “soccer war”\nbetween El Salvador and Honduras. After this episode, the partners tried to slowly re-establish their\ncollaboration. This may explain the abnormal trade effects observed. We may also notice that in Figure 4 of\nappendix 5, the CACM trade flows are limited to two years before the official date of entry into force (1962\nfor Costa Rica) because the database used is limited on the period 1960-1999.\n\n\n8", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003431", "page": 8, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "database\nused for the estimations", "probe_tag": "confusion", "probe_score": 0.3115411102771759, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 432, "end": 465, "key": "prwp:003431:8:1:0", "source": "camp2", "luna_reason": "Database data are used for the trade-effect estimations.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "regulatory framework until recently hampered its development <sup>40</sup> . The adoption of the _Ley_\n_de Habeas Data_ by Congress in June 2007, which has not yet been adopted pending its\nrevision by Colombia’s Constitutional Court, addresses many of the key issues and would\nfurther promote credit growth, including to SMEs. However, the law includes an\n‘amnesty’ provision that allows negative information on borrowers to be erased from\ntheir credit reports after only one year, as long as those borrowers pay or otherwise settle\ntheir obligations within six months from the date of entry of this law; subsequently to this\nperiod, such information will remain on credit records for four years. Although the\nomission of data from the report is only activated after a borrower’s overdue debt has\nbeen paid or otherwise settled (as opposed to when the loan goes into irregular status), the\nprovision is overly lenient and not in line with good international practice. The\ninterviewed banks have highlighted it as a factor that would inhibit the expansion of\naccess to credit for those borrower segments where delinquent behavior is more common\n(e.g. certain types of agricultural lending), although its overall effect remains unclear.\n\n\nHistorical macroeconomic volatility and recent policy measures that provide\nconflicting signals were also mentioned as important obstacles to further expanding SME\ncredit. A booming economy in the last few years has strongly benefited SMEs, which\ntend to be more susceptible to macroeconomic conditions than large corporates.\nHowever, a combination of an appreciating currency and accelerating inflation in recent\nmonths has led to concerns about possible overheating of the economy <sup>41</sup> . The gradual\ntightening of monetary policy by the central bank (the policy rate was raised from 6\npercent in April 2006 to 9.25 percent in July 2007) has thus far been ineffective in\nlimiting the growth of aggregate demand. In response, the authorities adopted a series of\npolicy measures in May and June 2007 in", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003688", "page": 28, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "credit reports", "probe_tag": "confusion", "probe_score": 0.4770149886608124, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 446, "end": 460, "key": "prwp:003688:28:0:0", "source": "camp2", "luna_reason": "Names credit-report records without showing their data used for analysis or a finding.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": " City<br>Heran City<br>Lana City<br>Dashti Bahasht<br>Shahan City<br>Shary Andazyaran<br>Pirash Village<br>Zilan City<br>Heran City_2<br>Lam Lite<br>Ayinda City_1<br>Zheyan City<br>Chawder City<br>Marina_3<br>Dubai City<br>Marina_1<br>_3<br> Kamarany<br>Shary Andazyaran<br>© OpenStreetMap (and) contributors, CC-BY-SA<br>Ü|Iraq<br>Iran<br>Syria<br>Turkey|\n\n\n###### 21\n\n**Information Management**\n\n**as Coordination Support**\n\n\n###### 42\n\n**3RP Financial Requirements**\n\n\n\n**Sulaymaniyah: Arbat Camp**\n\n\n\n**as Coordination Support**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001143", "page": 2, "chunk": 18, "split": "holdout_annotate", "spans": [{"text": "OpenStreetMap", "probe_tag": "drop", "probe_score": 0.03697805479168892, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 276, "end": 289, "key": "reliefweb:001143:2:18:0", "source": "camp2", "luna_reason": "Map attribution names OpenStreetMap without showing its data being used.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "**UNHCR • UNICEF • IOM** September 2019\n\n\n\n**ACCESS TO EDUCATION IN**\n**PRACTICE**\n\n\n_Data and definitions used across Europe_\n_do not allow for a full comparative analysis._\n_This section therefore provides a snapshot_\n_of the situation in selected European_\n_countries, illustrating_ **_the diversity of_**\n**_situations and disparities with regards_**\n**_to the availability, relevance and_**\n**_timeliness of data_** _on refugee and migrant_\n_children’s access to education. This is largely_\n_due to diverging national legislation, varying_\n_responsible authorities (national vs. federal/_\n_regional), and tools and methodologies to_\n_collect and analyse education data and_\n_statistics. Moreover, while in some countries_\n_data is recorded based on the migration_\n_status of children, in others this is done with_\n_a focus on citizenship or language skills._\n\n**Bulgaria**\n\n\nÔ **Ô** _Refugee and migrant children are_\n_recorded_ _in_ _national_ _education_\n_statistics only if they are asylum-_\n_seekers or beneficiaries of international_\n_protection._\n\n\nÔ **Ô** As of the end of December 2018,\nschool enrolment for refugee and\nmigrant children was five times\nhigher compared to the 20162017 school year due to increased\noutreach and support provided by\nthe government and humanitarian\nagencies.\n\n\n\nÔ **Ô** **50%** or **81** out of **161** schoolage refugee and migrant children\naccommodated in government\nreception centres in December\n2018 were enrolled in primary and\nsecondary public schools, while a\ntotal of **121** asylum-seeking and\nrefugee children were registered\noverall in the formal education\nsystem in the beginning of", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000457", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "education data", "probe_tag": "drop", "probe_score": 0.04513826221227646, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 659, "end": 673, "key": "reliefweb:000457:4:0:0", "source": "camp2", "luna_reason": "Generic data resource is discussed for availability and collection, not used for a finding.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": "/gifmm-colombia-resultados-evaluacion-conjunta-de-necesidades-para-poblacion-con-22)\nxix Colombian Observatory of Feminicides.\nxx National Observatory of Gender-based Violence, The national rate for 2024 is 262.3 per 100,000 inhabitants.\nxxi UARIV, Resolution 0171 of February 24, 2016, by which confinement is defined as a victimizing event in the framework of Law 1448 of 2011, issued by the\nVictims Unit.\nxxii Ibid.\nxxiii Office of the Attorney General of Colombia, Directive 002 of January 14, 2025.\nxxiv Integral Action Against Antipersonnel Mines Viewer (2025). National Report on APM/UXO/IEDs Victims, available at: AICMA Viewer.\n\n\n**Methodology**\n\n\nIn September 2024, the Protection Thematic Group (GTP) of Norte de Santander and the Protection Cluster, in\ncollaboration with the Areas of Responsibility (AoR) of Gender-Based Violence, Child Protection, and Mine Action,\norganized a mission to the Catatumbo sub-region. The objective was to update the regional context and identify the main\nprotection risks in the area. This mission identified the imminent risk of forced internal displacement and the confinement\nof rural communities. However, at the beginning of 2025, a humanitarian emergency occurred that required a coordinated\nresponse from the Local Coordination Team of Norte de Santander (ELC) for immediate humanitarian aid and institutional\ncoordination. This protection analysis document is based on quantitative and qualitative data from inter-sectoral\nassessments, rapid protection assessments, and reports prepared by partners from the subnational and national teams of\nthe Protection Cluster/Sector and the corresponding Areas of Responsibility.\n\n\nPage 13", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000324", "page": 12, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "AICMA Viewer", "probe_tag": "confusion", "probe_score": 0.5564662218093872, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 623, "end": 635, "key": "reliefweb:000324:12:4:1", "source": "camp2", "luna_reason": "Named source platform cited with the National Report on APM/UXO/IEDs Victims.", "usage_type": "declaration", "specificity": "named"}, {"text": "rapid protection assessments", "probe_tag": "drop", "probe_score": 0.031588029116392136, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1488, "end": 1516, "key": "reliefweb:000324:12:4:3", "source": "camp2", "luna_reason": "Existing assessments provide quantitative and qualitative data for the protection analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": ">2022,<br>subject<br>to<br>Covid<br>situation.<br>Lack of willingness and<br>capacity of partners<br> <br>Staff Turn-over<br> <br>Lack<br>of<br>UNHCR<br>capacity/ M&E resource<br>person support due to<br>lack of funding<br>40,000<br>(Annual Surveys)<br>Annual Indicator Survey<br>(Livelihoods<br>Assessments) Report<br> <br>Participatory<br>Assessments<br> <br> <br>Partners<br>Progress<br>Reports<br>PDM?<br> <br>Socioeconomic<br>Assessment (with JDC)<br>|M&E stock take exercise to<br>consolidate achievement made<br>so far + developing a framework<br>for efficient and real-time results<br>tracking using in-house capacity;<br>Review, Workshop, Field Visits to<br>validate the results so far collected and<br>draft M&E framework developed as part<br>of the strategy<br> <br>Validation Exercise, piloting annual<br>indicator survey<br>UNHCR<br>M&E<br>Consultant<br>with<br>Livelihoods<br>Team<br>(UNHCR<br>and<br>MINEMA)<br>By<br>end<br>2021/early<br>2022,<br>subject<br>to<br>Covid<br>situation.<br>Lack of willingness and<br>capacity of partners<br> <br", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001259", "page": 57, "chunk": 9, "split": "holdout_annotate", "spans": [{"text": "indicator survey", "probe_tag": "drop", "probe_score": 0.042913906276226044, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 817, "end": 833, "key": "reliefweb:001259:57:9:2", "source": "camp2", "luna_reason": "Annual indicator survey is being piloted as a planned data-production activity.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": "refugee settlements.|Advocate for telecommunication<br>companies to improve<br>telecommunication coverage in<br>refugee settlements.|Advocate for telecommunication<br>companies to improve<br>telecommunication coverage in<br>refugee settlements.|Advocate for telecommunication<br>companies to improve<br>telecommunication coverage in<br>refugee settlements.|Advocate for telecommunication<br>companies to improve<br>telecommunication coverage in<br>refugee settlements.|Advocate for telecommunication<br>companies to improve<br>telecommunication coverage in<br>refugee settlements.|Advocate for telecommunication<br>companies to improve<br>telecommunication coverage in<br>refugee settlements.|\n||Cross-Cutting Approaches|Cross-Cutting Approaches|Strengthen data-<br>driven<br>approaches to<br>refugee<br>livelihoods.|Conduct socio-economic profiling<br>of refugee households, including<br>baseline, midline, and end-line<br>surveys, market assessments, and<br>economic database development.|Conduct 3 assessments of the<br>strategy, 1 per year|1|100000|3|300000||\n||Cross-Cutting Approaches|Cross-Cutting Approaches|Strengthen data-<br>driven<br>approaches to<br>refugee<br>livelihoods.|Collaborate with host government<br>agencies to integrate refugee data<br>into national systems, ensuring<br>interoperability.|||||0|0|\n||Cross-Cutting Approaches|Cross-Cutting Approaches|Strengthen data-<br>driven<br>approaches to<br>refugee<br>livelihoods.|Partner with the World Bank and<", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000822", "page": 21, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "refugee data", "probe_tag": "drop", "probe_score": 0.03465311974287033, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1245, "end": 1257, "key": "reliefweb:000822:21:1:0", "source": "camp2", "luna_reason": "Planned integration of refugee data into national systems, not existing data use.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": "://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_eiord&lang=en)\n[have left the territory as a result of an order to leave (voluntary or forced) 2015-2017.](http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_eirtn&lang=en)\n\n\n48 THE WAY FORWARD", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001185", "page": 47, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "migr_eiord", "probe_tag": "confusion", "probe_score": 0.1202305257320404, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 52, "end": 62, "key": "reliefweb:001185:47:2:0", "source": "camp2", "luna_reason": "Standalone dataset code in URL lacks shown data use or attributed finding.", "drop_reason": "ref_list", "specificity": "vague"}, {"text": "migr_eirtn", "probe_tag": "drop", "probe_score": 0.038393184542655945, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 220, "end": 230, "key": "reliefweb:001185:47:2:1", "source": "camp2", "luna_reason": "Bare dataset URL parameter fragment, not a standalone data-use mention.", "drop_reason": "ref_list", "specificity": "vague"}]}
+{"text": "**Time: 15:00**\n\n# **Next Steps**\n\n\n- **Summary write up of workshop discussions**\n\n- **Preliminary output shared with ISCG to support RRP planning**\n\n- **Follow up agreements to improve or consolidate data sets**\n\n- **Bilateral meetings on specific identified issues**\n\n- **Work together, share information and jointly find solutions** ☺\n\n\n**Winterization Workshop, October 2022**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001548", "page": 50, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data sets", "probe_tag": "drop", "probe_score": 0.02711811475455761, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 202, "end": 211, "key": "reliefweb:001548:50:0:0", "source": "camp2", "luna_reason": "Next-step agreement concerns future data-set improvement, not existing data use.", "drop_reason": "promissory", "specificity": "vague"}]}
