diff --git "a/annotate_rafael.jsonl" "b/annotate_rafael.jsonl"
--- "a/annotate_rafael.jsonl"
+++ "b/annotate_rafael.jsonl"
@@ -1,240 +1,240 @@
-{"text": "**The World Bank**\nKenya Inclusive Growth and Fiscal Management DPO 2 (P172321)\n\n\n**PDO3/Pillar 3: Create Fiscal Space and Crowd in the Private Sector to Advance the Government’s Inclusive**\n**Growth Agenda**\n\nDPO1: PA7 & PA8. DPO2: PA5, PA6, & PA7\n\n26. Under DPO1 PA7, value added tax (VAT) exemptions were rationalized through the passage by\nParliament of the Finance Act 2018, which contained a provision for the removal of VAT exemptions on\npetroleum products and through the adoption of a governance framework that limited the number of tax\nexemptions that were granted to arrest the decline in VAT tax revenues. Under DPO2, PA5 an additional\nmeasure to reverse the decline in tax revenues was promoted by the Cabinet approving for submission to\nParliament the Income tax bill 2019 that also limited the number of tax income exemptions.\n\n27. DPO1 PA8 addressed corruption issues by establishing procedures for the investigation of collusive\nbehavior in public procurement bids. It also provided for the verification and reconciliation of external debt\nrecords in order to improve the accuracy of Kenya’s electronic debt registry. DPO2 PA6 increased the\ntransparency of public procurement through publishing online, details of contracts and tenders, including\ntender documents. It also would publish details of companies that had been awarded tenders as well as the\nnames of the directors of the companies. The Cabinet also approved under this PA new regulations that\nallowed for standard bidding documents to be revised in order to provide greater details on bidders.\nParliament also enacted the Competition Amendment Act that included penalties for collusive behavior with\nrespect to public procurement. DPO2 PA7 contained a provision for Cabinet approval of the Debt and\nBorrowing Policy that allowed for the Central Bank to launch the Treasury Mobile Direct System which\nprovided for institutional and retail investors to participate through an electronic online platform in the\nissuance of government securities that would enhance the transparency", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000459", "page": 18, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "external debt\nrecords", "probe_tag": "confusion", "probe_score": 0.183, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1043, "end": 1064, "key": "sample:fcv_pads_east_africa:000459:18:0:0", "source": "gold", "luna_reason": "Financial debt records are reconciled for registry accuracy, constituting routine bookkeeping.", "drop_reason": "bookkeeping", "specificity": "descriptive"}, {"text": "electronic debt registry", "probe_tag": "drop", "probe_score": 0.0169, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1109, "end": 1133, "key": "sample:fcv_pads_east_africa:000459:18:0:1", "source": "gold", "luna_reason": null}]}
 {"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": " Polish women.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 29. Effect of a 1 pp. change in employment share of Ukrainian refugees on gross wage change**\nCross-section model of all 380 poviats in 2023. Results are statistically significant at a 0.01 level.\n\n\n200\n\n\n150\n\n\n100\n\n\n50\n\n\n0\n\nOLS IV (pupils) IV (2019) IV (both)\n\nSource: Deloitte own elaboration based on GUS and ZUS data, as well as data for instrumental variables from Public Employment Services Portal and Open Data\ngovernmental portal. OLS is the standard Ordinary Least Squares model, IV are Instrumental Variables Two Stage Least Squares models with instrumental variables of\nthe share of Ukrainian pupils in Polish schools, distribution of Ukrainians from declarations on entrusting work to a foreigner in Poland in 2019, or both. For details see\nthe Online Technical Appendix.\n\n\n\nFurthermore, consistent with a positive\nproductivity shock, Polish citizens have\nbeen moving to better-paid occupations –\nas predicted by the theory of occupational\nupgrading (e.g., Beerli and Peri, 2018; Foged\nand Peri, 2016; Peri and Sparber, 2009).\nDeloitte has acquired quarterly data on\nthe occupational groups of Polish citizens\nwho are insured with ZUS from Q1 2022 to\nQ2 2024. This data is not exhaustive as ZUS\nonly began requiring such information in\n\n\n\ntowards higher-paid occupational groups.\nThe share of Poles in the two lowest\nsalary brackets (earning less than gross\nPLN 4,000 and PLN 4,000-6,000 in 2022)\ndecreased by 0.4 and 1.8 percentage\npoints, respectively, while the subsequent\nhigher salary brackets increased by\n1.4 pp. (PLN 6,000-8,000), 0.6 pp.\n(PLN 8,000-10,000), and 0.3 pp. (above\nPLN 10,000) (see", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "GUS", "probe_tag": "drop", "probe_score": 0.0061, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 405, "end": 408, "key": "sample:jad_paddy_docs:000001:20:1:0", "source": "gold", "luna_reason": null}, {"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.969, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 413, "end": 421, "key": "sample:jad_paddy_docs:000001:20:1:1", "source": "gold", "luna_reason": null}, {"text": "data for instrumental variables", "probe_tag": "confusion", "probe_score": 0.8616, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 434, "end": 465, "key": "sample:jad_paddy_docs:000001:20:1:2", "source": "gold", "luna_reason": "Data from named portals supports the chart's instrumental-variable analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " the economy. It provides information\non the total impact of shocks on various\naspects of the economy, including the\nlabour market, government revenue, as\nwell as key economic aggregates. It is the\nmost appropriate tool for accounting for\nthe multi-layered impact of Ukrainian\nrefugees. A counterfactual analysis was\nperformed using the latest data on the\nPolish economy to account for the effects\nof other shocks in the economy. The model\nenabled a counterfactual analysis to be\nconducted by isolating the refugee influx\nfrom all other economic shocks, e.g. the\nother macroeconomic consequences of the\nwar in Ukraine. The results were calculated\nfor 2022, 2023 and 2024 with an additional\nlong-term analysis up to 2030 to assess the\neconomy’s long-term adaptation (assuming\nno new shocks, including no countershocks <sup>34</sup> [^34: E.g. refugees keep having lower productivity rather than adapt to level of natives.] ).\n\n\n32 <u>Economics of climate change | Deloitte Australia</u>\n\n\n\n**Chart 32. Average weekly hours in main job**\n\nWomen in 15-64 age group\n\n\n\n68.4%\n\n\n2023-Q2\n\n\n\n68.8%\n\n\n2024-Q2\n\n\n\n2021-Q2\n\n\n\n67.5%\n\n\n2022-Q2\n\n\n\n40.3\n\n\n\n40.3\n\n\n\n40.4\n\n\n\n40.4\n\n\n\n\n\n\n\n\n\n\n\nSource: Deloitte own elaboration based of Eurostat\ndata (Labour Force Survey).\n\n\n\nSource: Deloitte own elaboration based of Eurostat\ndata (Labour Force Survey).\n\n\n\nPart-time\n\nFull-time\n\n\n\n31 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.\n\n\n42\n\n\n\n33 <u>https://www2.deloitte.com/pl/pl/pages/risk/solutions/analiza-ryzyk-klimatycznych-badanie-scenariuszy-z-modelem-DClimate.html34</u>\n\n34 E.g. refugees keep having", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 21, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data on the\nPolish economy", "probe_tag": "confusion", "probe_score": 0.4794, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 344, "end": 370, "key": "sample:jad_paddy_docs:000001:21:2:0", "source": "gold", "luna_reason": null}, {"text": "Eurostat\ndata", "probe_tag": "drop", "probe_score": 0.006, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1215, "end": 1228, "key": "sample:jad_paddy_docs:000001:21:2:1", "source": "gold", "luna_reason": null}, {"text": "Labour Force Survey", "probe_tag": "keep", "probe_score": 0.9867, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1230, "end": 1249, "key": "sample:jad_paddy_docs:000001:21:2:2", "source": "gold", "luna_reason": "Eurostat survey data underlie the chart’s reported employment figures.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " of workers – mostly made up\nof the youngest refugees who might not\nhave worked back in Ukraine. Employment\nin one’s pre-displacement sector appears\nto boost the median net wage by about\n6%, when compared to those who switch\nfields – a back-of-the-envelope calculation\nputs their median net earnings at 89% of\nthe overall median. However, this likely\noverstates the true effect of staying in the\nsame sector, since the higher-paid groups\n(for example, the majority of IT specialists)\n\n\n\nwere more likely to remain in their original\nindustry.\n\n\n**Highly skilled Ukrainian refugees**\n**are likely to suffer from significant**\n**downgrading.** With the median wages\nof Ukrainian refugees estimated at 84%\n(SEIS survey) or 80% (NBP 2024 survey)\nof the national median (see chapter 2),\nthe difference for average wages may be\neven larger. This is because medians are\ninsensitive to high earners who typically\ninflate average earnings. Such high earners\nmay suffer significant downgrading\nconsidering the unfavourable occupational\nstructure of Ukrainian refugees. There are\nmany reasons to this, from occupational\nlicensing to a high level of language fluency\nrequired by high-skill jobs. <sup>28</sup> [^28: Lessem and Sanders (2020) modelled immigrant wage growth in the United States, finding that in a counterfactual model eliminating barriers to occupational entry\nwould lead to only small earnings increase for the average immigrant, but a substantial increase for the most highly skilled.]\n\n\n\nUkrainian\n\nrefugees\n\n\n\n\n\n\n\n\n\n\n\n\n\nPre-war\nUkrainians\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nOther\nforeigners\n\n\n\nPolish\ncitizens\n\n\n\nDrivers (truck, bus)\n\n\nTeachers\n\n\nMedical professions\n(physician, dentist, nurse, midwife)\n\n\nLegal professions\n(legal counsel, barrister, notary, bailiff)\n\n\nTaxi drivers\n\n\nOthers\n\n\nSource: Deloitte own elaboration based on ZUS data\non June 30th 2024.\n\n\n\n26 As described in chapter 2, SEIS measures incomes on the household level. Using it to estimate individual wages likely underrepresents lowest and highest incomes.\nDetails are available in the Online Technical Appendix.\n\n27 Note that the GUS (2024) data for", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "SEIS survey", "probe_tag": "confusion", "probe_score": 0.5162, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 703, "end": 714, "key": "sample:jad_paddy_docs:000001:14:3:0", "source": "gold", "luna_reason": null}, {"text": "NBP 2024 survey", "probe_tag": "confusion", "probe_score": 0.8219, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 724, "end": 739, "key": "sample:jad_paddy_docs:000001:14:3:1", "source": "gold", "luna_reason": null}, {"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.9997, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1825, "end": 1833, "key": "sample:jad_paddy_docs:000001:14:3:2", "source": "gold", "luna_reason": null}, {"text": "SEIS", "probe_tag": "drop", "probe_score": 0.0004, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1886, "end": 1890, "key": "sample:jad_paddy_docs:000001:14:3:3", "source": "gold", "luna_reason": null}]}
-{"text": " earned by Ukrainian refugees than\n\n\n\nthe general population. UNHCR (2025b),\nusing a different method than the one in\nthis report, estimated average instead\nof median net wages based on the SEIS\ndata. The average net wage of a Ukrainian\nrefugee they arrived at was PLN 4,214, only\nslightly higher than calculated above. This\nwould yield 72% of the national average net\nwage. <sup>15</sup> Average is not used here, because\nmedian is more relevant for discussing\neconomic impact, as it is not disrupted\nby bottom or top earnings. Furthermore,\nthere are no outside estimates to compare\nit to. Second, as discussed previously, there\nare much fewer Ukrainian refugees with\nemployment contracts than Poles, and\nthis lowers their social contributions and\nthus gross earnings. Unfortunately, there\nis no such data available, as both SEIS and\nNBP (2024) measure only net earnings.\n\n\n\n**Chart 13. Polish citizens and Ukrainian refugees’ employment rates by age group**\n\n\nMale Female\n\n\n\n**Chart 14. Ukrainian refugee median net wage estimates in Q2 2024**\n\n\nMonthly net wage (PLN) Percengate of all workers total economy average\n\n\n84%\n\n\nUNHCR NBP UNHCR NBP\n15 May - 24 June 2024 6 May - 5 July 2024 15 May - 24 June 2024 6 May - 5 July 2024\n\n\nSource: Deloitte own elaboration based on SEIS survey, NBP (2024) survey. Monthly GUS median wage in the general economy has been recalculated to reflect the\nspecific time periods of SEIS UNHCR and NBP (2024) surveys.\n\n\n\nSource: Deloitte own elaboration based on Eurostat Labour Force Survey data SEIS UNHCR survey\nconducted in May and June 2024. For Polish citizens reference period is Q2 2024.\n\n\n\nPolish citizens Ukrainian refugees\n\n\n\n**The wages of Ukrainian refugees are**\n**higher for men than women, but the**\n**gap is not wider than in the economy**\n*", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 9, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "SEIS\ndata", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 190, "end": 199, "key": "sample:jad_paddy_docs:000001:9:2:0", "source": "gold", "luna_reason": null}, {"text": "SEIS", "probe_tag": "drop", "probe_score": 0.001, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 826, "end": 830, "key": "sample:jad_paddy_docs:000001:9:2:1", "source": "gold", "luna_reason": "Named survey supports the statement that gross-earnings data are unavailable.", "usage_type": "declaration", "specificity": "named"}, {"text": "SEIS survey", "probe_tag": "keep", "probe_score": 0.999, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1275, "end": 1286, "key": "sample:jad_paddy_docs:000001:9:2:2", "source": "gold", "luna_reason": null}, {"text": "NBP (2024) survey", "probe_tag": "confusion", "probe_score": 0.8582, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1288, "end": 1305, "key": "sample:jad_paddy_docs:000001:9:2:3", "source": "gold", "luna_reason": null}, {"text": "Eurostat Labour Force Survey data", "probe_tag": "keep", "probe_score": 0.9804, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1496, "end": 1529, "key": "sample:jad_paddy_docs:000001:9:2:4", "source": "gold", "luna_reason": "Eurostat survey data source an employment-rate comparison and chart.", "usage_type": "evidential", "specificity": "named"}, {"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9549, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1530, "end": 1547, "key": "sample:jad_paddy_docs:000001:9:2:5", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\nTo address price risks and monitor access to affordable bread, the project will finance third-party monitoring agency\n(TPMA), such as mobilization of Red Cross Volunteers with the Lebanese Red Cross/International Federation of Red Cross\nand Red Crescent Societies at community level/downstream. The TPMA will facilitate price data collection for flour at the\nmill, for bread at the bakeries, and for bread at retail outlets, on a weekly basis and for a sample of outlets across all\ngovernorates. At the same time, the project will finance high frequency ‘Listening to Poor and Vulnerable Household\nSurveys’, entailing data collection on bread prices and consumption for the poor and vulnerable households, by\nconducting random sampling and surveying (biweekly) using UNHCR and WFP beneficiary lists. This information will be\ntriangulated at MOET level with information consolidated from the consumer protection agency, GM, and WFP price\nmonitoring system, and used to adopt appropriate remedies, such as activating the preferential distribution clause\nforeseen in the Framework Agreement, for bakeries in areas where most of the poor and vulnerable groups are located.\nAll monitoring reports will be published on Central Inspection’s IMPACT online platform.\n\n35. **The component will also support consultancy services and technical assistance that will strengthen MOET’s**\n**oversight function as well as capacity** **to manage the gradual transition from the current wheat subsidy system to a**\n**more market-oriented system** . This will include developing a better price monitoring and data system (both for wheat\nand bread); developing an implementation plan for gradually removing wheat subsidies and bread prices and potentially\nincreasing importers’ financial participation in wheat import purchases, to be informed by the complementary activities\ndescribed below; conducting an adequate stakeholder outreach and communication about these reforms; and\nstrengthening regional cooperation around food security and risk management in the", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Listening to Poor and Vulnerable Household\nSurveys", "probe_tag": "confusion", "probe_score": 0.1039, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 635, "end": 685, "key": "sample:jdc_operational:000019:21:0:0", "source": "gold", "luna_reason": null}, {"text": "UNHCR and WFP beneficiary lists", "probe_tag": "keep", "probe_score": 0.9488, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 847, "end": 878, "key": "sample:jdc_operational:000019:21:0:1", "source": "gold", "luna_reason": "Existing beneficiary lists are used to draw a random survey sample.", "usage_type": "declaration", "specificity": "named"}, {"text": "WFP price\nmonitoring system", "probe_tag": "confusion", "probe_score": 0.5167, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1007, "end": 1034, "key": "sample:jdc_operational:000019:21:0:2", "source": "gold", "luna_reason": null}, {"text": "price monitoring and data system", "probe_tag": "drop", "probe_score": 0.0244, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1648, "end": 1680, "key": "sample:jdc_operational:000019:21:0:3", "source": "gold", "luna_reason": null}]}
-{"text": " the NRs and the respective\ndistrict, municipal and local authorities manage the secondary network.\n\n15. **Only 3.3 percent of the road network is paved; 52 percent are gravel roads and another about 45**\n**percent are earthen roads, which do not provide all-weather connectivity and are difficult to maintain.**\nOnly about 100-400 km of gravel NRs are being upgraded every year to paved roads. Some of the river\ncrossings on NRs do not have bridges and traffic movement on these highways is dependent on the ferry\ncrossings, which operate for only few hours in a day.\n\n\n16. **The road network is prone to disruption by floods, is not resilient, and has only few redundancies** <sup>**26**</sup> [^26: Redundancies are alternate routes] **but**\n**uncertainty about the future and limited resources make it difficult to plan robust mitigating measures.**\nUganda is exposed to a variety of natural hazards (droughts, flooding, landslides, heat waves). Each year,\nfloods impact nearly 50,000 people and over US$62 million in GDP. Uganda experiences both flash floods\nand slow-onset floods. Areas most prone to floods are the capital city, Kampala, and the northern and\neastern areas of the country.\n\n\n17. **According to UDHS, distance to health facilities in Uganda was reported as a serious problem to access**\n**health facilities and this is more acute in refugee-hosting districts in West Nile sub-region.** Mortality\nrate is still an issue in Uganda. Fertility and mortality rates, from the 2016 UDHS, forecasted that 2\npercent of women un Uganda would die from maternal causes at existing rates. Moreover, it is\ndocumented that health care services during pregnancy and childbirth and after delivery are important\nfor the survival and well-being of both the mother and infant. This situation worsens when roads are", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000001", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "UDHS", "probe_tag": "drop", "probe_score": 0.0457, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1217, "end": 1221, "key": "sample:jdc_operational:000001:7:1:0", "source": "gold", "luna_reason": null}, {"text": "2016 UDHS", "probe_tag": "keep", "probe_score": 0.9013, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1492, "end": 1501, "key": "sample:jdc_operational:000001:7:1:1", "source": "gold", "luna_reason": null}]}
+{"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": "they sought protection. However, government\nstatistics on first-time residence permits or other\nadministrative data sources in general do\nnot enable refugees, persons in a refugee-like\nsituation or persons with a refugee background\nto be identified unless they hold an asylum\nor humanitarian-related permit. <sup>13</sup> The figures\npresented in this report may therefore include\npeople who were admitted directly from one of\nthe seven countries of origin (Afghanistan, Eritrea,\nIran, Iraq, Somalia, Syria, Venezuela) and thus may\nnot have crossed an international border to meet\nthe definition of a refugee prior to arrival in an\nOECD country.\n\nGiven the high asylum recognition rates of\nnationals from the seven countries of origin\nconsidered (see Annex V for details), it can\nhowever be assumed that a large number of\nindividuals covered in this study would have a\nwell-founded refugee claim.\n\nFurther, this data collection exercise focuses\non first-time permits granted, excluding permit\nrenewals or status changes in the destination\ncountry to avoid double-counting individuals in\nthe data. Nevertheless, double-counting may\noccur in a few cases where the renewals and\nstatus changes could not be extracted from a\ncountry’s permit data (see Annex I for details).\nFurther, a few countries count native-born\n\n\n\nchildren of foreign nationals under the residence\npermit of their parents, although to our knowledge\nthis is not likely to lead to a large overestimation.\n\nThe definitional focus on first permits issued for\nentry into the host country excludes individuals\nwho obtain a visa or status regularization following\ntheir entry into the country—which is notably\nthe case for a large population of Venezuelans\nresiding in Chile and Colombia. Finally, while\ndata availability improves year to year, some\ngaps remain for specific country-year figures, but\nthese represent a relatively small percentage of\nundercoverage.\n\n\nThe figures in this report are based on the latest\navailable data in each reporting country. As a\nresult, some past figures have been", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000620", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "government\nstatistics on first-time residence permits", "probe_tag": "confusion", "probe_score": 0.7888, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 33, "end": 86, "key": "sample:reliefweb:000620:7:0:0", "source": "gold", "luna_reason": "Existing government statistics are discussed as a data source and limitation.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "administrative data sources", "probe_tag": "drop", "probe_score": 0.0163, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 96, "end": 123, "key": "sample:reliefweb:000620:7:0:1", "source": "gold", "luna_reason": null}, {"text": "permit data", "probe_tag": "keep", "probe_score": 0.9301, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1230, "end": 1241, "key": "sample:reliefweb:000620:7:0:2", "source": "gold", "luna_reason": null}]}
 {"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": " weaving, embroidery and clothes-making.\n\n\nScarce and poorly paid livelihood opportunities\nwere often indicated as having prompted further\nmigration. In FGDs both in Kabul and Mazar,\nreturnees explained that several male youth,\nmarried and unmarried, in their community had\ndecided to return to Pakistan soon after return\nbecause of extremely limited job opportunities.\nOne male returnee in Kabul estimated that around\n60% of male youth had returned to Pakistan.\nOther FGD participants added that they had male\nrelatives who were currently in Pakistan but “were\ntrying to go to Iran and even Europe”. In parallel,\nthe great majority of returnees stated that they\nwere receiving regular remittances from relatives\nabroad, including males that had returned to\nPakistan. This phenomenon is also captured in the\nreturnee monitoring report of November 2017. Due\nto lack of livelihood opportunities, 8% of the sample\n\n\n\n15", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000080", "page": 16, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "FGDs", "probe_tag": "drop", "probe_score": 0.0001, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 153, "end": 157, "key": "sample:reliefweb:000080:16:2:0", "source": "gold", "luna_reason": null}, {"text": "returnee monitoring report", "probe_tag": "confusion", "probe_score": 0.1948, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 808, "end": 834, "key": "sample:reliefweb:000080:16:2:1", "source": "gold", "luna_reason": null}]}
 {"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 ��frica 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": "**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": "**9.** **CONCLUSION AND RECOMMENDATIONS**\n\n\nThe Environment Impact Assessment for Augmentation and Rehabilitation of Gatanga\nWater Supply identified that the population pressure of Gatanga district is growing at a\nsteady 2.426% per annun form the population statistics form the census report 2009 now\nstanding at 130,000 people. The current water infrastructure can only provide 6,310\nm3/day against an estimated demand of 9880m3/day leaving a deficit of 3,570m3/day.\nThe proposed project is step towards providing water close to the people of Gatanga\ndistrict.\n\nNegative environmental impacts identified in the report can be mitigated as illustrated in\nthe Environmental Management Plan and proper monitoring throughout construction and\noperation phases of the project is advised.\n\nThere is overwhelming acceptance by the project by the local community in the areas of\nGitemi, Ndakaini, Gitiri, Gatur, Gathaithi, Rwagetha, Chomo and Gatanga sub locations.\nThe areas are experiencing inadequate water supply leaving residents with the option of\ngoing for raw water plants which is not treated therefore leaving them exposed to water\nborne diseases such as typhoid and diarrhea.\n\nRecommendation is therefore for implementation of the above project with compliance to\nrecommendations outlined in the Environment Management Plan and resident and other\nstakeholder views as described in chapter six of the report.", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020355", "page": 91, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "population statistics", "probe_tag": "keep", "probe_score": 0.9471859931945801, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 247, "end": 268, "key": "fcv_pads_east_africa:020355:91:0:0", "source": "camp2", "luna_reason": "Census statistics support the reported population growth estimate.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "census report 2009", "probe_tag": "keep", "probe_score": 0.9167974591255188, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 278, "end": 296, "key": "fcv_pads_east_africa:020355:91:0:1", "source": "camp2", "luna_reason": "2009 census report supports the stated population statistics and growth finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": ".\n\n**Relevance of Implementation** is rated as **high both before and after the restructuring.**\n\nThe overall relevance of objectives, design and implementation is assessed as **high.**\n\n**3.2 Achievement of Project Development Objectives (Efficacy)**\n\nProgress of the results indicators was notable both before and after the results framework\nwas revised for the Additional Financing in 2011. The appraisal mission for PBS II\nAdditional Financing undertook a comprehensive review of the PBS program\nperformance and in terms of progress towards Development Objectives and\nImplementation Progress, PBS II was rated Satisfactory.\n\nMeasured in terms of meeting its results indicators before the Additional Financing, the\nPBS Program, while not exceptional, was progressing relatively well. This was evidenced\nby data in the project ISR before the AF, and the accompanying mission documentation.\nFor example, in education the Net Enrollment Rate for children in primary school\nincreased from 79 percent to 87.9 percent between FY07 and FY10, which represents an\nincrease of almost 1.5 million additional children attending school. The ratio of primary\nhealth workers to population at the time (beginning of 2011) reached 1:2,500 from\n1:4,369 three years earlier. Similarly, in agriculture, the number of development agents\nproviding technical advice to small-scale farmers has risen from about 50,000 in FY08 to\n63,000 in FY10, an increase of 26 percent. For water, 65.8 percent of the rural population\nhad access to potable water in FY10, which represented a substantial improvement over\nthe baseline in FY07, where 46 percent had access. Finally, there was improved\n\n\n15", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016413", "page": 30, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data in the project ISR", "probe_tag": "keep", "probe_score": 0.9403, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 809, "end": 832, "key": "sample:fcv_pads_east_africa:016413:30:1:0", "source": "gold", "luna_reason": null}]}
-{"text": ",000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and teachers. The state of shelter in many <sup>areas is one</sup> <sup>of</sup>\nthe factors constraining the return of government employees and the revitalization of district and local\neconomic activity. The agricultural sector is particularly important because it currently <sup>employs 75%</sup> <sup>of</sup>\nthe country's labor force. The 2000 Baseline Service Delivery Survey reported that between <sup>65%</sup> <sup>and</sup>\n85% of the population do not have access to safe drinking water and sanitation facilities. Recent\nestimates in the most neglected communities of the \"newly accessible areas\", such as Bombali, <sup>suggest</sup>\nthat access to potable water and adequate sanitation are as low as 5% and 3%, respectively.\n\n\n\nWidespread human rights abuses during the civil war included the forced recruitment of children\nas combatants, porters and sex slaves. In addition, tens of thousands of people continue to suffer <sup>from</sup>\nthe traumatic effects of amputation and other injuries, sexual violence, loss of parents, and the general\nstress of living through a civil war. This has greatly increased the need for a kind of <sup>social service</sup>\nsupport that was not as widely needed before the war, integrating traditional health services <sup>with</sup>\npsycho-social care, counselling, foster homes and disability programs. The challenges ahead <sup>will include</sup>\n\nthe provision of community-", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018073", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2000 Baseline Service Delivery Survey", "probe_tag": "keep", "probe_score": 0.9403358101844788, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 568, "end": 605, "key": "fcv_pads_east_africa:018073:9:1:0", "source": "camp2", "luna_reason": "Named survey reports concrete access rates for drinking water and sanitation.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " sourced from<br>presentation at April 2015 JRIS, which essentially represent MoE data.<br>iv. Computed multiplying number of primary teachers (Grade 1-8) by per cent of qualified teachers. The<br>statistical abstracts do not report the absolute number of qualified teachers.|Note: The targets are as per the revised results framework.<br>* The target figures for 2012-13 and 2013-14 as shown in the results framework are not consistent.<br>i. <br>Computed using GER data from Education Statistics Annual Abstract, 2013-14<br>ii. Computed dividing number of enrolled students at Grade 5-8 by total number of teacher at that grade. The<br>data are collected from Education Statistics Annual Abstract, 2013-14. The estimated figures are different<br>from the student-teacher ratios reported in the Annual Abstract and the presentations made at April 2015<br>JRIS.<br>iii. The per cent of qualified primary teachers (Grade 1-8) having diploma and above are sourced from<br>presentation at April 2015 JRIS, which essentially represent MoE data.<br>iv. Computed multiplying number of primary teachers (Grade 1-8) by per cent of qualified teachers. The<br>statistical abstracts do not report the absolute number of qualified teachers.|Note: The targets are as per the revised results framework.<br>* The target figures for 2012-13 and 2013-14 as shown in the results framework are not consistent.<br>i. <br>Computed using GER data from Education Statistics Annual Abstract, 2013-14<br>ii. Computed dividing number of enrolled students at Grade 5-8 by total number of teacher at that grade. The<br>data are collected from Education Statistics Annual Abstract, 2013-14. The estimated figures are different<br", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010666", "page": 89, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "MoE data", "probe_tag": "confusion", "probe_score": 0.16021478176116943, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 78, "end": 86, "key": "fcv_pads_east_africa:010666:89:3:0", "source": "camp2", "luna_reason": "MoE data underlies the reported teacher qualification percentage.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "MoE data", "probe_tag": "confusion", "probe_score": 0.16917428374290466, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 78, "end": 86, "key": "fcv_pads_east_africa:010666:89:3:4", "source": "camp2", "luna_reason": "MoE data support the reported percentage of qualified primary teachers.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "40|0.68|0.32|0.30|0.51|\n|**Other**|**14,104**|0.16|45.79|**3,181**|0.32|0.44|0.29|0.34|0.08|\n|**Total**|**8,767,954**|**100.00**|**38.85**|**985,016**|**100.0**|**100.00**|**100.00**|**100.00**|**100.00**|\n|**Distribution of Households in Nairobi (%)**|**Distribution of Households in Nairobi (%)**|**Distribution of Households in Nairobi (%)**|**Distribution of Households in Nairobi (%)**|**Distribution of Households in Nairobi (%)**|**100.0**|**21.6**|**37.5**|**33.2**|**7.7**|\n\n\nSource: KNBS, 2010 <sup>17</sup> [^17: Kenya National Bureau of Statistics. 2010. 2009 Kenya Population and Housing Census: Volume II.\nMinistry of Planning, National Development and Visio 2030, Government of the Republic of\n<u>Kenya, Nairobi</u>]\n\n\n**2.1.3** **Addressing the Water and Sanitation Challenges**\n\nAddressing the two specific water and sanitation sector challenges identified in _Kenya Vision_\n_2030_, according to _Kenya Vision 2030_, will involve increasing development of water resources\nto meet the demand of an increasing population and a growing economy. It will also involve\ninvestment in infrastructure", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016391", "page": 31, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Kenya Population and Housing Census", "probe_tag": "confusion", "probe_score": 0.6922752857208252, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 572, "end": 607, "key": "fcv_pads_east_africa:016391:31:2:0", "source": "camp2", "luna_reason": "Named census cited as the source for the table data.", "usage_type": "declaration", "specificity": "named"}]}
-{"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": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012527", "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": "fcv_pads_east_africa:012527:51:0:0", "source": "camp2", "luna_reason": "Planned future reporting of project data, not use of existing data.", "drop_reason": "promissory", "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": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nTransforming Health Systems (P152394)\n\n\nThe added third objective (to provide immediate and effective response to an eligible crisis or emergency)\nwas fully achieved and rated High. The aggregation of achievement of all three objectives is indicative of a\nSubstantial rating for efficacy under the revised objectives.\n\n\n**Overall Efficacy Revision 1 Rating**\n\n\nSubstantial\n\n\n**5. Efficiency**\nThe cost benefit analysis (CBA) carried out at the time of appraisal adopted the approach of economic\nevaluation of complex interventions. This approach was used because it was not possible to determine the exact\ncombination of interventions that would be carried out during the life of the project. Benefits included lives saved\n(for both mothers and children) and increased productivity, valued at USD 954.2 million. The total cost was\nestimated as USD 174.9 million, resulting in a total benefit of USD 779.2 million, that is, a benefit-to-cost ratio of\nabout 5.5:1. The sensitivity analysis showed that, even if only half of the estimated benefits were achieved, the\nproject would continue to be economically viable. The CBA did not estimate an internal rate of return.\n\n\nThe ICR did not carry out a CBA, but it argued that the evidence indicated that the type of interventions carried\nout as part of the project had significant economic impact. For example, as per UNICEF data, childhood\nvaccination would provide a return of USD 20 per USD invested in low- and middle-income countries. Also,\nresearch carried out in Kenya showed that protective equipment for healthcare workers during the COVID-19\npandemic led to an 11-fold return on investment. The project team later delivered a rigorous CBA, based on the\nsame key assumptions as the analysis at appraisal, using data from the project implementation period. This\nanalysis found, at a three percent discount rate, a net present value of benefits", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004630", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data from the project implementation period", "probe_tag": "confusion", "probe_score": 0.8494898676872253, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1850, "end": 1893, "key": "fcv_pads_east_africa:004630:10:0:1", "source": "camp2", "luna_reason": "Existing implementation-period data used for a CBA yielding a net present value.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "### **Annex-6: Progress Towards Achieving MDGs**\n\nThe present evaluation has tracked progress towards MDGs (Goals 1 to 5) using counterfactual\nanalysis and based on latest available data. The findings are summarised in this annex.\n\n\n**Eradication of extreme poverty and hunger (Goal 1)** : The proportion of population below the\npoverty line declined sharply from 44.2 per cent in 1999-00 to 27.8 per cent in 2011-12 ( _Figure 1-A_ ).\nThis represents a whopping reduction by 17.7 per cent points over a period of one-and-a-half decade.\nA further reduction by 3.8 per cent points would enable the country achieve MDG target of 24 per\ncent. Given that inflation is now contained to single digit, the MDG target has possibly been achieved\nby this time. However, it should be borne in mind that even if poverty reduction touches 24 per cent\nthat would mean 22 million population still remaining below the poverty line.\n\n\n**Figure 1: Reduction in poverty and hunger**\n\n\n\n\n\n\n\n**55**\n\n\n**45**\n\n\n**35**\n\n\n**25**\n\n\n**15**\n\n\n\n**1999-00** **2004-05** **2010-11** **2011-12** **2015**\n\n\n\n**(A) Popula1on below poverty line (percent)**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe food poverty or hunger, as measured by proportion of underweight children (under 5 year), has\nalso declined from 47.2 per cent in 2000 to 28.7 per cent in 2011-12 ( _Figure 1-B_ ). If the trend\ncontinues, it is quite likely that MDG target of 22.7 per cent underweight children will be achieved in\n2015. On the whole, Ethiopia is on track to achieve MDG targets of poverty and hunger reduction", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010666", "page": 95, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "latest available data", "probe_tag": "confusion", "probe_score": 0.5755937695503235, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 165, "end": 186, "key": "fcv_pads_east_africa:010666:95:0:0", "source": "camp2", "luna_reason": "Existing data is explicitly used as the basis for MDG progress analysis.", "usage_type": "declaration", "specificity": "vague"}]}
