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|---|---|---|---|---|---|---|---|---|---|---|---|---|
jdc_operational:000026 | 39 | 0 | figures provided by MOI | 1,886 | 1,909 | named | descriptive | other | using ⟦figures provided by MOI⟧ | true | null | |
jdc_operational:000026 | 42 | 1 | ILO-ACTED labor needs assessment survey | 416 | 455 | named | named | survey | the results of a joint ⟦ILO-ACTED labor needs assessment survey⟧ that UNDP is financing | true | null | |
jdc_operational:000026 | 44 | 1 | Project related surveys and studies | 1,099 | 1,134 | descriptive | descriptive | survey | carrying out various ⟦Project related surveys and studies⟧ | true | null | |
jdc_operational:000026 | 48 | 1 | municipality budget system | 615 | 641 | descriptive | descriptive | system | generated directly from the ⟦municipality budget system⟧ | true | null | |
jdc_operational:000026 | 49 | 1 | data from the participating municipalities | 705 | 747 | descriptive | descriptive | administrative | collecting the needed ⟦data from the participating municipalities⟧ to complete the IFRs | true | null | |
jdc_operational:000026 | 50 | 1 | quarterly IFRs | 779 | 793 | descriptive | descriptive | report | as provided in the ⟦quarterly IFRs⟧ | true | null | |
jdc_operational:000026 | 50 | 1 | quarterly IFRs | 876 | 890 | descriptive | descriptive | report | based on ⟦quarterly IFRs⟧ which would provide actual expenditure | true | null | |
jdc_operational:000026 | 51 | 0 | quarterly IFR | 892 | 905 | descriptive | descriptive | report | as provided in the ⟦quarterly IFR⟧ | true | null | |
jdc_operational:000026 | 5 | 0 | PAD DATA SHEET | 11 | 25 | named | named | other | ⟦PAD DATA SHEET⟧ | false | null | |
jdc_operational:000026 | 5 | 1 | Project Financing Data | 150 | 172 | named | descriptive | other | ⟦Project Financing Data⟧ (in USD Million) | false | null | |
jdc_operational:000027 | 10 | 0 | community scorecards | 949 | 969 | descriptive | descriptive | other | as measured from baseline with ⟦community scorecards⟧ | false | null | |
jdc_operational:000027 | 10 | 0 | vulnerability index | 1,359 | 1,378 | descriptive | descriptive | other | identified through the Bank’s ⟦vulnerability index⟧ | false | null | |
jdc_operational:000027 | 11 | 2 | Implementation Status and Results | 1,022 | 1,055 | named | named | report | latest ⟦Implementation Status and Results⟧[1] (ISR) prepared in March 2021 | true | null | |
jdc_operational:000027 | 15 | 1 | ECRP functionality assessments | 562 | 592 | descriptive | descriptive | other | findings of the ⟦ECRP functionality assessments⟧[2] for previously engaged counties | true | null | |
jdc_operational:000027 | 2 | 0 | global development indicators | 739 | 768 | descriptive | vague | indicator | ranked almost at the bottom of the ⟦global development indicators⟧[3] | true | null | |
jdc_operational:000027 | 2 | 1 | satellite imagery and geodata | 1,321 | 1,350 | descriptive | descriptive | geospatial | analysis of ⟦satellite imagery and geodata⟧[4] | true | null | |
jdc_operational:000027 | 4 | 0 | Human Development Index | 776 | 799 | named | named | indicator | ranking of 185 out of 189 countries in the ⟦Human Development Index⟧[5] (HDI) 2020 | true | null | |
jdc_operational:000027 | 4 | 2 | Displacement Tracking Matrix | 1,124 | 1,152 | named | named | database | International Organization for Migration (IOM), ⟦Displacement Tracking Matrix⟧[6] (DTM), Round 9 | true | null | |
jdc_operational:000027 | 4 | 3 | women’s empowerment dashboard | 293 | 322 | named | named | indicator | HDI’s ⟦women’s empowerment dashboard⟧[7] compiles 13 woman-specific empowerment indicators | true | null | |
jdc_operational:000027 | 6 | 0 | intention surveys | 145 | 162 | descriptive | descriptive | survey | According to recent ⟦intention surveys⟧[8] by both the United Nations High Commission for Refugees and IOM | true | null | |
jdc_operational:000027 | 6 | 0 | IOM assessment | 1,408 | 1,422 | named | named | report | An ⟦IOM assessment⟧[9] commissioned by the World Bank found | true | null | |
jdc_operational:000027 | 6 | 2 | UNOCHA Humanitarian Needs Overview | 1,125 | 1,159 | named | named | report | 2019 figures from ⟦UNOCHA Humanitarian Needs Overview⟧[10], p.13 | true | null | |