+{"text": "**Table of contents**\n**Paving pathways for inclusion: A global overview of refugee education data**\n\n#### Table of f i gures\n\n\nFigure 1: Overview of the number of questionnaires covering different education areas by target\n7\n<u>population and presence of refugee identification questions</u>\n\n<u>Figure 2: Framework for the inclusion of refugees in education data systems</u> <u>23</u>\n\nFigure 3: Percentage of refugees hosted by selected countries of the total global refugee population,\n28\n<u>as of September 2021</u>\n\n<u>Figure 4: Disaggregation of 621 reviewed DCEs by target population and type</u> <u>31</u>\n\n<u>Figure 5: Disaggregation by SES and personal characteristics</u> <u>32</u>\n\n<u>Figure 6: Number of questionnaires containing refugee identification questions by type of question</u> <u>33</u>\n\n<u>Figure 7: Percentage of questionnaires that ask proxy and criteria questions by question</u> <u>34</u>\n\nFigure 8: Number of questionnaires with access questions that target refugees or include refugee\n36\n<u>identification questions</u>\n\n<u>Figure 9: Number of questionnaires with access questions by sub-indicator and target population</u> <u>37</u>\n\nFigure 10: Percentage of questionnaires asking refugee identification and access questions by\n38\n<u>refugee identification type and indicator</u>\n\nFigure 11: Number of questionnaires with quality questions that target refugees or include refugee\n41\n<u>identification questions</u>\n\n<u>Figure 12: Number of questionnaires with quality questions by target population</u> <u>42</u>\n\nFigure 13: Percentage of questionnaires asking refugee identification and quality questions by\n43\n<", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "refugee education data", "probe_tag": "drop", "probe_score": 0.02557229995727539, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 76, "end": 98, "key": "reliefweb:000382:14:0:0", "source": "camp2", "luna_reason": "Generic topic phrase names data without attributing a concrete finding or analysis.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"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": "ضية الخاصة بالعنف الجنسي والعنف الجندري. وقد أصدرت ال� <sup>ت</sup>\nيركّز **مرص** و **لبنان** و **ردنال** <sup>**أ**</sup> ي رس � <sup>ف</sup> ي هن ربات ال <sup>أ</sup> المفوضية تقريراً بعنوان «نساء بمفردهن»، حول الالجئات السوريات اللوا� <sup>ت</sup>\n\nدوار، والعزلة، والعنف الجنسي والعنف الجندري.مان المالي ، وتغ�ي ال <sup>أ</sup> عى مسائل الإسكان، والغذاء، والصحة، والعمل وال <sup>أ</sup>\n\n\n**نظـام إدارة المعلومات حول العنف الجندري**\n\n)، لضمان جمع وإدارة وتشارك بيانات آمنة GBVIMS( دعمت المفوضية ن� نظام إدارة المعلومات حول العنف الجندري <sup>ش</sup>\nي العمليات المختلفة. فنظام إدارة المعلومات حول العنف الجندري وأخالقية ورسية حول العنف الجنسي والعنف الج", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001417", "page": 37, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "GBVIMS", "probe_tag": "drop", "probe_score": 0.03760776296257973, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 476, "end": 482, "key": "reliefweb:001417:37:2:0", "source": "camp2", "luna_reason": "Names an information system without showing its data being used for analysis or decisions.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "Conversations examined the CRRF capacity to deliver timely humanitarian response with the depth of\n\ndevelopment programmes as well as doing so without undermining humanitarian principles and accountability.\n\nEnsuring that the views of diverse groups (ex. women youth, children, persons with disabilities, LGBTI) are\n\nreflected in the CRRF was also stressed, as was the need for an effective continuum of protection across borders\n\nand throughout the displacement cycle.\n\n\nCRRF implementation examples underscored that people, not structures implement the CRRF. Confusion in the\n\ndialogue accentuated the need to translate the CRRF into plain language and make it accessible to the whole\nof-society. This should include the application of consistent definitions and appropriately disaggregated data so\nas to be able to tell stories of change. <sup>20</sup> The need for more awareness raising, conducting outreach, localising\n\nthe CRRF and following the Principles of Partnership were also discussed.\n\n\nFor the sake of clarity, inputs from the NGO community are organised here according to clauses 6-8 from\nAppendix 1 of the New York declaration. <sup>21</sup> [^21: Clauses 6a, 6e, 8a, and 8c were not significant topics of discussion at the Consultations.]\n\n\n**Walk the talk- A multi-stakeholder approach in resourcing the comprehensive refugee response** <sup>**22**</sup> [^22: This session included discussion of New York Declaration, Appendix 1, 6.a to 6.d.]\n\n\nThis session discussed how cooperation with multilateral donors and private-sector partners can provide\n\nresources to Comprehensive Refugee Responses in a prompt, predictable, consistent and flexible manner. It\nalso addressed challenges in the transition from the ‘business as usual’ to a new way of working.\n\n\nThe Deputy High Commissioner for Refugees opened the discussion, acknowledging that a core challenge to\n\nCRRF implementation is the need to be operational very quickly while operating with little money. Impacting the\n\nquality and continuity of response, insufficient funding – especially for national NGOs, host communities and\n\nlocal government – was", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000146", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "disaggregated data", "probe_tag": "drop", "probe_score": 0.03085264191031456, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 779, "end": 797, "key": "reliefweb:000146:17:0:0", "source": "camp2", "luna_reason": "Generic data is recommended, but no existing finding or concrete use is shown.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": "(training duration of 2.5 weeks) or to an experienced, professional enumerator, but with less than\n\n\na day of IPV training. <sup>27</sup> While 21% of the women reported having experienced physical or sexual\n\n\nIPV to the untrained enumerators, 26% reported IPV to the trained ones (Jansen et al. 2004).\n\n\nAnother relevant data quality issue that we want to note from a companion study in the same\n\n\nsetting (Jeong et al. 2021) is that time into the survey at the point at which a question is asked\n\n\nappears to adversely impact response quality, a phenomenon known as survey fatigue. While fatigue\n\n\nwould be a consideration for any survey, it may be particularly germane for IPV measurement as\n\n\nmost surveys place the IPV module at the end - for example, the standard DHS surveys ask about\n\n\ndomestic violence at the end; we also chose to always place the IPV module at the end, even as\n\n\nwe randomized the location of other survey modules within the survey. While this is usually done\n\n\nto minimize shame or embarrassment stemming from continued interaction with the enumerator\n\n\nafter having answered the IPV module, we reiterate our read that concerns about stigmatization\n\n\nfrom the enumerator are very likely overblown, <sup>28</sup> and purported remedial actions, such as SI or late\n\n\nplacement within the survey may be opening up non-obvious channels of bias.\n\n\n27This was done in an effort to speed up the fieldwork midway through surveying after the assassination of then\nPrime Minister Zoran ~~D~~ in ~~d~~ i´c in March 2003.\n28In our study, we asked our enumerators a few debriefing questions after the IPV module and they reported that\namong respondents who reported any IPV incidence in FTFI, 44% in Liberia and 28% in Malawi shared more about\ntheir IPV experience with them than what was", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001571", "page": 18, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "DHS surveys", "probe_tag": "confusion", "probe_score": 0.8642601370811462, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 770, "end": 781, "key": "prwp:001571:18:0:0", "source": "camp2", "luna_reason": "Names surveys as an example of questionnaire placement, without using their data.", "drop_reason": "system_registry", "specificity": "named"}]}
+{"text": "multiple locations are mentioned. Our algorithm performs 25% better than LNEx even when comparing\n\n\nwhether any location extracted from the tweet is near the true location.\n\n\nAnalyzing the crash data produced using our algorithm and focusing on the truth dataset within the city\n\n\nlimits of Nairobi, we find that all crashes from July 2017 to July 2018 can be found in 435 clusters, each with\n\n\na maximum diameter of 300 m. Of these clusters, 67% have two or more crashes and there are 56 clusters\n\n\nwith 10 or more crashes. Additionally, 66 crash clusters represent over 50% of all the crashes. When looking\n\n\nat the 7.5 years of crowdsourced data for the city of Nairobi, the number of crash clusters does not grow\n\n\nlinearly, implying that the locations where crashes occur and are reported in Twitter are consistent across\n\n\nyears. Only 14% of crash locations have only a single crash, and there are 443 crash clusters with 10 or more\n\n\ncrashes. We see the concentration of crashes even more when we note that only 9% of crash clusters (133 of\n\n\n1,375) represent 50% of the crashes reported (Figure 3 shows crash heatmaps for the truth dataset from July\n\n\n2017 to July 2018 and for 2012-2020).\n\n\n**Figure** **3.** **Heatmap** **of** **crashes** Data in panel a is from July 2017 - July 2018, where we use the manually\ncoded Twitter dataset. Data in panel b is for August 2012 - July 2020. Road data comes from\nOpenStreetMap.\n\n##### **Discussion**\n\n\nCities are constantly evolving and understanding urban mobility is critical to creating urban designs that\n\n\nhelp to manage risks for pedestrians and vehicles. Severe data limitations hinder the development of policy\n\n\ninterventions needed to manage risks, especially in low- and middle-income resource-constrained countries.\n\n\nClosing the data deprivation gap can help avert divergence in socioeconomic conditions between data-poor\n\n\nand -", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000063", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "crash data", "probe_tag": "confusion", "probe_score": 0.41040101647377014, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 189, "end": 199, "key": "prwp:000063:10:0:0", "source": "camp2", "luna_reason": "Crash data are produced using the project’s algorithm.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "it is clear that the magnitudes are quite small. There are several reasons that help explain this\n\n\nfact.\n\n\nAs discussed in Section 1, the reforms in cotton markets have been relatively successful\n\n\nbut have not been smooth. Initially, the public monopoly was transformed into a private\n\n\nmonopoly. Entry was useful in early stages, but the failure of the outgrowing scheme limited the\n\n\nexpansion of the sector. In fact, the outgrower scheme was still failing in 1998, when the\n\n\nhousehold survey data was collected. This means that the evolution in income shares that we can\n\n\ncapture with the available data does not reveal the whole benefits on the reforms.\n\n\nUsing additional farm data, Brambilla and Porto (2005) report that the cotton reforms had\n\n\ntwo distinctive effects on cotton farming. First, there is a decline of the land area devoted to\n\n\ncotton in 1998-1999 (when the outgrowing scheme was failing) followed by a significant\n\n\nincrease in area planted in 2000-2001, when the outgrower scheme was perfected with the\n\n\nentrance of Dunavant. Second, the authors find that farm productivity in cotton showed a similar\n\n\npattern, declining in 1998-1999 and increasing in 2000-2001. In additional, their findings\n\n\nindicate that income shares increased, on average, by roughly 10-20 percent. These additional\n\n\nfactors could help increase the average gains from a 12 percent price increase to roughly 2\n\n\npercent of household income, on average. Although these figures are higher, the effects seem\n\n\nstill fairly low. The study by Brambilla and Porto (2005) reveals another reason why the increase\n\n\nin cotton prices may not have large impacts. Productivity of smallholder cotton production has\n\n\nbeen traditionally very low in Zambia. Although there is some evidence that the reforms have\n\n\ncaused productivity to increase in recent years, there is still room for improvements in this area.\n\n\nOne additional reason for the small impacts is that cotton activities are not really\n\n\nwidespread in Zambia. More importantly, we have only considered a first order", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002911", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "household survey data", "probe_tag": "confusion", "probe_score": 0.7382240295410156, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 481, "end": 502, "key": "prwp:002911:16:0:0", "source": "camp2", "luna_reason": "Existing household survey data supports analysis of income-share changes.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " the maintenance of a bank account.\nAnd credit can be used to acquire such non-financial assets as a home or an automobile, to\nsmooth consumer purchases over time, or to finance small business activities. The cost of credit\noutside the formal banking system is high, as the data in Box 1, below. Finally, all Mexicans\nmay pay a price as a result of such a large percentage of the population being outside of the\nbanking system, as informal savings are often not channeled to productive activities, lowering\nthe potential rate of growth of the economy. Box 2, on the following page, estimates the costs of\nbeing unbanked to a median income couple in Mexico City at 15% of total income. The individuals who are unbanked bear most of these costs.\n\n\n\n\n\n\n\n\n\n\n\n\n\n46", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003049", "page": 45, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data in Box 1", "probe_tag": "confusion", "probe_score": 0.5122389197349548, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 274, "end": 287, "key": "prwp:003049:45:1:0", "source": "camp2", "luna_reason": "Box 1 data supports the claim that formal banking credit costs are high.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "Oxford_\n_Bulletin of Economics and Statistics_, Vol. 43, No. 4 November.\n50. Simar, L. and P. Wilson (2000) “Statistical inference in non-parametric frontier\nmodels: The state of the art” _Journal of Productivity Analysis_, 13 pp 49-78.\n51. The State Failure Task Force, 2004. Political Instability (aka State Failure) Task\nForce Data, http://www.cidcm.umd.edu/inscr/stfail/sfdata.htm\n52. Tanzi V. 2004. Measuring efficiency in public expenditure. Paper presented in\nConference on Public Expenditure Evaluation and Growth. The World Bank.\nOctober.\n53. Varian, H. 1990 “Goodness-of-fit in optimizing models”, _Journal of Econometrics,_\n46, pp. 125-140.\n54. Wheelock D. and Wilson, P. 2003. “Robust Non-parametric estimation of efficiency\nand technical change in U.S. Commercial Banking” Working Paper. Federal Reserve\nBank of St. Louis. November.\n55. Wilson, P. (2004) “A preliminary non-parametric analysis of public education and\nhealth expenditures in developing countries”. Mimeo. The World Bank.\n56. Wobst, P.and C. Arndt. “HIV/AIDS and primary school performance in Tanzania”.\nPresented at the 25 <sup>th</sup> International Conference of Agricultural Economists. Durban,\nSouth Africa.\n57. World Bank, 2004. _Making Services Work for the Poor. World Development Report_\n_2004._\n58. Worthington, A. 2001. “An empirical survey of frontier efficiency measurement\ntechniques in education” _Education Economics_, Vol. 9, No. 3\n\n\n39", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002859", "page": 40, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Political Instability (aka State Failure) Task\nForce Data", "probe_tag": "confusion", "probe_score": 0.4208250045776367, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 277, "end": 334, "key": "prwp:002859:40:1:0", "source": "camp2", "luna_reason": "Bibliography entry citing a named dataset, without demonstrated data use.", "drop_reason": "ref_list", "specificity": "named"}]}