-{"text": "**The World Bank**\nLSMS-ISA Ethiopia Rural Socioeconomic Survey (P125475)\n\n\n**ABBREVIATIONS AND ACRONYMS**\n\n\nCAPI Computer Assisted Personal Interviewing\n\n\nCSA Central Statistical Agency, Ethiopia\n\n\nERSS Ethiopia Rural Socioeconomic Survey\n\n\nESS Ethiopia Socioeconomic Survey\n\n\nLSMS-ISA Living Standards Measurement Study- Integrated Surveys on Agriculture\n\n\nMOF Ministry of Finance, Ethiopia\n\n\nPDO Project Development Objective\n\n\nNSDS National Strategy for the Development of Statistics", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017539", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "ERSS Ethiopia Rural Socioeconomic Survey", "probe_tag": "confusion", "probe_score": 0.5416976809501648, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 199, "end": 239, "key": "fcv_pads_east_africa:017539:1:0:1", "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": "ESS Ethiopia Socioeconomic Survey", "probe_tag": "confusion", "probe_score": 0.5659033060073853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 242, "end": 275, "key": "fcv_pads_east_africa:017539:1:0:2", "source": "camp2", "luna_reason": "Survey acronym is merely defined, with no shown data use or finding.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "- 37 \n\n10. “Disbursement Linked Indicator” or “DLI” means in respect of a given Category,\nthe indicator related to said Category as set forth in the table in Section IV.A.2 of\nSchedule 2 to this Agreement.\n\n\n11. “Disbursement Linked Result” or “DLR” means in respect of a given Category,\nthe result under said Category as set forth in the table in Section IV.A.2 of Schedule\n2 to this Agreement, on the basis of the achievement of which, the amount of the\nFinancing allocated to said result may be withdrawn in accordance with the\nprovisions of said Section IV.\n\n\n12. “EFY” means the Ethiopian Fiscal Year, the fiscal year of the Recipient which\ncommences on July 8 and ends on July 7.\n\n\n13. “Eligible Crisis or Emergency” means an event that has caused, or is likely to\nimminently cause, a major adverse economic and/or social impact to the Recipient,\nassociated with a natural or man-made crisis or disaster.\n\n\n14. “Eligible Refugee Incentive Teachers” mean the refugee incentive teachers\ndeemed eligible to receive in-service skill upgrading Training on an annual basis:\n(i) in line with the eligibility criteria elaborated in the Operations Manual; and (ii)\nbased on data received from UNHCR.\n\n\n15. “Eligible Refugee Primary Schools” mean refugee primary schools which are\noperational in the five main refugee-hosting regions, based on data received from\nUNHCR, on an annual basis as further elaborated in the Operations Manual.\n\n\n16. “Eligible Refugee Secondary Schools” mean refugee secondary schools which are\noperational in the five main refugee-hosting regions, based on data received from\nUNHCR, on an annual basis as further elaborated in the Operations Manual.\n\n\n17. “Emergency Action Plan” means the plan referred to in Section I.F of Schedule 2\nto this Agreement, detailing the activities, budget,", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014916", "page": 37, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data received from UNHCR", "probe_tag": "confusion", "probe_score": 0.7820618152618408, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1171, "end": 1195, "key": "fcv_pads_east_africa:014916:37:0:0", "source": "camp2", "luna_reason": "Existing UNHCR data determines eligibility for refugee incentive teachers.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014600", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1188, "end": 1214, "key": "fcv_pads_east_africa:014600:31:0:2", "source": "camp2", "luna_reason": "Administrative data is listed without an attributed finding or demonstrated use.", "drop_reason": "system_registry", "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:019153", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household expenditure survey data", "probe_tag": "confusion", "probe_score": 0.7323, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 565, "end": 598, "key": "sample:fcv_pads_east_africa:019153:38:1:0", "source": "gold", "luna_reason": "Survey data provides enrollment-rate comparisons by expenditure quintile.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "survey data", "probe_tag": "confusion", "probe_score": 0.1461, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 870, "end": 881, "key": "sample:fcv_pads_east_africa:019153:38:1:1", "source": "gold", "luna_reason": null}, {"text": "data from the Household Survey", "probe_tag": "confusion", "probe_score": 0.1121, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1978, "end": 2008, "key": "sample:fcv_pads_east_africa:019153:38:1:2", "source": "gold", "luna_reason": "Household Survey data supports a concrete finding about girls leaving school.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "|No|Issues|Agreed Actions|Time frame|\n|---|---|---|---|\n|5.1|Recruit/assign E&S specialists for the<br>vacant regional positions.<br>|• E&S specialist positions at Dire Dawa and Southwest region to be hired and<br>deployed.<br>• MOE to assign an E&S expert to work and coordinate with the national and<br>regional PIU|• December 12, 2024<br>• December 18, 2024|\n|5.2|Capacity building|• NWCO and Federal PMUs to prepare a capacity development plan and share<br>with the Bank’s ES team<br>• NWCO and Federal PMUs to cascade the capacity development trainings for<br>woreda focal persons and relevant project workers at woreda level|• October 30, 2024<br>• By December 28,<br>2024|\n|5.3|Proper documentation of E&S instruments|• Federal and regional PMUs to assess, compile, and consolidate data on the ES<br>instruments for subprojects implemented and under implementation<br>• Federal and regional PMUs to share the available ESIA/ESMP for CR WASH<br>with the Bank E&S team|• December 28, 2024<br>• October 22, 2024|\n|5.4|Safeguards Instruments|Federal and regional PMUs: (i) to compile and share corrective action plan of the<br>internal due diligence reports from all regions; (ii) finalize, compile and share the<br>ESMPs for the identified high value contracts|December 30, 2024|\n|5.5|Independent E&S compliance audit|• Federal and regional PMUs share the independent E&S", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004976", "page": 6, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "internal due diligence reports", "probe_tag": "confusion", "probe_score": 0.11225901544094086, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1130, "end": 1160, "key": "fcv_pads_east_africa:004976:6:0:0", "source": "camp2", "luna_reason": "Planned compilation and sharing of internal compliance reports, not substantive data reuse.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "21\n\n\nthey have to purchase water from trucks which costs four times as high than a household connection;\nand qat consumption poses a major social, income and productivity issue.\n\n\nIn order to capture as much of the school-age population presently out of school due to the lack of\nexisting places, the project will construct additional/rehabilitate classrooms. In addition, sanitation\n\nservices will be rehabilitated, and a study will be undertaken on which sanitation services best serve\nthe area, especially in a drought-prone area, and the most cost-effective methods of implementation\nand maintenance. The project will finance a study to analyze the factors that hinder girls' attendance\nand achievement, and of the feasibility of measures to overcome them, including the issues\n\nsurrounding access to education by the poor. The problems are cross-sectoral which the project, in\nPhase I, will not address (unemployed youth, health issues, non-Djiboutian school-age population,\netc.). See Section C above for program details.\n\n\nThe IDA's regional team will discuss with Government on updating the initial 1997 poverty\n\nassessment in order to produce a better picture of the issues as they exist now. In addition, it is\nenvisaged that IDA will discuss the rising health issues with the Government and the best ways for\naddressing these problems.\n\n\n_6.2 Participatory Approach: How are key stakeholders participating in the project?_\n\n\nKey stakeholders participated in the National Educational Forum _(Etats-Generaux de l'Education)_\nwhich was held in December 1999. This included officials, teachers, parents, students, members of\nparliament and the general public. The project is based on the outcome of the conference. The new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019187", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "1997 poverty\n\nassessment", "probe_tag": "confusion", "probe_score": 0.6263846755027771, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1107, "end": 1131, "key": "fcv_pads_east_africa:019187:24:0:0", "source": "camp2", "luna_reason": "Existing dated poverty assessment is referenced as the basis for planned updating.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "will include broad based community _barazas,_ radio, SMS, brochures/leaflets, megaphone\nannouncements etc. Specifically, the Beneficiary Outreach Strategy with nuanced VMG messages\nwould be used to ensure inclusion of VMGs, and would provide the appropriate mechanisms to\nascertain that VMGs are reached and that information is provided in ways that are easily\nunderstood. This may need to be tailored to different VMG groups, depending on their\nremoteness, language, literacy level, integration into the broader communities and civic\neducation.\nb. Track the number and type of complaints that are lodged with the program and the actions taken\n\nand ensure that appropriate mitigation measures are planned and implemented.\nc. Carry out periodic reviews of beneficiary and grievance data to ensure targeted locations where\n\nminorities are present are reached and recurring complaints are investigated to ensure mitigation\nmeasures.\nd. Ensure that barriers to inclusion (e.g. difficulty securing IDs) are addressed for eligible\n\npopulation, including VMGs.\n\n61. There is a need to further sensitize and build capacity of all relevant stakeholders on proper\nidentification and inclusion of different categories of VMGs. As such, the KSEIP implementing agencies\nshould review the existing VMG databases under NSNP for each KSEIP county. Furthermore, program\nofficers should be sensitized on the stigmatized conditions, and how to include such groups in KESIP. This\nwill enhance understanding of the characteristics and locations of VMGs, and create awareness about the\nVMGs among the officers for better engagement and targeting. To increase the engagement with VMGs,\ncollaboration between SDSP and NDMA and other government and civil society organisations who work with\nVMGs should be encouraged.\n\n\n62. Training and civic education of communities should be undertaken to enhance understanding of rights\nand entitlements of all, including VMGs. Training of rights can be done as part of beneficiary outreach for all\nNSNP beneficiaries and communities.\n\n63. In communicating with VMG", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008714", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "beneficiary and grievance data", "probe_tag": "confusion", "probe_score": 0.40900054574012756, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 755, "end": 785, "key": "fcv_pads_east_africa:008714:15:0:0", "source": "camp2", "luna_reason": "Planned periodic review of data, not use of an existing dataset.", "drop_reason": "promissory", "specificity": "vague"}, {"text": "VMG databases under NSNP", "probe_tag": "confusion", "probe_score": 0.7324456572532654, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1284, "end": 1308, "key": "fcv_pads_east_africa:008714:15:0:1", "source": "camp2", "luna_reason": "Existing databases are reviewed to identify VMG characteristics, locations, and targeting needs.", "usage_type": "evidential", "specificity": "named"}]}
-{"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:018329", "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:018329:10:0:0", "source": "camp2", "luna_reason": "Past survey produced an attributed HIV prevalence finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": ">|SheepI Goat : Donkey<br> <br> <br>|BeeHive<br>|\n|. FartaSide<br>|2.713.64<br>|4.88<br>|3.88<br>! 1.62<br> <br>|3.88<br>! 1.62<br> <br>|7 <br>|\n|EbinatSide|2.512.66|3.84|4.4|1.88|4.1|\n\n\n\nSource: Household Survey. 2008\n\n\n3.3. Vulnerable Groups\n\n\nAs per the policy and legal framework of the Government and major donor\n\nagencies like the World Bank, vulnerable groups, like the elderly, women\nhousehold heads and those with physical and emotional impairment. are\nexpected to have special support to address part of their problems during the\nrelocation and resettlement process. These landless households are also\nexpected to have special support. The house to house survey result shows that\nabout six percent of the household heads are falling within the category of\nvulnerable groups. Those aged ones (65 and plus) and women headed who\nlost more than 25% of their land are also taken as vulnerable groups.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Table 3.3: Vulnerability Status amongst PAPs I Vulnerability Type|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|i <br>Woreda<br> <br>~~I ~~<br>Vulnerability Type<br>I <br>Old Age( 65+)<br>Hearing<br>~~I ~~Sight<br>Amputee<br>landless<br>1 household<br>Impair", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011334", "page": 18, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "house to house survey", "probe_tag": "confusion", "probe_score": 0.572488009929657, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 650, "end": 671, "key": "fcv_pads_east_africa:011334:18:2:1", "source": "camp2", "luna_reason": "Survey result supports the stated six-percent vulnerability finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**the Bank’s right to sanction and the Bank’s inspection and audit**\n**rights. The form of the Letter of Acceptance is attached in Appendix**\n**1** .\n\n\n**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables: **Not Applicable.**\n\n\n**_Procurement of Second Hand Goods_** _as specified under paragraph 5.11_\nof the Procurement Regulations – is allowed for those contracts identified in\nthe Procurement Plan tables: **Not Applicable.**\n\n\n**_Domestic_** **_preference_** _as_ _specified_ _under_ _paragraph_ _5.51_ of the\nProcurement Regulations **_(Goods and Works)_** .\n\n\nGoods : **Applicable for those contracts identified in the**\n**Procurement Plan tables**\n\n\nWorks: **applicable** **for** **those** **contracts** **identified** **in** **the**\n**Procurement Plan tables**\n\n\nThis being an emergency project, increased thresholds for Requests for\nQuotations (RFQ) to US$1 million for goods and services and US$5 million for\nworks **;**\n\n\n**Other Relevant Procurement Information:-**\n\n\n**Prior Procurement Arrangements:**\n\n\nThe Procurement Arrangements as indicated in the below table and within\nthe thresholds indicated in the below tables will be used. The thresholds for\nthe Bank’s prior review requirements are also provided in the table below:\n\n\nTable: **Prior review Thresholds**\n\n|Procurement Type|High<br>Risk|\n|---|---|\n|Works|5.0|", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000568", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "confusion", "probe_score": 0.06569124013185501, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 298, "end": 321, "key": "fcv_pads_east_africa:000568:1:0:0", "source": "camp2", "luna_reason": "Procurement planning documentation, not a substantive data resource or data use.", "drop_reason": "bookkeeping", "specificity": "descriptive"}, {"text": "Procurement Plan tables", "probe_tag": "confusion", "probe_score": 0.05065480247139931, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 298, "end": 321, "key": "fcv_pads_east_africa:000568:1:0:2", "source": "camp2", "luna_reason": "Routine procurement planning tables, not substantive data reuse.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "Kenya Power and Lighting Company PLC\n\nKenya **Off** grid Solar Access Project (KOSAP)\nAnnual Report and Financial Statements for the financial year ended June **30, 2025**\n\n\n**_2.8_** Summary of Overall Project Performance:\n\n\na) Budget Performance against Actual Amounts\n\nTo date the Project has received a total Kshs **136** million, which is 2.4 **%** of the budget.\n\n**b)** Physical Progress and Achievement of the Project\n\nUnder the KPLC component, the project entails the development of **83** mini-grids and 343\nsolar stand-atone systems, targeting to connect over **37,500** households, enterprises,\nand public facilities. Implementation progress to date includes handover of project sites,\ncompletion of site surveys, and ongoing detailed design works.\n\nDuringthe year under review, the Project absorbed **5.1 %** of the budget in the FY20242025\n\n\nc) Implementation Challenges and way forward\n\nThe acquisition of land for the construction of mini grids experienced significant delays.\nInitially, the adopted approach-donation of unregistered community land-was found\nto be inconsistent with the prevailing legal framework. Following extensive consultations,\nthe World Bank approved a Com pensation-in -Kind Strategy, whereby the Project would\nprovide community infrastructure, such as the construction of classrooms or the desitting of water pans, in lieu of cash payments.\nThe Ministry subsequently mobilized the required resources and engaged the National\nLand Commission **(NLC)** to lead the land acquisition process. Key milestones, including\ngazettement of the land, grantingof eartyentry, site inspections, and public inquiries, have\n\nbeen completed. Final surveys have also been undertaken jointly **by** the Directorate of\nSurveys and technical teams from KPLC and REREC and wilt be submitted to the Ministry\nof Lands for final vesting.\nThe", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000418", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "site surveys", "probe_tag": "confusion", "probe_score": 0.10653789341449738, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 712, "end": 724, "key": "fcv_pads_east_africa:000418:9:0:0", "source": "camp2", "luna_reason": "Site surveys are reported as completed project activities, not existing data used for analysis.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": " the consumption of MNR crops\nand led to increased HH dietary diversity and food security <sup>7</sup> [^7: Food Security was measured in terms of the food consumption score (FCS).] in project districts **_._** The project initiated a combination\nof activities that included community nutrition education forums, cooking demonstrations, information\n\n\n3 The Quasi-Experimental evaluation used panel data from the baseline, midline and endline evaluations surveys of the project. The evaluation approach\ninterviewed the same households from baseline and midline in 5 project districts and in 3 comparison districts (non-project districts). The sample survey\ncovered a total of 2,841HHs (1,897HHs from treatment project areas and 944HHs from non-project areas). The evaluation approach corrected for potential\nselection bias due to non-random allocation of districts to control and treatment groups. During the selection process, each treatment project group was\nmatched with one or two control (non-Project) districts with similarity in location, agroecological conditions and geographical closeness to minimize on\ndistrict level confounding differences. Treatment project districts were largely comparable to control districts in several aspects. Difference in Difference\nestimation of impacts were applied with (1) Propensity Score Matching estimators with Kernel matching and nearest neighbor matching and (2) regression\nbased non-matching estimators to ensure robustness of impact results. The study used the Agricultural Scalability Assessment Tool to qualitatively\ndetermine the effects of the project on beneficiaries and spill-over effects.\n4 Impact Evaluation Report of the Multisectoral Food Security and Nutrition Project, December 2023.\n5 35 percent more households in treatment districts than in control districts had higher awareness levels of OFSP; 17 percent more households in\ntreatment districts than in control districts had higher awareness levels of Amaranthus; 15 percent more households in treatment districts than in control\ndistricts had higher awareness levels of pumpkin while 4 percent more households in treatment districts than in control districts had higher awareness\nlevels of iron rich beans.\n6 Treatment districts produced higher quantities of MNR", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003462", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "panel data", "probe_tag": "confusion", "probe_score": 0.8625277876853943, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 392, "end": 402, "key": "fcv_pads_east_africa:003462:14:2:0", "source": "camp2", "luna_reason": "Panel data are explicitly used as the evaluation's analytical basis.", "usage_type": "declaration", "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": "**The World Bank** Implementation Status & Results Report\nUganda Multisectoral Food Security and Nutrition Project (P149286)\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**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\n1/6/2019 Page 5 of 6", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010599", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Data on Financial Performance", "probe_tag": "drop", "probe_score": 0.02300860546529293, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 166, "end": 195, "key": "fcv_pads_east_africa:010599:4:0:0", "source": "camp2", "luna_reason": "Standalone financial performance section header, not a substantive data citation.", "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:012788", "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:012788:31:0:0", "source": "camp2", "luna_reason": "Names project monitoring data without showing substantive use or analysis.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "br>Program (Number)|Comments on achieving targets|Comments on achieving targets|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|Pending UDG disbursement|\n|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|**RA 4 - Improved private sector engagement**|\n|Indicator Name|Baseline|Baseline|Actual (Previous)|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period|Closing Period|\n|Indicator Name|Result|Month/Year|Result|Date|Result|Date|Result|Month/Year|\n|Participating urban board with up-to-<br>date business enterprise database<br>(Percentage)|0.00|Jun/2023|0.00|14-Mar-2025|0.00|14-Mar-2025|50.00|Jun/2028|\n|Participating urban board with up-to-<br>date business enterprise database<br>(Percentage)|Comments on achieving targets|Comments on achieving targets|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|To be tracked in APA2|\n|Participating urban boards operating<br>within the county government's", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001991", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "business enterprise database", "probe_tag": "drop", "probe_score": 0.04906463250517845, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 906, "end": 934, "key": "fcv_pads_east_africa:001991:14:2:0", "source": "camp2", "luna_reason": "Indicator-table fragment, not an independently used data resource", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "business enterprise database", "probe_tag": "drop", "probe_score": 0.012327725067734718, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 906, "end": 934, "key": "fcv_pads_east_africa:001991:14:2:1", "source": "camp2", "luna_reason": "Fragment inside an indicator table, not an independently usable data mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "**_Kenya_** **_Agricultural Productivity_** **_and Sustainable Land Management Project (KAPSLMP)_**\n**_Reports_** **_and Financial Statements_**\n\n**_For the financial year ended June 30,_** **_2017_**\n\n\n**Specific** **Duties:**\n\n\n(i) Develop and **help** establish <sup>a</sup>\nsystem of routine records and\nperiodic monitoring reports at\ncommunity, district and\nproject level\n(ii) Assist in development of a\ndatabase of existing M&E\ncapacity in the districts for\ncapacity building\nrequirements\n(iii) Assist in development of\ncurriculum for training M&E\npersonnel\n(iv) Provide Technical Assistance\nto KAPAP Specialists and\nRSUs to develop\ncomprehensive monitoring\nand evaluation guidelines for\nthe various components\nobjectives. Develop\nappropriate indicators for\neffective implementation and\n\nimpact assessment at various\nlevels including community\nlevel\n(v) Coordinate and organize\nstudies/surveys and other field\nactivities in support of midterm and terminal evaluation\nof the project\n(vi) Liaise with and provide\ntechnical support to the\ndistricts evaluation needs\n(vii) Undertake project and\nthematic evaluations. This\nwill include diagnostic studies\nand in-depth reviews of\nproject interventions covering\neconomic, social and\nenvironmental impact\n(viii) Undertake impact assessment\nof project activities\n(ix) Act as the focal point for\norganizational evaluationresponsible for the\npreparation of periodic reports\n(x) Plan and implement\n\n\n**7**", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013875", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "database of existing M&E\ncapacity", "probe_tag": "drop", "probe_score": 0.014665377326309681, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 409, "end": 442, "key": "fcv_pads_east_africa:013875:9:0:0", "source": "camp2", "luna_reason": "The project proposes developing this database, so the data resource is not yet existing.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "- **_The procurement is open to eligible firms from any country;_**\n\n\n  - **_The request for bids/Proposal documents shall require that_**\n\n\n**_bidders/proposers submitting Bids/Proposal present a signed_**\n\n\n**_acceptance at the time of bidding, to be incorporated in any_**\n\n\n**_resulting contracts, confirming application of and compliance_**\n\n\n**_with the Bank’s Anti-Corruption Guidelines, including without_**\n\n\n**_limitation the bank’s right to sanction and the Bank’s inspection_**\n\n\n**_and audit right;_**\n\n\n  - **_Contracts with an appropriate allocation of responsibilities, risks_**\n\n\n**_and liabilities;_**\n\n\n  - **_Application of Standstill period and Publication of contract award_**\n\n\n**_information;_**\n\n\n  - **_Maintenance of records of the procurement process; and_**\n\n\n  - **_The Bank has the right to review procurement documentation_**\n\n\n**_and activities._**\n\n\nWhen other national procurement arrangements other than national open\ncompetitive procurement arrangements are applied by the Borrower, such\narrangements shall be subject to paragraph 5.5 of the Procurement\nRegulations.\n\n\n**_Leased Assets as specified under paragraph 5.10_** of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables. **_“Not Applicable”_**\n\n\n**_Procurement of Second-Hand Goods_** **_as specified under paragraph_**\n**_5.11_** of the Procurement Regulations – is allowed for those contracts identified\nin the Procurement Plan tables _“_ **_Not Applicable”_**\n\n\n**_Domestic preference as specified under paragraph 5.51_*", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002548", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.012609212659299374, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1250, "end": 1273, "key": "fcv_pads_east_africa:002548:1:0:0", "source": "camp2", "luna_reason": "Routine procurement planning tables, not substantive evidence or analysis.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011679", "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:011679:31:0:0", "source": "camp2", "luna_reason": "Names M&E data without showing an attributed finding or substantive analytical use.", "drop_reason": "system_registry", "specificity": "descriptive"}, {"text": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1188, "end": 1214, "key": "fcv_pads_east_africa:011679:31:0:2", "source": "camp2", "luna_reason": "Administrative data is listed as a monitoring source without shown substantive use.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "- To manage public land on behalf of the national and county governments;\n\n- To recommend a national land policy to the national government;\n\n- To advise the national government on a comprehensive programme for the\nregistration of Title in land throughout Kenya;\n\n- To conduct research related to land and the use of natural resources, and make\nrecommendations to appropriate authorities;\n\n- To initiate investigations, on its own initiative or on a complaint, into present or\nhistorical land injustices, and recommend appropriate redress;\n\n- To encourage the application of traditional dispute resolution mechanisms in\nland conflicts;\n\n- To assess tax on land and premiums on immovable property in any area\ndesignated by law; and\n\n- To monitor and have oversight responsibilities over land use planning\nthroughout the country;\n\n- On behalf of, and with the consent of the national and county governments,\nalienate public land;\n\n- To monitor the registration of all rights and interests in land;\n\n- To ensure that public land and land under the management of designated state\nagencies are sustainably managed for their intended purpose and for future\ngenerations;\n\n- Develop and maintain an effective land information management system at\nnational and county levels;\n\n- Manage and administer all unregistered trust land and unregistered community\nland on behalf of the county government; and\n\n- Develop and encourage alternative dispute resolution mechanisms in land dispute\nhandling and management.\n\nRelevance:\n\nThe National Land Commission will come in handy in cases of grievance solving\nmechanisms. It will also help to initiate investigations, on its own initiative or on a\ncomplaint, into present or historical land injustices that might relate to the project\nimplementation.\n\nThe commission also monitors and has oversight responsibilities over land use planning\nthroughout the country and will intervene should the proposed project go contrary to the\nland use plans.\n\n3.2.3 The Land Act 2012\n\nThis is an Act of Parliament intended to give effect to Article 68 of the Constitution, to\nrevise, consolidate and rationalize land laws; to provide for the sustainable administration\nand management of land and land based resources, and for connected purposes", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016432", "page": 30, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "land information management system", "probe_tag": "drop", "probe_score": 0.035073172301054, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1201, "end": 1235, "key": "fcv_pads_east_africa:016432:30:0:0", "source": "camp2", "luna_reason": "Names a land information system without showing its data being used.", "drop_reason": "system_registry", "specificity": "descriptive"}]}
-{"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:012936", "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:012936:30:0:0", "source": "camp2", "luna_reason": "MOE reports provide evidence for the stated enrollment increase.", "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": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008440", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.027876049280166626, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 240, "key": "fcv_pads_east_africa:008440:31:0:0", "source": "camp2", "luna_reason": "Logframe M&E verification source, not existing data used for analysis", "drop_reason": "promissory", "specificity": "named"}, {"text": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.11965898424386978, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 412, "end": 437, "key": "fcv_pads_east_africa:008440:31:0:1", "source": "camp2", "luna_reason": "Named administrative data source listed for program performance indicators.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "#### I Fig 4-1a: Consultative meeting Hoima I Fig4-1b: Sensitisation meeting In Buliisa\n\n**4.1.2** **Notification of meeting dates and venues**\n\n\nIntroductory letters from REA were delivered by team members to the district and Sub\n\nCounty headquarters (for both the Bunyoro and Ankole zones) after which a schedule of\n\nmeetings was prepared in'consulta!ti6n?.:with the district and sub county leaders. Having\n\nfixed the venues and meeting days/tim.es (shown under Annex 7 and Annex 8), the local\n\ncouncils in the area undertook to inform the communities about these meetings. This\n\nwas done to ensure that the LC can mobilise in time and prepare effectively for the\n\nmeetings.\n\n\n**4.1.3** **Meetings**\n\n\nAt the sensitisation mee,tiii~s, the _Team_ Leader would introduce his/her team and the\n\nsubject matter to be covered. The language used was mostly Runyoro with some\n\ninterjections in English for the Bunyoro zone, and Mostly Runyankore _I_ Rukiga also with\n\ninterjections in English for the Ankole zone. The list of the contacted people is attached\n\nas Annex 9\n\n\n~ **Information provided** **by** **the Social Team**\n\n\nThe Social Team explained the social component particularly as it related to the human\n\nfactor at the design stage 1 during Jmpl~!)1entation and during the operational phases of\n\nthe 33 kV Distribution Line. In particular the following were highlighted:\n\n - That the surveyor would demarcate the 33 kV Distribution Line on the ground;\n\n - That the names picked by the surveyor would be the same names picked by the social\nteam as well as the valuation team to ensure that all the data on PAPs is harmonised.\n\n - That", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019898", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on PAPs", "probe_tag": "drop", "probe_score": 0.028559239581227303, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1603, "end": 1615, "key": "fcv_pads_east_africa:019898:31:0:0", "source": "camp2", "luna_reason": "Generic data mention lacks an attributed finding or substantive analytical use.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Not Applicable\n\n\n**Procurement of Second Hand Goods** as specified under paragraph 5.11 of\nthe Procurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables: Not Applicable\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** .\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables\n\n\n**Other** **_Relevant Procurement Information._**\n\n\n_None_", "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004224", "page": 1, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.03880133852362633, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 258, "end": 281, "key": "fcv_pads_east_africa:004224:1:0:0", "source": "camp2", "luna_reason": "Routine procurement planning tables, not substantive data use.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"text": "diary, effectively blurring the line between consumption data collected by diary and by recall interview.\n\n\nThis mediation by interviewers is especially likely since most diary surveys instruct interviewers to return\n\n\nevery few days to update the diary in cases where it may not be completed by household members, such\n\n\nas in households with no literate adults.\n\n\nWhile well-implemented diary surveys might be expected to yield higher (and presumably closer\n\n\nto actual) levels of consumption, experimental evidence for this from developing countries is\n\n\nfragmentary. In urban Papua New Guinea, Gibson (1999) found that mean total expenditure per capita\n\n\nwas 14 percent higher (and food consumption 26 percent higher) using a diary rather than a recall survey.\n\n\nHowever, preliminary comparisons of consumption from the Bosnia and Herzegovina LSMS (recall)\n\n\nsurvey with the household budget survey (diary) in 2004 show levels to be similar (World Bank, 2006).\n\n\nThese studies pertain to household-level diaries and thus do not address an important source of\n\n\nmis-measurement – the difficulty of a sole respondent to perfectly capture total household consumption.\n\n\nPersonal diaries are generally considered better for obtaining complete household expenditure or\n\n\nconsumption data because it is unusual, in most societies, for any one household member to know the\n\n\nexpenditure/consumption of every other member, especially on items such as alcohol, tobacco, daily\n\n\ntravel, personal toiletries, daily newspapers/magazines, and meals (especially snacks and lunches) eaten\n\n\noutside the home. In Russia, as part of an effort to study the reliability of the Household Budget Survey, a\n\nrandom sample of households in the 3 <sup>rd</sup> quarter of 2003 were assigned personal diaries rather than the\n\n\nhousehold diary. The personal diary yielded expenditure levels which were 6-11 percent higher than a\n\n\nhousehold diary (World Bank, 2005). However, the personal diary was plagued with non-respondent\n\n\nproblems in this experiment; about 54 percent of households assigned the personal diary did not complete\n\n\nit. Personal diaries", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004687", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "consumption data", "probe_tag": "keep", "probe_score": 0.9299, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 45, "end": 61, "key": "sample:prwp:004687:7:0:0", "source": "gold", "luna_reason": null}, {"text": "Bosnia and Herzegovina LSMS", "probe_tag": "keep", "probe_score": 0.9895, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 824, "end": 851, "key": "sample:prwp:004687:7:0:1", "source": "gold", "luna_reason": "Named LSMS survey data are compared with a household budget survey.", "usage_type": "evidential", "specificity": "named"}, {"text": "household budget survey", "probe_tag": "keep", "probe_score": 0.9511, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 879, "end": 902, "key": "sample:prwp:004687:7:0:2", "source": "gold", "luna_reason": null}, {"text": "Household Budget Survey", "probe_tag": "keep", "probe_score": 0.9011, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1662, "end": 1685, "key": "sample:prwp:004687:7:0:3", "source": "gold", "luna_reason": null}]}
+{"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": " 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": " is built out of the school\nquestionnaire from PISA 2012 using the methodology from Anderson [2008]. All specifications include PISA _school_ _final_ _weights_\nand country fixed effects. School controls include school location, student-teacher ratio, log of the number of students, share of\ngovernment funding relative to total school funding, ratio of computers connected to the web as a proxy for school resources,\nand average student socio-economic status. For control variables, missing variables are replaced with a value of -99 and we\ninclude an indicator variable with a value of 1 for each imputed value, for each variable with imputed values dummies are added\nto the specifications.\n\n\nApp. 2", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001847", "page": 54, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "school\nquestionnaire from PISA 2012", "probe_tag": "keep", "probe_score": 0.9596311450004578, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 21, "end": 56, "key": "prwp:001847:54:1:0", "source": "camp2", "luna_reason": "PISA 2012 school questionnaire is used to construct the analysis measure.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**1.** **Introduction**\n\n\nThe shock associated with the COVID-19 pandemic has been large and persistent. As documented\n\nin Apedo-Amah et al. (2020) and Cirera et al. (2021), the private sector has experienced a large,\n\n\npersistent negative impact on sales across all regions of the world. Most firms had still not recovered\n\n\nthe levels of sales in 2019 more than a year after the beginning of the pandemic (Cirera et al., 2021)\n\n\nand some sectors are experiencing structural changes in the way products or services are produced\n\nand demanded. These changes and the associated reallocation of resources have already been\n\n\nidentified in the data from the United States (Barrero et al., 2021).\n\n\nA critical question for policy is how these changes will affect firm growth and aggregate produc\ntivity. Are surviving firms coming out stronger from the pandemic? The answer to this question\n\n\ndepends on many different channels that affect productivity, which in many cases are in opposing\n\n\ndirections. For example, Harris and Moffat (2021) implemented a survey of UK firms and found that,\n\non the one hand, 18% of firms have stopped and 45% reduced doing R&D but, on the other hand,\n\n40% of firms have increased ICT investments. Andrews et al. (2021) find a positive reallocation\n\neffect for three OECD countries, mainly driven by technology readiness to face the shock and the\n\nadditional investments in technology. This paper explores firms’ digitalization trends during the\n\nCOVID-19 pandemic using a novel firm-level data set of 57 countries across three periods of time\n\nsince the start of the pandemic. The paper identifies the digitalization effects on firms’ resilience,\n\n\ndifferences in adoption, and changes in market share distribution.\n\n\nThere are at least two forces associated with the pandemic, in opposite directions, driving the\n\n\ndecision of businesses to invest in and expand the use of digital technologies. On the one hand,", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000561", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data from the United States", "probe_tag": "keep", "probe_score": 0.9659, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 641, "end": 668, "key": "sample:prwp:000561:3:0:0", "source": "gold", "luna_reason": null}, {"text": "survey of UK firms", "probe_tag": "keep", "probe_score": 0.9731, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1052, "end": 1070, "key": "sample:prwp:000561:3:0:1", "source": "gold", "luna_reason": null}, {"text": "firm-level data set of 57 countries", "probe_tag": "keep", "probe_score": 0.9809, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1508, "end": 1543, "key": "sample:prwp:000561:3:0:2", "source": "gold", "luna_reason": null}]}
-{"text": " increase the savings share. Since investment is\nmodeled as being savings driven, total global investment is driven by total global savings, with\nthe amount of investment in a given country being a function of both domestic savings as well as\nthe current account balance, which is determined exogenously. The additional implication of the\nsavings driven investment assumption is that that as dependency ratios fall in a given country,\ndomestic savings will rise, which in turn will boost investment. The opposite would hold true for\na country where dependency ratios are rising.\n\n\nWhile LINKAGE provides the economy-wide effects of demographic change over time, the\nGIDD microsimulation framework (Bussolo et al., 2010; Bourguinon and Bussolo, 2013) will be\nused to generate income distributions under the various scenarios. GIDD draws on household\nlevel survey data benchmarked to 2010 to estimate income distributions by country that account\nfor demographics, household characteristics (e.g. age, gender, and education of different\nmembers), sector of employment, skill premia on wages, and income. <sup>10</sup> Using the simulated\nincome and employment under future scenarios from LINKAGE, and accounting for the\ndemographic shifts characterized in the UN (2015), GIDD is able to generate income\ndistributions by country that are consistent with both the more ‘aggregated’ changes under the\nCGE simulations and also what is known about households from survey data. In addition to\nincorporating the changes in key variables from the LINKAGE scenario results, the GIDD\nmethodology updates the household survey data for the terminal year of the simulation. This is\ndone by reweighting the population characterized by the base year household surveys using non\n\n10 Table A1 in the annex provides information on the household surveys used in the micro-simulation.\n\n\n11", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006809", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "household\nlevel survey data", "probe_tag": "keep", "probe_score": 0.9067097902297974, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 839, "end": 866, "key": "prwp:006809:12:1:0", "source": "camp2", "luna_reason": "Survey data are used to estimate country income distributions.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "##### Figures\n\n**Figure 1: Sowing/transplanting and harvesting periods of paddy in**\n\n**<u>Bangladesh</u>**\n\n\n\n\n\n\n\nSource: BBS 2004\n\n\n**<u>Figure 2: Seasonality in borrowing in 1998/99</u>**\n\n\nSource: World Bank-BIDS survey 1998/99\n\n\n32", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006981", "page": 33, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "World Bank-BIDS survey", "probe_tag": "keep", "probe_score": 0.9138402938842773, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 201, "end": 223, "key": "prwp:006981:33:0:0", "source": "camp2", "luna_reason": "Named survey cited as the source for a presented figure.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "from 2001 onward, the last two of these—arts and business—were removed\n(Orlale 2000, Kremer, Miguel, and Thornton 2009). As a consequence, the\nKLPS data include observations in which the maximum score is 700, and\nobservations where the maximum is 500. Throughout this paper, I normalize\nall scores to the 500-point scale.\n\nThose who are not admitted to any government school have several options if they wish to continue their education: they may repeat eighth grade\nand re-take the KCPE; they may still have access to private secondary schools\nand vocational schools; or they may travel to Uganda to enroll in school there.\n\n\n**A.1.3** **Re-taking** **the** **KCPE**\n\n\nOne clear pattern both from the survey data and the administrative records is\nthat students sometimes re-take the test. In the 2003-2005 round of surveying\n(KLPS1), the questionnaire asked not only for respondents’ KCPE score, but\nalso how many times they had taken the KCPE. Of KCPE-takers in the older\ncohorts (who had reached eighth grade before being interviewed in KLPS2),\napproximately 87 percent said they took it exactly once, 13 percent said that\nthey had taken the exam twice, and around one tenth of one percent said\nthey took it three times. The reason such a small fraction re-take such an\nimportant examination, according to my interviews with with both teachers\nand pupils, is that it is costly: they have to repeat eighth grade in order to do\nit. The survey data are in agreement: more than 98 percent of respondents\nwho report re-taking the KCPE also report repeating standard 8; conversely,\nof those who take the KCPE only once, comparatively few respondents (less\nthan 3 percent) repeat standard 8 for any reason. While a pupil’s decision to\nre-take", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006439", "page": 53, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "KLPS data", "probe_tag": "keep", "probe_score": 0.921, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 143, "end": 152, "key": "sample:prwp:006439:53:0:0", "source": "gold", "luna_reason": "KLPS data support the reported maximum-score observations and score normalization.", "usage_type": "evidential", "specificity": "named"}, {"text": "survey data", "probe_tag": "confusion", "probe_score": 0.7988, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 702, "end": 713, "key": "sample:prwp:006439:53:0:1", "source": "gold", "luna_reason": null}, {"text": "administrative records", "probe_tag": "keep", "probe_score": 0.9405, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 722, "end": 744, "key": "sample:prwp:006439:53:0:2", "source": "gold", "luna_reason": null}]}
+{"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": "ceij_ + µ _ijtk_,\n\n\nwhere _gtrade_ is trade growth. The _η_ s gives an estimate of _d_ γ in equation (8), which\n\n\nrepresents whether trade growth is biased toward more distant countries. It is the\n\n\npercentage point change in annual trade growth for a percentage change in distance. For\n\n\nexample, if η is -.1, it would imply that 10 percent increase in distance between two\n\n\ncountries leads to 1 percentage point slower trade growth.\n\n\nIn order to provide a benchmark, we also estimate equations (7) and (11) using\n\n\nthe aggregate bilateral trade data. This allows us to compare the average industry\n\n\ndistance elasticity with the distance elasticity from aggregate data.\n\n\n**V. Regression Results**\n\n\nWe use data on the value of bilateral trade for 766 SITC2 industries. <sup>8</sup> Within the\n\n\nindustries, we calculate average bilateral trade for three periods, 1985-89, 1990-1994,\n\n\n1995-2000. Using averaged data should reduce problems due to idiosyncratic shocks to\n\n\nan industry in any given year or exchange rate fluctuations.  We restrict the sample to be\n\n\na balanced sample. This has an advantage in making the data directly comparable across\n\n\nperiods, but a disadvantage because we are excluding new trade that may be more or less\n\n\n8 Here we dropped two industries that did not have enough observations to estimate a distance coefficient.\n\n\n14", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002587", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "aggregate bilateral trade data", "probe_tag": "confusion", "probe_score": 0.6836965680122375, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 523, "end": 553, "key": "prwp:002587:13:1:0", "source": "camp2", "luna_reason": "Existing aggregate trade data are used to estimate and compare distance elasticities.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "data on the value of bilateral trade", "probe_tag": "keep", "probe_score": 0.9319796562194824, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 711, "end": 747, "key": "prwp:002587:13:1:1", "source": "camp2", "luna_reason": "Existing bilateral trade data are used to estimate industry distance elasticities.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"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": " for these tasks. We specified a list of sanitation measures, and asked the Gram\nPanchayat members who was responsible for carrying them out, and whether these were ever\ndone in the village. Tables 1 and 2 summarize this information. To collect the direct\nobservation data, our investigators first constructed detailed maps of the village showing all\nthe roads and paths. They then assessed the condition of each road along the dimensions\ndetailed in Table 3, and noted the characteristics of the inhabitants by the side of that road. In\nparticular they noted the caste and religion of the inhabitants, whether they were GP\nmembers, and whether important village institutions such as schools, health centers, were by\nthe side of the road. Compared with the respondents’ reported perception of whether a task\nwas ever done, the direct observation data give us much more objective information on the\nactual sanitary conditions on the ground.\n\nIn addition to the sanitation outcomes, we have additional village-level information, collected\nin a previous survey conducted the previous year in 2002. This information was collected\nfrom the official census (population, literacy, area), interviews with GP members (whether\nthe village is the GP headquarter and whether the village is the GP president’s village), and\nfrom participatory appraisal methods (the fraction Scheduled Castes/Tribes in the village, the\nfraction land owned by the upper castes, and oligarchy – the extent to which the GP members\ncontrol the important functions in the village.)\n\n**4.** **Analytical Methods**\n\nTo analyze the determinants of information about GP responsibilities we use the village level\ndata. To examine the inter- and intra-village distribution of sanitation outcomes we use the road\nlevel dataset onto which we merged the village level information. Hence, the unit of observation\n\n7 The state-wise break up is AP: 69 villages, KA: 182 villages, KE: 126 wards; TN 129 villages.\n\n\n4", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003998", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "direct\nobservation data", "probe_tag": "confusion", "probe_score": 0.5249890685081482, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 249, "end": 272, "key": "prwp:003998:6:1:0", "source": "camp2", "luna_reason": "Investigators collected and generated the observation data through this exercise.", "drop_reason": "production", "specificity": "vague"}, {"text": "village level\ndata", "probe_tag": "keep", "probe_score": 0.9516411423683167, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1659, "end": 1677, "key": "prwp:003998:6:1:3", "source": "camp2", "luna_reason": "Village-level data are explicitly used as the basis for determinant analysis.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": " 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": ">\ncorrelated with satellite-derived indicators that affect the probability of selection of the village\n\ninto the HIES. We therefore adjust the weights based on the predicted probability of the\n\nvillage being sampled in HIES, based on satellite indicators available for all villages (Horvitz\n\nand Thompson, 1952; Wooldridge, 2002). This probability is obtained from the following\n\nprobit model:\n\n\n_INHIESv_ = _α_ + _βlassov_ + _λv,_ (4)\n\n\nwhere _INHIESv_ is a binary indicator for whether village _v_ is sampled into HIES, and _lassov_\n\nrepresents all LASSO-selected variables from the Poisson model. We estimate this model\n\nusing data for all 1,360 villages in the 55 sub-districts. The predicted probability of the\n\nvillage selection into the HIES, _INHIES_ - _v_ is used for correcting the weights in the following\nway : _V illagePopulation X_ <u>1</u> _INHIES_ - _v_ <sup>.</sup>\nUsing these above two sets of weights, we estimate the model in HIES-villages. Then,\n\nwe predict out-of-sample densities for the remaining 946 non-HIES villages and report out\nof-sample accuracy measures by comparing them with the actual census density. To provide\n\nadditional context, we compare the accuracy of this model to predictions from a similar census\nbased model and with density estimates from the publicly available “top-down” population\n\nproducts. Further, we calculate population count predictions by multiplying these density\n\npredictions with village-level area, and report their accuracy with respect to the census pop\nulation.\n\n\n17 Out-of-bag _R_ 2 is an out-of- sample statistic that refers to the average variance explained by the random\nforest predictions, across all villages, when", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007669", "page": 11, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "satellite indicators", "probe_tag": "confusion", "probe_score": 0.6548032164573669, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 234, "end": 254, "key": "prwp:007669:11:1:0", "source": "camp2", "luna_reason": "Existing indicators are used to predict village selection probabilities and adjust survey weights.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "data for all 1,360 villages", "probe_tag": "confusion", "probe_score": 0.7435092926025391, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 630, "end": 657, "key": "prwp:007669:11:1:1", "source": "camp2", "luna_reason": "Existing village data used to estimate the probability model and correct sampling weights.", "usage_type": "declaration", "specificity": "descriptive"}]}
+{"text": "; 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": "22\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Survey|Title in full|Core topics|No. of countries|History|Data collection<br>method|Sample size|Further<br>information on<br>data and access|\n|---|---|---|---|---|---|---|---|\n|MCSS|Multi-Country<br>Survey Study on<br>Health and<br>Responsiveness|Adult health state descriptions,<br>health conditions, screening,<br>health state valuations, health<br>system responsiveness, adult<br>mortality|60 countries of all income<br>levels and worldwide, 35 in<br>HEFPI (postal surveys<br>excluded, several countries to<br>be added)|2000-2001|Face-to-face<br>interviews,<br>telephone<br>interviews,<br>postal survey|Typically<br>600-6,000<br>adults|http://apps.who.i<br>nt/healthinfo/syst<br>ems/surveydata/i<br>ndex.php/catalog/<br>mcss/about|\n|MICS|Multiple <br>Indicator Cluster<br>Survey|Population, health, and<br>nutrition, with a focus on <br>reproductive, maternal and<br>child health|108 LMIC with completed<br>surveys, 89 with available<br>data, 73 in HEFPI (MICS 5 to<br>be added, a number of earlier<br>wave surveys to be added)|Ongoing since<br>1995, first<br>HEFPI data<br>from 1999|", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007497", "page": 23, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "HEFPI", "probe_tag": "confusion", "probe_score": 0.07145678997039795, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 480, "end": 485, "key": "prwp:007497:23:0:0", "source": "camp2", "luna_reason": "Standalone table cell fragment, not an independently cited data resource.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "HEFPI data", "probe_tag": "confusion", "probe_score": 0.12765614688396454, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1089, "end": 1099, "key": "prwp:007497:23:0:2", "source": "camp2", "luna_reason": "Fragment appearing inside a table cell, not an independently used data source.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": "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": "**<u>Variables</u>** **<u>Measures</u>** **<u>Sources</u>**\n**<u>Crisis measure:</u>**\nSignificant drop in stock market returns Basis for the crisis measure is the\npercentage change in US $ national,\ntotal return, stock market indices\nrelative to the previous month. A\nmonth is counted as a crisis month if\nthe total return drops at least 2\nstandard deviations below the sample\nmean. Subsequent months are also\ncounted as crisis months until returns\nmove back into the one standard\ndeviation band around the sample\n<u>mean.</u>\n\n\n\n2 sets of crisis measures: 1) IFC\ninvestable, total return indices,\n2) MSCI total return indices. For\nboth cases, we have to use local\nsources for Romania, Slovakia\nand Romania. To convert returns\nfrom these three national indices\ninto US dollars, we use end of\nperiod data on exchange rates\nfrom the IMF's International\nFinancial Statistics (IFS).\n\n\n\n**<u>Explanatory Variables:</u>**\nUncertainty measure Monthly data of the weighted\naverage of the standard deviations of\nthe current and following year\nforecast of GDP growth across\nsurvey respondents. In January, the\nstandard deviation of the current year\nforecast is given a weight of 11/12\nwhile the standard deviation of the\nfollowing year forecasts is given a\nweight of 1/12. In February, the\ncurrent year forecast receives a\nweight of 10/12 while the follwing\nyear forecast is weighted by 2/12.\nThis scheme continues until\nDecember where a weighting of 0/12\nis given for the current year forecast\nand 12/12 for the following year\nforecast.\n\nMean growth expectations Monthly data of the weighted\naverage of the mean forecast by\nsurvey respondents of the current and\nfollowing year GDP growth. The\nweighting scheme is the same as for\nthe standard deviation.", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004188", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "International\nFinancial Statistics", "probe_tag": "keep", "probe_score": 0.9486220479011536, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 838, "end": 872, "key": "prwp:004188:31:0:1", "source": "camp2", "luna_reason": "IMF exchange-rate data are used to convert national stock returns to US dollars.", "usage_type": "evidential", "specificity": "named"}, {"text": "Monthly data", "probe_tag": "confusion", "probe_score": 0.48858898878097534, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 937, "end": 949, "key": "prwp:004188:31:0:3", "source": "camp2", "luna_reason": "Generic data phrase defines a measure without an attributed finding or concrete claim.", "drop_reason": "bare_stat", "specificity": "vague"}]}
+{"text": "</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": "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": "SRTM Digital Elevation Data Version 4; 90m <sup>2</sup> resolution (Jarvis et al., 2008)\n\n\nBuilt-up Land Cover\n\nGHSL: Global Human Settlement Layers, Built-Up Grid 1975-1990-2000-2015 (P2016);\n\n38m <sup>2</sup> resolution (Pesaresi et al., 2015)\n\n\nNormalized Difference Vegetation Index/NDVI\n\nLandsat 8 Collection 1 Tier 1 32-Day NDVI Composite; 30m <sup>2</sup> resolution\n\n\nNormalized Difference Water Index/NDWI (U.S. Geological Survey)\n\nLandsat 8 Collection 1 Tier 1 Annual NDWI Composite; 30m <sup>2</sup> resolution (U.S. Geolog\nical Survey)\n\n\nLand Use\n\nCopernicus Global Land Cover Layers: CGLS-LC100 Collection 3; 100m <sup>2</sup> resolution\n\n(Buchhorn et al., 2020)\n\n#### Appendix B Additional Tests\n\n\nThis section provides additional computations to investigate possible effects of data\n\ncollection and of choice of different spatial units.\n\n\nB.1 Heterogeneity in Employment Data Collection\n\n\nThe employment data used throughout this work is collected either via travel surveys\n\nor via population and firm censuses <sup>16</sup> . This introduces noise to the data both with respect\n\nto heterogeneity of polygon sizes within which the data was originally collected but also in\n\nterms of what specific employment is measured. Travel surveys overall typically include any\n\ntype of employment, whereas firm censuses are generally limited to collecting information\n\non formal employment and do not capture employment within the informal sector. As the\n\ninformal sector represents a substantial part of jobs within developing countries (Bryan et al.,\n\n2020), omitting this might introduce a noticeable measurement issue within the training of the\n\nalgorithms. In order to test this, we split the", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002432", "page": 40, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Normalized Difference Water Index/NDWI", "probe_tag": "confusion", "probe_score": 0.6646755933761597, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 376, "end": 414, "key": "prwp:002432:40:0:1", "source": "camp2", "luna_reason": "Named NDWI dataset is identified as a geospatial input source.", "usage_type": "declaration", "specificity": "named"}, {"text": "Employment Data", "probe_tag": "drop", "probe_score": 0.046460848301649094, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 875, "end": 890, "key": "prwp:002432:40:0:5", "source": "camp2", "luna_reason": "Existing employment data are analyzed for collection heterogeneity and measurement effects.", "usage_type": "evidential", "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 6 shows the results from two estimations: one using annual data and the other using twoyear averages. <sup>7</sup> [^7: The simple two year average is performed for each of the variables; the first two-year average covers the period 1999-2000\nand the last two-year average the period 2007-08. CA is performed on these average values.] As noted earlier, the objective of using the two-year averages is to smooth out business\ncycle effects. Clearly, an even longer period would have been desirable from the perspective of purging\nbusiness cycle effects, but limitations in terms of the number of available data points prevented us from\ndoing so. The estimated coefficient in the multinomial regressions reflects the likelihood of being in one\ncluster relative to a reference cluster. As noted earlier, the reference group used is the lower growth\nand higher vulnerability (V) cluster, which is the worst of all possible outcomes.\n\n\n**Table 6. Multinomial Logit Estimations based on Growth and Vulnerability Clusters** 1/\n\n|Col1|Col2|Col3|VULNERABILITY|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n||||**Annual Data**|**Annual Data**|**Two-Year Averages**|**Two-Year Averages**|\n||||**Lower**|**Higher**|**Lower**|**Higher**|\n|Trade openness; exports plus imports (% of GDP)<br>Export and import growth rates, difference in %<br>Financial openness; FX assets & liabilities (% of GDP)<br>FDI, net, % of GDP<br>Counter-cyclical fiscal policies 2/<br>Monetary tightening; Δ in velocity<br>Exchange rate flexibility<br>Capital controls<br>Initial level of income, share", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004776", "page": 11, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "annual data", "probe_tag": "confusion", "probe_score": 0.764411211013794, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 58, "end": 69, "key": "prwp:004776:11:0:0", "source": "camp2", "luna_reason": "Annual data are used directly in estimations reported in Table 6.", "usage_type": "evidential", "specificity": "vague"}, {"text": "Annual Data", "probe_tag": "drop", "probe_score": 0.034862589091062546, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1108, "end": 1119, "key": "prwp:004776:11:0:2", "source": "camp2", "luna_reason": "Standalone table header identifying an estimation-data column", "drop_reason": "table_artifact", "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": " OECD for more than 40 years as the OECD group.\n\n\nThe rest of countries are classified by region and income. We use the average of GDP per capita (World Bank\n\n\n2017e) over 1985–2014 to break the sample into income quintiles. Table B.1 shows the country list by region and\n\n\nincome quintile groups, indicating their inclusion in the samples by type of analysis (descriptive and statistical),\n\n\ndata source (PWT, GTAP, and WDI), and other characteristics (oil rent and population).\n\n\n1 Heavy dependence is defined as reliance on oil production for more than 32 percent of GDP on average during 2006-15, which is 90th –\n100th percentile among 98 countries with positive oil rents (World Bank 2017j); Angola (45%), Congo, Rep. (46%), Equatorial Guinea\n(42%), Gabon (32%), Iraq (52%), Kuwait (47%), Libya (54%), Oman (37%), Saudi Arabia (44%), and South Sudan (45%).\n\n\n12", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001996", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "GTAP", "probe_tag": "confusion", "probe_score": 0.11710835248231888, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 411, "end": 415, "key": "prwp:001996:13:1:1", "source": "camp2", "luna_reason": "Named dataset declared as a data source for sample analyses.", "usage_type": "declaration", "specificity": "named"}, {"text": "WDI", "probe_tag": "drop", "probe_score": 0.020093610510230064, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 421, "end": 424, "key": "prwp:001996:13:1:2", "source": "camp2", "luna_reason": "Named World Development Indicators source used for sample analyses.", "usage_type": "declaration", "specificity": "named"}]}
+{"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": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAn ageing population coupled with a growing\neconomy causes labour shortages. Despite\nfalling number of available workers, the Polish\neconomy is growing steadily, as it modernises\nand converges to the level of development of\nold EU Member States. Despite the Covid-19\npandemic, real GDP growth averaged 3.7%\nduring the last decade. As a result, due to\nsteady demand for labour since 2019, the\nharmonised unemployment rate in Poland\nhas not exceeded 4%, oscillating around\n3% in recent years. According to Eurostat\ndata, in September 2023, harmonized\nunemployment in Poland reached 2.8%, the\nsame level as Malta. In the entire EU, only the\nCzech Republic reached a lower level: 2.7%.\nVacancies stood at record heights before\n\n\n\nthe refugee inflow. Before the refugee\ninflux, the share of companies reporting\nvacancies in the quarterly NBP survey\nstood at 49% in Q4 2021 – the highest\nlevel on record. This helps to explain the\nrelative ease of the refugees' labour market\ninclusion in terms of employment rates.\nAfter refugee inflow, the share of firms\nreporting vacancies stopped growing and\ndeclined slightly to 45% in Q3 2023. This\npartly indicates the fact that many refugees\nentered the labour market, and partly a\ncyclical economic slowdown. Despite that,\nthe labour market remains relatively strong.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 9.** Change in the number of workers registered for social security with Ukrainian citizenship by NACE sector between end of Q3\n2023 and 2021\n\n\nThousands\n\n\n\n\n\nManufacturing\n\n\nAccommodation and food service activities\n\n\nWholesale and retail trade; repair of motor vehicles and motorcycles\n\n\nHuman heatlh and social work activities\n\n\nAdministrative and support service activities\n\n\nEducation\n\n\nInformation and communication\n\n\nProfessional, scientific and technical activities\n\n\nPublic administration and defense; compulsory social security\n\n\nConstruction\n\n\nFinancial and insurance activities\n\n\nAgriculture, forestry and fishing\n\n\nReal estate activities\n\n\nWater supply: sewerage, waste management and", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Eurostat\ndata", "probe_tag": "keep", "probe_score": 0.9993, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 580, "end": 593, "key": "sample:jad_paddy_docs:000007:9:0:0", "source": "gold", "luna_reason": null}, {"text": "quarterly NBP survey", "probe_tag": "keep", "probe_score": 0.9884, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 899, "end": 919, "key": "sample:jad_paddy_docs:000007:9:0:1", "source": "gold", "luna_reason": null}]}
-{"text": " Poland of\n38%. Even before becoming refugees, they\nwould have required support to enter the\nworkforce and now, in the host country,\nthey would be likely to benefit from such\nhelp even more. Some of them may be\ndiscouraged by not having been able to find\na job, others may be marginally attached\nworkers who fell outside the labour\nforce, but have some desire and ability to\nreturn to work.\n\n\n\n**Chart 25. Ukrainian refugees’ employment rate in the 18-64 age group by previous**\n**status in Ukraine**\n\n\n91%\n\n\n\nHousehold\nresponsibilities\n\n\n\nOthers Studying Employed Self-employed\n\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey conducted in May and June 2024.\n\n\n\n29 A dummy variable that takes the value of 1 in case of none, beginner, or intermediate language knowledge, and 0 for other levels has been regressed against a\nnumber of explanatory variables.\n\n\n34 35", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 17, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9714944958686829, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 624, "end": 641, "key": "jad_paddy_docs:000001:17:3:0", "source": "camp2", "luna_reason": "Named survey cited as the basis for the employment-rate chart.", "usage_type": "evidential", "specificity": "named"}]}
+{"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": "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": " potential GDP should\nbe higher by around 0.9-1.35% due to\nrefugees contributions. <sup>44</sup> [^44: Note that long term refers to the time when the economy fully adjusts with no additional shocks. We do not model the current refugees from Ukraine\nchildren growing up and entering the labour market.]\n\n\nOur results are consistent with the\nprevious, similar studies. In estimating\nGDP impacts we take an approach that\nis most similar to the previous studies of\nthe pre-2022 Ukrainian migrants by NBP\neconomists (Gradzewicz, Jabłonowski,\nSasiela, and Żółkiewski, 2021; Strzelecki,\nGrowiec, and Wyszyński, 2022), but unlike\nthe previous Oxford Economics and ours\nimpact estimates of Ukrainian refugees\n(Urban, 2022; Deloitte, 2022) we do not\nallow for the possibility of a positive\nproductivity shock, because there is little\ndata to credibly estimate its size. Below,\nwe summarise impacts yielded by these\nstudies. As studies were done under\ndifferent assumptions on the number of\n\n\n\n\n\n\n\n\n\n41  Aggregate region in model consisting of Ukraine, Russia, Belarus, Moldova, Czechia, Slovakia, Hungary, Romania and Bulgaria.\n42  In other words it was assumed that money that would be spent e.g. through credit action for investments in Eastern Europe were spent for\nconsumption in Poland.\n\n\n34\n\n\n\n43  Data from forecast of Ministry of Finance from October 2023, <u>[Wytyczne dotyczące wskaźników makroekonomicznych - Ministerstwo Finansów - Portal](https://www.gov.pl/web/finanse/wytyczne-sytuacja-makroekonomiczna)</u>\n<u>[Gov.pl (www.gov.pl).](https://www.gov.pl/web/finanse/wytyczne-sytuacja-makroekonomiczna)</u>\n44  Note that long term refers to the time when the economy fully adjusts with no additional shocks", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Data from forecast of Ministry of Finance", "probe_tag": "keep", "probe_score": 0.973, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1295, "end": 1336, "key": "sample:jad_paddy_docs:000007:17:3:0", "source": "gold", "luna_reason": null}]}
-{"text": " for\nsome cautious inference with 4.2 million\nPolish citizens in mid-2022 and 6.2 million\nin mid-2024. This has been combined with\naverage salaries in 128 occupational groups\nin GUS data for October 2022 (the most\nrecent data). Over the two-year period from\nQ2 2022 to Q2 2024, following the arrival\nof Ukrainian refugees, the occupational\ngroup distribution of Polish citizens shifted\n\n\n\n**Chart 30. Polish citizens occupational distribution change by salary bracket, Q2 2022 and Q2 2024**\nQ2 2022 distribution, Q2 2024 distribution, and percentage point changes between them\n\n\n-1.8 pp.\n\n\n\n\n\n\n\n\n\n<= 4,000 (4,000; 6,000] (6,000; 8,000] (8,000; 10,000] - 10,000\n\n\n\nQ2 2022 Q2 2024\n\n\n41\n\n\n\n30 Unfortunately, GUS data for these time periods and poviat level include the enterprise sector (firms that employ 10 or more persons) and public sector, which is\nmost of the labour market, but not the total economy.\n\n\n40\n\n\n\nSource: Deloitte own elaboration based on ZUS data and GUS data on salaries of 128 3-digit occupations in\nOctober 2022. Note that ZUS data is not comprehensive.", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 20, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "ZUS data", "probe_tag": "keep", "probe_score": 0.9232459664344788, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 956, "end": 964, "key": "jad_paddy_docs:000001:20:4:0", "source": "camp2", "luna_reason": "ZUS data underlies the charted occupational distribution analysis.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": ". <sup>11</sup> [^11: According to the social security data until 30th September 2023.]\nWhile public data does not distinguish\nbetween refugees entering these sectors\nand pre-2022 Ukrainian workers changing\njobs, it is largely consistent with the MSNA\nPoland 2023 survey, in which the most\nrefugees are employed in manufacturing\n(14%), accommodation and food service\n(12%), and trade and repair (6%).\n\n\nUkrainian refugee households in Poland\n\nto the MSNA Poland 2023 survey, 20% of\nUkrainian refugee households earn less\nthan 3 000 PLN, 41% earn between 3 000\nand 6 000 PLN, and 12% earn more than\n6 000 PLN, while 27% of respondents\npreferred not to answer. That said, the\nstandard of living of Ukrainian refugees\nmay be significantly lower than that of\nnative residents, even at similar incomes,\ndue to their lack of housing, which in\nPoland is usually occupant-owned.\n\n\n\n**Inflow of Ukrainian refugees into**\n**Poland**\nThe beginning of the full-scale war in\nUkraine in February 2022 resulted in large\nflows of refugees, reaching more than\n6 million globally. <sup>3</sup> [^3: As of December 2023, according to UNHCR, based on governmental sources <u>[Situation Ukraine Refugee Situation (unhcr.org)](https://data.unhcr.org/en/situations/ukraine)</u>] Much of this exodus\nhappened through the Polish border.\nAs of October 2023, almost 1 million\nUkrainian refugees were living in Poland <sup>4</sup> [^4: According to the active PESEL UKR database.]\n(Chapter 1). In the past decade, Poland\nexperienced large labour migration from\nUkraine. The number of workers with\nUkrainian citizenship that registered for\nsocial security (this data does not include\nthose working in the shadow economy\nor some minor cases that do not require\nregistration) grew from just 33 thousand interm", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "social security data", "probe_tag": "keep", "probe_score": 0.9995, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 39, "end": 59, "key": "sample:jad_paddy_docs:000007:3:1:0", "source": "gold", "luna_reason": "Existing social security data are cited as the source for labor-market claims.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "MSNA Poland 2023 survey", "probe_tag": "keep", "probe_score": 0.9955, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 450, "end": 473, "key": "sample:jad_paddy_docs:000007:3:1:1", "source": "gold", "luna_reason": null}, {"text": "PESEL UKR database", "probe_tag": "keep", "probe_score": 0.9866, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1432, "end": 1450, "key": "sample:jad_paddy_docs:000007:3:1:2", "source": "gold", "luna_reason": null}]}
-{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nThe influx of refugees into Poland after the\nRussian invasion of Ukraine was large, with\nnearly 16 million border crossings <sup>18</sup> [^18: UNHCR data, <u>[https://data2.unhcr.org/en/situations/ukraine](https://data2.unhcr.org/en/situations/ukraine)</u>] from\nUkraine until the end of September 2023 and\ncumulatively 1.7 million PESEL registrations.\nIt must be noted that such a rapid population\nmovement of that scale was not seen in\nEurope since World War II. Not everyone\n\n\n\nstayed in Poland, however. A large number of\nthese refugees later returned to Ukraine or\nmoved to other European countries.\nBy October 2023, the remaining active PESEL\nUKR numbers stood at less than 1 million,\nwhile the border movement balance between\nPoland and Ukraine at 2.5 million.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 4.** Age and gender structure of refugees based with active PESEL numbers in\nOctober 2023\n\n\n|Col1|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|The s<br>imple<br>of for|udden<br>menta<br>eigner|drop in<br>tion of t<br>status a|registe<br>he 30-d<br>fter a r|red num<br>ay dead<br>egistere|bers is<br>line for<br>d depa|due to<br>revoca<br>rture fro|the<br>tion<br>m|Col18|\n|---|---|---|---|---|---|---|---|---|---|---|", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 7, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR data", "probe_tag": "keep", "probe_score": 0.9964, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 220, "end": 230, "key": "sample:jad_paddy_docs:000007:7:0:0", "source": "gold", "luna_reason": null}]}
-{"text": "Increased competition on the labour\nmarket could partially offset benefits\nfrom refugees. Although (due to a tight\nlabour market) increase in labour force\nis almost entirely absorbed into working\nforce, there should be slight increase\nin unemployment rate. Ultimately, it is\nestimated that it was higher by 0.14-0.25\npp. in 2022 and by 0.18-0.3 pp in 2023\nwhich corresponds to respectively 24-42\nthousand and 33-54 thousand additional\npeople being unemployed <sup>45</sup> [^45: Based on number of economically active people in III quarter of 2023 according to labour market survey.] . In the long\nrun, the unemployment rate should remain\nhigher by 0.15-0.3 pp. Because of that, it is\nestimated that growth of real wages was\nslower in 2022 and 2023. It is estimated\nthat due to the influx of refugees, real\nwages were lower in 2022 by 0.45-0.85%\nand in 2023 by 0.65-1.15%. Although in\neffect this is negative, it also means lower\ninflationary pressure from the labour\nmarket in the short term. Long-term real\nwages should be around 0.55-1.0% lower\nthan in a scenario without refugees.\nThat said, the actual labour market\neffect is likely to be null as evidenced by\neconometric studies (Gromadzki and\nLewandowski, 2023; Peri, 2014), which are\nelaborated on in Chapter 4. Gromadzki\nand Lewandowski (2023) in the early\nmonths of 2022 find no effect of Ukrainian\nrefugees on earnings, employment, and\nunemployment rate of natives and other\nimmigrants, except an actual slight positive\nimpact on the wages of native women.\n\n\nEven with the increase in unemployment\nand lower real wages, an increase in labour\nforce means a higher wage pool, which\nmeans higher tax income.\n\n\n\nMoreover, boosts in private consumption\nboth due to increase in population as\nwell as higher average spending rates\nmeans that refugees increased state\nincome from taxation on consumption.\nThese effects will be strengthened by\ninflux of capital from", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 18, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "labour market survey", "probe_tag": "keep", "probe_score": 0.9911, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 561, "end": 581, "key": "sample:jad_paddy_docs:000007:18:0:0", "source": "gold", "luna_reason": null}]}
-{"text": ", and Zenou, 2010;\nÅslund and Rooth, 2007), and Switzerland\n(Müller, Pannatier, and Viarengo, 2022),\nas well as the previously described crosscountry study. This could in principle stem\nfrom scarring on an individual level from\nweak initial opportunities, or persistently\nweak local labour market combined with\nimperfect geographic mobility. The effects\nare hard to disentangle, while Åslund and\nRooth (2007) find some indication that both\nphenomena are at play, Godøy (2017) finds\nevidence only for persistently weak local\nlabour markets.\n\n\n##### Migrants and refugees dispersed away from ethnic enclaves experience weaker labour market inclusion outcomes, and vice versa.\n\nCo-nationals can provide important\ninformation to refugees about employment\nopportunities. In Germany, Battisti, Peri,\nand Romiti (2022) found that immigrants\ninitially located in places with more conationals, as well as well as refugees and\nrepatriated ethnic Germans dispersed to\nsuch places, are more likely to be employed\nin the first 3 years. It was found, however,\nthat these groups had lower probability of\ninvesting in human capital. In Swiss data,\nMartén, Hainmueller, and Hangartner\n(2019) found that refugees dispersed to\nlocations with more co-nationals are more\nlikely to find work, especially in the first 3\nyears. In Danish data, Damm (2014) found that\nhigher skill levels of non-Western immigrant\nmen in an area raises employment probability\nof refugee men, while higher employment\nrates of their co-national men raises their\nearnings. Also in Danish data, Damm (2009)\nfound that larger size of ethnic network in an\narea increases earnings of refugees.\nIn Swedish data, Edin, Fredriksson,\nand Aslund (2003) found that refugees\ndispersed to areas with more co-nationals\nexperience higher earnings.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nKingdom,", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Swiss data", "probe_tag": "keep", "probe_score": 0.9927, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1120, "end": 1130, "key": "sample:jad_paddy_docs:000007:12:2:0", "source": "gold", "luna_reason": null}, {"text": "Danish data", "probe_tag": "keep", "probe_score": 0.9708, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1307, "end": 1318, "key": "sample:jad_paddy_docs:000007:12:2:1", "source": "gold", "luna_reason": null}]}