+{"text": "Fourth, practitioners emphasize the value of community-owned “score-cards” in mobilizing communities to take\n\naction. In interventions 2 and 3 the community created its own report card by testing children in math and reading. Both\n\nthe results and the tools were transferred to community members.\n\n\nPratham is the largest educational NGO in India. It has demonstrated success in several randomized evaluations\n\nof its programs and reaches millions of children throughout India. Pratham designed and runs the the Annual State of\n\nEducation Report (ASER), which tests children in all of India’s nearly 600 districts every year, and is extremely prominent\n\nin the discourse on education in India. The organization takes community participation in education very seriously (it is\n\nthe backbone of its flagship “Read India” program) and devotes considerable resources to make sure that the program is\n\n\nimplemented as well as possible. Pratham’s motivation and expertise thus made it an obvious candidate for implementing\n\nthese interventions.\n\n\nTaken together this suggests that we can be reasonably sure that what we are evaluating were well-designed and\n\neffectively implemented programs. It is also clear that they reached their intermediate goals: encouraging participation,\n\nholding meetings focused on education, and generating discussion, interest, and willingness on the part of at least some\n\npeople to act (as evidenced by the fact that Pratham was effective at recruiting volunteers for the reading camps).\n\n\n**3.3** **Why might we have expected these interventions to work?**\n\n\nThese interventions involved a combination of more information (about learning levels and levers for change such\n\nas the VEC) and more coordination on doing something about education. The predicted impact of more coordination\n\nseems unambiguous: More action and better results is what we would have expected.\n\nGiving people more information, on the other hand, need not always promote greater collective action. For\n\nexample, if the only people who were acting initially were those who believed that the returns to collective action were very\n\nlarge, information", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003791", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Annual State of\n\nEducation Report", "probe_tag": "keep", "probe_score": 0.9139615893363953, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 512, "end": 545, "key": "prwp:003791:12:0:0", "source": "camp2", "luna_reason": "Named existing education report referenced as a prominent data resource.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " board committees (20.45%), an independent board\n\n\n(26.85%), and a BEBCHUK index equal to 1 (18.60%). However, when INV_PROT1\n\n\nindex is equal or greater than 1.7, companies tend to have only one board committee\n\n\n(25.7%), a not independent board (46.33%), and a BEBCHUK index equal to 1\n\n\n(40.06%). There is, therefore, not a clear and monotonically relation between investor\n\n\nprotection at the country level and the existence of board committees. The largest\n\n\nmajority of companies have a low BEBCHUCK indicator, but there is an equal split\n\n\nin terms of board independence across the level of investor protection INV_PROT1.\n\n\n**Financial data**\n\n\nFor US companies, financial data are obtained from COMPUSTAT, while for\n\n\nnon-US companies we use Worldscope data. As mentioned before, our companies are\n\n\n16", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002461", "page": 16, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Worldscope data", "probe_tag": "keep", "probe_score": 0.9753850698471069, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 750, "end": 765, "key": "prwp:002461:16:1:2", "source": "camp2", "luna_reason": "Named financial dataset used for non-US companies' financial data.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": ".11\n(0.23) (0.33) (0.29) (0.37) (1.88) (0.33) (0.31) (0.24)\n\n\nObservations 6,510,590 5,378,875 3,827,927 2,531,263 648,764 4,359,788 5,447,012 7,328,290\n\n\n<u>Fixed</u> <u>Efectsf</u>\nFirm ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓\nOrigin-product-year ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓\nDestination-product-year ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓\nOrigin-destination ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓\n\n\nNotes: The dependent variable is the log unit value at the firm-product-origin-destination-year level in all columns. Significance: *** p _<_ 0.01, **\np _<_ 0.05, and - p _<_ 0.1 are based on robust standard errors, which are reported in parentheses. Data sources: Thirteen datasets of firms’ exports from\nthe World Bank Exporter Dynamics Database, China’s Customs Authority, and Egypt’s Customs Authority.\n\n\n49", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002308", "page": 52, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "World Bank Exporter Dynamics Database", "probe_tag": "keep", "probe_score": 0.9179083108901978, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 628, "end": 665, "key": "prwp:002308:52:4:1", "source": "camp2", "luna_reason": "Named database cited as a source for export regression analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "<u>*The OECD and RICYT basically provide the same definitions for sectors that finance and</u>\n\n\n<u>perform R&D. The OECD refers to the productive sector as “Business Enterprise Sector”, which</u>\n\n\n<u>covers private and public enterprises.</u>\n\n\n**R&D Personnel**\n\n\nThe data on R&D personnel corresponds to scientists and engineers, comprising persons working\n\n\nin those capacities, i.e. as persons with scientific or technological training (usually completion of\n\n\nthird level education) in any field of science, who are engaged in professional work on R&D\n\n\nactivities, administrators and other high-level personnel who direct the execution of R&D\n\n\nactivities.\n\n\n*RICYT divides R&D personnel in the following categories: Researchers (professionals who\n\n\ncreate new knowledge, methods and systems, and administer them), Graduate Students, and\n\n\nSupport Personnel (technicians and other support personnel).\n\n\n\n**2. Database on Innovation: Variables and Sources**\n\n\n\n\n\n\n\n\n\n\n\n\n|Variable|Definition|Units|Source|\n|---|---|---|---|\n|R&D Variables<br> <br> <br> <br>|R&D Variables<br> <br> <br> <br>|R&D Variables<br> <br> <br> <br>|R&D Variables<br> <br> <br> <br>|\n|Pat<br>|Total patents<br>granted by the<br>USPTO  by<br>year for each<br>country<br>|Unit<br>|U.S. Patent & Trademark Office<br>|\n|Patepo<br>|Total patents<br>granted by the<br>EPO by year<br>for each<br>country", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002988", "page": 29, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on R&D personnel", "probe_tag": "confusion", "probe_score": 0.4353017210960388, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 271, "end": 292, "key": "prwp:002988:29:0:0", "source": "camp2", "luna_reason": "Generic data phrase is defined conceptually without an attributed finding or analytical use.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": "that occur within different distance radii of the DHS household-cluster centroid. We\n\n\ncount all events that occur within different distance belts—for example, 0–50 km or 51–\n\n\n100 km. We take a threshold of 50 km to define distant events, but we conduct sensitivity\n\n\nanalyses increasing and decreasing this threshold. We also build a continuous indicator\n\n\nthat counts all events that occur beyond 50 km from the household cluster and weighs\n\n\nthese events using the inverse of the distance. For example, all attacks within a radius\n\n\nof 51 km of the household cluster are assigned a weight of 1, and attacks farther away\n\n\nreceive weights smaller than 1. We also consider the number of deaths as an alternative\n\n\nmeasure of violence.\n\n\nWe also use information on attacks conducted by the Fulani. Between 2008 and 2018,\n\n\nthe ACLED data register 1,038 violent events in which at least one of the agents involved\n\n\nwas Fulani. About 70 percent of these events are classified as violence against civilians\n\n\nand 25 percent as battles, while the remainder are explosions or remote violence. These\n\n\nevents led to 7,236 registered fatalities. Most of the violent events are concentrated in the\n\n\nnorth central region. About 25 percent of the events occurred in Benue State, followed\n\n\nby 22 percent in Plateau State, and 9 percent in Taraba State (these statistics are not\n\n\ndisplayed in any table).\n\n\n_Displacement_ _data._ We use data on the number of displaced people from the IOM’s DTM\n\n\nproject, particularly the site- and location-assessment databases. We use these data to\n\n\ncalculate the number of IDPs who live near the household cluster. To do so, we count\n\n\nthe number of IDPs residing within a 10 km radius of the DHS household cluster. In\n\n\naddition, we build binary indicators at the LGA level indicating the presence of IDPs.\n\n\nSince July 2014, the IOM has been collecting displacement data from key informants\n\n\n(such as village chiefs and religious leaders) at IDP-hosting locations.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000984", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on the number of displaced people", "probe_tag": "confusion", "probe_score": 0.8116751909255981, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1430, "end": 1468, "key": "prwp:000984:17:0:1", "source": "camp2", "luna_reason": "IOM DTM data are used to calculate nearby IDP counts and indicators.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "consumption may do a better job in this respect, but will still be an imperfect welfare indicator\n\n\ngiven that inter-temporal markets do not work perfectly. There are also uncertainties about how\n\n\nbest to normalize for heterogeneity in consumption needs, such as stemming from demographic\n\n\ndifferences between households (Pollak, 1991). <sup>4</sup> And even if we had an ideal measure of\n\n\naverage economic welfare for a household, health status is an individual attribute, which will\n\n\ndepend directly on personal economic welfare. Individual income is a flawed metric of\n\n\nindividual command over commodities given some degree of income pooling within households.\n\n\nAnd household expenditure may well be equally flawed as an indicator of individual economic\n\n\nwelfare given that pooling is almost certainly incomplete. <sup>5</sup> [^5: It is instructive that, in the same setting, Ravallion and Loskhin (2001) find evidence that many\n“non-income” factors at the individual and household levels impinge on perceived economic welfare in\nRussia at given current incomes or expenditures on consumption deflated by standard poverty lines.]\n\n\nIn short, heterogeneity in relevant individual and household circumstances, inter\n\ntemporal consumption smoothing and inter-personal income sharing may entail that neither\n\n\nmeasured current income nor consumption are particularly good proxies for economic welfare,\n\n\nas relevant to health. This too will lead one to underestimate the true economic gradient in\n\n\nhealth using the methods commonly found in the literature.\n\n\nThis paper proposes a method of estimating the economic gradient in health status that is\n\n\nlikely to be more robust to non-ignorable errors in _SAH_ data and the measurement errors in data\n\n\non incomes or expenditures. The essential idea is to use largely independent covariates of both\n\n\n_SAH_ and perceived economic welfare to attempt to purge the raw data of the non-ignorable\n\n\nerrors, prior to testing for the economic gradient in health status. To calibrate a broader measure\n\n\nof economic welfare we draw on subjective data, though recognizing that this too contains\n\n\nmeasurement errors when used as an indicator of objective economic welfare. Our estimation\n\n\n4 For example, the poverty lines used", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002912", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "subjective data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 2083, "end": 2098, "key": "prwp:002912:3:0:0", "source": "camp2", "luna_reason": "Subjective data are used to calibrate a broader economic welfare measure.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": "no. 224. https://www.imf.org/en/Publications/WP/Issues/2020/11/05/COVID-19-and-the-CPI-Is\nInflation-Underestimated-49856.\n\n\nRodriguez-Takeuchi, Laura, and Katsushi S Imai. 2013. “Food Price Surges and Poverty in Urban\n\nColombia: New Evidence from Household Survey Data.” _Food Policy_ 43 (C): 227–36.\n\nhttps://doi.org/10.1016/j.foodpol.2013.09.017.\n\n\nSanchez-Paramo, Carolina, and Ambar Narayan. 2020. “Impact of COVID-19 on Households: What Do\n\nPhone Surveys Tell Us?” Voices [Blog]. 2020. https://blogs.worldbank.org/voices/impact-covid-19\nhouseholds-what-do-phone-surveys-tell\nus?cid=ECR_E_NewsletterWeekly_EN_EXT&deliveryName=DM85808 .\n\n\nSkoufias, Emmanuel, Sailesh Tiwari, and Hassan Zaman. 2012. “Crises, Food Prices, and the Income\n\nElasticity of Micronutrients: Estimates from Indonesia.” _The World Bank Economic Review_ 26 (3):\n\n415–42. https://doi.org/10.1093/wber/lhr054.\n\n\nVu, Linh, and Paul Glewwe. 2011. “Impacts of Rising Food Prices on Poverty and Welfare in Vietnam.”\n\n_Journal of Agricultural and Resource Economics_ 36 (1): 14–27.\n\n\nWorld Bank. 2020a. “Iran Economic Monitor, Fall 2020 : Weathering the Triple-Shock.” Washington, DC.\n\nhttps://openknowledge.worldbank.org/handle/10986/34973.\n\n\n———.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002397", "page": 22, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Household Survey Data", "probe_tag": "confusion", "probe_score": 0.33007124066352844, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 247, "end": 268, "key": "prwp:002397:22:0:0", "source": "camp2", "luna_reason": "Fragment appears within a bibliography title, not as evidence used in the passage.", "drop_reason": "ref_list", "specificity": "vague"}]}
+{"text": " <sup>0</sup> <sup>_,_</sup> (6)\n\n\n\nsince _dσ_ <sup>_<u>dϵ</u>_</sup>\n\n\n\n_dσ_ <sup>_<u>dϵ</u>_</sup> <sup>_>_</sup> <sup>0 and</sup> <sup>_ϵ >_</sup> <sup>1.</sup> <sup>Therefore, both the value of the investment option</sup> <sup>_X_</sup> <sup>and the critical threshold</sup>\n\n\n\n_C_ <sup>∗</sup> are increasing functions of the variance _σ_ <sup>2</sup> :\n\n\n\n_X_ ∝ _σ_ <sup>2</sup> <sup>_ϵ_</sup> _,_ _C_ <sup>∗</sup> ∝ _σ_ <sup>2</sup> _._\n\n\nThis proportionality demonstrates that as uncertainty (volatility) increases, the value of the option\n\n\nto delay investment rises, similar to financial options where greater volatility expands the range of\n\npossible outcomes. This flexibility allows firms to respond more effectively to future changes, such as\n\n\nshifts in prices or market trends. Firms can capitalize on upside opportunities by exercising the option\n\n\nto invest or expand, while avoiding losses by deferring in unfavorable conditions. This asymmetry,\n\n\nwhich favors the investor, means that higher uncertainty or a broader range of potential outcomes\n\n\nbenefits the firm by increasing the value of waiting.\n\n\nThe following sections outline the data sources and empirical strategies used to", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001211", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data sources", "probe_tag": "confusion", "probe_score": 0.8434655070304871, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1158, "end": 1170, "key": "prwp:001211:7:1:0", "source": "camp2", "luna_reason": "Merely introduces forthcoming data-source sections without identifying or using existing data.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": "$575 billion, including projects already executed, in implementation phase and planned. Based\non this data, US$525 billion or 91 percent of total identified investments is expected to benefit IBRD or\nIDA-eligible countries. <sup>3</sup> Only US$66 billion in completed projects has been identified as of end-2016; most\nBRI investment is still in the construction or planning phase. The analysis largely focuses on 50 developing\ncountries, which have been identified as lying on the original BRI transport and connectivity corridors (De\nSoyres et al., 2018) and for which debt and macroeconomic data are available. This approach implies that,\nfor example, only two Sub-Saharan African countries, namely Kenya and Tanzania, are included in the\ndatabase, despite significant Chinese investment in Sub-Saharan Africa, some of which has been recently\nrebranded as BRI related. <sup>4</sup> [^4: In October 2018, the Forum on China-Africa Cooperation announced US$60 billion financing to African Countries\nand this financing has been re-branded as part of the BRI (see https://thediplomat.com/2018/09/focac-2018rebranding-china-in-africa/).]\n\n\nSeveral countries have already scaled back on BRI investments or requested debt relief from China. In\nOctober 2018, Malaysia decided to suspend and renegotiate US$20 billion worth of projects fearing not\nto be able to repay such debt and Pakistan cut down the cost of a large railway project. China had to\nprovide debt relief to several borrowing countries in recent years <sup>5</sup> [^5: Hurley _et al._ (2018) provide a comprehensive list.] ; in some rare cases, difficulties in\nrepaying debt has resulted in China taking possession of key infrastructure in lieu of repayment in Sri\n\n\n2 See, for example, “How Big Is China’s Belt and Road?”, April 3, 2018, Center of Strategic and International Studies.\n3 US$ 10 billion of financing directed to Latin American Countries was not", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000014", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "debt and macroeconomic data", "probe_tag": "confusion", "probe_score": 0.675757646560669, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 571, "end": 598, "key": "prwp:000014:3:1:0", "source": "camp2", "luna_reason": "States data availability as a selection criterion without showing analyzed findings.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": "##### **7 Conclusions**\n\nPrevious studies of the elasticity of input tariffs on firm level productivity have docu\n\nmented sizeable effects that are difficult to reconcile with firms’ cost minimization prior\n\n\nto the trade reform. We revisit this result incorporating the fact that when firms expand\n\n\ntheir foreign sourcing, there are important changes in their input costs. When input\n\n\ntariffs drop, firms substitute towards lower variable, but higher ordering and inventory\n\n\nholding cost inputs. The use of aggregate price deflators in the estimation of productiv\n\nity is ill suited to capture the heterogeneity in firms’ input costs. We propose to control\n\n\nfor firm level input costs that capture price differentials, ordering costs and inventory\n\n\nholding costs by including import intensity and the inventory usage in the estimation of\n\n\nproductivity. When we apply the control function, the elasticity of productivity to input\n\n\ntariffs drops by 37% in the case of India’s trade liberalization of the 1990s.\n\n\nThese findings illustrate that, without quantity data, it is important to account for\n\n\nthe different margins of input cost in the evaluation of the firm performance. While\n\n\nthis paper focused on the setting of trade liberalizations, similar mismeasurement might\n\n\nbe consequential in the response to other trade shocks. For example, during large de\n\nvaluations, productivity drops have been accompanied by large responses in inventories\n\n\n(Gopinath and Neiman (2014)). On the other hand, in this paper, we do not take a stand\n\n\non whether the effects are driven by physical efficiency or markups, but the additional\n\n\ncosts of engaging in international trade we refer to might as well be viewed as requiring\n\n\nhigher per unit markups. An interesting avenue of future work is to incorporate the or\n\ndering and inventory holding costs described here and reassess the documented increase\n\n\nof markups after trade liberalizations (De Loecker et al. (2016), Brandt et al. (2017)).\n\n\nFinally, this paper emphasizes that trade liberalizations affect multiple", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001747", "page": 34, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "quantity data", "probe_tag": "confusion", "probe_score": 0.7117177248001099, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1059, "end": 1072, "key": "prwp:001747:34:0:0", "source": "camp2", "luna_reason": "Notes missing quantity data without citing analysis or substitute estimates.", "drop_reason": "availability", "specificity": "vague"}]}
+{"text": " of countries (albeit only 11 African countries are included)\nand comes to a similar premature deindustrialization for Sub-Saharan Africa and\nLatin America.\n\n\nThus, there is a dearth of literature focused on sub-Saharan Africa’s manufacturing experience, and those that do have utilized a limited number of SSA\ncountries due to data inadmissibility. This paper attempts to fill this void by assembling data on 41 sub-Saharan African countries from multiple sources including\nthe Groningen Growth and Development Center 10-sector Database, the Maddison Project Database, the World Development Indicators, and the International\nLabor Organization’s ILOSTAT database. Our data spans 1960-2016, which is\nthe longest panel data on output and employment shares on Sub-Saharan African\ncountries to our knowledge. If sub-Saharan African countries are experiencing\nprematurely deindustrialization, this has potentially negative ramifications for the\nregion’s economic development.\n\n\n1See also Dasgupta & Singh (2005).\n\n\n2", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001839", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Groningen Growth and Development Center 10-sector Database", "probe_tag": "keep", "probe_score": 0.9203234910964966, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 479, "end": 537, "key": "prwp:001839:4:1:1", "source": "camp2", "luna_reason": "Named existing database used to assemble panel data for economic analysis.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "Figure 5. Work stoppages in Lao PDR, PNG, and Vietnam\n\nLao PDR\n\n\nNote: 95% confidence intervals for difference from Q1 are shown (rather than from zero). Including controls for respondent\ncharacteristics do not qualitatively change results. See Appendix Table 2 for regression tables with controls.\nSource: HFPS; Round 3 is used for Vietnam Jul-Sep 2020\n\nIndonesia and the Philippines - Like other countries discussed above, Indonesia and the Philippines\nexperienced a steep decline in mobility early in 2020, but unlike the others, they faced a pandemic-induced\nhealth crisis relatively early in 2020 and a prolonged period of depressed mobility (lower than -20 percent).\nFar-reaching mobility restrictions translated into employment shocks that were similarly widespread across\nthe welfare distribution (Figure 6). A wide range of sectors experienced work stoppages during early stages\nof the pandemic, including sectors such as retail, transportation, and finance in which significant shares of\nwealthier workers were employed. For example, in Indonesia, HFPS data indicate that more than half of\nworkers in the top 20 percent of the welfare distribution were employed in retail, transportation, or\n\n\n14", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001702", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "HFPS data", "probe_tag": "keep", "probe_score": 0.9801008701324463, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1058, "end": 1067, "key": "prwp:001702:15:0:0", "source": "camp2", "luna_reason": "HFPS data support a concrete employment-distribution finding.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**Data collection**\n\nQuantitative surveys were administered on tablets and paper questionnaires with all enrolled\nparticipants at two time points (wave 1, August 2018 - February 2019 and wave 3, June 2021 January 2022). Surveys included questions on employment and income, client history, sexual\nbehavior, HIV/STI risks, mental health, and gender-based violence. Surveys at the end of the study\nperiod included additional questions about changes in work and sexual activity related to COVID19. An additional survey was administered via phone to a subset of participants in the control arm\nonly (wave 2, July-October 2020), and included a reduced set of survey questions focused on\nwealth and income, income shocks related to COVID-19, food security, and sexual history.\n\nQualitative interviews were conducted with a subset of 20 wave 3 participants using a semistructured interview guide to elicit views on the intervention and to understand the effects of\nCOVID-19 on employment, income, client type, and work conditions. The interview guide was\ninformed by preliminary findings from the wave 3 quantitative surveys which indicated that\nparticipants had been experiencing changes in income and work activity related to COVID-19,\nthus the interviews served to gather additional perspectives and insights into the experiences of\nFSW during COVID-19. Interviews were approximately 60 minutes in duration and audio\nrecorded.\n\nAll data were collected in Kiswahili by trained research assistants at Innovations for Poverty\nAction Tanzania.\n\n**Data analysis**\n\nQuantitative data were analyzed in STATA version 15.1. Descriptive statistics were generated to\n1) assess the demographic characteristics of participants at enrollment (wave 1, 2018) and to\ncompare the overall study population with those who were reached for phone surveys (wave 2,\n2020) and at the end of the study period (wave 3, 2021); 2) examine self-reported data on\nemployment and income before and during COVID-19. Linear first difference regression with\nrobust standard", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001040", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Quantitative surveys", "probe_tag": "confusion", "probe_score": 0.16993354260921478, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 21, "end": 41, "key": "prwp:001040:5:0:0", "source": "camp2", "luna_reason": "Surveys were administered as part of the study's data collection.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": " and especially so in non-project\nareas. Local officials’ payment of their own property taxes increases substantially in non-project\nareas, and they also are more likely than project-area officials to report efforts to improve local\ntax collection.