-{"text": ">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": "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": ", to account\nfor spending of savings from Ukraine, data\nfrom the National Bank of Ukraine on\ncash withdrawals and retail transactions\nfrom Ukrainian bank cards in Poland was\nused <sup>55</sup> and then calibrated to data for\nprivate consumption in Poland. Additionally,\nthe same data was used to calibrate the\nnegative shock to investment in Eastern\nEurope.\n\n\n\nFor productivity two options were tested.\nFirstly, neutral impact: no shock to\nproductivity. Secondly, lower productivity of\nworkers from Ukraine negatively impacting\ntotal labour productivity. These shocks were\ncalibrated to match the difference in data\nbetween refugees income from labour in\nUNHCR survey and average wage in Poland\nfrom Statistics Poland weighted by refugees\nshare in total workforce.\n\n\nAs one period in the model is set to one\nyear and refugees started coming to Poland\nby the end of February 2022 it was assumed\nthat their impact on economy started being\nfelt starting from II quarter of the year.\nAs such shocks were set so that ¾ of shocks\nwere calibrated to data from 2022 and ¼ to\ndata for 2023 <sup>56</sup> .\n\n\n\n51  Computational General Equilibrium.\n52  Global Trade Analysis Project, <u>[GTAP Models: Current GTAP Model (purdue.edu).](https://www.gtap.agecon.purdue.edu/models/current.asp)</u>\n53  Region combined from: Russia, Belarus, Ukraine, Moldova, Czechia, Slovakia, Hungary, Romania, and Bulgaria.\n54  All shocks are percent deviations.\n55 <u>[Oversight of financial market infrastructures (bank.gov.ua)](https://bank.gov.ua/en/payments/oversite)</u>\n56  E.g. for total increase in number of workers of 350 thousand around 262.5 thou. was set to have happened in 2022 while rest in 2023.", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 21, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data\nfrom the National Bank of Ukraine", "probe_tag": "keep", "probe_score": 0.9987, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 51, "end": 89, "key": "sample:jad_paddy_docs:000007:21:1:0", "source": "gold", "luna_reason": null}, {"text": "data for\nprivate consumption in Poland", "probe_tag": "keep", "probe_score": 0.9774, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 216, "end": 254, "key": "sample:jad_paddy_docs:000007:21:1:1", "source": "gold", "luna_reason": null}, {"text": "UNHCR survey", "probe_tag": "keep", "probe_score": 0.9653, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 655, "end": 667, "key": "sample:jad_paddy_docs:000007:21:1:2", "source": "gold", "luna_reason": null}, {"text": "data from 2022", "probe_tag": "keep", "probe_score": 0.9704, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1043, "end": 1057, "key": "sample:jad_paddy_docs:000007:21:1:3", "source": "gold", "luna_reason": null}]}
+{"text": "\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": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**The only reliable timeseries of the**\n**number of Ukrainians in Poland over**\n**the past decade is social insurance**\n**data on insured Ukrainian nationals,**\n**though it accounts only for workers.**\nThe focus on workers rather than on\nthe entire group does not change much\nin the data from before February 2022,\nas the previous influx consisted mainly\nof Ukrainians seeking employment in\nPoland. However, the actual number\nof employed Ukrainian nationals must\nhave been higher. First, certain types\nof legal work often undertaken by\ntemporary employees do not require\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 4. Age and gender structure of Ukrainian refugees**\n\n\n\n**Most of the refugees from Ukraine**\n**currently living in Poland are women**\n**and children, though over half of**\n**the total population is of working**\n**age.** The best population data available\nis the regularly updated active PESEL\ndatabase. <sup>4</sup> [^4: Available in the repository maintained by the government <u>https://dane.gov.pl/pl/dataset/2715</u> as well as UNHCR data portal <u>https://app.powerbi.com/</u>\n<u>view?r=eyJrIjoiODhkOGZiMzctZTliMi00NzA5LTgyM2QtZGZhM2IwZjBiZDk2IiwidCI6ImU1YzM3OTgxLTY2NjQtNDEzNC04YTBjLTY1NDNkMmFmODBiZSIsImMiOjh9</u>] According to the registry, 61.5%\nof the registered are women and 38.5%\nare men. The database also includes the\nage of PESEL UKR holders, which indicates\nthat over half (57.4%), i.e. more than\n560 thousand people, are of working age\n(18-65). While the male and female shares\nof people below 18 years of age (20% and\n19%, respectively) and 66+ (1%", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data on insured Ukrainian nationals", "probe_tag": "keep", "probe_score": 0.9623, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 198, "end": 233, "key": "sample:jad_paddy_docs:000001:4:0:0", "source": "gold", "luna_reason": null}, {"text": "PESEL\ndatabase", "probe_tag": "keep", "probe_score": 0.9643, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1020, "end": 1034, "key": "sample:jad_paddy_docs:000001:4:0:1", "source": "gold", "luna_reason": null}]}
-{"text": " (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's Doctoral\n\n\n\n30%\n\n\n\nLower\nsecondary or\n\nbelow\n\n\n\nSource: Survey data, SAG estimates\n\n\n\n**11**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Survey data", "probe_tag": "keep", "probe_score": 0.9985, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 130, "end": 141, "key": "sample:jad_paddy_docs:000010:10:1:0", "source": "gold", "luna_reason": null}, {"text": "Survey data", "probe_tag": "keep", "probe_score": 0.9994, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 309, "end": 320, "key": "sample:jad_paddy_docs:000010:10:1:1", "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": "%\n\n\n\n\n\n\n\n62%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\nNote: For comparability, employment rates for host countries have been recalculated assuming a similar gender distribution to that of refugees\n\n\nSource: ILO, survey data\n\n\n14. The employment rate is defined as the number of employed or self-employed individuals of working age (15-64) as a share of\nthe total number of people in this age group\n15. The labor force is defined as the number of people that are either employed or unemployed\n\n\n**10**", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "ILO, survey data", "probe_tag": "confusion", "probe_score": 0.8690335750579834, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 278, "end": 294, "key": "jad_paddy_docs:000010:9:1:0", "source": "camp2", "luna_reason": "ILO survey data is cited as the source for employment-rate figures.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## Executive summary\n\n\n##### Progress in market integration\n\n**Ukrainian refugees have been**\n**increasingly successful in terms of**\n**labour market integration.** The large\ninflux of refugees since February 2022,\nhas further increased and changed the\ndemographics of the already significant\nUkrainian migrant population in Poland.\nRefugees from Ukraine are primarily\nwomen and children, with over 67% of\nfemale-headed households. Poland was\nquick to open its labour market to refugees\nfrom Ukraine, who – despite difficulties\n\n- surprisingly promptly began their\neconomic integration and soon supported\nthemselves primarily from employment.\nIn the past year, refugees’ employment\nrate grew from 61% to 69%, with the\nmedian net wage rising from PLN 3,100 to\nPLN 4,000 and narrowing the gap to the\nmedian net wage in the entire economy.\n**As Ukrainian refugees entered the**\n**labour market, the economy adapted,**\n**resulting in more specialization and**\n**higher productivity.** In a simplistic\nsupply-demand framework, the influx\nof Ukrainian refugees would have had\na negative impact on Polish workers\nemployment or caused a decline in real\nwages. However, this has not occurred.\nFirst, Polish citizens employment rates\nhave grown, and unemployment rates\nhave fallen. Second, poviats in which the\nemployment share of Ukrainian refugees\nhas grown by 1 pp. saw 0.5 pp. higher\nemployment rates among Polish citizens,\nand 0.3 pp. lower unemployment rates.\nThird, there is no evidence of lowered\nwages, in fact the limited available data\nindicates that a higher share of Ukrainian\nrefugees in a poviat may have caused local\nwages to rise. Such findings are in line with\nacademic literature, which documents\na positive impact of migrants on native\nworkers. With foreigners entering the\n\n\n04\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n*", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 2, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "limited available data", "probe_tag": "confusion", "probe_score": 0.8446, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1588, "end": 1610, "key": "sample:jad_paddy_docs:000001:2:0:0", "source": "gold", "luna_reason": null}]}
-{"text": "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": " 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": " security administration, also known as Social Insurance Institution.\n\n\n44\n\n\n\nChart 1. Poland-Ukraine border movement balance and registered/active PESEL data\b 07\nChart 2. Ukrainians registered for social insurance\b 07\nChart 3. Number of Ukrainians registered in Poland for social insurance by sex\b 08\nChart 4. Age and gender structure of Ukrainian refugees\b 09\nChart 5. Ukrainian refugee households’ demographic composition\b 10\nChart 6. Local population shares of Ukrainian refugees\b 11\nChart 7. Income of Ukrainian refugee households by source\b 12\nChart 8. Ukrainian refugee household incomes from Poland and Ukraine in 2023 and 2024\b 12\nChart 9. Ukrainian refugee labour status 15\nChart 10. Ukrainian refugee median net wage 15\nChart 11. Main occupational groups of Ukrainian refugees, pre-war Ukrainians, other foreigners,\n\nand Polish citizens registered for social insurance, Q2 2022 and Q2 2024 (civilian, non-agricultural)\b 16\nChart 12. Ukrainian refugee wages relative to Polish citizens in the same employee-cells\b 17\nChart 13. Polish citizens and Ukrainian refugees’ employment rates by age group\b 18\nChart 14. Ukrainian refugee median net wage estimates in Q2 2024\b 19\nChart 15. Ukrainian refugees wages median net wage by age group\b 20\nChart 16. Median net wages of Ukrainian refugees median net wage by sector \b 21\nChart 17. Gross domestic product growth paths with and without Ukrainian refugees\b 23\nChart 18. Over-qualification rates by citizenship\b 27\nChart 19. Tertiary education and corresponding occupational groups shares\b 28\nChart 20. Ukrainian refugees median net wages by educational attainment\b 28\nChart 21. Share of regulated professions by citizenship and legal status, Q2 2024\b 29\nChart 22. Econometric model of determinants of Ukrainian refugees’ net wages\b 32\nChart 23. Average number of months since arrival of a Ukrainian refugee by Polish language fluency\b 33\nChart 24. What Ukrainian refugee groups have weakest Polish language fluency?\b 33\nChart 25. Ukrainian refugees’ employment rate in", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 22, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "PESEL data", "probe_tag": "confusion", "probe_score": 0.6316, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 148, "end": 158, "key": "sample:jad_paddy_docs:000001:22:1:0", "source": "gold", "luna_reason": null}]}
-{"text": " net wage of\na Ukrainian refugee (estimated based on\nthe SEIS UNHCR survey in chapter 2) from\n80% to 98% of the median in the economy\nas a whole (or from 80% to 93% according\nto Ukrainian refugee’s median in the NBP’s\n2024 survey), almost closing the gap to the\neconomy as a whole in these terms. It is in\nfact higher than the PLN 500 median net\nwage premium of the pre-war Ukrainian\nmigrants over Ukrainian refugees in the\nNBP (2024) survey, even though 68% of the\nformer and only 28% of the latter said they\nhad a high level of fluency in Polish.\n\n\n31\n\n\n\nprofessions (physicians, dentists, nurses,\nand midwives) have opened to migrants\nand refugees to reduce shortages, and\nwhile the shares for all of them stand at\njust 0.9% compared to 1.9% for Polish\ncitizens, the gap is actually very narrow for\nphysicians and dentists, who constitute\n0.7% of Ukrainian refugees and 0.8% of\nPolish citizens. In legal professions (legal\ncounsels, barristers, notaries, and bailiffs),\nthe gap remains wide, although in addition\nto occupational licensing, the likely causes\nmay be the differences between the Polish\nand Ukrainian legal systems as well as\nnew entrants’ struggles with attracting\nclients due to advertising restrictions. In\neffect, just 0.02% of Ukrainian refugees\nwork in legal professions, compared to\n0.4% of Polish citizens. There are also\nhigh contrasts across the remaining\nregulated professions, which employ\n0.8% of Ukrainian refugees and 3.3% of\nPolish citizens. These are construction\nengineers (0.02% Ukrainian refugees),\npharmacists (0.01%), and psychologists\n(0.09%), compared to the following shares\nfor Polish citizens: 0.26%, 0.19%, and 0.18%,\nrespectively.\n\n\n\n**One of the", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 15, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9287, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 57, "end": 74, "key": "sample:jad_paddy_docs:000001:15:3:0", "source": "gold", "luna_reason": "Survey data estimates refugee wages and supports the reported comparison.", "usage_type": "evidential", "specificity": "named"}, {"text": "NBP’s\n2024 survey", "probe_tag": "confusion", "probe_score": 0.533, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 212, "end": 229, "key": "sample:jad_paddy_docs:000001:15:3:1", "source": "gold", "luna_reason": null}, {"text": "NBP (2024) survey", "probe_tag": "confusion", "probe_score": 0.0598, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 424, "end": 441, "key": "sample:jad_paddy_docs:000001:15:3:2", "source": "gold", "luna_reason": null}]}
+{"text": "\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 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": " 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": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nImportantly, most of the income of\nUkrainian nationals living in Poland, both\nrefugees and pre-2022 migrants, comes\nfrom their work. Our calculations based\non the UNHCR MSNA Poland 2023 survey\nresults show that 80% of refugee income\ncomes from employment, with other\nsources on average playing a much lesser\nrole. The income brackets presented in the\nsurvey show that 20% of households earn\nless than 3000 PLN, 41% earn between\n3,000 and 6,000 PLN and 12% earn more\nthan 6,000 PLN, while 27% of respondents\npreferred not to answer. Meanwhile, in the\nNBP (2023) survey conducted in November\n2022 the net income of refugees oscillated\nbetween 2,000 and 3,000 PLN, while the\nnet income of pre-2022 migrants was\ncloser to between 3,000 and 4,000 PLN.\nIn the case of Ukrainians that were out\nof work, the monthly income was more\nvaried, especially because there were fewer\nprevious migrants in this situation.\nThe median income for non-employed prewar immigrants was around 2,500 PLN <sup>32</sup> .\nAmong refugees from Ukraine remaining\nout of work at the time of the survey, the\nmedian income equaled around 600 PLN.\n\n\nThe standard of living of refugees from\nUkraine may be significantly lower than\nnatives, even at similar incomes due to\ntheir lack of housing capital. 87% of the\npopulation in Poland resided in owneroccupied housing in 2021 and 2022,\naccording to Eurostat. As most refugees\nfrom Ukraine do not possess housing of\ntheir own in Poland, they need to rent in a\nrelatively tight market, especially when they\nreside in large metropolitan areas that offer\nthe most opportunities. Initially, in the first\nmonth after the outbreak of the full-scale\nwar in Ukraine, the number of renting\noffers in the OLX and Otodom portals\ndropped by approximately 60%, though it\nlater", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR MSNA Poland 2023 survey", "probe_tag": "keep", "probe_score": 0.9899, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 239, "end": 268, "key": "sample:jad_paddy_docs:000007:14:0:0", "source": "gold", "luna_reason": "Survey results support calculations and income-distribution findings.", "usage_type": "evidential", "specificity": "named"}, {"text": "NBP (2023) survey", "probe_tag": "confusion", "probe_score": 0.8845, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 626, "end": 643, "key": "sample:jad_paddy_docs:000007:14:0:1", "source": "gold", "luna_reason": null}]}
-{"text": "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": " 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": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nTo account for refugees impact on\neconomy shocks for economy were\ncalibrated according to existing data.\nAs the refugees started coming to Poland\nby the end of February and in March\n2022 it was assumed that their impact\non the economy should be seen starting\nfrom the second quarter of 2022. As such\ntheir primary impact on yearly data was\ndivided as between 2022 and 2023 setting\n¾ of it in 2022 and ¼ in 2023. The total\nnumber of refugees was set according to\nthe newest data from the PESEL registry\n(Chart 3. in Chapter 1). Their employment\nwas calibrated to match data presented\nin Chapter 2. Changes in population and\n\n\n\nlabour supply in Poland were offset by\nequivalent changes for Eastern Europe\nregion <sup>41</sup> [^41: Aggregate region in model consisting of Ukraine, Russia, Belarus, Moldova, Czechia, Slovakia, Hungary, Romania and Bulgaria.] . It was also assumed that refugees\nshould have higher spending needs which\nmeans a lower saving rate than natives.\nMoreover, data shows that it is partially\nfinanced by savings they have in Ukrainian\nbanks which was calibrated as them having\nnegative saving rate while being offset\nby lowering investment levels in Eastern\nEurope <sup>42</sup> [^42: In other words it was assumed that money that would be spent e.g. through credit action for investments in Eastern Europe were spent for\nconsumption in Poland.] . Lastly, their productivity may\ndiffer from productivity of natives (Box 2)\nwhich also was taken into account.\nIn total there were three major sources\nof uncertainty: total level of employment,\nproductivity, and impact on consumption.\n\n\n\nwould increase GDP by 0.9-1.3% – the mid\nto higher bound of our estimate.\nThird, Urban (2022) uses an Oxford\nEconomics model to estimate the impact of\nUkrainian refugees on the potential GDP by\n2030", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "yearly data", "probe_tag": "confusion", "probe_score": 0.8706, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 476, "end": 487, "key": "sample:jad_paddy_docs:000007:17:0:0", "source": "gold", "luna_reason": null}, {"text": "PESEL registry", "probe_tag": "keep", "probe_score": 0.9697, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 639, "end": 653, "key": "sample:jad_paddy_docs:000007:17:0:1", "source": "gold", "luna_reason": null}]}
-{"text": " 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": " in the July-August 2023 MSNA\nsurvey to 76% in the May-June 2024 SEIS\nsurvey. <sup>7</sup> This is not surprising, as the\nsituation of Ukrainians in the Polish labour\nmarket has clearly improved. First,\nemployment rate of working-age refugees\n\n\n\nfrom Ukraine has increased from 61% to\n69%, while their unemployment rate has\nhalved from 15% to 8%. Second, median\nnet wage of Ukrainian refugees grew from\nPLN 3,100 to PLN 4,000, i.e. by 29%. While\nhalf of this wage growth came from the\noverall high earnings growth in the country\ndue to high inflation (gross wages in the\ngeneral economy grew by 15% <sup>8</sup> ), it was still\na major improvement. Gross wage gains\nappear lower, with ZUS social insurance\ncontributions data for the period from\n\n\n\nJune 30, 2023 and June 30, 2024 showing\nan increase of 18% (compared to 15% for\nPolish citizens). As of June 30, 2024, only\n44% of ZUS-insured Ukrainian refugees\nhad an employment contract (compared\nto 82% of Polish citizens). Many may opt for\ncivil law contracts and self-employment to\nlimit their social insurance contributions to\nthe level of minimum wage.\n\n\n\n7 Together with refugees working remotely in Ukraine, their income from work would add up to 80% in the SEIS survey.\n\n8 From Q2 2023 to Q2 2024, <u>https://stat.gov.pl/en/latest-statistical-news/communications-and-announcements/list-of-communiques-and-announcements/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", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 7, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "SEIS\nsurvey", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 65, "end": 76, "key": "sample:jad_paddy_docs:000001:7:2:0", "source": "gold", "luna_reason": null}, {"text": "ZUS social insurance\ncontributions data", "probe_tag": "confusion", "probe_score": 0.6881, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 685, "end": 724, "key": "sample:jad_paddy_docs:000001:7:2:1", "source": "gold", "luna_reason": "ZUS contribution data support reported wage and employment comparisons.", "usage_type": "evidential", "specificity": "named"}, {"text": "SEIS survey", "probe_tag": "confusion", "probe_score": 0.4802, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1215, "end": 1226, "key": "sample:jad_paddy_docs:000001:7:2:2", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n**I.** **STRATEGIC CONTEXT**\n\n\n**A. Country 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", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "global development indicators", "probe_tag": "keep", "probe_score": 0.9799, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 777, "end": 806, "key": "sample:jdc_operational:000049:14:0:0", "source": "gold", "luna_reason": null}, {"text": "Global Climate Risk Index", "probe_tag": "keep", "probe_score": 0.9976, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1663, "end": 1688, "key": "sample:jdc_operational:000049:14:0:1", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nUganda COVID-19 Education Response Project (P174033)\n\n\nalso increase with education level. For higher education the regional average is 21 percent, while the returns\nto primary and secondary education are 14.4 and 10.6 percent, respectively. As shown in the figure below,\nin Uganda, the average expected income also increases according to the highest education level attended.\n\n\n**Figure 1. Mean monthly wage, 14-64 years old, by highest education level attended, in UGX**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n_Source:_ UNHS 2016/17.\n_Notes:_ Monthly wage from main job, for those employed as paid employees, employers or self-employed.\n\n<mark>11.</mark> <mark>The direct project beneficiaries of the proposed project are 14 million</mark> <mark>students in preprimary, primary and</mark>\n<mark>lower-secondary students; and 520,000</mark> <mark>teachers and school administrators in Uganda. The main goal is to</mark>\n<mark>ensure learning continuity. The expected positive outcomes are therefore higher retention rates, as the</mark>\n<mark>pandemic might increase dropouts, affecting particularly harder children from poorer households and young</mark>\n<mark>girls.</mark>\n\n<mark>12.</mark> <mark>Costs are equivalent to the total cost of the project – which will disburse US$ 14.7M over a period of 18</mark>\n<mark>months – and additional costs due to the increased number of students enrolled in primary and lower</mark>\n<mark>secondary education as a result of the implementation of project’s activities. These additional students</mark>\n<mark>correspond to those who are currently enrolled in either primary or lower secondary education and would</mark>", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 46, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHS", "probe_tag": "keep", "probe_score": 0.9989, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 517, "end": 521, "key": "sample:jdc_operational:000034:46:0:0", "source": "gold", "luna_reason": "UNHS 2016/17 supplies wage data presented in the figure.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n14. **On the national level, the main reasons for a girl dropping out of secondary school is pregnancy,**\n**marriage, and cost of schooling.** <sup>**18**</sup> [^18: Ibid, pp. 5.] Though the incidence of child marriage and early pregnancy have declined over\nthe years, Uganda’s levels of child marriage are above expectations given the level of income. The share of women\naged 18-22, who married before the age of 18, was 36.5 percent according to the latest Demographic and Health\nSurvey (2011). A more recent study supported by UNICEF <sup>19</sup> [^19: Amin et al., 2013.] indicated that child marriage in Uganda is even more\npervasive with 20 percent of girls in the country marring between the ages of 15 and 19 years old. One in seven\nwomen aged 18-22 have their first child before the age of 18. <sup>20</sup> [^20: Wodon, K. 2016, Uganda Note: Child Marriage and Education, p. 2.] The probability of completing secondary education\nfor a woman aged 25-34 who married after 18 is 12.9 points higher than for women who married earlier.\n\n15. **Additional evidence suggests that continued schooling delays marriage** when appropriate policies are\nimplemented by schools to prevent early marriage and pregnancy. These should include Violence Against Children\n(VAC) and Gender Based Violence (GBV) prevention activities and other measures ensuring a safe school\nenvironment that to ensure girls stay at school without the risk of falling victim to sexual violence. Additionally,\ndistance to lower secondary schools for young adolescents, especially girls from poor families, tends to raise\nopportunity costs and physical risks. Hence, increasing access to lower secondary schools, reducing cost of\neducation for poor households and providing incentives", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 17, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Demographic and Health\nSurvey", "probe_tag": "keep", "probe_score": 0.9206541776657104, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 536, "end": 565, "key": "jdc_operational:000018:17:0:0", "source": "camp2", "luna_reason": "2011 survey provides the cited child-marriage prevalence finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**The World Bank**\nUganda COVID-19 Education Response Project (P174033)\n\n\nFinancing Facility Advisory Services and Analytics is providing catalytic resources to provide technical assistance\nin three main areas linked to strengthening continuity of health services during the context of COVID-19.\n\n\n**B. Sectoral and Institutional Context**\n\n\n11. **In Uganda, there are over 15 million students enrolled in the education system, including higher**\n**education.** The majority of Ugandan students are enrolled in day schools while others are in boarding schools\nwhere many facilities are shared and students are constantly in close contact with each other, their teachers and\nother visitors on a daily basis, presenting an environment for easy transmission of the COVID-19. <mark>The education</mark>\n<mark>[system in Uganda has a structure of seven years of primary education](https://en.wikipedia.org/wiki/Primary_education)</mark> _<mark>,</mark>_ <mark>[six years of secondary education](https://en.wikipedia.org/wiki/Secondary_education)</mark> <mark>(divided</mark>\n<mark>into four years of lower secondary and two years of upper secondary school). Based on the data in 2017, the gross</mark>\n<mark>enrollment</mark> <sup>8</sup> [^8: EMIS data 2017, Ministry of Education and Sports] <mark>for preprimary was 14.4 percent, primary 115.7 percent, and secondary 28 percent, respectively.</mark>\n\n12. **All schools are currently closed as part of the Government’s COVID-19 response.** In response to the\ndanger posed by the pandemic to Ugandan students, the Government announced the closure of all schools from\nMarch 20, 2020 for a period of 30 days in a bid to", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data in 2017", "probe_tag": "keep", "probe_score": 0.9998, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1166, "end": 1178, "key": "sample:jdc_operational:000034:12:0:0", "source": "gold", "luna_reason": null}, {"text": "EMIS data 2017", "probe_tag": "keep", "probe_score": 0.9653, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1239, "end": 1253, "key": "sample:jdc_operational:000034:12:0:1", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nUganda Skills Development in Refugee and Host Communities (P176263)\n\n\nimprove quality of TVET, promote sustainable TVET financing, and ensure effectiveness of TVET management and organization. The\nBTVET Strategic Plan (2011) also provides a shift in the approach to employment-led skills development by providing labour marketrelevant skills and competencies. The core tenets are to increase internal efficiency and resource available to TVET, as well as to\nprovide more equitable access to skills development which is in line with this project’s PDO.\n14 See Table 16 (page 48) of the Education Response Plan for Refugees and Host Communities in Uganda (2018) presents data from\nRMIS and multiple sources in September 2017.\n15 Only 8 percent of refugees have received some form of formal training. See\nhttp://documents.worldbank.org/curated/en/571081569598919068/Informing-the-Refugee-Policy-Response-in-Uganda-Resultsfrom-the-Uganda-Refugee-and-Host-Communities-2018-Household-Survey\n16 In 2016, over 50% of GDP and 80% of the labor force can be attributed to the informal sector in Uganda (UBOS, 2014). While there\nare no official statistics on informal labor market in Uganda’s RHC, the UNHCR reports the economy in RHC as a predominantly informal\nsector.\n17 Violence against children in schools is widespread and has negative lasting impacts on physical and mental health, leading to risk of\nlow levels of educational attainment. A Raising Voices (2017) study identified that 93% of boys and 94% of girls aged 11-14 have\nexperienced physical violence from teachers in school. Sexual violence is likely to be underreported due to associated stigma.\n[18 For more details on Prospects, see the Vision Note (https://www.ilo", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000016", "page": 13, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "RMIS", "probe_tag": "keep", "probe_score": 0.9689, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 698, "end": 702, "key": "sample:jdc_operational:000016:13:0:0", "source": "gold", "luna_reason": "Table presents data from the named RMIS system.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": " clear land and remove barriers,\nnegotiating with village chiefs to acquire plots of land for refugees, and increasing the number of water\npoints in the refugee camps.\n.\n\n\n10 According to the UNHCR SGBV Strategy for Chad 2012-2016. https://www.unhcr.org/protection/operations/56b1fd9f9/chadsgbv-strategy.html\n11 Percentage of women who have experienced physical and/or sexual violence from an intimate partner at some time in their\nlives. _Source:_ OECD, Gender, Institutions and Development Database 2015 (GID-DB) (accessed September 2017).\n\n\nPage 33 of 76", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 36, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "GID-DB", "probe_tag": "keep", "probe_score": 0.9488775730133057, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 507, "end": 513, "key": "jdc_operational:000048:36:2:0", "source": "camp2", "luna_reason": "Named database cited as source for the violence indicator.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " in armed conflict may facilitate substantial population**\n**movement.** About 1.2 million people have returned from displacement within and outside of South Sudan since 2016 to\ndate. Among them, over 534,000 people (45 percent) returned since the signing of the revitalized peace agreement in\nSeptember 2018 until March 2019. <sup>13</sup> [^13: IOM DTM] This demonstrates that more people returned in a shorter period of time since the\nsigning of the agreement. According to both the UNHCR and IOM’s recent intention surveys, major pull factors for return\nare improved security, family reunification, access to basic services, and livelihood opportunities. For refugees, 30 percent\nof them in neighboring countries consider returning but majority are waiting to see how the situation unfolds. Slightly\nhigher numbers of IDPs have longer term return intentions to home areas. The prevailing security and basic living\nconditions are not yet conducive to more widespread return movements among both populations, however. In addition,\nthere have been new/secondary displacements triggered by intensifying inter-communal clashes in areas such as Unity,\nWarrap, Lakes, Western Bahr-el-Ghazal, Central Equatoria and Jonglei. <sup>14</sup> [^14: UNMISS (August 2019) ( _Mimeo_ )] Population movement thus remains volatile,\nwhere temporary visits by single family members to look after assets and property in home areas predominate. Should\nthe unity government be formed in November 2019 and security situation improve, however, the return of some of the\n4.2 million displaced (both refugees and IDPs) is likely to accelerate.\n\n9. **Unlike in other countries where significant numbers of returnees gravitate to major cities, in South Sudan the**\n**evidence suggests that IDPs and refugees are likely to return to their original villages or in their vicinity.** Existing data\nshows that a large majority (87 percent) of IDP and refugee returns are primarily to areas of habitual residence while\nrelocations to third areas is quite", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000014", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "IOM DTM", "probe_tag": "keep", "probe_score": 0.9374, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 347, "end": 354, "key": "sample:jdc_operational:000014:4:1:0", "source": "gold", "luna_reason": null}, {"text": "intention surveys", "probe_tag": "confusion", "probe_score": 0.8434, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 509, "end": 526, "key": "sample:jdc_operational:000014:4:1:1", "source": "gold", "luna_reason": "UNHCR and IOM surveys support identified return-factor findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "65. No Designated Account will be opened for this project. A Blanket Commitment will be\nset up for WFP and FAO for the full amount to be transferred to each UN agency as an Advance.\nThe Grant will finance 100 percent of eligible expenditures of the project, inclusive of taxes.\n\n\n66. On August 22, 2014, the Financial Management Operation Review Committee approved\nthe Request for Elimination of Audit Requirements for the proposed emergency project,\ncoordinated by the EAPSP, as part of project preparation. Alternative mechanisms (detailed in\nthe request) will be put in place to support the elimination of the Bank’s audit requirements,\nhowever. First, at least two field-based visits will be conducted during the first 12 months of the\nproject implementation period. The supervision intensity will be adjusted over time, taking into\naccount the project’s financial management performance and financial management risk level.\nSecond, the Government of Chad will have the entire responsibility to ensure during the project\nimplementation period that goods and services are delivered effectively to the beneficiaries.\nWhere deemed appropriate, however—for example, if the UN agencies’ systems or periodic\nreports have showed some weaknesses or deficiencies—the Bank team may request the\ngovernment to institute arrangements to physically inspect works, goods, and services delivered\nby WFP and FAO.\n\n\n**D.** **Procurement**\n\n67. **_Guidelines._** Procurement for the proposed project will be carried out in accordance with\nthe World Bank “Guidelines: Procurement of Goods, Works, and Non-Consulting Services under\nIBRD Loans and IDA Credits and Grants by World Bank Borrowers,” dated January, 2011, and\n“Guidelines: Selection and Employment of Consultants under IBRD Loans and IDA Credit and\nGrants by World Bank Borrowers,” dated January, 2011, and the provisions stipulated in the\nLegal Agreement. Contract awards will also be published in UNDB, in accordance with the\nBank’s Procurement Guidelines", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNDB", "probe_tag": "confusion", "probe_score": 0.4866, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1943, "end": 1947, "key": "sample:jdc_operational:000007:27:0:0", "source": "gold", "luna_reason": null}]}
-{"text": "6.9|17,160.3|22.0|\n|Appraisal period<br>reduced to 3 years|4,296|19.9|2,781|28.6|(9,239)|−11.9|6,874|30.2|59,200|45.1|\n|Appraisal period<br>reduced to 5 years|13,780|34.3|7,990|45.8|2,454|9.0|19,152|47.2|136,276|60.9|\n\n\n\n_Source:_ Based on World Bank staff estimates.\n\n\n\nPage 81 of 94", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 86, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "World Bank staff estimates", "probe_tag": "confusion", "probe_score": 0.2598624527454376, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 240, "end": 266, "key": "jdc_operational:000049:86:1:0", "source": "camp2", "luna_reason": "Source line attributes the table's estimates to World Bank staff analysis.", "usage_type": "evidential", "specificity": "named"}]}
-{"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**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nbuilding power and voice through women’s identification of water and sanitation infrastructure needs.\nThis activity will be measured at the component level with the indicator: proportion of women in WASH\ninfrastructure/O&M groups. Progress on supporting the closing of the gender gaps through these efforts\nwill be measured through gender-disaggregated data in the M&E framework.\n\n\n81. **Citizen Engagement** . Citizen engagement is an essential element of the project, which is based on\na community-driven development approach, to improve community resilience and social cohesion. The\nproject mainstreams citizen engagement throughout the project cycle. Measures built in include:\nestablishment and strengthening of inclusive community institutions; a strong participatory planning\nprocess; inclusion of local communities in project implementation; community-based monitoring; training\non community-led O&M; a robust communication and outreach to communities; and a strong grievance\nredress mechanism to close the feedback loop. This will ensure community ownership of the project,\nadaptation of subprojects on local needs, efficient use of resources, and enhanced sustainability by\nincluding the communities in subproject O&M. Citizen engagement is also an essential tool for social risk\nmanagement, including a functioning grievance redress mechanism, meaningful consultations in line with\nESF/ESS10, prevention of elite capture, and inclusion of the most vulnerable. Implementing partners of\nthis project have considerable experience on citizen engagement in South Sudan, essential for effective\ncitizen engagement in the complex and diverse situations in different parts of the country.\n\n\n**B. Fiduciary**\n\n\n**(i) Financial Management**\n\n82. The overall fiduciary responsibility will be with UNOPS through the PMU with key staff responsible\nfor providing effective FM oversight. Since IOM will participate in the implementation of Components 1\nand 2 (and possibly some of Component 3 activities), IOM will establish similar FM arrangements. This will\nbe", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 43, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "gender-disaggregated data", "probe_tag": "confusion", "probe_score": 0.09011052548885345, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 435, "end": 460, "key": "jdc_operational:000049:43:0:0", "source": "camp2", "luna_reason": "Future project monitoring through the M&E framework is planned, not existing data use.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": "**The World Bank**\nPromoting Financial Inclusion Policies and Regulations in Jordan ( P163719 )\n\n\nBank Universal Financial Access (UFA) data portal estimates that 0.8 million adults can be reached by the\ncountry opportunity of drafting and implementing the NFIS[1]. Affordable access to and use of financial\nservices helps young, women and small business owners (including those in the remote areas) generate\nincome, manage irregular cash flow, invest in opportunities, strengthen resilience to downturns, and work\ntheir way out of poverty.\n\n   - **The Project’s objective is aligned with the World Bank’s Twin Goals and global initiative to provide universal**\n\n**financial access around the world by 2020.** Financial inclusion - access and usage of quality financial services,\nincluding credit, savings, payments and insurance - is an enabler and a catalyst for achieving the Bank Group's\ngoals of ending extreme poverty by 2030 and boosting shared prosperity for the bottom 40 percent of the\npopulation in all developing countries.\n\n\n[1] http://ufa.worldbank.org/country-progress/jordan\n\n\n**C. Project Development Objective(s)**\nProposed Development Objective(s)\nThe project development objective is to support the implementation of the National Financial Inclusion Strategy (NFIS)\nin Jordan.\n\n\nKey Results\n\n   - Progress towards achieving the project’s objectives will be measured by a series of quantitative and qualitative\n\nindicators at the PDO level and at the intermediate level.\n\n   - The Financial Inclusion Monitoring and Evaluation (M&E) framework that will be developed under Component\n\n1, will include relevant NFIS indicators[1] and will track the implementation of NFIS and monitor progress and\nimpact. The framework will be segmented by intermediate outcomes, outcomes and national headline\nprogress. These indicators are meant to measure national progress, which has contributing factors beyond the\nscope of this project. Thus, this project will _only_ track national financial inclusion progress and will", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Bank Universal Financial Access (UFA) data portal", "probe_tag": "confusion", "probe_score": 0.2098, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 98, "end": 147, "key": "sample:jdc_operational:000013:5:0:0", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n\n\n\n\n\n\n\n\n\n|Table 6.2. Select Results of|the Survey Surveyed Provinces|Col3|Col4|Col5|\n|---|---|---|---|---|\n|<br> <br>|<br>**Surveyed Provinces**<br>|<br>**Surveyed Provinces**<br>|<br>**Surveyed Provinces**<br>|**Average**<br>|\n|<br> <br>|<br>**Guéra**<br>|<br>**Kanem**<br>|<br>**Logone**<br>**Occidental**<br>|<br>**Logone**<br>**Occidental**<br>|\n|Household size, number of people<br>|5.4<br>|4.6<br>|<br>6.8<br>|5.8<br>|\n|<br>Female-headed households, percentage<br>|<br>9.4<br>|<br>26.6<br>|<br>10.4<br>|<br>13.3<br>|\n|<br>Male-headed households, percentage<br>|<br>90.6<br>|<br>73.4<br>|<br>89.6<br>|<br>86.7<br>|\n|<br>Use of mobile money, percentage<br>|<br>12.0<br>|<br>11.0", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 90, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Chad Energy Access Scale Up Project", "probe_tag": "confusion", "probe_score": 0.8523, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 19, "end": 54, "key": "sample:jdc_operational:000051:90:0:0", "source": "gold", "luna_reason": null}, {"text": "Survey Surveyed Provinces", "probe_tag": "keep", "probe_score": 0.9685, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 110, "end": 135, "key": "sample:jdc_operational:000051:90:0:1", "source": "gold", "luna_reason": null}]}
-{"text": ". <sup>15</sup> [^15: Informal refugees have not been profiled by the government.] Based on the lists of registered beneficiaries,\nvouchers will be delivered every month at designated distribution sites by NGO partners with the\nnecessary expertise, contracted by WFP. They will check the beneficiaries’ photo registration\ncards <sup>16</sup> [^16: Many refugees and returnees lose their national identification cards in their flight from CAR, so beneficiaries will\nreceive registration cards with their photos.] against the list of beneficiaries. To limit the possibility of unauthorized reproduction and\nredemption, each voucher has a specific security code and hologram.\n\n\n32. WFP will use its extensive experience in managing these processes to work with\ngovernment counterparts and establish agreements with a national bank, financial institutions,\nstorekeepers, and traders to implement the voucher/food delivery system. Under its current\nemergency operation, WFP assists about 75,000 displaced individuals, including the 31,200\nincluded under the proposed project. WFP intends to extend this operation through the end of\n2014, when a related WFP program (a Protracted Relief and Recovery Operation) will assume\nresponsibility for assisting these individuals. World Bank funding will represent about 42 percent\nof the operation’s needs for 12 months.\n\n\n33. **Component B: Agricultural Production and Livestock Stabilization (US$11 million**\n**IDA).** Component B aims to restore and maintain crop and livestock production capacity among\nthe affected populations in a context where pressure on the natural resource base is increasing\nrapidly. Under this component, the proposed project will finance the purchase and distribution of\n\n13 They may choose among 14 food items that have been selected based on local eating habits and healthy diets.\n14 When food prices rise during the lean season, the value of the vouchers declines, so people cannot obtain as much\nfood with the vouchers as before. Another drawback of using vouchers in the lean season is that they could trigger\nfood price inflation,", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 17, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "lists of registered beneficiaries", "probe_tag": "confusion", "probe_score": 0.6806410551071167, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 96, "end": 129, "key": "jdc_operational:000007:17:1:0", "source": "camp2", "luna_reason": "Existing beneficiary lists inform voucher delivery and beneficiary verification.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "—Uganda National Household Survey\n2016–17.” World Bank, Washington, DC.\n2 Other contributing factors were the overall economic slowdown and widening in regional inequality observed since 2012/13. The\nonly region where poverty did not increase was the Northern region. Poverty declined in this region because of favorable weather\nconditions and increased transfers (remittances and social transfers).\n\n\nJun 15, 2021 Page 3 of 13", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000005", "page": 2, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "Uganda National Household Survey", "probe_tag": "confusion", "probe_score": 0.8966912031173706, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1, "end": 33, "key": "jdc_operational:000005:2:2:0", "source": "camp2", "luna_reason": "Named existing national survey cited as the source for reported poverty findings.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": "<br>|\n|<br>N’Djamena<br>|<br>51.0<br>|<br>43.8<br>|<br>49.6|\n\n\n2. The gap in electricity access is also visible when looking at quintiles of wealth, although it only\nbecomes sizable for the highest quintile. From all male-headed households in the top quintile, 40.9\npercent have access to electricity while the same figure is 29.79 percent for female-headed households.\n\n\n\n\n\n\n|Location|Male (%)|Female (%)|All (%)|\n|---|---|---|---|\n|<br>Poorest|<br>0.01|<br>0.03|<br>0.01|\n\n\n\n43 The data on the distribution of household heads were updated by a survey on ability and willingness of households to pay for\nelectricity services, completed in 2021. Details are provided in annex 6.\n\n\nPage 71 of 87", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 76, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "data on the distribution of household heads", "probe_tag": "confusion", "probe_score": 0.5760777592658997, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 484, "end": 527, "key": "jdc_operational:000051:76:2:0", "source": "camp2", "luna_reason": "Survey data updated the household-head distribution used in the analysis.", "usage_type": "evidential", "specificity": "descriptive"}, {"text": "survey on ability and willingness of households", "probe_tag": "keep", "probe_score": 0.9391711354255676, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 546, "end": 593, "key": "jdc_operational:000051:76:2:1", "source": "camp2", "luna_reason": "Completed survey updated household-head distribution data used in analysis.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n**ANNEX 3: Gender Gap Analysis**\n\n\n\n**Rationale: Why a Focus on Gender in Energy Matters**\n\n1. Access to reliable household energy, clean and efficient cookstoves, or productive-use equipment\ncan reduce energy poverty and time spent on drudgery and give women and men additional incomeearning opportunities. In Chad, some key elements to consider include the following:\n\n\n\n(a) **Distribution of household heads.** About 22.1 percent of households in Chad are headed by\n\n\n\nfemales. The share is slightly higher in urban areas in general (23.6 percent); it is lower in\nN'Djamena (19.3 percent), <sup>43</sup> [^43: The data on the distribution of household heads were updated by a survey on ability and willingness of households to pay for\nelectricity services, completed in 2021. Details are provided in annex 6.] as detailed in Table 3.1. However, the project target with respect to\nelectrification of female-headed households is set at 15 percent according to more recent data\non the share of female-headed households in Chad that are provided in annex 6.\n\n\n\n\n\n|Location|Male (%)|Female (%)|\n|---|---|---|\n|<br>Nationwide<br>|<br>78.0<br>|<br>22.1<br>|\n|<br>Urban<br>|<br>76.5<br>|<br>23.6<br>|\n|<br>Rural<br>|<br>78.4<br>|<br>21.6<br>|\n|<br>N’Djamena<br>|<br>80.7<br>|<br>19.3<br>|\n\n\n(b)", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 76, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "data\non the share of female-headed households in Chad", "probe_tag": "confusion", "probe_score": 0.841, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1040, "end": 1093, "key": "sample:jdc_operational:000051:76:0:0", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nSupport for Social Recovery Needs of Vulnerable Groups in Beirut (P176622)\n\n\n**3.** **Compounded by the global economic shock presented by COVID-19, disruptions in international food supply chains**\n**and trade networks exacerbate Lebanon’s food security vulnerabilities.** Lebanon's remittances dropped by 20%,\nfrom 3.9 billion U.S. dollars in the first half of 2019 to 3.1 billion dollars in the first half of 2020, according to Bank\nByblos' Lebanon This Week report released on Tuesday. <sup>6</sup> [^6: Bank Byblos (February 2020) Lebanon This Week ‘Lebanon’s expats’ remittances drop by 20% in H1 of 2020 in Xinhuanet.] Furthermore, the restrictions on movement to combat the\npandemic have hindered food-related logistic services, disrupting food supply chains and jeopardizing food security\nfor millions of people. The higher levels of export restrictions particularly leave food-importing countries vulnerable\nto commodity price fluctuations. The CPI witnessed an annual inflation of 133% between October 2019 and November\n2020ii, while Food Price Index (FPI) registered an inflation of 423% – representing an all-time high since CAS started\nprice monitoring on a monthly basis in 2007. <sup>7</sup> [^7: World Food Program (December 202) Lebanon, VAM Update of Food Price and Market Trends.] This is particularly relevant as Lebanon imports at least 80% of its food\nsupplies (ESCWA 2016). As a result of these crises, the real GDP growth of Lebanon contracted by 20.3% in 2020 and\na further contraction of about 9.3% is projected for 2021. These severe economic crises forced over 45% of the\nLebanese population below the poverty line.\n\n**4.** **The pandemic and ensuing lockdowns have affected the poor, refugees and other vulnerable populations**\n**disproportionately, on a global scale as well as on", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000054", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Food Price Index", "probe_tag": "confusion", "probe_score": 0.8807109594345093, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1064, "end": 1080, "key": "jdc_operational:000054:3:0:1", "source": "camp2", "luna_reason": "Index is tied to a documented 423% inflation finding.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": " uniform data standards and\nclassification. Some of these key databases are; the maternal and neonatal registry, cancer registry,\ncommunicable disease surveillance registry, primary health care information system, and hospital\nutilization and billing system (visa billing system).\n\nThe aim of this component is to design a database that will allow for interoperability and serve as a\nmain repository of health sector data ready for analysis and dissemination. The database will not\nonly link the key MoPH databases, but will also pull relevant data from other sources such as CAS\nhousehold surveys (including Demographic and Health survey), NHA, and national hospital\nmorbidity and mortality reporting.\n\nThis component will work on the following activities:\n\n➢❨¢ Develop key performance indicators for assessing the performance of the health sector\nincluding disease burden, efficiency and equity of the health sector, PHC and hospital key\nperformance indicators, health economics indicators, as well as setting a plan to extract and monitor\nthe progress in the health and health-related Sustainable Development Goals indicators\n➢❨¢ Design an ICT system for ensuring interoperability of the existing databases including\nunification of patient identification numbers to facilitate statistical analyses for evidence based\ndecision making in the implementation of the national health sector plan\n\n\nPage 4 of 7", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000046", "page": 3, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "communicable disease surveillance registry", "probe_tag": "confusion", "probe_score": 0.345010370016098, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 130, "end": 172, "key": "jdc_operational:000046:3:1:0", "source": "camp2", "luna_reason": "Registry is listed as an existing system, but its data are not shown informing analysis or decisions.", "drop_reason": "system_registry", "specificity": "descriptive"}, {"text": "CAS\nhousehold surveys", "probe_tag": "keep", "probe_score": 0.9010677933692932, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 576, "end": 597, "key": "jdc_operational:000046:3:1:1", "source": "camp2", "luna_reason": "Future database integration plans to pull survey data; no completed analytical use is shown.", "drop_reason": "promissory", "specificity": "named"}, {"text": "Demographic and Health survey", "probe_tag": "confusion", "probe_score": 0.4907922148704529, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 609, "end": 638, "key": "jdc_operational:000046:3:1:2", "source": "camp2", "luna_reason": "Existing survey data will be integrated for health-sector analysis and dissemination.", "usage_type": "declaration", "specificity": "named"}, {"text": "NHA", "probe_tag": "confusion", "probe_score": 0.24544283747673035, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 641, "end": 644, "key": "jdc_operational:000046:3:1:3", "source": "camp2", "luna_reason": "Future database integration plans to pull NHA data; no completed use is shown.", "drop_reason": "promissory", "specificity": "vague"}, {"text": "national hospital\nmorbidity and mortality reporting", "probe_tag": "confusion", "probe_score": 0.8718696236610413, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 650, "end": 701, "key": "jdc_operational:000046:3:1:4", "source": "camp2", "luna_reason": "Existing hospital reporting data will be integrated for health-sector analysis.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "\nby facilitating citizens’ ability to monitor municipal investments and performance.\n\n  - _Local economic development:_ Based on the participatory needs identification and\n\nprioritization, UNDP will facilitate and support governorates and municipalities in\nanalyzing and assessing the local opportunities and challenges for economic growth and\njob creation. Such support will be designed around the results of a joint ILO-ACTED\nlabor needs assessment survey that UNDP is financing and an effort to bridge vocational\ntraining services with labor demands. It will also include market and value chain\nassessments, preparation/updating of participatory local economic development plans or\nother exploratory analysis related to livelihoods and income generating potential.\n\n20. Subcomponent 2A will finance the costs of Project related supervision, coordination and\nmonitoring, FM, procurement, safeguards management, audits of participating municipalities and\nother Project entities, etc. This subcomponent will also finance the preparation and dissemination\nof the Project OM, Project related information and communication activities, workshops,\ntrainings, and various studies and surveys related to monitoring and evaluation.\n\n21. Subcomponent 2B will seek to strengthen the institutional capacity and resilience of\nGovernment entities at the central, governorate and municipal level to better address the adverse\nimpacts of external shocks and stresses. While the municipal grants seek to alleviate some of the\n\n31", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000026", "page": 42, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "ILO-ACTED\nlabor needs assessment survey", "probe_tag": "confusion", "probe_score": 0.48251771926879883, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 418, "end": 457, "key": "jdc_operational:000026:42:1:0", "source": "camp2", "luna_reason": "Project-financed survey is planned for future use, not an existing data source.", "drop_reason": "promissory", "specificity": "named"}]}
-{"text": "**The World Bank**\nUganda COVID-19 Education Response Project (P174033)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|of COVID-19 and mitigate<br>against negative impacts on<br>children’s wellbeing and<br>learning. This is intended to:<br>a) increase preventive<br>knowledge; b) promote<br>attitude change about for<br>example, a perceived risk of<br>infection and safe practices.<br>Design the messages in line<br>with existing SOPs, have it<br>verified and approved by<br>Communication & Advocacy<br>working group; and<br>dessiminate as: SMS, text in<br>national newspapers, short<br>commercial scripts on TVs<br>and radios.|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|IRI 2: Self-learning materials adapted to<br>large print and braille for students with<br>special needs (yes/no)|Defn: Self-learning materials <br>refer to any learning<br>resource that can be used<br>by a learner without the<br>physical presence of a<br>teacher.<br> <br>Braille is a symbolic code<br>used to write various<br>languages and are read by<br>touch rather than eyesight.<br>|Once a<br>year<br>|Delivery<br>records at<br>MoES<br>and SNED<br>|Review delivery records<br>at MoES (obtained from<br>DLGs)<br>|NCDC<br>|\n\n\n\nPage 32 of 43\n\n\nOfficial Use", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 36, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "DLGs", "probe_tag": "confusion", "probe_score": 0.8546180725097656, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1156, "end": 1160, "key": "jdc_operational:000034:36:0:0", "source": "camp2", "luna_reason": "A fragment within a monitoring table, not a standalone 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\n\n\n\n|Col1|selected to receive SNSOP<br>who are refugees, defined<br>as forcibly displaced HHs<br>originating from a country<br>other than South Sudan and<br>registered as refugees in<br>South Sudan by the UNHCR.<br>A household will be<br>considered as a beneficiary<br>household if it is both<br>enrolled in the project and<br>have received a cash<br>transfer, at least for one<br>payment cycle.|measured at<br>least on a<br>quarterly<br>basis<br>including<br>through<br>missions and<br>ISRs|beneficiary<br>registration<br>and payment<br>data|beneficiary data during<br>targeting and<br>registration. The<br>payment service<br>provider will collect<br>payment data and<br>share with the<br>implementing partner.|Col6|\n|---|---|---|---|---|---|\n|Beneficiary households of social safety<br>net programs- Host Communities|The number of total<br>beneficiaries households<br>that are selected to receive<br>SNSOP who are from host<br>communities, defined as<br>local population groups<br>living in counties with a high<br>concentration of refugees. A<br>household will be<br>considered as a beneficiary<br>household if it is both<br>enrolled in the project and<br>have received a cash<br>transfer, at least for one<br>payment", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 56, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "beneficiary data", "probe_tag": "confusion", "probe_score": 0.1255, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 639, "end": 655, "key": "sample:jdc_operational:000057:56:0:0", "source": "gold", "luna_reason": null}, {"text": "payment data", "probe_tag": "confusion", "probe_score": 0.0977, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 748, "end": 760, "key": "sample:jdc_operational:000057:56:0:1", "source": "gold", "luna_reason": null}]}
+{"text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **2.** Situation of refugees from Ukraine on the labour market in Poland\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 7.** Unemployment rate\n\n\n12%\n\n\n10%\n\n\n8%\n\n\n6%\n\n\n4%\n\n\n2%\n\n\n0%\n\n\n**Source:** Harmonized data, Eurostat, <u>[Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/une_rt_m/default/table?lang=en)</u>\n\n\n##### Refugees from Ukraine fit well into the needs of the Polish labour market.\n\nUkrainians arrived on a labour market that\nstructurally needs more workers, as the\ndomestic population is ageing rapidly, while\nthe economy is growing. High levels of\neducation, cultural proximity and previous\nconnections to Poland helped refugees\nadapt to the labour market. Furthermore,\nPoland made an important and strategic\npolicy decision by promptly opening\nthe labour market and supporting their\ninclusion.\n\n\n16\n\n\n\n17\n\n\n\n**Chart 6.** Working age population with Polish citizenship (20-64 years old)\n\n\n\n25\n\n\n24\n\n\n23\n\n\n22\n\n\n21\n\n\n20\n\n\n\n\n\n\n\n\n\n\n\nThe number of people of working age\nin Poland is shrinking and is expected\nto keep declining. Although substantial\nmigrations from Poland after EU accession\nin 2004 <sup>19</sup> [^19: Statistics Poland data, <u>[https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n<u>[temporary-stay-from-poland-between-2004-2020,8,14.html](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>] distort population data, the\ndomestic", "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 8, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Harmonized data", "probe_tag": "keep", "probe_score": 0.993, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 309, "end": 324, "key": "sample:jad_paddy_docs:000007:8:0:0", "source": "gold", "luna_reason": null}, {"text": "Statistics Poland data", "probe_tag": "keep", "probe_score": 0.9929, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1275, "end": 1297, "key": "sample:jad_paddy_docs:000007:8:0:1", "source": "gold", "luna_reason": null}, {"text": "population data", "probe_tag": "confusion", "probe_score": 0.6838, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1857, "end": 1872, "key": "sample:jad_paddy_docs:000007:8:0:2", "source": "gold", "luna_reason": null}]}
+{"text": "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\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": "**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": "**The World Bank**\nGreater Beirut Public Transport Project (P160224)\n\n\nproject to be implemented by the CDR are (a) the lack of proper registry of asset lists; (b) delays in\nsubmission of timely audit reports; and (c) complex project where many other agencies are involved such\nas the RPTA and MPWT and that entails PPP and operators’ contributions. and the need to have strong\nFM staff within the PIU to be able to advise and support such activities and assume coordination among\nthe different stakeholders.\n\n\n6. Thus, to mitigate FM-related risks, (a) the CDR will ensure that the assets module of its accounting\nsoftware is well operationalized and is able to capture the work in progress and the assets acquired under\nthe project, (b) it will recruit an acceptable external auditor in the early stages of the project to enable\nconstant audit compliance, and (c) additional staff will be recruited as needed to ensure that FM\nimplementation is well supervised and followed up, in addition to the preparation of a Project\nImplementation Manual including an FM chapter that will detail the FM arrangements to be established\nfor carrying out the project FM implementation and defining the roles and responsibilities. The FM chapter\nwill include a detailed description of the process for expropriation and resettlement and the working\nrelationship with the RPTA, the PPP modalities, and the operators’ contributions mechanisms.\n\n\n7. **Staffing.** The existing CDR FO has adequate experience in managing World Bank-financed projects\nand will thus manage the project FM arrangements. This FO will be supervised by the Head of Funding\nDivision at the CDR and may be assisted by an additional financial staff as needed and as project activities\nbecome more complex.\n\n\n8. **Project accounting software.** The CDR has in place customized accounting software that has been\nused for the FM implementation of the World Bank-financed projects and can be used to record the\nproject’s accounting transactions and generate the", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000022", "page": 55, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "registry of asset lists", "probe_tag": "confusion", "probe_score": 0.057524215430021286, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 135, "end": 158, "key": "jdc_operational:000022:55:0:0", "source": "camp2", "luna_reason": "Asset registry is routine project financial and fixed-asset administration.", "drop_reason": "bookkeeping", "specificity": "descriptive"}]}
-{"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": "jdc_operational", "corpus_id": "jdc_operational:000041", "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": "jdc_operational:000041:45:3:0", "source": "camp2", "luna_reason": "Future verification machinery checks project training certification records.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "certification records", "probe_tag": "drop", "probe_score": 0.004437553230673075, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 239, "end": 260, "key": "jdc_operational:000041:45:3:2", "source": "camp2", "luna_reason": "Future verification of training records is DLI monitoring machinery.", "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": "jdc_operational:000041:45:3:1", "source": "camp2", "luna_reason": "Future verification of training records is planned monitoring machinery.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": " under terms of reference satisfactory to the Bank. Apart from this, the\nPMU will be entrusted with compiling the annual financial statements and preparing any ad hoc financial\nreports to follow up on the Program financial activities, as necessary.\n\n\n**E.** **Capacity Building and Institutional Strengthening**\n\n\n46. **The World Bank and other development partners are undertaking substantial capacity**\n**building and institutional strengthening efforts in coordination with the PforR.** Some highlights of\nthis support include the following:\n\n\n(a) **Investment climate reform:** (i) Jordan Economic Legislation Reform (ASA financed by the\n\nMiddle East and North Africa Transition Fund), tackling the regulatory reform pillar; (ii)\nDoing Business Reform aiming at improving the business environment in areas measured by\nthe Doing Business report, including reforms on secured lending (collateral registry) that is\nkey to access to finance; and (iii) Inspections Reform (ongoing ASA), aiming at streamlining\nand simplifying the inspection regimes;\n\n\n(b) **Investment Promotion:** Jordan Competitiveness and Investment Promotion and Jordan\n\nInvestment Policy and Promotion projects (also financed by the Middle East and North Africa\nTransition Fund) are supporting the JIC—including relevant functions of the JIC: (i)\n\n\n14", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 22, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Doing Business report", "probe_tag": "drop", "probe_score": 0.0037, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 826, "end": 847, "key": "sample:jdc_operational:000045:22:1:0", "source": "gold", "luna_reason": null}]}
-{"text": "---|---|---|\n|**1: Roads**<br>**Rehabilitation and**<br>**Maintenance**|Drainage structures and culverts; retaining<br>walls; routine maintenance.|184.6<br>|50<br>|0|\n|**2: Improving Road**<br>**Emergency**<br>**Response Capacity**|Increased MPWT’s capacity to deal with road<br>emergency works; purchase of necessary<br>equipment.|7.5<br>|7.5<br>|0|\n|**3.1: Strengthen**<br>**Road Asset**<br>**Management**|The creation of a road asset database for<br>Lebanon, and the revision of design and<br>maintenance standards to reflect changing<br>climate conditions.|2 <br>|2|0|\n|**3.2: Support the**<br>**planning and**<br>**implementation of**<br>**road safety**|n.a|2 <br>|0|0|\n|**3.3: Support**<br>**Planning and Design**<br>**Studies**|Finance necessary studies to produce<br>planning and design documents in the<br>transport sector, particularly public", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 34, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "road asset database", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 426, "end": 445, "key": "sample:jdc_operational:000008:34:1:0", "source": "gold", "luna_reason": null}]}
-{"text": ">6 months<br>|MOPH<br>reports/ site<br>visit reports<br>|Administrative data<br>|PMU and MOPH<br>|\n|Number of communication initiatives<br>supported by the project to address<br>vaccine hesitancy <br>|<br>This indicator will track the <br>number of communication<br>initiatives that are either<br>conducted or/and<br>substantially supported by<br>MOPH for the public to<br>address the issue of<br>vaccine hesitancy. <br>|6 months<br> <br>|MOPH and<br>TPM reports<br> <br>|Administrative data<br> <br>|PMU/MOPH<br> <br>|\n|Percentage of vaccination sites visited by<br>the technical auditor in the last quarter|<br>This indicator will monitor<br>the percentage of project|3 months<br>|MOPH and<br>TPM reports|TPM reports<br>|PMU and TPM<br>|\n\n\nPage 46 of 54", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 50, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Administrative data", "probe_tag": "confusion", "probe_score": 0.7699, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 57, "end": 76, "key": "sample:jdc_operational:000000:50:1:0", "source": "gold", "luna_reason": null}, {"text": "Administrative data", "probe_tag": "drop", "probe_score": 0.0084, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 472, "end": 491, "key": "sample:jdc_operational:000000:50:1:1", "source": "gold", "luna_reason": null}]}
-{"text": "):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|\n|**4.**Municipal** r**oads built<br>or rehabilitated with<br>related infrastructure<br>using urban LDG|√|3|Km<br>Targets|53.02|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Annually|Municipal reports|Participating<", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 36, "chunk": 4, "split": "holdout_annotate", "spans": [{"text": "Municipal reports", "probe_tag": "drop", "probe_score": 0.0016635797219350934, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1379, "end": 1396, "key": "jdc_operational:000006:36:4:0", "source": "camp2", "luna_reason": "Annual verification source in project results framework, not demonstrated existing data use.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": " between construction firms it does not permit any\nforced partnerships. Therefore, the PPDA instruction that 30 percent of the Civil works should be outsourced\nto local staff and companies shall not apply. However, the contract will require that the Contractor only hires\nUgandans for non-skilled, and semi-skilled trades including operation of various equipment. UNRA has put in\nplace a robust contract management arrangement including strengthened its in house monitoring and\nsupervision capacity for the contract execution stage.\n\nFor high-value, high-risk, or complex contracts such as the road works, contract management plans will be\nprepared. To mitigate procurement capacity risks, there will be a need for staff capacity building and training,\n<u>continuous oversight, reviews and audits, and the use of real-time monitoring and tracking tools.</u>\n\n20. **Systematic Tracking of Exchanges in Procurement (STEP).** The project will use STEP, a planning and\ntracking system, which would provide data on procurement activities, establish benchmarks, monitor delays and\nmeasure procurement performance.\n\n21. **Use of National Procurement System.** National procurement procedures shall only apply if the\nrequirements as required by paragraph 5.3 of the Procurement Regulations <sup>64</sup> are met. In March 2017 (updated\n\n\n64 (a) open advertising of the procurement opportunity at the national level; (b) the procurement is open to eligible firms from any country;\n(c) the request for bids/request for proposals document shall require that Bidders/Proposers submitting Bids/Proposals present a signed\nacceptance at the time of bidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the Bank’s\nAnti-Corruption Guidelines, including without limitation the Bank’s right to sanction and the Bank’s inspection and audit rights; (d)\nProcurement Documents include provisions, as agreed with the Bank,", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 69, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data on procurement activities", "probe_tag": "drop", "probe_score": 0.048870399594306946, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1002, "end": 1032, "key": "jdc_operational:000050:69:1:0", "source": "camp2", "luna_reason": "Future STEP output is planned, not existing data used for analysis.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n|Col1|project will undertake<br>proactive efforts to<br>communicate the service<br>standard to address and<br>respond to feedback that<br>will be received.|Col3|Col4|mechanism|Col6|\n|---|---|---|---|---|---|\n|Beneficiaries reporting satisfaction with<br>project activities<br>|Percentage of beneficiaries<br>in component 1 satisfied<br>with project application,<br>grant disbursement,<br>implementation, and<br>technical support.<br>Beneficiaries in component<br>2 reporting improved<br>community cohesion,<br>enhanced social inclusion,<br>and neighborhood<br>revitalization.<br>The findings of these<br>surveys will be published<br>and/or that the survey<br>findings will be used by the<br>implementing entity to<br>generate an action plan to<br>address the feedback<br>acquired through the<br>surveys.|At mid-<br>point of<br>project and<br>project<br>closure<br>|The scope of<br>the GRM will<br>include<br>complaints<br>and other<br>types of<br>feedback<br>such as<br>suggestions,<br>queries (e.g.<br>Quality of<br>Life<br>Survey) and<br>compliments<br>|A survey will be carried<br>out with direct<br>beneficiaries of the<br", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 46, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "surveys", "probe_tag": "drop", "probe_score": 0.0087, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 712, "end": 719, "key": "sample:jdc_operational:000012:46:0:0", "source": "gold", "luna_reason": null}, {"text": "surveys", "probe_tag": "drop", "probe_score": 0.0022, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 903, "end": 910, "key": "sample:jdc_operational:000012:46:0:1", "source": "gold", "luna_reason": null}]}
+{"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": " 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": " the temporary rental of housing by displaced owners is projected\nat US$173.3 million for the same period. <sup>93</sup> [^93: RDNA]\n\n**7.** **Units and buildings remaining in need of repair are mainly those that are severely damaged, requiring**\n**more costly structural works, encompassing historic including heritage-grade buildings.** The wide national and\ninternational immediate response mostly focused on the less damaged units due to the technical complexity of\naddressing severely damaged units. As of 25 February 2021, 5,777 buildings remain with low or cosmetic damage\n(L1 damage level), 1,881 buildings with major but not structural damage (L2 level), and 1,093 with structural\ndamage (L3 level).\n\n**8.** **Most of the impacted residential buildings with cultural heritage value are still unattended and remain**\n**in precarious condition, requiring rehabilitation to allow habitability (see figure 3).** So far early recovery efforts\nhave focused on addressing affected residential buildings that suffered minor damage <sup>94</sup> [^94: Buildings with less than 10 percent of physical damage.] due to a lack of leadership\nfrom the authorities, as well as funds, capacity, and time required to assume the complex rehabilitation works of\nthe most severely damaged buildings during what was considered the “humanitarian phase”. According to the\nUN-Habitat damage inventory for all the buildings within the blast affected area of damaged buildings,\napproximately 25 buildings have not received any type of rehabilitation assistance yet, 20 have been propped but\nnot rehabilitated, 50 buildings are still under rehabilitation, and 80 have been completely rehabilitated. According\nto the DGA, 80 percent of the 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", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 57, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "UN-Habitat damage inventory", "probe_tag": "drop", "probe_score": 0.0131, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1357, "end": 1384, "key": "sample:jdc_operational:000012:57:1:0", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\nprotective support to HHs and investment in resilience building community assets will help sustain livelihoods, strengthen\nresilience, and prevent the most vulnerable from falling into destitution or being forcibly displaced. It will also directly\nsupport the Government’s Community Empowerment and Socioeconomic Development Strategy for Refugee Hosting\nAreas in South Sudan, with cash transfers promoting section 4.6 of the strategy on creation of livelihood and income\ngenerating opportunities given the lack of employment prospects in refugee-hosting environments.\n\n37. **In the absence of an enabling environment for widescale mobile payment systems, beneficiaries will receive**\n**physical cash at the time of payment, except for Juba where mobile money payment will be piloted.** A financial service\nprovider (i.e., paying agent), which will be competitively selected by the MAFS, will deliver cash to beneficiaries. The\nMAFS will provide the recipient list and amount of money to the financial service provider, and the list of beneficiaries\nwill be generated from the MIS. The MIS will capture beneficiaries' biometric data, which will be used to ensure that only\nthe eligible individuals will receive the cash transfer. The financial service provider pays beneficiaries verifying them\nbiometrically. In addition, implementing partners (i.e., UNOPS and NGOs contracted by MAFS to implement the project)\nand community leaders will be present and monitor the transfer process to ensure transparency and accountability.\nBased on the findings of a recently concluded analytical work, the project will pilot the use of mobile money payments\nin Juba. Mobile money payments would help strengthen transparency and safety and were assessed to be feasible in\nlarge urban center like Juba under the SSSNP. This pilot would inform potential future scale up of mobile money payments\nin urban areas.\n\n**Sub-component 1.1: Cash for Labor-Intensive Public Works and Complementary Social Measures** *", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 23, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MIS", "probe_tag": "confusion", "probe_score": 0.1458, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1169, "end": 1172, "key": "sample:jdc_operational:000057:23:0:0", "source": "gold", "luna_reason": null}, {"text": "MIS", "probe_tag": "drop", "probe_score": 0.0462, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1178, "end": 1181, "key": "sample:jdc_operational:000057:23:0:1", "source": "gold", "luna_reason": null}, {"text": "biometric data", "probe_tag": "confusion", "probe_score": 0.2475, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1210, "end": 1224, "key": "sample:jdc_operational:000057:23:0:2", "source": "gold", "luna_reason": null}]}
-{"text": " 335,000 hectares that require only modest\ninvestments in infrastructure to become productive. This resource, coupled with the country’s\nagro-ecological diversity, creates huge potential for crop diversification.\n\n\n16. The livestock subsector contributes significantly to the Chadian economy, although its\ncontribution to export revenues is suboptimal owing to the enormous uncontrolled migration of\nherds to markets in Nigeria each year. The dominant herding practices in Chad, affecting 80\npercent of livestock, are transhumance and extensive herding. Cattle herding is the primary\nagricultural activity in the Sahel and a secondary activity in the Sudanian zone, although the\nrelatively greater availability of food, agricultural by-products, and agro-industrial operations in\nthe Sudanian zone attract many herders from the north. In some instances, the herders’\ncoexistence with the agro-pastoralists poses land management problems and can be a source of\nconflict.\n\n\n17. Food security is volatile in Chad because agricultural production systems rely largely on\nrainfall rather than irrigation. Numbers of food-insecure individuals more than triple when\ndroughts deplete harvests and food prices soar. In southern Chad, where most of the refugees and\nreturnees are being settled, agriculture is dominated by small-scale farmers producing a\nmoderate, locally marketed surplus. Cross-border trade with Cameroon and CAR is also\nimportant. While local trade with CAR has been significantly curbed by the conflict, markets in\nthe areas where vouchers are being implemented continue to be well stocked and no unusual\nprice movements have been observed in the past few months since voucher transfers became\noperational. A January 2014 market assessment indicated that food production surpluses were\n\n\n4", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 13, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "January 2014 market assessment", "probe_tag": "drop", "probe_score": 0.0022, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1719, "end": 1749, "key": "sample:jdc_operational:000007:13:1:0", "source": "gold", "luna_reason": null}]}