\n\nTo offer ideas and recommendations from research for further innovation in the design of\nsuch projects in Tanzania and beyond, we closely reviewed project documents to understand the\ngeneral design and theory of change on which these capacity building projects are founded. We\nfind that these projects share a common, global template that is being applied across different\ncountries and contexts, centered on the role of an Annual Performance Assessment which is expected to verify whether local governments have certain institutional features that are found in\nhigh state capacity countries: such as, existence of planning documents, council meeting minutes, audit reports, procurement tenders and the like. <sup>26</sup> Qualitative research has critiqued this\napproach to building state capacity as “isomorphic mimicry” (Andrews et al., 2017), whereby\ndeveloping countries are made to produce documents and establish protocols that resemble institutions in donor countries, but fail to effectively perform the functions of a state. The lack of\ndifference in measured outcomes of state functioning in the data from Tanzania offers quantitative evidence that is consistent with such critiques.\n\nAlternatively, the amounts committed or the scope of the capacity building component might\nbe too small to make a dent. <sup>27</sup> Further, the rationale for using a financial incentive approach is\n\n\n26See examples from Egypt (World Bank, 2018a), Ethiopia (World Bank, 2014b), India (West Bengal) (World Bank,\n2016a), Indonesia (World Bank, 2005), Uganda (World Bank, 2016b), and Vietnam (World Bank, 2014a).\n27For the project in Tanzania, the total donor contribution was US$255 million, but only US$54 million was\n\n\n27", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000123", "page": 29, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data from Tanzania", "probe_tag": "confusion", "probe_score": 0.3799571096897125, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1357, "end": 1375, "key": "prwp:000123:29:1:0", "source": "camp2", "luna_reason": "Tanzanian data support quantitative evidence about unchanged state-functioning outcomes.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " 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 component will support civil works for widening and upgrading of the approximately 105 km-long\nKoboko-Yumbe-Moyo road corridor to bituminous paved road standards adopting the World Bank’s\nguidelines and requirements with respect to the procurement, social and environmental safeguards. The\nworks will be maintained for a period of five years post completion of construction of works. This component\nwill also support the associated (i) construction supervision consultants, (ii) third-party audit consultants to\nperform semi-annual integrated performance audits covering, among others, engineering designs,\nmanagement of social and environmental issues including implementation of the SEA/SH action plan, and\nquality assurance, (iii) safeguards management consultants for implementation of the Resettlement Action\nPlans, (iv) Consultants/Non-Governmental Organizations for implementation of Gender Based Violence,\nViolence Against Children, and HIV/AIDS action plans, (v) Road User Satisfaction Survey consultants to carry\nout baseline, midterm, and end-stage user satisfaction surveys - disaggregated by gender, refugees and\nhosts, (vi) consultants for monitoring and evaluation of Project’s outcome and intermediate indicators; and\n(vi) preparation of environmental and social risk management documents as well as detailed engineering\ndesigns of civil works and carrying out land acquisition, and resettlement and rehabilitation.\n\n\nPage 21 of 80", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 25, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Road User Satisfaction Survey", "probe_tag": "confusion", "probe_score": 0.3882821500301361, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1265, "end": 1294, "key": "jdc_operational:000050:25:1:0", "source": "camp2", "luna_reason": "Consultants will carry out future baseline, midterm, and end-stage satisfaction surveys.", "drop_reason": "production", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nNational Youth Opportunities Towards Advancement Project (P179414)\n\n\n\n|Col1|component 1 or under<br>recognition of prior learning<br>and received a certificate<br>from the National Industrial<br>Training Authority.|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Youth beneficiaries receiving business<br>development support and grant|This indicator measures the<br>youth who received<br>business development<br>support under component 2<br>such as access to networks<br>and open market. The<br>targets are cumulative,<br>unique individuals.|Bi-annual<br>|MIS<br>|MIS data reported by<br>MSEA<br>|MYAAS through MSEA<br>|\n|Host community youth beneficiaries<br>receiving business development<br>support and grant|This indicator measures host<br>community youth<br>beneficiaries in Garissa,<br>Turkana and Wajir Counties<br>who received business<br>development support under<br>component 2 such as access<br>to networks and open<br>market. The targets are<br>cumulative, unique<br>individuals.|<br>Semi-<br>Annual<br>|MIS<br>|MIS data reported by<br>MSEA<br>|MSEA<br>|\n|Refugee youth beneficiaries receiving<br>business development support and<br>grant|This indicator measures<br>refugee youth beneficiaries<br>in Garissa, Turkana and<br>Wajir Counties who received<br>business development<br>support under component 2<br>such", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002639", "page": 59, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MIS data", "probe_tag": "confusion", "probe_score": 0.2639444172382355, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 583, "end": 591, "key": "fcv_pads_east_africa:002639:59:0:0", "source": "camp2", "luna_reason": "Names MIS data without showing an analyzed finding or substantive data use.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": "Figure 1: A district map of India\n\n\nNotes: Light gray lines denote district borders, while black lines\n\ndenote state borders. The gray shaded area is the Ganga Basin\n\n(240 districts), while the black shaded area is our group of four\n\n“treatment” districts (Kanpur, Unnao, Fatehpur, and Rae Bareli).\n\n\n29", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006810", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "district map of India", "probe_tag": "confusion", "probe_score": 0.4456934332847595, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 12, "end": 33, "key": "prwp:006810:30:0:0", "source": "camp2", "luna_reason": "Figure caption describing a map, not a standalone cited data resource.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
+{"text": "19-Impact-on-Refugees-in-Ethiopia-Results-from-a-High-Frequency-Phone-Survey-of-Refugees.pdf)</u>\nIraq: _Report Forthcoming_\n[Kenya: See https://www.kenyacovidtracker.org/rrps and Socioeconomic impacts of COVID-19 in Kenya](https://www.kenyacovidtracker.org/rrps)\n[Uganda: For information on refugees see Monitoring Social and Economic Impacts of COVID-19 on Refugees in Uganda :](https://documents1.worldbank.org/curated/en/682171613766616044/pdf/Monitoring-Social-and-Economic-Impacts-of-COVID-19-on-Refugees-in-Uganda-Results-from-the-High-Frequency-Phone-Survey-First-Round.pdf)\n<u>[Results from the High-Frequency Phone Survey - First Round, and Third Round Results for Ugandans can be found here. A](https://documents1.worldbank.org/curated/en/682171613766616044/pdf/Monitoring-Social-and-Economic-Impacts-of-COVID-19-on-Refugees-in-Uganda-Results-from-the-High-Frequency-Phone-Survey-First-Round.pdf)</u>\n<u>[policy paper comparing refugee and Ugandan welfare can be found here.](https://documents.worldbank.org/en/publication/documents-reports/documentdetail/794251624902794307/one-year-in-the-pandemic-results-from-the-high-frequency-phone-survey", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000604", "page": 17, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "High-Frequency Phone Survey", "probe_tag": "confusion", "probe_score": 0.822841465473175, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 604, "end": 631, "key": "reliefweb:000604:17:3:0", "source": "camp2", "luna_reason": "Named existing phone survey cited as the source of linked results.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": " and mostly kept in paper form.** Procurement-related records\n(from advertisements to final invoices) are also maintained in hard copy. The execution of Program procurement\ntransactions through the JONEPS will ensure the systematic tracking, recording, and processing of procurement. It will also\nfacilitate the enhancement of procurement performance and the retrieval of procurement records when needed. The\nJONEPS developed a contract management module. However, it is not fully operational, and it is being enhanced to\naccommodate works contracts as well. In parallel, the JONEPS is having discussions with the GFMIS to develop an\nApplication Programming Interface (API) to connect both systems and consolidate data. Once the contract management\nfunction is tested, consolidation will be meaningful.\n\n\n**68.** **According to Article 84 of the Procurement Bylaw No. 8/2022, Jordanian courts will be referred to for the settlement**\n**of disputes during the execution of contracts.** However, the contract may provide other dispute resolution methods,\nstarting with amicable settlement and escalating to arbitration. The contracting parties may have recourse to a third party\nfor the settlement of disputes using conciliation and mediation. This could be done by appointing dispute experts or dispute\nreview boards, along with the related appointment procedures for such conciliators.\n\n\n_Internal Controls and Internal Audit_\n\n\n**69.** **The overall control environment continues to be acceptable for Program implementation** . Internal controls and the\ninternal audit function are governed by the applicable Financial By-law (1994) and its Amendment (2015) and the Financial\nControl By-law (2011) and its Amendment (2015). Each ministry has its own internal audit unit in the Finance Department,\nand an Internal Control Unit (ICU) is responsible for the effective operation of the internal financial control system. In the\nministries participating in the Program, there is also a financial control unit comprised of employees from the MOF, which\nperforms a", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 75, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Procurement-related records", "probe_tag": "confusion", "probe_score": 0.09009736776351929, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 34, "end": 61, "key": "refugee_pads:000181:75:1:0", "source": "camp2", "luna_reason": "Routine procurement records maintained for administrative tracking, not substantive data use.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda (P176747)\n\n\n\n|Col1|training, disaggregated by<br>age and disability status.|Col3|Col4|completion to the<br>MGLSD or the PSFU.|each month.|\n|---|---|---|---|---|---|\n|Women in RHDs||||<br>||\n|Refugee women||<br>||||\n|Beneficiaries supported by the project<br>stating that their involvement in decision-<br>making over household expenditures has<br>increased|Number of women that are<br>empowered in the<br>household sphere.<br>Beneficiaries are the women<br>entrepreneurs that benefit<br>from at least two services<br>supported by the project.|<br>Baseline<br>data when<br>enterprises<br>start,<br>annual<br>surveys<br>from year<br>2.<br>|Surveys of a<br>panel of<br>women<br>entrepreneur<br>s benefiting<br>from the<br>project.<br>|This will be calculated<br>through annual surveys<br>of enterprises<br>participating in the<br>project.<br>|MGLSD to administer the<br>surveys, and compile and<br>report the data.<br>|\n|Women in RHD||<br>||||\n|Refugee women||||<br>||\n|Women microenterprises accessing credit<br>from a formal financial institution<br>(Number", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 52, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "annual surveys", "probe_tag": "confusion", "probe_score": 0.0742877796292305, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 864, "end": 878, "key": "jdc_operational:000025:52:0:0", "source": "camp2", "luna_reason": "Future project surveys will generate the indicator data.", "drop_reason": "production", "specificity": "vague"}]}