-{"text": ">psycho-social support.|Defn: Emergency response<br>preparedness and psycho-<br>scial support refer to<br>strategic measures put in<br>place (by national COVID<br>taskforce) to manage the<br>spread and mitigate against<br>negative impacts of COVID-<br>19.<br> <br>Train or orient head<br>teachers of grant-supported<br>schools on the above<br>measures to help guide their<br>response at school level;|<br>once<br>|Training<br>reports<br>|Data collection through<br>monitoring of training<br>and review of<br>attendance registers<br>|MoES through<br>Directorate of Basic and<br>Secondary Education<br>|\n\n\nPage 34 of 43\n\n\nOfficial Use", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 38, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "attendance registers", "probe_tag": "drop", "probe_score": 0.014660093933343887, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 508, "end": 528, "key": "jdc_operational:000034:38:1:0", "source": "camp2", "luna_reason": "Routine attendance records reviewed for project training monitoring.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\non the other sectors by enhancing connectivity of the host population and refugees to markets. The existing\nroad infrastructure in West Nile Sub-Region is of poor quality and not motorable especially during rains.\nAccess to health facilities and referral medical units is also encumbered by the dilapidated road network.\n\n\n11. **Uganda was ranked 127** <sup>**th**</sup> **out of 162 countries in the 2018 Gender Inequality Index** <sup>11</sup> . Prevalence rates of\ngender-based violence (GBV) in Uganda are high. According to the Uganda Demographic and Health Survey\n(UDHS) <sup>12</sup>, 56 percent of women have experienced spousal violence and 22 percent sexual violence. The\nfigures for Violence Against Children (VAC) are also high, with 59 percent of females and 68 percent of males\nreporting experiencing physical violence during childhood. <sup>13</sup> Adolescent girls in Uganda are more likely to\nbe poor, miss out on school and are at a greater risk of contracting HIV. <sup>14</sup> Of Ugandans ages 13-17 years,\none in four girls and one in ten boys reported sexual violence in 2015. <sup>15</sup> Nearly a quarter of teenage girls in\nUganda become pregnant. <sup>16</sup> The intersection with poverty and lack of access to education is the greatest\nrisk to violence against adolescent girls, particularly in rural areas. Refugee women/girls are at high risk of\nseveral forms of GBV including sexual exploitation and abuse (SEA), rape, forced and child marriage and\nintimate partner violence (IPV) <sup>17</sup>", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000146", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "2018 Gender Inequality Index", "probe_tag": "keep", "probe_score": 0.9486983418464661, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 499, "end": 527, "key": "refugee_pads:000146:14:0:0", "source": "camp2", "luna_reason": "Named index provides Uganda's ranking among 162 countries.", "usage_type": "evidential", "specificity": "named"}, {"text": "Uganda Demographic and Health Survey", "probe_tag": "keep", "probe_score": 0.9706239700317383, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 631, "end": 667, "key": "refugee_pads:000146:14:0:1", "source": "camp2", "luna_reason": "Survey provides cited violence prevalence findings for Ugandan women.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "s=NE)\n[2 World Bank Group. 2025. Niger. https://www.worldbank.org/en/country/niger/overview#3.](https://www.worldbank.org/en/country/niger/overview#3)\n3 Recent data from the World Food Program indicates that over 3.3 million individuals were classified as acutely food insecure during the 2023 season (June–August). An estimated 4.3 million people (2.4 million of whom are\nchildren) require humanitarian assistance. Additionally, Niger’s global acute malnutrition rate is estimated at 12.7 percent, and 42 percent of children under 5 years old are stunted. Severe recorded food crises in 1980, 1988,\n[1990, 1997, 2001, 2005, 2009, 2011–-.https://openknowledge.worldbank.org/handle/10986/37620).](https://openknowledge.worldbank.org/handle/10986/37620)\n[4 World Bank Group. 2021. Data. Poverty headcount ratio at US$2.15 a day (2017 PPP) (% of population) - Niger. https://data.worldbank.org/indicator/SI.POV.DDAY?locations=NE](https://data.worldbank.org/indicator/SI.POV.DDAY?locations=NE)\n5 In the transport sector women hold less than one percent of jobs. Although data on women in technical roles is unavailable, their share is likely lower due to inadequate skills and strong gender norms.\n6 When referring to host communities in this document, internally displaced persons are considered part of the host population unless noted otherwise.\n7 P. Thenkabail et al. 2016. Global Food Security Support Analysis Data (GFSAD) Crop Dominance 2010 Global 1 km", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000184", "page": 11, "chunk": 3, "split": "holdout_annotate", "spans": [{"text": "Global Food Security Support Analysis Data", "probe_tag": "keep", "probe_score": 0.9406164884567261, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1374, "end": 1416, "key": "refugee_pads:000184:11:3:1", "source": "camp2", "luna_reason": "Standalone bibliography entry without shown analytical use", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": "children, **l6** and child (under 5) mortality due to perinatal period conditions increased substantially in\n2002 to become the leading cause of death for children under 5 and the second leading cause of death\noverall). Per capita food consumption has declined by a quarter since 1998. The incidence o f Post\nTraumatic Stress Disorder (PTSD) has risen significantly and affects women and children in particular.\nNevertheless Palestine society remains fairly cohesive and families for the most part remain functional.\nThis situation together with the responses of the Palestine Authority i s described in more detail in _Twenty_\n_Seven Months, Intifada, Closures and Palestine Economic Crisis,_ May 2003, and ‘in _Palestine: The_\n_Current Socio-Economic Crisis and the Ministry of_ _Social Affairs,_ December, 2002, Report # 25262-02).\n\n\nThe coping capacity of poor households has been strained to the limit. Families have used a variety of\nstrategies to cope with a sharp decline in income.” Initially, many made up for lost income by drawing\non their savings (24 percent), assistance from family and friends (15 percent), cultivating land (10\npercent), or selling property (8 percent). B y November 2001, the number of families reporting income\nwas not enough for their needs had increased to 68 percent, and 17 percent were reducing their expenses,\n\n15 percent were relying on assistance from family and friends, and only 13 percent were able to draw\nfrom their savings. In terms of food, 82 percent of families rely on their own income for their food needs,\nwhile 11 percent rely on family and friends and 7 percent rely on relief assistance. Of those relying on\nrelief assistance for food, the majority were in Gaza. The surveys help illuminate the effectiveness of the\nrelief programs in reaching the poor. Households identified as Hardship Cases receive 56 percent of all\nfood assistance, and those below the poverty line receive another 26 percent", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "surveys", "probe_tag": "keep", "probe_score": 0.9045634865760803, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1725, "end": 1732, "key": "refugee_pads:000047:25:0:0", "source": "camp2", "luna_reason": "Surveys support concrete findings about relief-program reach among poor households.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": " 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:000161", "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": "refugee_pads:000161:38:1:1", "source": "camp2", "luna_reason": "Survey data support reported enrollment-rate differences by expenditure quintile.", "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:000161:38:1:2", "source": "camp2", "luna_reason": "Household Survey data supports the finding that parents withdraw girls from school.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nCosta Rica Results in Education (CORE) (P181174)\n\n\n**<u>Figure 1b: Technical education graduates by gender in strategic STEAM fields</u>**\n\n\n12. **By the end of 2022, Costa Rica was hosting 270,636 forcibly displaced and stateless people, and the uneven**\n**preparedness of these students strains the education system.** <sup>19</sup> [^19: UNHCR, Strategy 2024, Situation Analysis.] Even if the influx of migrants and refugees acts as a\npositive factor for some schools that would be facing closure due to decline of the native-born population, the education\nsystem faces stress because of the differential quality of preparedness and disruptions faced by immigrant students. In\nrecent decades, the country has seen the arrival of migrants and refugee applicants fleeing political and economic\nconditions in Colombia, Cuba, El Salvador, Nicaragua, and Venezuela. According to the United Nations High Commissioner\nfor Refugees and administrative records from the General Directorate of Migration and Foreigners, the number of asylum\nseekers in Costa Rica increased from 27,993 in 2018 to 273,066 by December 2023. While the country offers public\neducation to all children regardless of migratory status, more efforts are needed to ensure that enrollment requirements\ndo not exclude migrant children from the classroom, and that learning environments are inclusive. As of September 2023,\n64,455 students enrolled in the Costa Rican education system were foreigners (5.4 percent of the total student\npopulation). According to administrative registries, 38,870 migrant students (60.3 percent of the total migrant student\npopulation) are under irregular status or pending regularization. <sup>20</sup> [^20: Data from MEP’s Saber, as of September 26, 2023.] The issue of disabilities is also a priority item for\nGovernment policies on inclusion. MEP statistics indicate 19,643 students with disabilities, with alternative solutions\nproviding services", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000189", "page": 14, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "administrative registries", "probe_tag": "keep", "probe_score": 0.9571810960769653, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1543, "end": 1568, "key": "refugee_pads:000189:14:0:0", "source": "camp2", "luna_reason": "Administrative registry data supports the reported count of migrant students.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000038", "page": 19, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "household\nexpenditure survey data", "probe_tag": "keep", "probe_score": 0.9439554214477539, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1661, "end": 1694, "key": "refugee_pads:000038:19:0:0", "source": "camp2", "luna_reason": "Survey data supports a concrete enrollment inequality finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
+{"text": "|\n|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|**Expected Disbursements (in USD Million)**|\n|Fiscal Year|2015|2016|2017||||||||||||||\n|Annual|9.00|6.00|3.00||||||||||||||\n|Cumulative|9.00|15.00|18.00||||||||||||||\n|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional", "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 6, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Institutional Data", "probe_tag": "drop", "probe_score": 0.036259736865758896, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 877, "end": 895, "key": "jdc_operational:000007:6:1:0", "source": "camp2", "luna_reason": "Standalone table header, not an actual cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "vague"}, {"text": "Institutional Data", "probe_tag": "drop", "probe_score": 0.011391296982765198, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 877, "end": 895, "key": "jdc_operational:000007:6:1:2", "source": "camp2", "luna_reason": "Standalone table header, not a cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "vague"}]}
+{"text": " (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": "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 - 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": " 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": " meet the high barriers to entry but are most likely to work\nin these areas are given opportunities by creating pathways and ladders to gain entry and broaden the set of\nrequirements of access by supporting programs that can validate acquired experience or through recognition of\nprior learning programs. While there are really no apparent systemic barriers within the training sector that\nprevents women from participating in technical education and vocational training programs, the number of\nwomen in non-traditional programs and courses continues to be small. The USAID’s Workforce Development\nprogram’s Gender Assessment reveals that a combination of prevalent social norms, parental influence, and poor\ncommunications, impacts decisions by women to participate in these programs. The assessment also highlights\nfinancial barriers for women to access to TVET (to cover the cost of courses including equipment as well as the\ncost of transportation), supply-side barriers (discrimination and harassment during trainings, few female trainers\nplaying as role models, lack of targeted trainings to female needs/interests due to their limited participation in\ndecision-making, etc.). These issues will need to be addressed to help improve system equity in terms of gender.\nNotwithstanding these concerns, it does need to be acknowledged that the official statistics suggest that nearly\n41 percent of students in the TVET sector are women, suggesting that the sheer lack of opportunities and access\nin other programs (such as, higher education) does result in a significant number of women accessing these\nprograms. Nevertheless, it is important and critical to support not only the expansion of opportunities for more\nwomen, but also to increase the range of opportunities thereby incentivizing women and young girls to access\ntraining in non-traditional programs.\n\n32. **The government is committed to ensuring access to quality education for all students considered as**\n**vulnerable, which include girls from host communities, refugees, and children with special needs.** Girls’\nenrollment is lower at all education levels and makes up 49 percent of preschool, 46 percent", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000195", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "official statistics", "probe_tag": "confusion", "probe_score": 0.1952, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1345, "end": 1364, "key": "sample:refugee_pads:000195:23:1:0", "source": "gold", "luna_reason": null}]}
-{"text": "**The World Bank**\nENHANCING CONNECTIVITY AND RESILIENCE IN THE FAR NORTH OF CAMEROON FOR INCLUSIVENESS\nPROJECT (P178207)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|passability during the rainy<br>season.|Col3|Col4|passable road within<br>five kilometers of the<br>MDK road section|Col6|\n|---|---|---|---|---|---|\n|Number of refugees and host<br>communities population with access<br>to an all-weather passable road within<br>five kilometers of the MDK road<br>section.|<br>Number of refugees and<br>people in host communities<br>with access to an all-season<br>road. Climate change<br>impacts are expected to<br>affect road passability<br>during the rainy season.|Yearly<br>|Surveys<br>UNHCR data<br>|The methodology will<br>consist on using survey<br>to calculate the number<br>of refugees and host<br>communities<br>population<br>located within a 5km-<br>buffer zone of each<br>road section<br>rehabilitated and<br>maintained with<br>climate<br>resilience features.<br>|Project Implementation<br>Unit<br>|\n|Share of women with improved<br>access to an all-weather passable<br>road within five kilometers of the<br>MDK road section.|This sub-indicator measures<br>the percentage of women<br>with improved access to an<br>all-weather passable road<br>within five kilometers of the<br>MDK", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000003", "page": 62, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNHCR data", "probe_tag": "confusion", "probe_score": 0.6173585057258606, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 664, "end": 674, "key": "refugee_pads:000003:62:0:0", "source": "camp2", "luna_reason": "UNHCR data is identified as the source for calculating refugee and host-community access.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": " component, the project will reinforce the Government’s capacity by financing technical assistance and\nsocial protection system investments that will support achievement of the project objectives. Specifically, the component\nwill finance the scale-up of the national social registry of vulnerable households and strengthening of targeting\nprocedures, including the PMT methodology developed under the SSNP and community-based targeting. This will include\nmaking the necessary modifications to incorporate refugees in the social registry, given that they have become eligible\nfor several social programs in Djibouti. The program’s corresponding MIS will be reinforced for improved enrollment,\npayment, grievance and redress management, and monitoring as well as referral of potential beneficiaries to other\n\n\nPage 13 of 44", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 17, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "national social registry of vulnerable households", "probe_tag": "confusion", "probe_score": 0.15545132756233215, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 258, "end": 307, "key": "refugee_pads:000154:17:2:0", "source": "camp2", "luna_reason": "Planned registry scale-up; no existing registry data are shown informing targeting.", "drop_reason": "promissory", "specificity": "descriptive"}, {"text": "social registry", "probe_tag": "confusion", "probe_score": 0.8105584383010864, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 521, "end": 536, "key": "refugee_pads:000154:17:2:1", "source": "camp2", "luna_reason": "Names a registry being modified, without showing its data used for analysis or targeting.", "drop_reason": "system_registry", "specificity": "vague"}]}
-{"text": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Household Expenditure Survey", "probe_tag": "confusion", "probe_score": 0.8797882199287415, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1906, "end": 1934, "key": "refugee_pads:000049:9:0:0", "source": "camp2", "luna_reason": "Existing household survey is cited for a concrete population-distribution finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the adverse effects of the situation on\nthe students. The keeping of photographic archives was begun during this mission.\n\n\nThe impacts considered will not be due solely to the project but also to the prevailing situation, which is\ncharacterized by significant degradation of the existing facilities. Since a particular aim of the project is\nto increase the capacity of schools, the main environmental measure to be included in the project will be\nto construct or rehabilitate the sanitary facilities of these schools, and to design a system of upkeep and\nmaintenance that will ensure the appropriate functioning of the schools.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 65, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "photographic archives", "probe_tag": "confusion", "probe_score": 0.21480418741703033, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 363, "end": 384, "key": "refugee_pads:000147:65:1:0", "source": "camp2", "luna_reason": "Archives were begun during the mission, indicating newly produced project documentation.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "\nfor quarterly and bi-annual assessments moving to a bi-annual census of health facilities once monitoring capacity\nis established, anticipated in Year 2. Quarterly TPM visits will incorporate the following:\n(i) **Quarterly health facility functionality assessments.** At baseline and endline, the assessments will\nincorporate a sample of operational health facilities not supported by the project to generate\ncomprehensive information on health service delivery nationwide and the added value of the project.\nMeasures on disability access will be included in the assessments.\n(ii) Quarterly data quality verification to provide measures of partner data quality and reporting accuracy.\n(iii) Bi-annual health service quality assessment to capture the quality of key health services, focusing on health\nservice process and structural quality. On an annual basis the health service quality assessment will include\ndirect observation of health service process quality measures at hospitals and health centers.\n(iv) Bi-annual patient feedback using exit surveys.\n(v) Bi-annual visits to a sample of BHTs to measure service outputs and quality.\n**(b)** **Periodic TPM data collection:**\n\n(i) Biennial household coverage surveys as baseline/endline surveys in the project’s three-year timeframe. <sup>35</sup> [^35: Given the planned project length of three years, this is a baseline and an endline survey. Potential timeframe changes would include interim surveys, which are\nplanned to be light surveys focusing on key indicators.]\n(ii) Citizen engagement survey collected at the household level, with the coverage survey every other year.\n\n2. **Data Analysis and Visualization Platform.** The platform will emphasize development of an integrated,\ninstitutionalized, and sustainable system. The platform will include analysis of health service delivery in refugee and\nhost community areas. The platform will include the following:\n(a) Interactive data visualization platform presenting Results Framework and core indicators. The platform will use\n\ndata from DHIS2 and the TPM and will include BHI data. It will be updated at least on a", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000006", "page": 64, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Biennial household coverage surveys", "probe_tag": "confusion", "probe_score": 0.41503533720970154, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1187, "end": 1222, "key": "refugee_pads:000006:64:1:0", "source": "camp2", "luna_reason": "Planned baseline/endline surveys are future project data production.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "Citizen engagement survey", "probe_tag": "confusion", "probe_score": 0.531532883644104, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1532, "end": 1557, "key": "refugee_pads:000006:64:1:1", "source": "camp2", "luna_reason": "Survey collection is presented as planned project monitoring activity.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "DHIS2", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 2053, "end": 2058, "key": "refugee_pads:000006:64:1:2", "source": "camp2", "luna_reason": "DHIS2 data are used in an integrated health-service analysis platform.", "usage_type": "declaration", "specificity": "named"}, {"text": "BHI data", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 2088, "end": 2096, "key": "refugee_pads:000006:64:1:3", "source": "camp2", "luna_reason": "Future platform inclusion of BHI data is planned, not demonstrated existing use.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n\n\n|Col1|financial support through<br>the project in the<br>reconstruction of their<br>residential unit from the<br>PoB explosion.<br>Rationale: 100 rental<br>contracts x 3.5 people/HH|Col3|and<br>Evaluation<br>Reports. Esti<br>mates by<br>Project<br>Management<br>Team.|disaggregating the<br>beneficiary data of the<br>progress reports|Team/UN-Habitat|\n|---|---|---|---|---|---|\n|Direct beneficiaries of cultural production<br>work|Number of people including<br>cultural practitioners,<br>individuals in cultural<br>entities and additional<br>workers involved in the<br>implementation of the<br>cultural productions.|Quarterly<br>|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports.<br>Third-Party<br>Monitoring<br>Agent<br>reports.<br>Estimates by<br>Project<br>Management<br>Team.<br>|Number of<br>beneficiaries will be<br>tracked in the progress<br>reports through<br>reporting updates by<br>each grant recipient of<br>the total number of<br>people participating on<br>each cultural<br>production work<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are female|Number of females<br>including cultural<br>", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 40, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "beneficiary data", "probe_tag": "confusion", "probe_score": 0.0908, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 400, "end": 416, "key": "sample:refugee_pads:000034:40:0:0", "source": "gold", "luna_reason": "Embedded in a project monitoring table artifact.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "Annex 6\nPage 5 of 6\n\n\n\n**Table B: Thresholds for Procurement Methods and Prior Review 1**\n\n\n\n**Expenditure Category** **Contract Value** **Contracts Subject to**\n**Threshold** **Procurement** **Prior Review**\n(US$ thousands) Method (US$ millions)\n1. **Works** - US$50,000 NCB All ICB if any.\n< US$50,000 Simplified NCB NCB contracts above US$150,000\nFirst 5 contracts regardless of\nvalue; first 3 contracts for each\n\n\n\nyear starting January 1.\n**2. Goods** - US$100,000 ICB All ICB.\n< US$100,000 NCB NCB contracts above US$70,000\n< US$50,000 IS or NS where there are at First 5 contracts regardless of\n\n\n\nleast 3 capable national value; first 3 contracts for each\nsuppliers. year starting January 1.\n<US$10,000 DC\n**3. Services** - US$50,000 QCBS Contracts above US$200,000\n(Firms) would be advertised in the UNDB.\n\n              - US$25,000 Contracts for firms above\n(Indiv.) CQ US$50,000, and for individuals\nSS above US$25,000.\n< US$25,000 First 5 contracts regardless of\n=< US$15,000 value; first 3 contracts for each\nyear starting January 1.\nAll TORs\n_____________________________________________________________IAll Sole Source\nThresholds generally differ by country and project.", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000149", "page": 47, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "UNDB", "probe_tag": "confusion", "probe_score": 0.22304409742355347, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 809, "end": 813, "key": "refugee_pads:000149:47:0:0", "source": "camp2", "luna_reason": "Span occurs within a procurement-threshold table artifact.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": "- World Bank diagnostics and international benchmarks also warrant the Program’s sectoral focus on education and\nhealth. According to the Global Digital Health Monitor 2023 <sup>13</sup> [^13: See State of Digital Health around the world today – Jordan profile.], the digital landscape in the health sector is\nconsidered more mature in Jordan compared to neighboring countries in the MENA region, especially in\ndeveloping digital services and applications (see the technical assessment for further detail). However, due to\nlimited governance and multiple services and systems designed and operated in silos, health information systems\nhave been fragmented with inconsistent data standards and quality. The education sector has also been advancing\non the digital front. Jordan was one of the first countries in the region to respond to the COVID-19 pandemic and\nschool closures by developing an online learning platform called Darsak covering the curriculum’s core subjects of\nArabic, English, math, and science for grades 1 through 12. In addition, a newly launched platform for teacher\ntraining offers courses on distance learning tools, blended learning, and educational technology. The MOE has\ndeveloped an integrated, comprehensive, flexible, and trusted educational management information system\n(EMIS) using OpenEMIS, which provides a system that is accessible countrywide, covering over 2 million students,\n7,300 schools, and 170,000 educational staff.\n\n  - World Bank diagnostics and international benchmarks also warrant the Program’s focus on transparency and\naccountability. Under international governance indicators, Jordan is on par with other upper middle-income\ncountries, but it lags on voice and accountability. Regarding transparency, although Jordan was the first country\nin the region to legislate access to information, it is poorly rated under the Right to Information Index and ranks\namong the 15 percent least well-performing countries. According to an assessment of the whole of government\ncitizen feedback platform, only 33 percent of citizens filing a grievance using the At Your Service online\ngovernment grievance redress platform surveyed in 2022 had received any response. Opinion surveys reflect a\npervasive perception", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 27, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Right to Information Index", "probe_tag": "confusion", "probe_score": 0.6405578255653381, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1870, "end": 1896, "key": "refugee_pads:000181:27:0:1", "source": "camp2", "luna_reason": "Index ranking provides evidence of Jordan’s transparency performance.", "usage_type": "evidential", "specificity": "named"}, {"text": "Opinion surveys", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 2204, "end": 2219, "key": "refugee_pads:000181:27:0:2", "source": "camp2", "luna_reason": "Surveys are cited as evidence of pervasive public perception.", "usage_type": "evidential", "specificity": "vague"}]}
-{"text": "required for local government involvement, and arrangements for maintenance, monitoring and\nevaluation (M&E). Social capital enhancing activities would be a mandatory part of all sub-projects, and\nwould be tailored to support activities chosen by the communities.\n\nSupport to Decentralized Government Structures. Most local administrations are beginning\nto operate again with a limited number of staff and other inputs. District and chiefdom authorities are\nvery weak, however, and lack the financial and human resources needed to address their concerns and\npnorities effectively. NGOs have demonstrated their ability to implement successful community-based\nsocial and economic projects and have played a key role in shelter reconstruction activities. With the\ngradual strengthening of local government capacity, partnerships between community groups and local\nauthorities are expected to increase. Upon completion of initial training, district and chiefdom authorities\nwould be required to demonstrate that they have used the training by showing that there have been some\nimprovements in their community. For instance, at the end of each training session, district authorities\nwould be required to develop a simple action plan that specifies some activities that NSAP or other\npartners could support. District and chiefdom authorities would also gain experience in implementing,\nsupporting or overseeing community development activities.\n\nHealth. The unfavorable health indicators in Sierra Leone can be attributed to several factors.\nHigh fertility, female genital mutilation and the presence of HIV/AIDS increase morbidity and mortality\nrisks for women and children. Many risk factors that have contributed to HIV/AIDS epidemics in other\nAfrican countries have long been present in Sierra Leone, and the protracted conflict has created the\nconditions for explosive growth in HIV/AIDS infection rates. The Centers for Disease Control carried\nout a survey in 2002 which found the HIV prevalence among adults (aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000050", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "survey in 2002", "probe_tag": "confusion", "probe_score": 0.7887161374092102, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1950, "end": 1964, "key": "refugee_pads:000050:10:0:0", "source": "camp2", "luna_reason": "Past survey is attributed to CDC and reports HIV prevalence findings.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**The World Bank**\nTajikistan Water Supply and Sanitation Investment Project (P177325)\n\n\ndrinking water quality. The quality of drinking water sources may also be compromised by increased\nsediment and nutrient inputs due to extreme storm events. Sanitation-related public health risks tend to\nbe higher during/after the occurrence of extreme weather events such as floods and droughts, and the\nabsence of sustainable WASH solutions may further exacerbate the spread and transmission of\nwaterborne diseases. The impact of increasing temperatures on the incidence, transmission, season\nduration, and spread of diseases represents a major threat to rural communities, particularly those\naffected by heat waves. <sup>28</sup> Investments in piped water supply services to the rural areas, where wastewater\ncollection and treatment is almost nonexistent will result in an inevitable increase in volume of\nwastewater flows in the medium term, which if not considered and addressed duly may be associated\nwith the environmental and public health threats.\n\n\n16. The World Bank multi-sector rapid needs and impact assessment was conducted by the World\nBank in September 2021 to support the Government to prepare for potential influx of refugees under\ndifferent scenarios. Based on existing data and information, the impact assessment focused on Khatlon\nand GBAO provinces as locations for temporary refugee settlements. The assessment identified urgent\nand short- and medium-term needs to reduce the negative impacts of inflow on host communities and\nmaximize the positive benefits of refugee arrivals and settlement after registration. The assessment\nidentified provision of at least basic WSS services among priorities for the Khatlon and GBAO regions,\nparticularly along the border areas and high-density rural and peri-urban settlements characterized by\nlow coverage and poor quality of basic infrastructure and services (especially for children and women).\n\n\n**Sector Policy and Strategy**\n\n\n17. Recognizing the importance of water to its development agenda, Tajikistan has embarked on a\nprocess of water sector transformation in the last decade. Tajikistan’s goals and macro-strategies are laid", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000162", "page": 16, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "existing data and information", "probe_tag": "confusion", "probe_score": 0.8919, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1272, "end": 1301, "key": "sample:refugee_pads:000162:16:0:0", "source": "gold", "luna_reason": null}]}
-{"text": " of Expenditures (SOE) and the Special\nAccount (SA), would be audited quarterly internally and annually by an independent auditor, in\naccordance with internationally accepted standards. In addition, the auditor would carry out field spot\ncheck audits to ascertain compliance with contractual requirements. Compliance with conditional cash\ntransfers would be monitored by an independent external consultant (paragraph _C.3)._\n\n\n**4.** **Social**\n\nOpportunities, constraints, impacts, and risks arising. out of the socio-cultural and political context.\n\nThe impact of closure and incursions in the West Bank and Gaza has been extensively documented. On\nthe rise are poverty, unemployment, school drop out rates; on the decline or deteriorating are household\nincomes, living conditions, school attendance rates, at-large nutritional status and in particular of children\n0-5 years of age.13\n\nThe so called “newly poor”, those who are just above the poverty line before the outbreak of the second\nIntifada, in the third quarter of 2000, have been assisted by various interventions. To date, it has been\nmuch more difficult to find ways to assist the very poor, or first decile, whose coping mechanisms are\nessentially exhausted. The proposed project i s designed to support children (0-18 years old) in the first\ndecile. Although the SHC has targeted the first decile for more than 20 years, the program i s very small\ntoday in relation to need and requires new instruments to address the present situation and to shift\nMOSA’s overall strategy from one of coping to one of social springboard. Therefore, the project will\nsupport MOSA in reshaping its social assistance strategy and to improve effectiveness and efficiency of\n\n\n~\n\n**l3** PCBS quarterly household surveys, Palestinian Living Conditions quarterly surveys, IUCN, University of Geneva, Living\n\nStandards quarterly surveys, Nutrition Study, Johns Hopkins University, _2002,_ Nutrition Survey, PCBS and", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 20, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "PCBS quarterly household surveys", "probe_tag": "confusion", "probe_score": 0.7826956510543823, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1732, "end": 1764, "key": "refugee_pads:000047:20:1:0", "source": "camp2", "luna_reason": "Named household surveys cited as evidence for documented social conditions", "usage_type": "evidential", "specificity": "named"}, {"text": "Palestinian Living Conditions quarterly surveys", "probe_tag": "keep", "probe_score": 0.9613426923751831, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1766, "end": 1813, "key": "refugee_pads:000047:20:1:1", "source": "camp2", "luna_reason": "Named existing survey cited among sources documenting social conditions.", "usage_type": "declaration", "specificity": "named"}, {"text": "Living\n\nStandards quarterly surveys", "probe_tag": "confusion", "probe_score": 0.7496303915977478, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1843, "end": 1878, "key": "refugee_pads:000047:20:1:2", "source": "camp2", "luna_reason": "Existing survey source listed among evidence documenting social conditions.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": "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:000062", "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:000062:51:0:0", "source": "camp2", "luna_reason": "Planned project reporting of data is future monitoring machinery.", "drop_reason": "promissory", "specificity": "vague"}]}
-{"text": " 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 operation will seek to help Jordan improve the delivery of education services and\nstrengthen its resilience in response to the current Syrian refugee crisis.\n\n24. **_Rationale for the use of PforR_** **.** The PforR instrument will enhance the impact of the World\nBank’s financial and technical support and increase the overall results orientation of the government’s\nNational Human Resources Development Strategy (NHRDS). The decision to use this instrument was\nbased on the following considerations:\n\n- **Results orientation** : The GOJ’s program as depicted by the NESP provides a comprehensive set of\nactivities for making the education system more result‐oriented. The PforR will push forward the\nresults orientation of the sector plan by rewarding the achievement of results with\ndisbursements.\n\n\n- **Upfront momentum** : The PforR instrument will be used to generate momentum around key\nactivities that are potential bottlenecks in the system. Disbursement‐linked indicators (DLI) will\nbe a critical tool for shifting the policy dialogue toward results, especially in the initial years.\n\n\n- **Stakeholder harmonization** : The PforR will not only enhance the partnership between the\ngovernment and the World Bank by using the government’s own systems, but also the\nharmonization of donor interventions in the sector targeting a common results framework. The\nNESP lays out a comprehensive results framework that has been developed in coordination with\neducation partners.\n\n\n- **Institutionalization of measurement** : The use of the PforR instrument is an opportunity to\nleverage MOE’s investments in data systems, such as the OpenEMIS, and to strengthen", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 14, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "OpenEMIS", "probe_tag": "confusion", "probe_score": 0.529739260673523, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1896, "end": 1904, "key": "refugee_pads:000127:14:1:0", "source": "camp2", "luna_reason": "Named data system is mentioned without showing its data being used.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": " least once from project-supported<br>groups. The data is disaggregated by gender, youth (18-30 years) and refugee/host community status.|\n|Frequency|Quarterly|\n|Data source|Project MIS.|\n|Methodology for<br>Data Collection|Monitoring project implementation.|\n|Responsibility for<br>Data Collection|IA|\n|**New or improved jobs generated through the project (Number)**|**New or improved jobs generated through the project (Number)**|\n|Description|Quantitative indicator counting number of jobs created through all three main project components.|\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-supported groups trained on climate-resilient practices and technologies (Percentage)**|**Project-supported groups trained on climate-resilient practices and technologies (Percentage)**|\n|Description|Quantitative indicator counting percentage of project-supported groups under component 3 who receive<br>capacity-building support from the project on climate-resilient business planning, value chains, market<br>assessments, etc., and on climate-smart technologies, such as drought-resistant seeds, etc.|\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-supported groups still operational one year after project support (Percentage)**|**Project-supported groups still operational one year after project support (Percentage)**|\n|Description", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000186", "page": 47, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Project MIS", "probe_tag": "drop", "probe_score": 0.024715568870306015, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 174, "end": 185, "key": "refugee_pads:000186:47:1:0", "source": "camp2", "luna_reason": "Project MIS is merely listed as a monitoring source without shown substantive data use.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "Project MIS and Project Progress Reports", "probe_tag": "drop", "probe_score": 0.0461568608880043, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 580, "end": 620, "key": "refugee_pads:000186:47:1:1", "source": "camp2", "luna_reason": "Project monitoring reports are planned administrative reporting outputs, not substantive reused data.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "**Annex 8: Procurement**\n\n**EGYPT: Early Childhood Education Enhancement Project (ECEEP)**\n\n\n**A. General**\n\n\n1. Procurement for the Bank-funded activities o f the project would be carried out in accordance\nwith the World Bank’s “Guidelines: Procurement Under IBRD Loans and IDA Credits” dated\nMay 2004; and “Guidelines: Selection and Employment o f Consultants by World Bank\nBorrowers” dated M a y 2004, and the provisions stipulated in the Legal Agreement. The general\ndescription o f various items under different expenditure categories are described below. For each\ncontract to be financed by the Loan, the different procurement methods or consultant selection\nmethods, the need for prequalification, estimated costs, prior review requirements, and time\nframe are agreed between the Borrower and the Bank project team in the Procurement Plan. The\nProcurement Plan will be updated at least annually or as required to reflect the actual project\nimplementation needs and improvements in institutional capacity.\n\n\n**Institutional Arrangements for Procurement**\n\n\n2. Procurement will be managed by the F S M O E designated procurement staff working closely\nwith the financial management officers, both at the central and the governorate level.\nProcurement financed by the loan would comprise civil works (US$16 m) which are essentially\nconstruction o f new KG classrooms and rehabilitated facilities donated by local communities for\nconversion into KGs; goods (US$2.35 m) which include equipment for new and rehabilitated\nKGs, and educational materials for KG instruction.\n\n\n3. The works contracts will be procured by GAEB. This will include construction and\nfurnishing o f the new KGs as well as rehabilitation o f community KGs. GAEB will also lead the\nidentification o f sites for construction o f KGs based on its extensive and well-tested GIS and\nschool mapping system. GAEB will work closely with the MOE/Finance Sector assigned\nProcurement Officers, at both the", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000040", "page": 60, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "GIS and\nschool mapping system", "probe_tag": "drop", "probe_score": 0.027937540784478188, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1843, "end": 1872, "key": "refugee_pads:000040:60:0:0", "source": "camp2", "luna_reason": "Existing GIS and school-mapping data inform construction-site identification.", "usage_type": "declaration", "specificity": "descriptive"}]}