+{"text": ". The with-project scenario in\nthe ex-ante analysis assumed pavement overlay as the intervention type; during the additional financing stage, this\nwas changed to full structural rehabilitation due to the steep increase in heavy goods vehicle composition on the\nproject roads. The ex-post analysis reflects this intervention change. Both scenarios include annual routine\nmaintenance and future periodic maintenance delivered through an OPRC covering rehabilitation and maintenance\nover a 10-year contract period. After that period, responsive condition-based maintenance is assumed.\n\n\n4. The ex-post economic analysis evaluated the improved road sections, replicating the appraisal evaluation based on\nthe revised intervention type, actual costs, and actual traffic volumes at completion.\n\n\n5. Based on the feasibility study and technical design reports, the pre-project road surface conditions measured in\n2019, expressed as the International Roughness Index (IRI), were as follows: Lot 1 (Koloni–Soroti of 27.3 km) = 4.08\nm/km; Lot 2A (Soroti–Lira of 123.8km) = 4.90 m/km; and Lot 2B (Lira–Kamdini of 66.5 km) = 4.50 m/km.\n\n\n6. The intervention type on the project roads changed fundamentally between appraisal and implementation — from\na pavement overlay assumed at appraisal to full structural rehabilitation, driven by the exponential increase in heavy\ngoods vehicle traffic on the corridor, as shown in Table 1. Pavement thickness was increased on both Lot 1 and Lot\n2 to accommodate the substantially higher traffic loading, while the 20-year design life target remains unchanged\nin the ex-post analysis. Two additional scope changes are noted: the weighbridge on Lot 1 at km 46+700 was\ntransferred from IDA to Government of Uganda financing due to insufficient time for completion under IDA, and\nthe OPRC contract, originally planned for signing in late 2014/early 2015, was not signed until 2018.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003408", "page": 40, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "International Roughness Index", "probe_tag": "confusion", "probe_score": 0.3722153902053833, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 929, "end": 958, "key": "fcv_pads_east_africa:003408:40:1:0", "source": "camp2", "luna_reason": "IRI measurements from feasibility and technical design reports support reported road conditions.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**Table 1.** List of Variables and Data Sources\n\n\n**<u>Indicator</u>** **<u>Description</u>** **<u>Source</u>**\n\n\n\nSocial trust Percentage of respondents stating that, “Generally speaking,\nmost people can be trusted”; survey waves mapped to 4-year\nperiods as follows: survey 2005-2009 (period 1), survey 20102014 (period 2), survey 2017-2019 (period 3)\n\nWBG engagement WBG own commitment (% of GDP): Total amount committed\n\nfor projects related to domestic resource mobilization by\napproval fiscal year as a share of the recipient country’s GDP\n<u>(scaled by factor 1,000 for better readability)</u>\n\n\n_Source:_ Authors’ compilation.\n\n\n\nWorld Values Survey\n\n\nWorld Bank (public and internal\ndata) as reported in Table A3 in\nthe appendix\n\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\n6 8 10 12\n\nLog GDP per capita\n\n\n0 100 200 300 400\n\nTrade Openness\n\n\n\n**Figure 2.** Economic Fundamentals and Revenues, 2016-2019\n\n\n\nShare of Agriculture in GDP\n\n\n0 20 40 60 80 100\n\nAge Dependency Ratio\n\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\n_Notes:_ The sample consists of 182 countries. The dotted line represents the result of a bivariate linear regression of revenue\non the indicator shown on the x-axis (see Table A2 in the appendix).\n_Source:_ Authors’ analysis based on the variables and data sources described in Table 1.\n\n\nThe indicator of technological readiness (see Table 1, Panel D) is countries’ score on the\n“Technological Readiness Index” from the World Economic Forum’s Global Competitiveness Report.\n\n\n10", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001867", "page": 11, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Technological Readiness Index", "probe_tag": "confusion", "probe_score": 0.5856208205223083, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1419, "end": 1448, "key": "prwp:001867:11:0:2", "source": "camp2", "luna_reason": "Named index from the Global Competitiveness Report used as an analytical indicator.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": " (Net Enrolment Ratio), and the percentage of overage refugees included in each education cycle.\n\n\nIf available, age:\n\n - % primary/secondary school-aged refugee students\nenrolled in national education system’s primary or\nsecondary schools;\n\n\n - [% overage (see: http://uis.unesco.org/en/glos-](http://uis.unesco.org/en/glossary-term/over-age-students)\n<u>[sary-term/over-age-students) refugee students](http://uis.unesco.org/en/glossary-term/over-age-students)</u>\nenrolled in national education system’s primary\nor secondary schools.\n\n\n**Methods and Guidance:** The UNESCO Institute\n[for Statistics (http://uis.unesco.org) has guidelines on](http://uis.unesco.org)\nthe compilation of data to calculate Gross Enrolment\nRatio. However, enrolment and population data referring only to refugees should be considered.\n\n\nIf disaggregation by age is possible, and therefore it is\npossible to calculate the Net Enrolment Ratio and the\npercentage of overage students enrolled in each education cycle, guidance on Net Enrolment Ratio and\ndefinition of “overage students” can also be found on\n<u>[http://uis.unesco.org.](http://uis.unesco.org)</u>\n\n###### Data Sources\n\n\nEducation data may be derived from administrative\nsources typically coordinated and disseminated through\nthe Ministry of Education. Additional sources may include school registers, school surveys or census for\ndata on enrolment by level of education; population\ncensus or estimates for school-age population. UNHCR’s\nRefugee Education Information Management System\n(REMIS) may also serve as a complementary data source", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000789", "page": 21, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "population\ncensus", "probe_tag": "confusion", "probe_score": 0.20402252674102783, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1413, "end": 1430, "key": "reliefweb:000789:21:1:4", "source": "camp2", "luna_reason": "Potential source is merely listed; no census data finding or analysis is attributed.", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nAgricultural Employment Support for Refugees and Turkish Citizens through Enhanced Market Linkages (P171543)\n\n\nincorporated inputs from local employers had double the impact on employment and earnings relative to\na traditional program with no inputs from employers. Building on international evidence, the proposed\nproject aims to provide skill training to workers in line with the demands of employers, which will be\ndetermined through a needs assessment and updated regularly.\n\n\n68. **While wage subsidies can be effective tools to improve the employability of vulnerable**\n**populations, consideration should be given to how to avoid deadweight losses.** Lessons learned in other\ncountries identify four potential effects that would lead to a program being ineffective or detrimental to\nemployment: <sup>55</sup> [^55: Hirshleifer, Sarojini, McKenzie, David, Almeida, Rita, and Cristobal Ridao-Cano. 2014. _The Impact of Vocational Training for_\n_the Unemployed: Experimental Evidence from Turkey (English)_ . EnGender Impact: the World Bank's Gender Impact Evaluation\nDatabase. Washington, DC: World Bank Group. _[http://documents.worldbank.org/curated/en/209871468310469519/The-](http://documents.worldbank.org/curated/en/209871468310469519/The-impact-of-vocational-training-for-the-unemployed-experimental-evidence-from-Turkey)_\n_[impact-of-vocational-training-for-the-unemployed-experimental-evidence-from-Turkey](http://documents.worldbank.org/curated/en/209871468310469519/The-impact-of-vocational-training-for-the-unemployed-experimental-evidence-from-Turkey)_ . Bördős, K., Csillag, M., and A. Scharl.\n2015. _What Works in Wage Subsidies for Young People: A Review of Issues, Theory, Policies and Evidence_ (No.\n994898973402676). International Labour Organization.] (a) employer may substitute a worker eligible for the subsidy with another who is\nineligible; (b) employers may use the wage subsidy to hire a worker that they would have hired even\nwithout the subsidy; (c) by improving the employability of the workers with their initial human capital, the\nsubsidy", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000114", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Gender Impact Evaluation\nDatabase", "probe_tag": "confusion", "probe_score": 0.4460524618625641, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1066, "end": 1099, "key": "refugee_pads:000114:31:0:0", "source": "camp2", "luna_reason": "Named database cited as the source for an evaluation informing program lessons.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "**The World Bank**\nStrengthening Lebanon’s Covid-19 Response (P178587)\n\n\n**C.** **Learning Agenda**\n\n\n14. **The project will support adaptive learning throughout implementation, as well as from international**\n**organizations including the WHO, International Monetary Fund (IMF), Centers for Disease Control (CDC), United**\n**Nations Children's Fund (UNICEF), and others.** It will adjust to emerging technical, social, and economic evidence,\nas applicable, and incorporate lessons learned from ongoing global vaccine rollout and COVID-19-related service\ndelivery. In Lebanon, this learning agenda involves a continuation of on-going World Bank technical assistance\n(TA), including:\n\n\n\n\n- **Technical:** Monitoring of vaccine deployment readiness assessments and technical support to regular\nupdates of the NDVP\n\n- **Social behaviors** : The following data collection initiatives will be undertaken to improve knowledge and\nunderstanding of perceptions and attitudes towards vaccination as well as performance of the vaccination\ninitiative **:**\n\n\n\na. Facebook Surveys to assess beliefs and attitudes towards COVID-19 vaccination and identify\n\ncauses of hesitancy\nb. Testing of communication messages to improve uptake of vaccines\nc. Iterative Beneficiary Monitoring (IBM): an iterative feedback loop that collects information\n\ndirectly from beneficiaries and identifies challenges at the local level\nd. Third-party monitoring of vaccine deployment: Performance score cards to monitor\n\n\n\nperformance by vaccination sites and identify challenges in vaccination deployment\n\n- **Digital vaccination registry:** An innovative approach for data transparency based on the digitalization of\nvaccination data has significantly enhanced public trust in the COVID-19 vaccination program. This approach\nutilizes the digital platform pioneered by the Inter-ministerial and Municipal Platform for Assessment\nCoordination and Tracking (IMPACT), hosted by the oversight body Central Inspection Bureau (CIB).\n\n\n\n**<mark>II.", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Facebook Surveys", "probe_tag": "confusion", "probe_score": 0.6936389207839966, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1052, "end": 1068, "key": "jdc_operational:000000:15:0:0", "source": "camp2", "luna_reason": "Planned surveys will collect data for future vaccination learning.", "drop_reason": "production", "specificity": "named"}, {"text": "Digital vaccination registry", "probe_tag": "confusion", "probe_score": 0.11878561973571777, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1576, "end": 1604, "key": "jdc_operational:000000:15:0:1", "source": "camp2", "luna_reason": "Registry data supports transparency and a concrete public-trust finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"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:014881", "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:014881:65:0:0", "source": "camp2", "luna_reason": "States epidemiological data are unavailable without substitute estimates or analysis.", "drop_reason": "availability", "specificity": "descriptive"}]}
+{"text": " this paper, as they measure\n\nthe management and delivery of aid while the remaining 5 measure quality of country systems etc.\n\n(Table 1).\n\n\n**<u>Table 1: Ten PD Survey Indicators</u>**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Principle|Indicators|How Measured|\n|---|---|---|\n|Alignment|**Ind 3:** Aid flows are aligned with national<br>priorities (aid on budget)|Aid flows reported in the annual budget by<br>government/aid<br>flows<br>actually<br>disbursed<br>by<br>development partners (%)|\n|Alignment|**Ind 4:**Strengthen capacity by coordinated<br>support (technical assistance)|Amount of coordinated technical cooperation /<br>total technical cooperation (%)|\n|Alignment|**Ind 5a:**Use of country PFM systems|Use of PFM/total assistance (%)|\n|Alignment|**Ind 5b:**Use of country procurement<br>systems<br>|Use of procurement / total assistance (%)|\n|Alignment|**Ind 6:**Strengthen capacity by avoiding<br>parallel<br>project<br>implementation<br>units<br>(PIUs)|Number of parallel PIUs|\n|Alignment|**Ind 7:**Aid is more predictable|Actual<br>aid<br>flows<br>recorded<br>by<br>the<br>government/scheduled aid flows by development<br>partners (%)|\n|Alignment|**Ind 8:** Aid is untied|OECD-DAC data|\n|Harmonization|**", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005210", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "PD Survey Indicators", "probe_tag": "confusion", "probe_score": 0.3120687007904053, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 159, "end": 179, "key": "prwp:005210:6:1:0", "source": "camp2", "luna_reason": "Standalone table caption naming survey indicators, not an independently used data resource.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
+{"text": " recommendations\nare presented for each of the five countries. Overall\nrecommendations include a call to take advantage of\nexisting regional interagency initiatives as platforms for\nregional advocacy around child labour law and policy,\nsharing of expertise across borders, and tracking regional\nchild labour trends and program outcomes.\n\n\nCapacity development and resources are needed among\nactors in all relevant sectors. Child labour data may need\nsupport to harmonize their systems and increase data\nevidence. Investments are needed to develop the social\nservice workforce in all countries, as well as to build\nteachers’ protection capacity.\n\n\n1 Matz, Peter, (2016). Child labour within the Syrian refugee response:\nStocktaking report\n2 UNHCR/WFP/UNICEF, (2021). Vulnerability Assessment of Syrian Refugees\nin Lebanon\n\n\n\n6", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000489", "page": 4, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Child labour data", "probe_tag": "confusion", "probe_score": 0.43519148230552673, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 423, "end": 440, "key": "reliefweb:000489:4:2:0", "source": "camp2", "luna_reason": "Generic data resource mentioned for system harmonization, without an attributed finding.", "drop_reason": "system_registry", "specificity": "vague"}]}
+{"text": "**The World Bank**\nEthiopia Digital ID for Inclusion and Services Project (P179040)\n\n\n**ANNEX 3: Gender Analysis and Action Plan**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Problem statement. In Ethiopia, there is a notable gender gap in the existing ID system (Kebele ID) coverage. According to the<br>ID4D-Findex Survey (2017), 36 percent of the population ages 18 and older lack a Kebele ID, with significant gender gap of 46<br>percent of women lacking one, compared to 25 percent of men.|Col2|Col3|\n|---|---|---|\n|**ANALYSIS:** <br>**Gender gaps identified**|**ACTIONS:**<br>**Proposed actions Taken to address gaps**|**INDICATORS**: <br>**How bridging the gap**<br>**will be measured**|\n|**Women have less knowledge about benefits**<br>**of having an ID.**Country-specific research,<br>including a Social Risk Analysis and a Gender<br>Gap in ID Study, outline low literacy, a general<br>lack of awareness on the day-to-day use of ID,<br>perceived irrelevance of formal identification,<br>and limited knowledge of individual rights as<br>key factors contributing to lower Kebele ID<br>enrolment by women. Based on the most<br>recent data from 2017, the adult (age 15 and<br>above) literacy rate for men is 59 percent,<br>compared to 44 percent for women (World<br>Bank 2022), which can make it harder for<br>women to navigate the ID registration<br>process.|", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000005", "page": 48, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "ID4D-Findex Survey", "probe_tag": "confusion", "probe_score": 0.6765053868293762, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 283, "end": 301, "key": "refugee_pads:000005:48:0:0", "source": "camp2", "luna_reason": "Named 2017 survey supports reported gender gaps in Kebele ID coverage.", "usage_type": "evidential", "specificity": "named"}, {"text": "data from 2017", "probe_tag": "confusion", "probe_score": 0.17555128037929535, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1118, "end": 1132, "key": "refugee_pads:000005:48:0:1", "source": "camp2", "luna_reason": "Bare date-only qualifier cannot inherit the World Bank source or literacy finding.", "drop_reason": "ref_list", "specificity": "vague"}]}
+{"text": " due to irregularities and lack of transparency in local tax administration, obstruction of\ninvestments by some unscrupulous politicians, and a general perception that LGs do not offer useful support,\nwithin their mandates, for local private sector development <sup>11</sup> . In addition, little support is provided to local\nfirms by municipal LGs, even though they have the mandate to provide support to micro-enterprises and\nother firms through the Commercial Office. There is also an absence of meaningful public private dialogue,\nparticularly in terms of consulting the private sector in the development of local development plans. The\nstudy made three main recommendations to LGs in Uganda: (i) to make infrastructure investments that are\nbetter prioritized according to local economic potentials – building on the major recent investments in roads\nand connectivity to transition to other strategic investments in tourism site development, market\n\n4 Arch Design Ltd, 2012 – Municipal Assets Inventory and Conditions Assessment Final Report\n5 From UGX 37 million in 1993/4 to UGX1.6 trillion in 2011/12.\n6 Local Government Finance Commission (2012) **.** Review of Local Government Financing: Financing Management and\nAccountability for Decentralized Service Delivery.\n7 FDA section 7.2\n8 DDEG has replaced the Local Development Grant (LDG) as part of the broader GoU IGFT reform\n9 For example, unit costs of paving 1 km of urban road ranges between US$800,000 to US$1 million and for a primary drainage\n(with box culverts at road crossings and armoflex linings) about US$500,000 to US$1.1 million per km.\n10 USAID (2015) Ugandan Decentralization Policy and Issues Arising in the Health and Education Sectors: A Political Economy\nStudy. October 2015.\n11 World Bank 2016. _Uganda - Repositioning local governments for economic growth_ . Washington, DC: World Bank.\n\n\n2", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 9, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Municipal Assets Inventory and Conditions Assessment", "probe_tag": "confusion", "probe_score": 0.6535274386405945, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 980, "end": 1032, "key": "jdc_operational:000006:9:2:0", "source": "camp2", "luna_reason": "Named assessment report cited as an existing source.", "usage_type": "declaration", "specificity": "named"}]}
+{"text": "Iganga, Kayunga, Mukono, Wakiso, Luwero, Mityana and Buikwe. The details of the\nprojects, their scope (size and area) are presented as annexures herein. The ESMP\nfurther covers the environmental and social aspects of the project during construction\nand operational phases.\n\n\nMethodology\nThe methods used in the development of this ESMP included but were not limited to:\n\nSite inspection and observation\nVisits were made to the proposed project areas during the course of developing this\nESMP. Site visits were conducted with the aim of identifying potential causes of\nenvironmental and social risks. This was aimed at ensuring that appropriate\nenhancement and/or mitigation measures are prescribed to manage any potential\nrisks.\n\nConsultation with stakeholders\nConsultations were carried out through interviews and discussions with relevant\nstakeholders including communities to ensure public participation in the ESMP\ndevelopment process.\n\n\nREA Team Engaging Works Supervisor BDL Community Engagement in Makonge & Kyambogo\nVillage,\nDocument Review\nThe Literature reviewed included; Background data concerning the local communities,\nincluding from the UBOS National Census (2014); Demographic and Health Survey\n(2006), and District Development plans, legal and policy frameworks, ESMF for ERT\nIII and the World Bank safeguard requirements among others.\n\n\n2", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008341", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Demographic and Health Survey", "probe_tag": "confusion", "probe_score": 0.8643768429756165, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1181, "end": 1210, "key": "fcv_pads_east_africa:008341:7:0:1", "source": "camp2", "luna_reason": "Existing 2006 survey cited as reviewed background data.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "The general procedure to calculate the fuel shock's indirect effects is as follows. Firstly, we map the\n\n\nhousehold consumption expenses to the IO matrix sectors. Secondly, we match the Gasoline and Diesel\n\n\nitem to a fuel sector in the IO matrix. We then determine the price shock according to the forecasted price\n\n\nchange. <sup>5</sup> [^5: We calculate a weighted price shock based on gasoline and diesel annual sales based on Paraguay’s Ministry of Industry and\nCommerce data.] Finally, the model is solved, and the percentage change in final prices is matched with the items\n\n\nin the household survey according to the mapping of the first step. The purchasing power variation due to\n\n\nthe percentage change in final prices is calculated similarly to the Paasche Variation for the direct effect\n\n\nshock.\n\n\nb. Data manipulation\n\n\nData comes from two main sources, the “Encuesta de Ingresos y Gastos 2011-2012 (EIG)” and the\n\n\n“Encuesta Permanente de Hogares 2019 (EPH)”, both household surveys available in Paraguay. The EIG is\n\n\na household survey that contains expenditure records for almost 6,000 households and is representative\n\n\nat the national level, urban and rural areas, the country’s capital, Asunción, and the following departments:\n\n\nSan Pedro, Caaguazú, Itapúa, Alto Paraná, and Central. The EPH surveys 5,099 households and is\n\n\nrepresentative at the national level, urban and rural areas, and Asunción, and the following departments:\n\n\nSan Pedro, Caaguazú, Itapúa, Alto Paraná, Central, and a group assigned as “others” that agglomerates the\n\n\nrest of the deparments in the country. The EPH survey contains information on unemployment, income,\n\n\nand the main demographic characteristics of the household that allow measurement of household welfare\n\n\nin Paraguay.\n\n\nIn order to construct market income and disposable income (see\n\n\n) following the CEQ approach, we use income and demographic information from\n\n\nthe EPH. However, as", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000898", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "household survey", "probe_tag": "confusion", "probe_score": 0.7077391743659973, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 590, "end": 606, "key": "prwp:000898:14:0:1", "source": "camp2", "luna_reason": "Household survey data are used to map price effects and calculate purchasing-power variation.", "usage_type": "declaration", "specificity": "vague"}]}
+{"text": " made 11 key findings._\n\n\n1. Refugees have similar access to mobile networks as the global population. However, when we look\nat the urban and rural split, rural refugees have less access to connectivity and are often overlooked\nin connectivity initiatives.\n\n\nGiven that developing countries today host more than 80 per cent of the world’s refugees, the\nperception has arisen that a large part of the world’s refugee population must live in areas not well\ncovered by mobile networks. UNHCR’s research has determined that this is not the case. Using the\nmost recent data, UNHCR has found that 93 <sup>2</sup> [^2: Affordability constraints – the most significant hurdle to overcome in connecting refugees – cause\naverage phone ownership and internet access for refugee households to be much lower than for\nglobal households.] per cent of all refugees live in places that are covered\nby at least a 2G network, and that 62 per cent live in locations covered by 3G networks.\n\n\nHowever, there are large differences in the availability of mobile networks when the urban and rural\ndata are examined separately. Unsurprisingly, urban areas tend to have better coverage. Ninety per\ncent of refugees living in urban areas are covered by 3G networks, similar to the proportion of global\nurban population living in 3G areas (89 per cent).\n\n**Refugees vs. Global Population:**\n**Mobile Network Coverage**\n\n100%\n\n\n\n80%\n\n\n60%\n\n\n40%\n\n\n20%\n\n\n0%\n\n\n\nRefugees* Global\n\nPop**\n\n\n\n\n\nownership\n\n\n\n\n\n\n\n**Global Household**\n**Phone Ownership**\n\n\n\n\n\nFigure 10: Refugee\n\n\n\nversus global\nhousehold phone\n\n\n\n**Refugee Household**\n\n\n\n\n\n\n\n\n\n\n\n\n\nRefugees* Global\n\nPop**\n\n\n\nRefugees* Global\n\nPop**\n\n\n\n\n### **VS.**\n\n\n\nRural Urban Total\n\n3G 2G No Coverage\n\n\nIn rural areas, while coverage and quality is progressively improving thanks to increasing mobile\nnetwork penetration, refugees risk being overlooked in these expansion plans. For instance, only\n17 per cent of rural refugees live", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000123", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "urban and rural\ndata", "probe_tag": "confusion", "probe_score": 0.527599573135376, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1057, "end": 1077, "key": "reliefweb:000123:6:1:0", "source": "camp2", "luna_reason": "Urban and rural data are analyzed to establish coverage differences.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "communities and schools. The ECEEP, therefore, i s designed to lay the ‘groundwork’ for\nextensive reforms at the ECE level (with significant impacts expected also at the primary\nlevel) and build on the innovative and successful models o f education provision implemented\nin Egypt and in the region and on the strengths and comparative advantages of the specific\ndevelopment partners (World Bank, CIDA, and WFP).\n\n\n16. The proposed project supports the Bank’s strategy in Egypt. Key objectives o f the Egypt\nCountry Assistance Strategy (CAS, June 2001) are the reduction  - f poverty and\nunemployment through: (i) upgrading human capital; (ii) removing obstacles to private sector\ndevelopment; and (iii) addressing critical policy issues o f agriculture development and water\nresource management. The proposed project directly supports the attainment  - f the first\nobjective (upgrading human capital) through the provision o f ECE programs o f adequate\nquality. The proposed project is also consistent with the MENA Regional Strategy (2002),\nwhich includes ‘education’ as one  - f the focus areas. The project builds on the\nrecommendations  - f the ECE Strategic Options paper (2002) prepared by the World Bank\n\nand endorsed by the GOE.\n\n\n17. The ECEEP has been prepared in a participatory manner with the MOE as well as CIDA and\nWFP and is also jointly financed. In this project the World Bank is leveraging about US$90\nmillion o f Government and donor funds with US$20 million o f Bank loan.\n\n\n**B.** **PROJECT DESCRIPTION**\n**1.** **Lending instrument**\nSpecific Investment Loan (SIL)\n\n\n**Project Financing Data**\n\n**[XI Loan** [ **]Credit** [ **] Grant** [ **] Guarantee** [ **]Other:**\n\n\n\n**Commitment fee:** 0.85", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000040", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Project Financing Data", "probe_tag": "confusion", "probe_score": 0.13256356120109558, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1592, "end": 1614, "key": "refugee_pads:000040:9:0:0", "source": "camp2", "luna_reason": "Standalone table header, not a substantive data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " Grade Six, as determined by the primary\nschool, allows one to enter upon lower secondary education ( _enseignement moyen_ ), which consists of four years.\nCompletion of basic education is certified with the _Brevet d’Etudes Fondamentales_ (BEF), which is granted upon successful\ncompletion of examinations. In 2019/2020, about 39 percent of primary schools were community schools, established\nand managed by the community <sup>5</sup> [^5: 46 percent were public schools and 15 percent private (Statistics Education Yearbook 2019-2010)] . While the primary school system is officially bilingual, only 7 percent of students were\nenrolled in bilingual schools. The main language of instruction is French for 87 percent of students and Arab for 6 percent.\nMulti grade teaching is common, with 40 percent of teachers in a classroom teaching two or more grades.\n\n\n7. **The school population is mostly composed of primary-school children, of which about 63 percent are at the**\n**appropriate age** . According to the Fourth Household Living Standards Measurement Survey ( _Enquête sur la_\n_Consommation des ménages et le le Secteur Informel au Tchad_  - ECOSIT IV), roughly three-quarters (75 percent) of inschool children were enrolled in primary school in 2018, followed respectively by those enrolled in lower secondary (15\npercent), upper secondary (6 percent), University (2 percent) and pre-primary ( 1 percent). The distribution of students\nby age group within school levels shows that a meaningful number of them were not enrolled at the appropriate age. As\nshown in Graph 1, the proportion of students enrolled at the right level of education decreases as one 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", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Household Living Standards Measurement Survey", "probe_tag": "confusion", "probe_score": 0.8336538076400757, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1019, "end": 1064, "key": "jdc_operational:000009:3:1:0", "source": "camp2", "luna_reason": "ECOSIT IV survey supplies enrollment figures for 2018.