-{"text": " / LHW and PMU,<br>DOH<br>|\n|Children under 1 year immunized with the<br>first dose of measles vaccination in target<br>districts|<br>Percentage of children<br>under 1 immunized at EPI<br>centres, PHC, and in the<br>community in target<br>districts.|Bi-Annually<br>|DHIS, EPI MIS<br>|Routine HMIS<br>|DHIS/EPI<br>|\n|Women receiving iron/folic acid<br>supplementation during pregnancy in<br>target districts|Percentage of all pregnant<br>women receiving iron/folic<br>acid supplementation at<br>PHC facilities, or in the<br>community in target<br>districts.|Bi-Annually<br>|DHIS, LHW<br>MIS<br>|Routine HMIS<br>|IMU, PMU, DOH<br>|\n|Health professionals (doctors, nurses,<br>non-medical staff) receiving refresher and<br>on-the-job training|Number provincial and<br>district staff trained<br>(Cumulative number).|Bi-Annually<br>|PMU<br>|PMU Records<br>|IMU, PMU, DOH<br>|\n\n\n\nPage 38 of 48", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000126", "page": 42, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "PMU Records", "probe_tag": "drop", "probe_score": 0.047011904418468475, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 835, "end": 846, "key": "refugee_pads:000126:42:1:0", "source": "camp2", "luna_reason": "Standalone table cell naming a project monitoring record source.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "**The World Bank**\nBalochistan Human Capital Investment Project (P166308)\n\n\n(FMS), and an environmental and social safeguards specialist/officer. <sup>47</sup> [^47: During the early phase of implementation, the Governance and Policy Program (GPP) PMU will provide back‐up support.] The PMUs will be fully authorized\nto implement the planned activities approved by the Project Steering Committee (PSC).\n\n\n46. **A Project Coordination Committee (PCC) will be set up to coordinate project implementation**\n**and a PSC will be set up to provide strategic guidance and oversight.** The PCC, co‐chaired by Secretaries\nHealth and Secondary Education, will meet quarterly. The PSC, chaired by the Additional Chief Secretary,\nwill meet biannually (see figure 2).\n\n\n**Figure 2. Institutional and Implementation Arrangements**\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**B. Results Monitoring and Evaluation Arrangements**\n\n\n47. **Building on the results chain, the M&E framework identified indicators to track project**\n**implementation progress and impact.** The PDO‐level health indicators are taken from the RMNCHN\nindicators in the DHIS, while digitization and integration of various HMIS is an intermediate indicator. The\neducation indicators are taken from the EMIS. Where possible, relevant indicators will be disaggregated\nby gender. Discussions with the GoB and the UNHCR have confirmed, however, that beneficiary data by\nnationality will not be routinely collected or publicly released.\n\n\n48. **The project M&E will leverage and strengthen existing routine information systems, and finance**\n**the generation of user‐friendly evidence for efficient service delivery.** Routine surveys will be used to\ncollate data from target facilities, which will be triangulated through the existing management\ninformation system within the Health and Secondary Education Departments. The remote monitoring\nsystem within the SED uses technology‐based data management solutions with a dashboard to display\nthe broader analysis. The project will support the", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000085", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "RMNCHN\nindicators", "probe_tag": "confusion", "probe_score": 0.7368855476379395, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1085, "end": 1102, "key": "refugee_pads:000085:25:0:0", "source": "camp2", "luna_reason": "Existing RMNCHN indicators from DHIS are used as PDO health indicators.", "usage_type": "declaration", "specificity": "named"}, {"text": "DHIS", "probe_tag": "confusion", "probe_score": 0.5660116672515869, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1110, "end": 1114, "key": "refugee_pads:000085:25:0:1", "source": "camp2", "luna_reason": "Existing DHIS indicators are used as project health monitoring indicators.", "usage_type": "declaration", "specificity": "named"}, {"text": "EMIS", "probe_tag": "confusion", "probe_score": 0.7092921137809753, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1241, "end": 1245, "key": "refugee_pads:000085:25:0:2", "source": "camp2", "luna_reason": "Education indicators are sourced from the named EMIS information system.", "usage_type": "declaration", "specificity": "named"}, {"text": "beneficiary data by\nnationality", "probe_tag": "drop", "probe_score": 0.04482332617044449, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1385, "end": 1416, "key": "refugee_pads:000085:25:0:3", "source": "camp2", "luna_reason": "States data will not be routinely collected or released, without substantive use.", "drop_reason": "availability", "specificity": "vague"}]}
-{"text": " during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<br>partner will collect<br>beneficiary data during<br>targeting and<br>registration. The<br>payment service<br>provider and<br>implementing agency<br>will document payment<br>data<br>|Implementing Partner<br>|\n|Beneficiary households of social safety<br>net programs- Refugees|The number of total<br>beneficiaries HHs that are|This indicator<br>will be|SNSOP MIS<br>which hosts|The implementing<br>partner will collect|Implementing Partner<br>|\n\n\nPage 51 of 74", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000153", "page": 55, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "beneficiary data", "probe_tag": "drop", "probe_score": 0.010647853836417198, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 163, "end": 179, "key": "refugee_pads:000153:55:1:0", "source": "camp2", "luna_reason": "The implementing partner will collect this beneficiary data during targeting and registration.", "drop_reason": "production", "specificity": "vague"}]}
-{"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:000062", "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:000062:16:0:0", "source": "camp2", "luna_reason": "Planning unit generates the data; it is project-sector production, not existing data use.", "drop_reason": "production", "specificity": "vague"}]}
+{"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": "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": " and ranks according to the proxy-means testing (PMT) formula; (iv) maintaining the PMT formula;\n(v) analyzing national data and reporting findings to the Social Inter-Ministerial Committee (Social-IMC); (vi) monitoring the\n**NPTP** targeting; and (vii) auditing data processing. The central unit in **MOSA** (through its SDCs) is responsible for (i) comanaging the central **NPTP** database; (ii) receiving household applications; (iii) interfacing with applicants; (iv) entering data; **(v)**\nconducting household visits; (vi) checking for data errors; (vii) transmitting data to the central database of the **NPTP** **CMU;** and\n(viii) managing the public relations campaign.\n**3** Other options were considered at the time and are detailed in the EPP of the **ESPISP** II.\n\n\n**_52_**", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000109", "page": 51, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "national data", "probe_tag": "drop", "probe_score": 0.039643608033657074, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 111, "end": 124, "key": "refugee_pads:000109:51:2:0", "source": "camp2", "luna_reason": "Existing national data are analyzed to report findings to the committee.", "usage_type": "declaration", "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:000086", "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:000086:24:0:0", "source": "camp2", "luna_reason": "Project will collect and analyze this data through future social-analysis rounds.", "drop_reason": "production", "specificity": "vague"}]}
-{"text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000096", "page": 31, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.027876049280166626, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 226, "end": 240, "key": "refugee_pads:000096:31:0:0", "source": "camp2", "luna_reason": "Logframe verification data, not an already-used external data source.", "drop_reason": "promissory", "specificity": "named"}, {"text": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.11965898424386978, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 412, "end": 437, "key": "refugee_pads:000096:31:0:1", "source": "camp2", "luna_reason": "Named administrative data source listed for verifying program indicators", "usage_type": "declaration", "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:000096:31:0:2", "source": "camp2", "luna_reason": "Listed as future logframe verification data, with no existing finding or analysis.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": " <br>Technical<br>audit report<br> <br>Technical audit<br> <br>SEAS<br>|Community sub-projects functional one<br>year after completion<br>Percentage of infrastructure<br>assets rated as functional by<br>an independent technical<br>auditor one year after they<br>are completed (with<br>completion defined as<br>having passed the stage of<br>réception provisoire)<br>Once<br> <br>Technical<br>audit report<br> <br>Technical audit<br> <br>SEAS<br>|Community sub-projects functional one<br>year after completion<br>Percentage of infrastructure<br>assets rated as functional by<br>an independent technical<br>auditor one year after they<br>are completed (with<br>completion defined as<br>having passed the stage of<br>réception provisoire)<br>Once<br> <br>Technical<br>audit report<br> <br>Technical audit<br> <br>SEAS<br>|\n|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>", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 37, "chunk": 6, "split": "holdout_annotate", "spans": [{"text": "Survey at end of project", "probe_tag": "drop", "probe_score": 0.026881590485572815, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1072, "end": 1096, "key": "refugee_pads:000154:37:6:0", "source": "camp2", "luna_reason": "Planned end-of-project survey in a monitoring framework, not existing data use.", "drop_reason": "promissory", "specificity": "descriptive"}]}
-{"text": "|No|Key risks|Mitigation Actions|By Whom|By When|\n|---|---|---|---|---|\n|||<br>Organize a workshop to train procurement<br>staff in the DFM on World Bank<br>procurement procedures and work closely<br>with World Bank Procurement Specialist|<br>PIU/IDA|<br>At Project launch and<br>throughout project<br>life|\n|4|Lack of an adapted manual of<br>procedures with a section dedicated<br>to the procurement|Draft and submit to IDA a satisfactory<br>Project Implementation Manual (PIM)<br>with section on procurement detailing out<br>all applicable procedures, instructions and<br>guidance for handling procurement|MoD/PIU|Final version prior to<br>effectiveness|\n|<br>5|Lack of Procurement Plan|Preparation Procurement Plan for the first<br>18 months and agreed with the World<br>Bank<br>and<br>subsequently<br>updating<br>of<br>procurement plans in tandem with annual<br>work plan and budget and for agreed<br>Contracts. The critical approval times will<br>be reflected in the timelines of the<br>procurement plans.|MoD/ Others<br>ministries/DFM<br>|Throughout<br>project<br>life|\n|6|Poor record keeping system|Setting up adequate filling system for<br>project records to ensure easy retrieval of<br>information/data. Designate an officer to<br>be responsible for data management.|PIU|No<br>later<br>than<br>3 <", "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000148", "page": 73, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "project records", "probe_tag": "drop", "probe_score": 0.03292074054479599, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1148, "end": 1163, "key": "refugee_pads:000148:73:0:0", "source": "camp2", "luna_reason": "Routine project records for filing and retrieval are administrative bookkeeping.", "drop_reason": "bookkeeping", "specificity": "vague"}]}
-{"text": " ensure the protection of stateless persons, the\nnaturalization of the Makonde community, and an agreement to naturalize qualifying members of the\nShona community. However, scarce socioeconomic information of stateless populations that is comparable to nationals prevents a deeper understanding of their living conditions, hence hindering efforts\nto design targeted policy aimed at solving statelessness.\n\n\n**The Shona SES provides comparable socioeconomic profiles for the Shona community and nation-**\n**als, while contributing toward informing a targeted response to address the socioeconomic impacts**\n**of the COVID-19 pandemic.** Together with the Department of Immigration Services (DIS) and the\nKenya National Bureau of Statistics (KNBS) of the GoK, UNHCR Kenya, with technical support from the\nWorld Bank, conducted a preregistration exercise and socioeconomic survey for the Shona commu\nnity. The Shona SES marks one of the first quantitative studies of a stateless population that is based\non a national socioeconomic assessment tool. The SES compares the living conditions of the Shona\ncommunity residing in Nairobi and urban Kiambu counties to the conditions of Kenyan nationals in\nsuch counties, as well as to the national urban average. <sup>3</sup> [^3: Results from the Shona survey are compared to those from the Kenya National Bureau of Statistics and its Kenya Integrated\nHousehold Budget Survey 2015/16.] This approach does not attempt to establish\na causal connection between their legal status and living conditions. It does, however, provide evidence that shows strong correlations between statelessness, access to rights, and key indicators of\nwell-being. In addition, the SES links its findings to the results of the first wave of the Kenya COVID-19\nRapid Response Phone Surveys (RRPS) designed to assess the socioeconomic impacts of the COVID19 pandemic on nationals, refugees, and stateless persons.\n\n\n1 Based on the information available from 76 countries.\n2 [https://www.unhcr.org/protection/statelessness/54621bf49/global-action-plan-end-statelessness-2014-2024.html](https", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001424", "page": 10, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Shona SES", "probe_tag": "keep", "probe_score": 0.96, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 413, "end": 422, "key": "sample:reliefweb:001424:10:1:0", "source": "gold", "luna_reason": null}, {"text": "Kenya COVID-19\nRapid Response Phone Surveys", "probe_tag": "keep", "probe_score": 0.9836, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1761, "end": 1804, "key": "sample:reliefweb:001424:10:1:1", "source": "gold", "luna_reason": null}]}
-{"text": " The most notable national level analysis is the 2018 World Bank skills survey, but there are also other studies\nconducted at the regional level, including the recent Refugee Studies Centre reports on Dollo Ado and Addis Ababa,\nand a number of more specific assessments in Jigjiga. The World Bank skills survey provides a range of findings\nabout the level of education and skill of refugees, as well as their current level of economic engagement and poverty\nstatus in Ethiopia (see Table 1). The skills survey highlights both the significant variation in educational attainment\namong different refugee cohorts and the relatively small percentage of completion of secondary school education.\nThe educational challenges have been clearly recognised by the government to the extent that increasing educational\nattainment is a key commitment under the 2016 pledges and the draft NCRRS.\n\n\n28 UNHCR (2017a). Bringing the New York Declaration to Life Applying the Comprehensive Refugee Response Framework (CRRF).\n\n29 UNHCR (2005). Handbook for Self Reliance; see: https://www.unhcr.org/44bf7b012.pdf\n\n30 Available through the ReDSS website; see: https://www.dropbox.com/sh/8k983otoua3xucz/AADPmAkA-twjGyQDmzguMPMwa/Module%205%20Self%20reli<u>ance?dl=0&preview=Module+5+ODI+checklist.doc</u>\n\n31 Holzaepfel and Tadesse (2015). Evaluation: Evaluating the Effectiveness of Livelihoods Programs for Refugees in Ethiopia; Samuel Hall (2014). Living Out of\nCamp: Alternative to Camp-Based Assistance for Eritrean Refugees in Ethiopia; Samuel Hall (2018). Local Integration Focus: Refugees in Ethiopia. Gaps and\nOpportunities for Refugees Who Have Lived in Ethiopia for 20 Years or More.\n\n32 GoE (2019).\n\n33 Woldetsa", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001587", "page": 14, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "skills survey", "probe_tag": "keep", "probe_score": 0.948649525642395, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 496, "end": 509, "key": "reliefweb:001587:14:2:1", "source": "camp2", "luna_reason": "Existing World Bank survey supports findings on refugees’ educational attainment.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "........................................................................................ 21\n\n\n5. CONCLUSION ...................................................................................................................... 23\n\n\n**Figures & Tables**\n\n\nFigure 1. Displacement as of 8 July 2015……………………………………………………………………………………………..5\n\n\nFigure 2. Displacement as of 30 September 2015………………………………………………………………………………..5\n\n\nFigure 3. Family tracing and reunification data, per quarter, 2015……………………………………………………….6\n\n\nFigure 4. Types of GBV reported in the South Sudan GBV IMS, per quarter, 2015…………………………………8\n\n\nFigure 5. Incidents of grave violations reported to", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000601", "page": 1, "chunk": 6, "split": "holdout_annotate", "spans": [{"text": "GBV IMS", "probe_tag": "keep", "probe_score": 0.9576, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 561, "end": 568, "key": "sample:reliefweb:000601:1:6:1", "source": "gold", "luna_reason": "GBV IMS data are presented in a figure showing reported GBV types.", "usage_type": "evidential", "specificity": "named"}]}
+{"text": "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": "la grossesse et de l'accouchement sont la principale\ncause de décès chez les 15-19 ans. <sup>13</sup> Les\nadolescentes enceintes sont plus susceptibles que\nles adultes de recourir à l’avortement à risque ;\nenviron trois millions d'avortements à risque se\nproduisent chaque année chez les filles 15-19 ans. <sup>14</sup>\nLes avortements à risques chez les adolescentes et\nles jeunes de 15-24 ans représentent un peu moins\nde la moitié (40 pour cent) de tous les avortements\nà risque dans le monde. <sup>15</sup> Les effets néfastes de la\ngrossesse chez les adolescentes se répercutent sur\nleurs enfants. Les mortinatalités et décès néonatals\nsont 50 pour cent plus élevés chez les enfants nés\nde mères adolescentes que chez les enfants nés de\nfemmes âgées de 20-29 ans. <sup>16</sup> Les nouveau-nés de\nmères adolescentes sont plus susceptibles d'avoir\nun poids insuffisant à la naissance, avec le risque de\nconséquences à long terme. <sup>17</sup>\n\nUne étude réalisée en 2006 par Magadi et al.\ncomportant des données de l'enquête\ndémographique et de santé de 21 pays d'Afrique\nsubsaharienne a indiqué que les services de santé\nmaternelle ont été généralement sous-utilisés par\nles 15-19 ans par rapport aux femmes de 20", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000749", "page": 10, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "enquête\ndémographique et de santé", "probe_tag": "keep", "probe_score": 0.9377965331077576, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1022, "end": 1055, "key": "reliefweb:000749:10:0:0", "source": "camp2", "luna_reason": "Existing health survey data support a study finding on maternal-service underuse.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "\n7 Includes movement through official crossing points.\n8 [Movements recorded through border monitoring (UNHCR Afghanistan 2024 Border Monitoring Report).](https://data.unhcr.org/en/documents/details/114012)\n9 UNHCR Regional Protection Monitoring System (RPMS) dashboard indicates Türkiye as previous country of asylum for 27 per cent of Afghan nationals. Furthermore,\nRPMS indicates that 50 per cent of the Afghan nationals in Türkiye fled Afghanistan between one and five years ago, and 9 per cent fled Afghanistan more than five\nyears ago, before undertaking onward movements from Türkiye to the EU. Many Afghan nationals interviewed have lived for a long time in Türkiye and often in Iran\nbefore their onward movements due to, for example, administrative measures that force people to move from one province to another, loosing jobs and housing, and\nthe earthquakes.\n10 A significant pathway for refugees, asylum-seekers and migrants en route to Europe from the Middle East, Asia and Africa with Türkiye as the main transit country to\nreach Greece, Cyprus and Bulgaria.\n\n\n**REGIONAL BUREAU FOR ASIA AND THE PACIFIC (RBAP) & REGIONAL BUREAU FOR EUROPE (RBE) |** JULY 2025 3", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000518", "page": 2, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "UNHCR Afghanistan 2024 Border Monitoring Report", "probe_tag": "keep", "probe_score": 0.9243109226226807, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 104, "end": 151, "key": "reliefweb:000518:2:2:1", "source": "camp2", "luna_reason": "Named border monitoring report provides recorded movement evidence.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**DEPARTMENT OF ARAUCA** | August 2024\n\n\n**Methodology**\n\n\nThe methodology of this Protection Analysis Update (PAU) has combined periodic monitoring by the Arauca Local\nCoordination Team, the Children’s Sub-Working Group and the GBV Sub-Working Group, as well as qualitative inputs from\nmeetings and consultations with local partners, key informants, and affected population. The analysis process has followed\nthe methodology of severity, estimations of Persons in Need (PIN), and Protection Analytical Framework (PAF).\n\n\n**Limitations**\n\n\nThis analysis has followed a logic of qualitative and quantitative analysis derived from official data for subsequent\ninterpretation by experts. On the other hand, to avoid potential risks that could be generated for the communities, the\nmeetings with them were limited.\n\n\nTherefore, the exercises for information gathering and analysis of the humanitarian situation focused on secondary data\nand interviews with local actors.\n\n\nFor more information, please contact: **Sebastián Díaz** <u>[diazj@unhcr.org](mailto:diazj@unhcr.org)</u> | **Gabriela Villota** <u>[gabriela.villota@drc.ngo](mailto:gabriela.villota@drc.ngo)</u>\n\n\nPage 10", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000935", "page": 9, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "official data", "probe_tag": "confusion", "probe_score": 0.30548232793807983, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 629, "end": 642, "key": "reliefweb:000935:9:0:0", "source": "camp2", "luna_reason": "Official data is declared as the basis for subsequent analysis.", "usage_type": "declaration", "specificity": "descriptive"}, {"text": "secondary data", "probe_tag": "confusion", "probe_score": 0.5749077796936035, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 918, "end": 932, "key": "reliefweb:000935:9:0:1", "source": "camp2", "luna_reason": "Generic secondary data is mentioned as an information source without concrete use or finding.", "drop_reason": "system_registry", "specificity": "vague"}]}
-{"text": ">|**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>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><", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 17, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "monthly data", "probe_tag": "confusion", "probe_score": 0.0935145914554596, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 146, "end": 158, "key": "reliefweb:001058:17:1:0", "source": "camp2", "luna_reason": "Generic data phrase appears within a table caption and description.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "*35** All figures related to mid-2018.\n\n**36** Refugee figure for Iraqis was a Government estimate. UNHCR has registered\n15,700 Iraqis at the end of 2018. According to some reports many stateless\npersons were naturalized between 2011-2018, but no official figures are yet\nconfirmed.\n\n**37** Refugee figure for Syrians in Turkey was a Government estimate.\n\n**38** IDP figure in Ukraine includes 700,000 people who are in an IDP-like situation.\n\n**39** The statelessness figure refers to stateless persons with permanent residence\nreported by the Government of Uzbekistan in 2010. The figure has been adjusted\nto reflect that citizenship of Uzbekistan has been granted to 6,761 persons since\nDecember 2016.\n\n**40** A study is being pursued to provide a revised estimate of statelessness figure.\n\nSource: UNHCR/Governments.\n\n\n\nUNHCR > **GLOBAL TRENDS 2018** 69", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000649", "page": 67, "chunk": 6, "split": "holdout_annotate", "spans": [{"text": "Refugee figure for Iraqis", "probe_tag": "confusion", "probe_score": 0.7506072521209717, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 47, "end": 72, "key": "reliefweb:000649:67:6:0", "source": "camp2", "luna_reason": "Government-estimated refugee figure for Iraqis is an attributed existing data finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "**A/AC.96/1178**\n\n\ncities in 2017. In April 2018, the OECD published research from 72 cities on local\napproaches to integration, accompanied by a checklist for cities and regions to use in\npromoting integration.\n\n\n56. Successful local integration programmes require efforts from all parties, including\nrefugees in their willingness to adapt, host communities in welcoming them and public\ninstitutions in meeting their needs. In some countries, significant additional support from\nthe international community, taking into account the needs of receiving communities, is\nessential.\n\n\n**D.** **Other pathways for admission**\n\n\n57. Other pathways for the admission of persons needing international protection can\nfacilitate access to protection and solutions, and alleviate pressure on host countries,\nparticularly in large-scale and protracted situations. Such pathways also create\nopportunities for refugees to learn new skills, acquire an education and reunite with family\nmembers in third countries.\n\n\n58. Although refugees sometimes find complementary pathways themselves, such\nprocesses may require the facilitation of administrative measures, complemented with\nprotection safeguards. To this end, UNHCR helped support the establishment and\nexpansion of complementary pathways, including in Argentina, Brazil, Chile, Colombia,\nFrance, Japan and Peru, along with other States in the MERCOSUR region. A new\npartnership was established with the United World Colleges to expand secondary education\nfor refugee students in third countries, and Talent Beyond Boundaries was commissioned to\ncreate a database of refugee talent in Jordan and Lebanon to facilitate labour mobility to\nthird countries. UNHCR and OECD initiated a mapping of non-humanitarian entry visas\nused by refugees in OECD countries to help develop guidance on complementary\npathways. UNHCR also supported the adoption of the African Union Protocol on Free\nMovement of Persons, Right of Residence and Right of Establishment, which will facilitate\naccess to other pathways for admission.\n\n\n59. Despite progress, refugees continue facing barriers and challenges in accessing\ncomplementary pathways, including being unable to obtain exit permits, entry visas and\ntravel documents. Other challenges include", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001472", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "database of refugee talent", "probe_tag": "confusion", "probe_score": 0.12524649500846863, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1594, "end": 1620, "key": "reliefweb:001472:15:0:0", "source": "camp2", "luna_reason": "Database is being created by a commissioned activity, so it does not yet exist.", "drop_reason": "production", "specificity": "descriptive"}, {"text": "mapping of non-humanitarian entry visas", "probe_tag": "confusion", "probe_score": 0.848197340965271, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1720, "end": 1759, "key": "reliefweb:001472:15:0:1", "source": "camp2", "luna_reason": "Mapping was initiated as an ongoing data-production activity, not cited existing data.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": "98<br>1,164<br>-<br>227<br>350<br>7,023<br>7,023<br>2,158<br>-<br>5<br>207<br>2,705<br>26,893<br>102<br>376<br>7,409<br>341<br>-<br>10,668<br>3,293<br>155<br>57,705<br>79<br>24<br>6,905<br>233<br>4,121<br>-<br>218<br>13,788<br>90<br>2,364<br>-<br>7<br>128<br>230<br>76,418<br>10<br>549<br>87<br>1,710<br>10,419|\n\n\n\n**62** UNHCR Global Trends 2015", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001367", "page": 60, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "UNHCR Global Trends 2015", "probe_tag": "confusion", "probe_score": 0.13581140339374542, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 322, "end": 346, "key": "reliefweb:001367:60:5:0", "source": "camp2", "luna_reason": "Named UNHCR report cited as an existing data source.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": " government-controlled areas report slightly worse food security\nthan those in NSAG-controlled areas (68% report skipping a meal in government-controlled areas versus 64%\nin NSAG-controlled areas), possibly because the most\nvulnerable IDPs have fled NSAG areas. Female-headed\ndisplaced households face greater food-related challenges than male-headed households (77% versus 64%),\nbut there is no significant difference in food security\nbetween urban and rural IDPs. While there is need\nfor further analysis to determine the reasons for this\ndeterioration in food security, it is to be noted that last\nyear Afghanistan faced a nationwide drought, the worst\nin a lifetime affecting more than 3 million Afghans and\nresulting in massive displacement in several parts of the\ncountry, in particular the western region.\n\n\nwww.unhcr.org       9\n\n\n\nIDPs\n\n\n**2017 Survey**\n\n\n\n65%\n\n\n\nHost Community\n\n\n\n2017 Returnees 2016 Returnee\n\n\n\nIDPs\n\n\n\n55%\n\n\n\nHost Community\n\n\n\nYes", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000497", "page": 8, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "2017 Survey", "probe_tag": "confusion", "probe_score": 0.42743954062461853, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 849, "end": 860, "key": "reliefweb:000497:8:1:0", "source": "camp2", "luna_reason": "Standalone chart label rather than an independently used survey source.", "drop_reason": "table_artifact", "specificity": "descriptive"}]}
-{"text": "### **Introduction**\n\nThe recent Global Compact for Refugees has acknowledged that the increasing number of forcibly\ndisplaced persons and the difficulty to predict mass-movements of people have created an urgent\nneed for data-driven early warning systems that allow governments and humanitarian organisations\nto use their limited resources most efficiently [1, 2]. Efforts to install early warning systems have led to\nadvances in predicting and forecasting global migration flows; however, forced displacement remains\nthe most elusive and challenging migration form to predict [3, 2, 4].\n\n\nPeople base their decision to migrate on a complex set of different factors. However, in addition to the\ncomplexity of the individual decision-making process, predicting forced displacement flows is further\ncomplicated by the necessity to early detect or predict trigger events. Trigger events, which are often\nthe last link in a long chain of other events that tilt the individual’s decision towards flight, often happen\nrandomly and abruptly [5]. Both processes are difficult to model in and by themselves. However, the\nlack of timely and accurate data at the micro-, meso-, and macro-level further aggravates this problem.\nData needed to model these processes are often either unavailable (micro-level) or outdated (mesoand macro-level).\n\n\nFurthermore, whilst existing refugee flows between countries often are self-perpetuating and can be\npredicted based on historical data, refugee flows from new events pose a challenge because (i) the\nevent might no yet be known to the modeler; (ii) the effect of a new event on future refugee flows is\nunknown; (iii) no historical data from a recent event exist, and it is uncertain to which degree historical\ndata from other events are applicable to predict refugee flows from the new event. The prediction of\nforced displacement flows requires, therefore, first and foremost, a thorough understanding of the\nmechanisms of forced displacement. In particular:\n\n\n1. The factors that lead", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001630", "page": 5, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "historical data", "probe_tag": "confusion", "probe_score": 0.861609697341919, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1453, "end": 1468, "key": "reliefweb:001630:5:0:0", "source": "camp2", "luna_reason": "Existing historical data are used as the basis for predicting refugee flows.", "usage_type": "declaration", "specificity": "vague"}, {"text": "historical data", "probe_tag": "confusion", "probe_score": 0.41850805282592773, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1453, "end": 1468, "key": "reliefweb:001630:5:0:1", "source": "camp2", "luna_reason": "Historical data are used to predict existing refugee flows.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "\n2. Для врегулювання конфлікту багато позитивних ініціатив були виконано донорами під керівництвом або за підтримки в тому числі компенсаційних фондів, що фінансувалися\nдонорськими організаціями. Таким чином, існує необхідність інформування донорів про їх роль в підтримці житлових програм в поєднанні з питаннями доступу до правосуддя на\nперіод відновлення.\n\n\n3. Географія важлива для забезпечення доступу до правосуддя. У ряді країн, які були найбільш успішними в управлінні, існувала добре розвинена система реєстрів нерухомості\n(кадастри) і шкала оцінки землі, які стали важливими чинниками як докази в ході роботи претензійних комісій. Для України потрібна підтримка в розробці системи кадастру країни,\nяка не була розвинена до кризи", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001579", "page": 0, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "реєстрів нерухомості", "probe_tag": "confusion", "probe_score": 0.09233927726745605, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 511, "end": 531, "key": "reliefweb:001579:0:2:0", "source": "camp2", "luna_reason": "Real estate registries served as evidence in claims commission work.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"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": "in accordance with this MOU, UNHCR has deployed 18 support staff in 2014 to the Asylum Service\n(including the COI Department and Regional Asylum Offices), to assist with its quality assurance activities. It should also be noted that the Asylum Service regularly produces detailed, accurate and reliable\nstatistical data and analysis. In order to maintain the progress made to date, EU MS and institutions\nneed to continue support, including through UNHCR, to the Asylum Service.\n\n\nThe processing time for adjudicating applications for international protection has improved significantly. While there are still unprocessed cases pending appeal for more than seven years under the\n“old procedure” operated by the police, the average time in all RAOs from registration to issuance of\nfirst instance decision is 90 days, while the average time from the appeal to the issuance of an appeal\ndecision is 49 days. <sup>103</sup> [^103: These figures represent the average processing time, according to official data by the Asylum Service.] Processing times for applications lodged in administrative pre-removal detention take on average slightly more than 100 days for both first and second instance.\n\n\nImprovements in the quality of the decision-making process have also had an impact on protection\nrates. While under the old system operated by the police, protection rates ranged between 0.86 per\ncent and 2.05 per cent from 2005 to 2014, the new asylum procedure has a first instance recognition\nrate of 17.2 per cent for refugee status and a 7.6 per cent protection rate for subsidiary protection.\nThe average rejection rate is still higher than in a number of other EU MS, and stands at 75.2 per cent.\nIt should be noted, however, that the protection rate for Syrians is 99.5 per cent, Eritreans 79.7 per\ncent, Somalis 66 per cent, Afghans 61.9 per cent, and Ethiopians 61.4 per cent (all figures as of August\n2014).\n\n\nThe appeal stage comprises an administrative examination on issues of fact and", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000978", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "statistical data", "probe_tag": "confusion", "probe_score": 0.5496, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 303, "end": 319, "key": "sample:reliefweb:000978:25:0:0", "source": "gold", "luna_reason": "The sentence states the Asylum Service produces this data.", "drop_reason": "production", "specificity": "vague"}, {"text": "official data by the Asylum Service", "probe_tag": "confusion", "probe_score": 0.8592, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 994, "end": 1029, "key": "sample:reliefweb:000978:25:0:1", "source": "gold", "luna_reason": null}]}
-{"text": "Capítulo 9\n\n## **Limitaciones de datos**\n\n\n\nLa recolección, compilación, control de calidad y\ndifusión de estadísticas sobre personas refugiadas,\nsolicitantes de asilo, desplazadas internas (PDI) y\napátridas sigue siendo un reto. En este capítulo, se\nevalúan las principales limitaciones actuales en relación\ncon los datos y se describen varias medidas que el\nACNUR y sus socios están adoptando para subsanarlas.\n\n\n**Cobertura demográfica**\n\n\nEl desplazamiento forzado y la apatridia afectan a las\npersonas de forma diferente, según su edad, sexo,\ndiscapacidad y otras características de su diversidad.\nLa política del ACNUR basada en la edad, el género y la\ndiversidad (AGD) <sup>**139**</sup> busca garantizar que cada persona\n\n\n\nde la población de interés participe plenamente en las\ndecisiones que la afectan y pueda ejercer sus derechos\nen igualdad de condiciones que las demás.\n\n\nEl ACNUR recoge anualmente datos demográficos\ndesglosados por edad y sexo para sus estadísticas\noficiales. Los datos suelen proceder de los sistemas de\nregistro gestionados por el ACNUR o los Gobiernos de los\npaíses de acogida, o de estimaciones basadas en fuentes\nde datos alternativas, incluidos los datos de registro\nparcialmente disponibles o encuestas por muestreo.\n\n\nEl desglose por sexo está disponible para el 64%", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000160", "page": 65, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "encuestas por muestreo", "probe_tag": "confusion", "probe_score": 0.5040799975395203, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1233, "end": 1255, "key": "reliefweb:000160:65:0:1", "source": "camp2", "luna_reason": "Generic survey source is mentioned without an attributed finding or analytical use.", "drop_reason": "bare_stat", "specificity": "vague"}]}