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "A counterpart shortfall meant the project could not complete implementation/roll out of the\nconsultancies/studies financed under component 1, so $6.3 million remained uncommitted. SDR 2.08\n($2.94 million) of this was reallocated to KCC. The rest was cancelled. Disbursements from GOU were\nlower than expected due to this cancellation.\n\n\n**6. Sustainability**\n\n\n_6.1_ _Rationale for sustainability rating:_\nLikely\n\n\nIn the design phase, the teams took care to maximize sustainability of the system being tested, by building\nin the following: (i) efforts to enhance the local revenue base; (ii) affordability of investments; (iii)\nstakeholder participation; (iv) per capita investment level within government’s fiscal potential; (v) LG and\ncommunity responsibility for development and O&M costs; and (vi) charge of user fees. These contributed\nto the likely sustainability of the main project results, namely the decentralized 'system' that included the\ngrants and the capacity improvements in LGs. However, one element of the system, namely the ability to\nraise local revenues necessary for the O&M of local infrastructure investments proved a consistent\nchallenge and remains an obstacle to sustainability of the local investment rather the system itself.\n\nThe fiscal impact of LGDP was 3% of the national budget so did not pose much risk to macro\nsustainability. At its peak LGDP would only finance 7% of the development budget. On the other hand,\nthe LGDP funds were spent in line with national sectoral priorities, reinforcing the intended expenditure\npattern under the PEAP. There were sustainable improvements in capacity and understanding by LGs of\ntheir roles and responsibilities, particularly in planning, budgeting and financial management, as evidenced\nby the Annual Assessments and Audits. This also demonstrates improved capacity in the MoLG. The\nmajor instruments for monitoring LG performance were initiated under LGDP I and integrated more\nstrongly into mainstream", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017863", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Annual Assessments and Audits", "probe_tag": "confusion", "probe_score": 0.44966477155685425, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1771, "end": 1800, "key": "fcv_pads_east_africa:017863:17:0:0", "source": "camp2", "luna_reason": "Assessments and audits provide evidence of improved local-government capacity.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "stayed.\n\n\nOur objective is to identify the factors that facilitated or hampered the return of\n\n\nthese refugees. However, an inherent challenge in the literature on conflict and forced\n\n\nmigration is the absence of a complete longitudinal data set for conditions in countries\n\n\nof asylum and origin that can be mapped onto refugee characteristics. Establishing\n\n\ncausality is even more challenging. We make progress on the first part by combin\n\ning different sources and types of data. For demographic characteristics of refugees\n\n\nand their arrival and return information, we use administrative data from the Profile\n\n\nGlobal Registration System (ProGres) database of UNHCR. For the conditions faced\n\n\nby refugees in exile, we use vulnerability surveys conducted by UN agencies in Jordan\n\n\nand Lebanon, and complement these with a new household survey comprising similar\n\n\ndemographic and socioeconomic modules but also including vignettes about the drivers\n\n\nof return. Finally, for conditions in Syria, we have compiled a novel monthly conflict\n\n\nevents data set to use along with nighttime light emissions data that proxies access to\n\n\nutilities.\n\n\nThese sources are utilized in two different but complementary ways. First, we exploit\n\n\nthe temporal and spatial variation of the nightlights and conflict events series to build a\n\n\nsub-district-month panel for conditions inside Syria. This is used to analyze the impact\n\n\nof changes in conflict and luminosity patterns on return in an aggregate manner using\n\n\nordinary least squares (OLS) and Poisson quasi maximum likelihood (PQML) count\n\n\nmodels. Second, we use the detailed information on refugee characteristics provided by\n\n\nProGres together with conditions in countries of asylum, <sup>4</sup> to analyze individual return\n\n\ndecisions. Given that we have arrival and - where applicable - return dates for each\n\n\nrefugee, we can study their likelihood of return for a given month using both discrete\n\n\n4Since the conditions in countries of asylum are only captured for a small sample of registered\nrefugees in Lebanon and Jordan, we approximate host country conditions with district averages for\nthe full sample.\n\n\n3", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002426", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "nighttime light emissions data", "probe_tag": "confusion", "probe_score": 0.823226273059845, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1083, "end": 1113, "key": "prwp:002426:4:0:5", "source": "camp2", "luna_reason": "Existing nightlight data proxy utility access and supports panel analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " encuestados en el HFS2 que indicaron haber tenido\n\nque trabajar a cambio de alojamiento; y la cantidad de personas encuestadas que indicó haber tenido\n\nque mudarse a un apartamento o vivienda más económica aumento 7% con respecto a los resultados\n\nobtenidos en los ejercicios HFS1 y HFS2.\n\n\nDentro de las nacionalidades que recurrieron con mayor proporción a los mecanismos de\n\nafrontamiento para la situación de vivienda se puede mencionar que 48% de los hogares de\n\nnacionalidad nicaragüense y salvadoreña indicaron no haber podido pagar la renta por varios meses,\n\n44% los de nacionalidad venezolana y colombiana. 34% de los hogares de nacionalidad nicaragüense\n\ny salvadoreña señalaron haber tenido que trabajar a cambio de alojamiento, seguido por 30% de\n\nhogares de nacionalidad colombiana y 26% de nacionalidad venezolana.\n\n\nDentro de las principales medidas consideradas para hacer frente a la situación de vivienda por los\n\nhogares encuestados se puede señalar que algunas familias tomaron varias opciones. Así, un 67%\n\nindicó haber establecido acuerdos, ya sean formales o informales, con el arrendador; 53% indicó\n\n\nUNHCR / Febrero 2022 30", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001181", "page": 28, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "HFS2", "probe_tag": "confusion", "probe_score": 0.26230964064598083, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 19, "end": 23, "key": "reliefweb:001181:28:1:0", "source": "camp2", "luna_reason": "HFS2 respondents' reported housing coping outcomes are used as findings.", "usage_type": "evidential", "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": "26.|A draft National report on the findings of the National Survey was done. The report is<br>awaiting presentation to senior management for validation in this financial year 2025/2026.|A draft National report on the findings of the National Survey was done. The report is<br>awaiting presentation to senior management for validation in this financial year 2025/2026.|A draft National report on the findings of the National Survey was done. The report is<br>awaiting presentation to senior management for validation in this financial year 2025/2026.|A draft National report on the findings of the National Survey was done. The report is<br>awaiting presentation to senior management for validation in this financial year 2025/2026.|\n|New classrooms constructed<br>in existing schools as per the<br>needs-based school<br>infrastructure investment<br>plan (Number)|0|Jan/2022|26,726|05-Dec-2025|||13,400|Dec/2029|\n|New classrooms constructed<br>in existing schools as per the<br>needs-based school<br>infrastructure investment<br>plan (Number)|Comments on<br>achieving  targets|Comments on<br>achieving  targets|A total of 26,726 classrooms (cumulative) have been constructed. 12,085 classrooms were<br>constructed during the reporting period of Nov-Dec 2024.|A total of 26,726 classrooms (cumulative) have been constructed. 12,085 classrooms were<br>constructed during the reporting period of Nov-Dec 2024.|A total of 26,726 classrooms (cumulative) have been constructed. 12,085 classrooms were<br>constructed during the reporting period of Nov-Dec 2024.|A total of 26,726 classrooms (cumulative) have been constructed. 12,085 classrooms", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005625", "page": 24, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "National Survey", "probe_tag": "confusion", "probe_score": 0.5470954775810242, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 51, "end": 66, "key": "fcv_pads_east_africa:005625:24:1:0", "source": "camp2", "luna_reason": "Survey findings are used in a draft national report.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": " propose the use of survey data to measure preharvest losses in crop production. However, there is yet scant evidence applying the method for\nmicro-level loss measurement and a need for refinement to make full use of a variety of data\nsources including agricultural household survey data and geospatial data (FAO, 2018). This paper\nconducts a thorough descriptive assessment of the suitability of existing survey data to measure\npre-harvest production losses of annual crops in LMICs at the micro-level. For this, it draws on a\ndiverse set of data sources, rich plot-level data on harvest, inputs and different losses proxies along\nwith household- and community-level data from the Living Standards Measurement Study –\nIntegrated Surveys on Agriculture (LSMS-ISA), geospatial data, as well as experimental data from\ncrop cut and survey experiments, in three SSA countries.\n\nThe paper’s approach is guided by a set of six distinct questions that we attempt to empirically test\nand mold into concrete recommendations for survey design and measurement. These questions fit\ninto two broad issues for the measurement of disaster crop losses, the **quantification** of losses (i.e.\n\n\n2 Authors’ calculations based on (FAO et al., 2020; Our World In Data, no date; World Bank, no date)\n3 Throughout this paper, we follow the definitions employed in (FAO, 2021, pp. 198–200):\n“Disaster: A serious disruption of the functioning of a community or a society at any scale due to hazardous events\ninteracting with conditions of exposure, vulnerability and capacity, leading to one or more of the following: human,\nmaterial, economic and environmental loss and impacts (UNDRR Terminology).”\n“Damage: The monetary value of total or partial destruction of physical assets and infrastructure in disaster-affected\nareas, expressed as replacement and/or repair costs.” In agriculture, this comprises, for example, the destruction of\nstored agricultural inputs", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001848", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "agricultural household survey data", "probe_tag": "confusion", "probe_score": 0.26739826798439026, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 253, "end": 287, "key": "prwp:001848:3:1:0", "source": "camp2", "luna_reason": "Generic survey-data mention lacks an attributed finding or concrete analytical use.", "drop_reason": "bare_stat", "specificity": "descriptive"}]}
+{"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:010810", "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:010810:65:0:0", "source": "camp2", "luna_reason": "States epidemiological data are unavailable without citing or using existing data.", "drop_reason": "availability", "specificity": "descriptive"}]}
+{"text": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\nWithdrawal Application.\n\n\n   - Withdrawal Applications submitted to the Bank will be prepared separately by MoITS, final\nauthorization and signatures sits with MOPIC before submission to the Bank. Project expenditures\nwill be documented through IFRs;\n\n   - MoITS will have the sole responsibility to disburse on behalf of the project to suppliers, contractors,\nand consultants. Additionally, MoITS will maintain a monthly reconciliation statement between their\nrecords and the Bank’s records per the World Bank’s Client Connection. Such reconciliation will set\nout the disbursements by category as well as the DA balance. Disbursement and payment requests\nwill be based on approved contracts and services predefined in the project documents;\n\n   - DAs bank account records will be reconciled with bank statements on a monthly basis by the MoITS\nA copy of each bank reconciliation statement together with a copy of the relevant bank statement\nwill be reviewed monthly by the project’s Financial Officer at MoITS, who will investigate and resolve\nany identified differences. Detailed banking arrangements, including control procedures over all\nbank transactions (for example, check signatories, transfers, and so on), are documented in the\nFinancial Section of the POM **.**\n\n**Flow of Funds for each component**\n\n\nPage 50 of 54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 54, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "DAs bank account records", "probe_tag": "confusion", "probe_score": 0.2834671437740326, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 811, "end": 835, "key": "jdc_operational:000024:54:0:0", "source": "camp2", "luna_reason": "Routine financial reconciliation records used for project administration.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
+{"text": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000097", "page": 51, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "multi-level data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1720, "end": 1736, "key": "refugee_pads:000097:51:0:0", "source": "camp2", "luna_reason": "Planned project reporting of data is future activity, not existing data use.", "drop_reason": "promissory", "specificity": "vague"}]}