-{"text": "**MYANMAR SITUATION**\n\n\n\n\n**Overview**\n\n\nMILLION\n### **2.4** **67%** **50%** **27%**\n\npersons of concern from Myanmar\n\n\nare stateless persons (Rohingya)\n\n\nare refugees or asylum-seekers\n\n\nare internally displaced persons\n\n\n### **30,700**\n\n\n\nfled to a neighbouring country in\n\n\n\n2021, following 1 February 2021\n\n\n\n26 Asia & the Pacific Regional Trends on Forced Displacement 2021", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000836", "page": 24, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Asia & the Pacific Regional Trends on Forced Displacement", "probe_tag": "confusion", "probe_score": 0.6935531497001648, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 316, "end": 373, "key": "reliefweb:000836:24:0:0", "source": "camp2", "luna_reason": "Standalone report title in a page header, with no shown data use.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": "### ACRONYMS\n\n\n\n01\n\n\n\n**ACLED** Armed Conflict Data & Event\nData Project\n\n\n**AGD** Age, gender and diversity\n\n\n**BH** Boko Haram\n\n\n**DHS** Demographic Health Surveys\n\n\n**DRC** Democratic Republic of\nthe Congo\n\n\n**FTS** Financial Tracking System\n\n\n**GBV** Gender-based violence\n\n\n**GDFD** Gender Dimensions of\nForced Displacement\n\n\n**HRP** Humanitarian Response Plan\n\n\n**ICRC** International Committee of\nthe Red Cross\n\n\n**IDMC** Internal Displacement\nMonitoring Centre\n\n\n**IDP** Internally displaced person\n\n\n**IOM** International Organization\nfor Migration\n\n\n**IPV** Intimate partner violence\n\n\n**MENA** Middle East and North Africa\n\n\n**MPI** Multidimensional Poverty\nIndex\n\n\n\n**ODI** Overseas Development\nInstitute\n\n\n**SGBV** Sexual and gender-based\nviolence\n\n\n**UCDP** Uppsala Conflict Data\nProgram\n\n\n**UN** United Nations\n\n\n**UNFPA** United Nations Population\nFund\n\n\n**UNHCR** United Nations High\nCommissioner for Refugees\n\n\n**UNICEF** United Nations Children’s\nFund\n\n\n**UN OCHA** United Nations Office\n\nfor the Coordination of\nHumanitarian Affairs\n\n\n**USAID** United States Agency for\nInternational Development\n\n\n**VAW** Violence against women\n\n\n**WGSS** Women and girls’ safe\nspaces\n\n\n**WPS** Women, peace and security\n\n\n\nThe authors of this paper conducted their research under the Gender Dimensions of Forced\nDisplacement project. The project is co-led by Lucia Hanmer and Diana Arango under the guidance of\nHana Brixi, Global Director, Gender Unit, World Bank Group.\n\n\nThis work is part of the program ‘Building the Evidence on Protracted Forced Displacement: A MultiStakeholder Partnership’. The program is funded by UK aid from the United Kingdom’s Foreign", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001238", "page": 3, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Demographic Health Surveys", "probe_tag": "confusion", "probe_score": 0.22044359147548676, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 139, "end": 165, "key": "reliefweb:001238:3:0:1", "source": "camp2", "luna_reason": "Acronym glossary entry with no evidence of survey data use.", "drop_reason": "system_registry", "specificity": "named"}, {"text": "Uppsala Conflict Data\nProgram", "probe_tag": "confusion", "probe_score": 0.08120754361152649, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 772, "end": 801, "key": "reliefweb:001238:3:0:2", "source": "camp2", "luna_reason": "Acronym expansion only; no data use or cited finding is shown.", "drop_reason": "system_registry", "specificity": "named"}]}
-{"text": "### **ACHIEVEMENTS FROM THE FIELD:** **SUBNATIONAL CLUSTERS**\n\n\n\nthe subcluster led one meeting with all\n\nthe organizations working with the pro\nvision of assistance and information\n\nfor people on the move, to identify the\n\nmain protection risks and the possible\n\nresponse for each of them. The results\n\nwere shared with all the partners and\n\nenabled them to support their financial\n\npleas to donors.\n\n\nIn alliance with cluster partners and the\n\nGBV AoR, the subnational Cluster car\nried out a training on GBV prevention,\n\nsafe referrals, clinical management of\n\nsexual violence, the Child and Adoles\ncent Protection System in Venezuela,\n\nfirst-aid, and psychosocial support. In\n\naddition to the training, a joint response\n\nwas activated through additional ser\nvices related to sexual and reproductive\n\nhealth and GBV case management pro\nvided in the information points by some\n\npartners.\n\n\n\nAs part of the Mental Health and Psycho\nsocial Support (MHPSS) in Emergencies\n\nWorking Group, the subnational Clus\nter along with the health cluster, co-led\n\nmeetings with partners providing psy\nchosocial support services to identify the\n\ngaps and needs related to mental health\n\nin the States of Táchira and Mérida,\n\nupdate the mapping of MHPSS services,\n\nand prepare an action plan for the work\n\ngroup with roles and responsibilities for\n\nhumanitarian organizations.\n\n\n**Subnational** **Cluster** **Barinas.** In\n\nBarinas State, in coordination with sub\nnational Cluster members, assistance\n\nwas provided to returnees, and livelihood\n\nactivities were carried out to facilitate\n\ncommunity reintegration. Permanent\n\nlinks are maintained with the Administra\ntive Service for Identification, Migration,\n\nand Foreigners (SAIME by its Spanish\n\nacronym), the Department of Protection,\n\n\n\nthe Child Protection Council, and the pre\nfecture for the referral of cases involving\n\npeople on the move and returnees with\n\nspecific protection risks.\n\n\nStrategic campaigns were also con\nducted with", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001013", "page": 21, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "mapping of MHPSS services", "probe_tag": "confusion", "probe_score": 0.32243630290031433, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1221, "end": 1246, "key": "reliefweb:001013:21:0:0", "source": "camp2", "luna_reason": "Updating a service mapping produces or maintains project information, not existing data use.", "drop_reason": "production", "specificity": "descriptive"}]}
-{"text": " countries studied in OECD\ncountries plus Brazil in the respective years.\n\n\nThere is further undercoverage with respect to data\non family permits: the data obtained for some host\ncountries exclude permits for family reunification\nwith a person under international protection (Japan,\nMexico) or under subsidiary international protection\n(Switzerland), whereas the data for Ireland exclude\nchildren below the age of 16 and the data for Canada\nexclude family members who reunified with persons\nissued with non-humanitarian permits.\n\n\n# 5 Analysis of admission trends\n\n\n\nOver the 2010–2019 period, a combined total of\nfour million new asylum applications were submitted\nin OECD countries and Brazil by nationals of\nAfghanistan, Eritrea, Iran, Iraq, Somalia, Syria and\nVenezuela. In the same period, close to 1.5 million\nfirst-time residence permits were granted by OECD\ncountries and Brazil to nationals of the seven\ncountries for family, work, or education-related\n\n\n\nreasons, including about 156,000 in 2019 alone.\nDuring the decade, about 2.2 million individuals\nof the same nationalities were recognized as\nrefugees or granted a subsidiary form of protection\nand 572,000 persons from the seven populations\nconcerned arrived in OECD countries and Brazil\nthrough resettlement programmes.\n\n\n\n<u>14</u>", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001237", "page": 12, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data for Canada", "probe_tag": "confusion", "probe_score": 0.302289217710495, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 425, "end": 440, "key": "reliefweb:001237:12:1:1", "source": "camp2", "luna_reason": "Existing Canadian data support a concrete coverage-exclusion finding.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " Facebook products is that Facebook only provides very\nlimited information on their methods and definitions. It is, for example, unclear how Facebook defines\nits user’s ex-pat status [58, 6, 60].\n\n\nSince Zagheni et al. [58] introduced Facebook’s advertising platform as a new Big Data source, it\nhas become a popular alternative data source for migration and demographic researchers, as its\nfree API makes the data easily accessible [58, 59]. However, scraping the Facebook Advertising\nplatform might, under certain conditions, violate Facebook’s terms of services (Alex Pompe, verbatim). Zagheni et al. introduce data from Facebook’s Advertising platform to estimate migrant stocks.\nSpyratos et al. [60] use data on migration from Facebook’s advertising platform to map-out migration\nflows to 119 countries of residence for two time periods. The data allows them to detail migration\nflows by age, gender, and country of origin. They suggest a method to correct the bias in the Facebook data and find that the estimates positively correlate with official statistics on migration. They\nconclude that data from Facebook advertising, once corrected for biases, can be used as a cheap\nand globally available real-time supplement to official migration statistics and are accurate enough to\nbe used in trend-analyses and early-warning purposes. Palotti et al. [59] support this finding and develop a method to use Facebook’s advertising data for real-time monitoring of crises situations using\nVenezuelan migrants as a case study. They conclude that despite the biases in the Facebook data\nand the potential noise in the Facebook algorithm that determines a user’s country of origin, data from\nthe Facebook advertising platform correlate sufficiently with official statistics to be used for density\nmapping in crises.\n\n\n24 UNHCR", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001630", "page": 23, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "data from Facebook’s Advertising platform", "probe_tag": "confusion", "probe_score": 0.8003168702125549, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 614, "end": 655, "key": "reliefweb:001630:23:1:0", "source": "camp2", "luna_reason": "Facebook advertising data are used to estimate migrant stocks.", "usage_type": "evidential", "specificity": "named"}, {"text": "data on migration from Facebook’s advertising platform", "probe_tag": "confusion", "probe_score": 0.879402220249176, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 709, "end": 763, "key": "reliefweb:001630:23:1:1", "source": "camp2", "luna_reason": "Facebook migration data are used to map flows and compare with official statistics.", "usage_type": "evidential", "specificity": "named"}, {"text": "Facebook data", "probe_tag": "confusion", "probe_score": 0.897508978843689, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 978, "end": 991, "key": "reliefweb:001630:23:1:5", "source": "camp2", "luna_reason": "Facebook data are used to show estimates correlate with official migration statistics.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "**BANGLADESH.** **_Amir Khan (65), works at_**\n**_sewing clothes, under the light provided_**\n**_by solar panels, at night, in Camp 1 East,_**\n**_Kutupalong camp, Cox’s Bazar,_**\n**_Bangladesh. An estimated 915,000_**\n**_Rohingya live in refugee camps in the_**\n**_area of Cox’s Bazar, Bangladesh._**\n**_More than half of them (nearly 55%)_**\n**_are children under the age of 18 years._**\n\n© UNHCR / VINCENT TREMEAU\n\n\nUNHCR > **MID-YEAR TRENDS REPORT 2020** 29", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000911", "page": 28, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "MID-YEAR TRENDS REPORT 2020", "probe_tag": "confusion", "probe_score": 0.12928646802902222, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 428, "end": 455, "key": "reliefweb:000911:28:0:0", "source": "camp2", "luna_reason": "Report title appears as document header without shown data use.", "drop_reason": "ref_list", "specificity": "named"}]}
-{"text": " and in total children survivors\ncan be explained by the fact that most of those who seek help are\n\n\n6 \u0007Women and young persons with disabilities https://www.unfpa.org/featuredpublication/women-and-young-persons-disabilities\n\n\n7 \u0007Management Sciences for Health & UNFPA, We Decide Young Persons with\nDisabilities: Equal Rights and a Life Free of Violence (May 2016), https://www. msh.\norg/sites/msh.org/files/ we_decide_infographic.pdf\n\n\n\nsupported by child protection actors who are not part of the GBV\nIMS Task Force as per established standard operating procedures\n(SOPs) and referral pathways.\n\n\nGay and bisexual men face increased risks of sexual violence. In\nthis context, it is important to underline that the establishment\nor strengthening of services for male survivors should not affect\nservice provision for women and girls: funding for “Safe Spaces for\nWomen and Girls” (SSWG) should be maintained, while additional\nfunding should be sought for interventions for male survivors.\nNevertheless, there is a need to strengthen GBV prevention and\nresponse programming to outreach Lesbian and bisexual women\nwho may expose to further risks based on their sexual orientation.\n\n\nWomen and young persons with disabilities experience the same\nforms of GBV as individuals without disabilities <sup>6</sup> . In fact, studies\nshow that persons with disabilities are three times more likely\nto experience physical violence, sexual violence, and emotional\nviolence than persons without disabilities <sup>7</sup> .\n\n\nCollected data in 2020 indicates 28% increase in GBV incidents\nreported by survivors with disabilities compared to 2019. In line\nwith previous years trend more people with physical disability\nreported incidents compared to people with mental disability.\n\n\nThis comes as a result of continues capacity building efforts by\nthe Task Force members to other humanitarian aid workers and\ncommunity based organisations staff who work with persons with\n\n\n\n6", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001279", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "Collected data in 2020", "probe_tag": "confusion", "probe_score": 0.5744212865829468, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1513, "end": 1535, "key": "reliefweb:001279:5:1:0", "source": "camp2", "luna_reason": "Existing 2020 data supports a reported increase in GBV incidents.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": " credibility. When available, video material, lists of victims and supplementary\ninformation from protection cluster partners is incorporated.\n\nCIMP monitors civilian impact that occurs after an incident of armed violence have taken place, thus CIMP numbers on\n\ndisplacement, loss of livelihood and restriction of movements/obstruction to flight only covers households that have experienced a\ndirect impact from armed violence, e.g. a house destroyed or a vehicle hit. Therefore, CIMP data does not include full numbers of\npeople being displaced, loosing livelihood or experiencing restricted freedom of movement/obstruction to flight, where numbers are\nnaturally much higher than what is captured by CIMP.\n\nCivilian impact incidents recorded by CIMP are divided into direct and indirect impact, with associated direct and indirect protection\nimplications. Direct impact includes incidents in which individuals or households are directly affected by the incident, e.g. damage to\nhouses and farms, damage to markets and local businesses, impact on vehicles or as well as exposure to UXOs and armed conflict\ngenerating casualties. Indirect impact can broadly be defined as incidents of armed violence impacting on infrastructure and basic\nservices and in turn restricting access of civilians to various vital services, infrastructure and goods, e.g. healthcare, education, food\nand water and transport infrastructure. Due to the nature of the indirect impact, the number of households impacted is often much\nhigher than during direct impact.\n\nAs CIMP aims to collect and disseminate data on civilian impact that occurs as a result of armed conflict, some incidents are\nexcluded. This includes incidents related to crime, domestic violence and small arms fire incidents that occurs away from areas of\nactive conflict and have less than two casualties. Small arms fire incidents are always included when they occur in areas of active\nconflict.\n\n\n###### **3**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000783", "page": 4, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "CIMP data", "probe_tag": "confusion", "probe_score": 0.3748, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 480, "end": 489, "key": "sample:reliefweb:000783:4:1:0", "source": "gold", "luna_reason": null}, {"text": "data on civilian impact", "probe_tag": "drop", "probe_score": 0.0067, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1581, "end": 1604, "key": "sample:reliefweb:000783:4:1:1", "source": "gold", "luna_reason": null}]}
-{"text": "EGYPT REFUGEE AND RESILIENCE RESPONSE PLAN (ERRRP)\nJanuary - December 2025 5\n\n### AT A GLANCE\n##### Country Planned Response January-December 2025\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**<mark>Population Planning Figures</mark>**\n\n\n**Country**\n\n\nSudanese Refugee Population\n\nSyrian Refugee Population\n\nOther Refugee Population\n\n\nHost Community\n\n\n\n**Refugees pre**\n**15 April 2023**\n\n\n60,779\n\n146,995\n\n85,846\n\n\n\n**Population as of**\n**end of Dec 2024**\n\n\n602,702\n\n147,797\n\n126,513\n\n\n\n**Planned**\n**Population as**\n**of end of 2025**\n\n\n1,142,331\n\n137,962\n\n149,035\n\n\n432,017\n\n\n\nTotal Projected Population in Need: **1,861,345**\n\n\n\n\n\n**14%**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000675", "page": 4, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Population Planning Figures", "probe_tag": "drop", "probe_score": 0.04828067496418953, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 176, "end": 203, "key": "reliefweb:000675:4:0:0", "source": "camp2", "luna_reason": "Standalone table header, not an independent data-use mention.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "BuildUp was also developed to counter hostile and toxic narratives against refugees online and promote digital](https://howtobuildup.org/)</u>\npeacebuilding and acceptance by host communities.\n\n\nImportantly, in relation to the COVID-19 pandemic, **89 per cent of 140 countries** reporting indicated that areas\ninhabited by refugees, internally displaced persons (IDPs) and other forcibly displaced and stateless persons were\nreached by information campaigns about COVID-19 pandemic risks.\n\n\n**~~Feedback and Response~~**\n\n\nIn 2021, important efforts were made to maintain or expand opportunities for feedback from the people that\nUNHCR worked with and for, though with higher reliance on remote methods and technology than in the past. New\ninitiatives were also initiated to address gaps in operations’ capacity to manage large unstructured quantities of\nfeedback data and investments were made in multiple communication channels to maintain proximity with people\nof concern to UNHCR. This included further development of contact centres’ referral and response mechanisms,\nincluding at the inter-agency level.\n\n\nAs a result, **65 per cent of reporting operations** have multi-channel feedback and response systems designed\nbased on consultations with communities.\n\n\n**~~Organizational Learning and Adaptation~~**\n\n\nThis is an area that requires further investment. Reporting on this aspect remained quite limited in 2021, highlighting\nthe need for strengthened knowledge-sharing to support learning and adaptation and the scale-up of innovative\napproaches. Interim findings from the ongoing longitudinal evaluation of the AGD Policy also suggested limited use\nof feedback from participatory exercises to inform adaptations of programme activities. <sup>4</sup> Moreover, siloed ways of\nworking often prevent a more systematic inclusion of feedback and learning.\n\n\n4 UNHCR, “Longitudinal evaluation of the implementation of UNHCR’s Age, Gender and Diversity Policy – Year 1 report” (2022). Available from <u>[www.un", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000524", "page": 7, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "feedback data", "probe_tag": "drop", "probe_score": 0.0077, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 855, "end": 868, "key": "sample:reliefweb:000524:7:1:0", "source": "gold", "luna_reason": null}]}
-{"text": "**<u>2.3 Challenges and Limitations</u>**\n\n\n**The research instruments were translated**\n**from English to Bangla. The enumerators were**\n**unable to use Rohingya language to conduct**\n**research at field level. However, using Bangla**\n**questionnaires, the enumerators articulated**\n**the questions in the** **_Chittagonian_** **dialect,**\n**and took notes in Bangla. Some richness and**\n**nuances in data might have been lost due**\n**to applying different languages in the data**\n**collection process.**\n\n\n**Limited time was allocated for reviewing**\n**and adapting quantitative and qualitative**\n**tools from CARE’s gender analysis toolkit and**\n**customising training for this research. Limited**\n**comprehension of the tools could have led**\n**to misinterpretation of the survey questions**\n**by the enumerators as well as respondents.**\n**This could also have been due to the limited**\n**understanding of gender concepts.**\n\n\n**Qualitative data from the host community**\n**was very limited. More effort could also have**\n**been placed on identifying people living with**\n**disabilities in the host community, as well as**\n**from the camps.**\n\n\n\nWhile the experiences and views of people living with\ndisabilities from the host community were absent in the\ndata gathered, data collected from people living with\ndisabilities in the refugee communities gave limited\ninsight into their experiences. Out of four participants,\none pregnant woman was included as a person living\nwith a disability, indicating a limited understanding of the\ntopic among enumerators or little time to identify and\nrecruit people living with", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000732", "page": 28, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "Qualitative data", "probe_tag": "drop", "probe_score": 0.03573555499315262, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 934, "end": 950, "key": "reliefweb:000732:28:0:0", "source": "camp2", "luna_reason": "Qualitative data are reported as very limited in the host community.", "usage_type": "evidential", "specificity": "vague"}, {"text": "data collected from people living with\ndisabilities", "probe_tag": "confusion", "probe_score": 0.2422303855419159, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 1276, "end": 1327, "key": "reliefweb:000732:28:0:1", "source": "camp2", "luna_reason": "Collected disability data provided limited insight into refugee communities' experiences.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": ">4,755<br>3,113<br>Before<br>2019<br>2019<br>2020<br>2021<br>2022<br>2023<br> <br>* Figures have been revised in June by removing individuals found in<br>VolRep and Data Transfer Request.<br> <br>*** The flow**s**<br>country of a<br>|926<br>3,276<br>1,777<br>2,051<br>4,755<br>3,113<br>Before<br>2019<br>2019<br>2020<br>2021<br>2022<br>2023<br> <br>* Figures have been revised in June by removing individuals found in<br>VolRep and Data Transfer Request.<br> <br>*** The flow**s**<br>country of a<br>|", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001463", "page": 3, "chunk": 2, "split": "holdout_annotate", "spans": [{"text": "VolRep and Data Transfer Request", "probe_tag": "drop", "probe_score": 0.016291508451104164, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 154, "end": 186, "key": "reliefweb:001463:3:2:0", "source": "camp2", "luna_reason": "Named data mechanisms used to revise figures by removing duplicate individuals.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": " APC.\n## **CONCLUSION**\n\n\nThe APC Guidance Note facilitates the identification of key areas of work to redefine strategic priorities\nfor the APC. It provides highlights on some patterns of abuse and specific categories of population\nthat are exposed to threats. It also suggests key coordination and partnership areas for the APC to\nstrengthen.\n\n\nHowever, it also highlights the APC’s limited capacity to collect protection data and build up a more\nrobust and comprehensive protection analysis. The main challenges have been identified as limited\nhumanitarian access, sensitivity related to some protection thematic, a lack of information sharing\namong different agencies, limited capacity and knowledge to operationalize the protection risks\nequation, a lack of conflict sensitivity analysis and limited protection assessments. The available\nprotection analysis is usually limited to the overall chronic issues in the country, while conflict and\ndisplacement related risks and threats remain less explored and assessed.\n\n\nThose limitations can be overcome should the APC members prioritize the resources to fill those gaps\nand increase their commitment to the coordination system for the protection sector.\n\n\nA workshop with APC members will be organized in the course of August 2017 which will provide an\nopportunity to produce a joint protection analysis that would support a prioritization exercise.\n\n\nIntegrated protection response plans are also under development at regional level and will provide a\nregional perspective of the protection context and priorities.\n\n\nPage **10** of **12**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000384", "page": 9, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "protection data", "probe_tag": "drop", "probe_score": 0.047031424939632416, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 413, "end": 428, "key": "reliefweb:000384:9:1:0", "source": "camp2", "luna_reason": "Data collection capacity is discussed, not use of existing protection data.", "drop_reason": "production", "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": "Refugee women founded the Heriyetu Foundation at Nakivale settlement in Uganda – a group that has launched a wine-making business, pharmacy and savings and\nloans programme. © UNHCR/Esther Ruth Mbabazi\n\n\n~~X~~ **~~Inclusive Programming~~**\n\n\n\n\n\n\n\n**3** Core Action 1 of the AGD Policy is applicable to UNHCR primary data collection activities. It applies only to operational data, defined as data and information that\npertains to a crisis/situation, the persons affected by the crisis/situation, and the response to the crisis/situation.\n\n\n14", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000271", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "operational data", "probe_tag": "drop", "probe_score": 0.02806559018790722, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 362, "end": 378, "key": "reliefweb:000271:12:0:0", "source": "camp2", "luna_reason": "Defines a generic data category without showing existing data use.", "drop_reason": "system_registry", "specificity": "vague"}]}
-{"text": "##### Appendix 1:\n## **Search terms**\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|String Search #|Search terms|Date of the search|Database/source|Number of total results|Number of potentially relevant results (title screening)|Number of results of i fcially meeting inclusion criteria (abstract screening)|\n|---|---|---|---|---|---|---|\n|1|(“Myanmar” OR “Burma” OR “Rakhine” OR<br>“Bangladesh” OR “Malaysia” OR “India” OR<br>“Thailand” OR “Asia” OR Refugee* OR Asylum<br>Seeker* OR Displace* OR Rohingya*)**AND** <br>(“Humanitarian” OR “Emergency” OR “Disaster”<br>OR “Confict” OR “War” OR “Violence” OR<br>“Warfare” OR “Armed Confict” OR “Mass<br>Confict” OR Persecut* OR “Civil Confict” OR<br>“Genocide” OR “Mass Murder” OR “Human<br>Rights” OR “Ethnic Cleansing” OR “Mass<br>Violence”)|25/10/2017|CINAHL|3424|6|1|\n|1|(“Myanmar” OR “Burma” OR “Rakhine” OR<br>“Bangladesh” OR “Malaysia” OR “India” OR<br>“Thailand” OR “Asia” OR Refugee* OR Asylum<br>Seeker* OR Displace* OR Rohingya*)**AND** <br>(“Humanitarian” OR “Emergency” OR “Disaster”<br>OR “Confict” OR “War” OR “Violence", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001165", "page": 46, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "CINAHL", "probe_tag": "drop", "probe_score": 0.040794093161821365, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 797, "end": 803, "key": "reliefweb:001165:46:0:0", "source": "camp2", "luna_reason": "Named database used for the documented literature search and results.", "usage_type": "declaration", "specificity": "named"}]}
-{"text": ">Men (51%)<br>Women (49%)|**Hosts**<br>(KIHBS<br>2015)<br>Men (52%)<br>Women (48%)|**Hosts**<br>(KIHBS<br>2015)<br>Men (52%)<br>Women (48%)|\n||Gender|Gender|Gender|Gender|Gender|Gender|Gender|\n||Age|Below 18:<br>71%<br>Above 64:<br>0.6%|Below 18:<br>61%<br>Above 64:<br>0.4%|Below 18: 60%<br>Above 64: 0.4%|Below 18:<br>45%<br>Above 64:<br>1.8%|Below 18: 32%<br>Above 64:<br>0.7%||\n||Dependency<br>ratio|1.9|1.2|1.4|0.6|0.4||\n||Women-<br>headed<br>households|66%|56%|47%|41%|32%|➢ Women and girls’ empowerment programmes in camps and urban<br>areas can help alleviate barriers to accessing socioeconomic<br>opportunities and build and maintain human capital.<br>➢ Financial inclusion programmes coupled with entrepreneurship skills,<br>business training and cash grants targeting women, especially those<br>with young dependents, can be a starting point to unlock refugee<br>women’s socioeconomic potential.|\n||Improved<br>housing|5%|3%|8%|82%|78%|➢ Scaling up permanent shelters in Kalobeyei with", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000574", "page": 5, "chunk": 1, "split": "holdout_annotate", "spans": [{"text": "KIHBS", "probe_tag": "drop", "probe_score": 0.0011, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 40, "end": 45, "key": "sample:reliefweb:000574:5:1:0", "source": "gold", "luna_reason": null}, {"text": "KIHBS", "probe_tag": "drop", "probe_score": 0.0006, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 97, "end": 102, "key": "sample:reliefweb:000574:5:1:1", "source": "gold", "luna_reason": "Named household survey cited as the source for demographic figures.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "|-|101,760|97,012|-|-|-|3,790|-|-|202,562|\n|Cayman Islands|36|-|36|13|-|-|-|-|-|52|101|\n|<br>Central African Rep.|7,175|-|7,175|311|46,523|669,906|90,672|-|-|-|814,587|\n|<br>Chad|442,672|-|442,672|3,759|308|170,278|-|-|122,359|-|739,376|\n|Chile|2,053|-|2,053|8,545|-|-|-|-|2,073|452,712|465,383|\n|China, Hong Kong SAR|130|-|130|-|-|-|-|-|-|-|130|\n\n\n72 UNHCR > **GLOBAL TRENDS 2019**", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001657", "page": 71, "chunk": 5, "split": "holdout_annotate", "spans": [{"text": "GLOBAL TRENDS 2019", "probe_tag": "drop", "probe_score": 0.022953441366553307, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 362, "end": 380, "key": "reliefweb:001657:71:5:0", "source": "camp2", "luna_reason": "Standalone report/table heading, not a cited or analyzed data resource.", "drop_reason": "table_artifact", "specificity": "named"}]}
-{"text": "**Annex 1: Matrix for HIV/AIDS Interventions in Emergency Settings**\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Sectoral Response|Emergency preparedness|Minimum response (to be conducted<br>even in the midst of emergency)|Comprehensive response<br>(Stabilized phase)|\n|---|---|---|---|\n|1. Coordination|• Determine coordination structures<br>• Identify and list partners <br>• Establish network of resource<br>persons <br>• Raise funds <br>• Prepare contingency plans <br>• Include HIV/AIDS in humanitarian<br>action plans and train accordingly<br>relief workers|<br>1.1 Establish coordination mechanism <br> <br> <br> <br>|• Continue fundraising <br>• Strengthen networks <br>• Enhance information sharing <br>• Build human capacity <br>• Link emergency to development HIV action <br>• Work with authorities <br>• Assist government and non-state entities to promote and protect<br>human rights4 <br>|\n|2. Assessment and<br>monitoring <br>3. Protection|• Conduct capacity and situation<br>analysis <br>• Develop indicators and tools <br>• Involve local institutions and<br>beneficiaries <br>• Review existing protection laws<br>and policies <br>• Promote human rights and best<br>practices <br>• Ensure that humanitarian activitie s<br>minimize the risk of sexual violence,<br>and exploitation, and HIV-related<br>discrimination <br>• Train uniformed forces and<br>humanitarian workers on HIV/AIDS<br>and sexual violence|2.1 Assess baseline data <br> <br>2.2 Set up and manage a shared database <", "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000612", "page": 12, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "baseline data", "probe_tag": "drop", "probe_score": 0.021905558183789253, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 1403, "end": 1416, "key": "reliefweb:000612:12:0:0", "source": "camp2", "luna_reason": "Span is embedded in a table listing assessment activities.", "drop_reason": "table_artifact", "specificity": "vague"}]}
-{"text": "_Figure 4 Ranking the criticality of links in Peru’s road network_\n\n\nFigure 5 maps the economic costs of disruption over all candidate critical links. The links with daily costs\nhigher than $2 million are shown in red and all are located on the Pan Americana Highway. This is not\nsurprising as this is the road with the highest daily traffic and it is located between the sea and the\nmountains; thus, it has little redundancy.\n\n\nNext, we explore the critical links most exposed to disruptions caused by natural disasters.\n\n\nFirst, we overlay the network with the flood maps described in section 2.2. The links with the highest cost\nand kilometers increase that are also exposed to floods are all on the Pan Americana highway (Figure 5).\nThe cluster Pan Americana – a set of critical links located on the Pan Americana highway – is exposed to\nriver and coastal floods, and if disrupted costs close to $3 million a day to its users – forcing them to drive\nan average of 300 additional kilometers. The area North of Arequipa presents the highest economic losses\nand very low redundancy, so we focus our analysis on this section (cluster Pan Americana in Figure 6).\n\n\n14", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007005", "page": 15, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "flood maps", "probe_tag": "confusion", "probe_score": 0.368268221616745, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 563, "end": 573, "key": "prwp:007005:15:0:0", "source": "camp2", "luna_reason": "Flood maps are overlaid with the network to identify disruption exposure and losses.", "usage_type": "evidential", "specificity": "descriptive"}]}
-{"text": "Systematically collecting and disseminating such data should follow best practices.\n\n\nBalancing reporting costs against obvious benefits, surveys could be updated to\n\n\nincorporate critical information missing in existing questionnaires. Closer collaboration\n\n\nbetween transport ministries or departments and statistical agencies would leverage\n\n\nexisting knowledge base, inform data needs and capabilities, and help avoid replication\n\n\nof efforts. As alluded to in Table 1, governmental agencies can increase the use and\n\n\nbenefit of their existing products by providing transparent procedures to facilitate access\n\n\nto micro-data and sharing aggregated statistics in their websites—and making these\n\n\navailable in English for global reach. Moreover, low-cost improvements to existing\n\n\nefforts could make them more informative for measuring overland transportation costs.\n\n\nFor example, to aide estimation from price gaps, data that is regularly collected for\n\n\ncompiling the consumer price index (CPI) could cover additional locations so as to\n\n\ngenerate sufficient geographic and spatial variation for this methodology to be more\n\n\nreliable. Another consideration described above is the comparability of products for\n\n\nwhich prices are collected. To the extent possible, targeting the same brands for any\n\n\ngiven product would be a good practice for not just precisely measuring transport\n\n\ncosts but also the CPI. Other potentially helpful data products are consistent and\n\n\nfrequent measures of road quality and traffic volumes. Once again, such data are\n\n\noften collected in order to monitor maintenance needs and congestion. There are well\n\nestablished methods to define and quantify road quality such as the International Road\n\n\nRoughness Index. Appropriately designing the spatial features of these collection efforts\n\n\nwould come at minimal additional cost but increase their usefulness for the purpose of\n\n\nmeasuring and lowering overland transportation costs.\n\n#### **References**\n\n\nAlder, S., Song, Z. and Zhu, Z. (2021). Unequal returns to China’s intercity road\n\n\nnetwork. Working Paper.\n\n\nAllen, T., and Arkolakis, C. (2014). Trade and the Topography of the Spatial Economy.\n\n\nThe Quarterly Journal of Economics, 129(3), 1085", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001016", "page": 22, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "consumer price index", "probe_tag": "confusion", "probe_score": 0.8055770993232727, "luna_label": 0, "human_verdict": null, "human_note": "", "start": 977, "end": 997, "key": "prwp:001016:22:0:0", "source": "camp2", "luna_reason": "Proposes expanding CPI data coverage for future estimation rather than using existing data.", "drop_reason": "promissory", "specificity": "named"}]}
-{"text": "efficiency and equity. Likewise, they must guarantee the costs of the teaching, management, and\nadministrative personnel with their corresponding social benefits. Thus, an associated cost per\nstudent is assigned for each ETC and educational level, with differential costs between urban and\nrural areas.\n\nThe sources of information used come from: the initial distribution document of SGP-education\nresources in order to extract the allocation per student, ETC, educational level, and urban or rural\narea. The GEIH is used to identify students according to educational level (transition, primary,\nmiddle, and high school in official schools) and the information collected in the CEQ 2017 on the\nSole Regional Form (FUT, as per the acronym in Spanish) containing the municipalities'\nexpenditures on education.\n\nIn CEQ 2017, the distribution of resources executed in education was calculated between the SGP\nand other sources, within which the ETCs' own resources are included. This led to the calculation\nof a constant that is interpreted as the additional percentage to the SGP resources to finance\neducation in each ETC. Assuming that there are no significant changes in this percentage between\n2017 and 2021, this value is multiplied by the initial assigned value of the distribution document,\nupdated to 2021. In addition to this assumption, it is also assumed that each additional resource\nto the SGP is distributed proportionally to each student. The Table A20 presents the value\nassigned in the 2017 CEQ and current CEQ for 10 selected ETCs (out of 95 in total).\n\n**Table A20. Distribution of resources executed in education between SGP and other sources (in pesos)**\n\n<u><mark>2021 GEIH</mark></u>\n<u><mark>ETC</mark></u> <u><mark>Preschool</mark></u> <u><mark>Primary</mark></u> <u><mark>", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000584", "page": 84, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "GEIH", "probe_tag": "confusion", "probe_score": 0.6442582011222839, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 509, "end": 513, "key": "prwp:000584:84:0:0", "source": "camp2", "luna_reason": "GEIH data are used to identify students by educational level.", "usage_type": "evidential", "specificity": "named"}]}
-{"text": "24\n\n\nAlthough we cannot predict the future height of the Saigon River, this evidence\nsuggests that the height of the Saigon River may significantly surpass the 45 cm threshold\nto which the Baseline Strategy is robust. This further suggests that the Baseline Strategy\ndoes not meet its objectives in a wide enough range of plausible conditions, i.e. is not\nsufficiently robust. It strongly supports the city’s desire to seek additional flood risk\nmeasures, and supports Steering Center for Flood Control’s pursuit of an integrated flood\nrisk management strategy that augments the infrastructure described by the Baseline\nStrategy.\n\n\n**Figure 5.4. Range of future conditions in which the Baseline strategy meets**\n**decision makers’ objectives, defined as reducing risk for the poor and non-poor.**\n\n_Note: Vertical lines over rainfall intensity estimates show IPCC SREX mean and high projections_\n_for extreme precipitation events in Southeast Asia in 2045-2065. Horizontal lines over Saigon_\n_River levels show recent estimates of eustatic sea level rise and eustatic sea level rise with_\n_subsidence._\n\n###### **Scenarios Help Compare the Robustness of Alternative Strategies**\n\nThe analysis so far suggests that Ho Chi Minh City should consider augmenting the\nBaseline Strategy. This section examines the performance of the Baseline Strategy when\naugmented with a variety of adaptation and retreat options that Ho Chi Minh City might\npursue, in particular the nine alternative strategies described in Section 4. The analysis\naims to help decision makers ask two key questions: Which options or combination of", "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005616", "page": 25, "chunk": 0, "split": "holdout_annotate", "spans": [{"text": "IPCC SREX", "probe_tag": "confusion", "probe_score": 0.8140744566917419, "luna_label": 1, "human_verdict": null, "human_note": "", "start": 859, "end": 868, "key": "prwp:005616:25:0:0", "source": "camp2", "luna_reason": "IPCC projections provide rainfall estimates used in the figure’s scenario analysis.", "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": "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"}]}