jdc_operational:000027 | 6 | 2 | IOM DTM | 1,170 | 1,177 | named | named | database | 2019 figures from UNOCHA Humanitarian Needs Overview (2018). and ⟦IOM DTM⟧[11], p.4 | true | null | |
jdc_operational:000028 | 13 | 0 | global development indicators | 731 | 760 | descriptive | vague | indicator | ranked near the bottom of ⟦global development indicators⟧[12] | true | null | |
jdc_operational:000028 | 13 | 2 | South Sudan IPC Results | 536 | 559 | named | named | report | IPC. ⟦South Sudan IPC Results⟧[13] October 2020–July 2021 | true | null | |
jdc_operational:000028 | 14 | 0 | Human Development Index | 578 | 601 | named | named | indicator | ranking of 185 out of 189 countries in the ⟦Human Development Index⟧[14] (HDI) 2020 | true | null | |
jdc_operational:000028 | 14 | 2 | women’s empowerment dashboard | 635 | 664 | named | named | indicator | HDI’s ⟦women’s empowerment dashboard⟧[15] compiles 13 woman-specific empowerment indicators | true | null | |
jdc_operational:000028 | 15 | 2 | Global Rapid Post-Disaster Damage Estimation | 1,025 | 1,069 | named | named | report | ⟦Global Rapid Post-Disaster Damage Estimation⟧[16] (GRADE) Note on May–October 2021 South Sudan Floods | true | null | |
jdc_operational:000028 | 16 | 2 | Refugees in South Sudan – by months | 592 | 627 | named | named | database | ⟦Refugees in South Sudan – by months⟧[17], UNHCR, January 31, 2022 | true | null | |
jdc_operational:000028 | 17 | 0 | South Sudan Refugees and Asylum-Seekers by State | 608 | 656 | named | named | database | Adapted from UNHCR (2021) ⟦South Sudan Refugees and Asylum-Seekers by State⟧[18], April 30, 2021 | true | null | |
jdc_operational:000028 | 25 | 0 | local service mapping | 909 | 930 | descriptive | descriptive | other | Communities’ priorities will be validated through ⟦local service mapping⟧[19] | true | null | |
jdc_operational:000028 | 25 | 1 | composite vulnerability index | 966 | 995 | descriptive | descriptive | other | based on a ⟦composite vulnerability index⟧[20] that the World Bank team developed | false | null | |
jdc_operational:000028 | 26 | 1 | refugee data | 1,063 | 1,075 | vague | vague | other | UNHCR will share ⟦refugee data⟧[21] to facilitate inclusion of refugee and host communities | true | null | |
jdc_operational:000028 | 26 | 1 | data from humanitarian organizations | 1,510 | 1,546 | descriptive | vague | other | using the most recent ⟦data from humanitarian organizations⟧[22] | true | null | |
jdc_operational:000028 | 26 | 2 | data from humanitarian organizations | 162 | 198 | descriptive | vague | other | using the most recent ⟦data from humanitarian organizations⟧[23] | true | null | |
jdc_operational:000028 | 38 | 0 | 2020 Flood Damage Needs Assessment | 1,583 | 1,617 | named | named | report | As part of the ⟦2020 Flood Damage Needs Assessment⟧[24] | true | null | |
jdc_operational:000028 | 40 | 0 | flood assessments | 1,823 | 1,840 | descriptive | descriptive | other | the empirical findings of ⟦flood assessments⟧[25] | true | null | |
jdc_operational:000028 | 67 | 1 | Geo-referenced data | 164 | 183 | descriptive | descriptive | geospatial | ⟦Geo-referenced data⟧[26] on subproject progress uploaded in the MIS | true | null | |
jdc_operational:000028 | 71 | 0 | geo-referenced monitoring system | 1,807 | 1,839 | descriptive | descriptive | system | a strong M&E mechanism with ⟦geo-referenced monitoring system⟧[27] | true | null | |
jdc_operational:000029 | 104 | 0 | database of NAF | 1,898 | 1,913 | named | descriptive | database | the Project will leverage the ⟦database of NAF⟧[28] | true | null | |
jdc_operational:000029 | 104 | 1 | database of NAF | 235 | 250 | named | descriptive | database | leverage the ⟦database of NAF⟧ | true | null | |
jdc_operational:000029 | 105 | 0 | large databases | 141 | 156 | descriptive | descriptive | database | leveraging ⟦large databases⟧ for analysis | true | null | |
jdc_operational:000029 | 106 | 0 | statistics of floods and flashfloods | 1,323 | 1,359 | descriptive | vague | other | As shown by ⟦statistics of floods and flashfloods⟧ around the world | true | null | |
jdc_operational:000029 | 107 | 0 | World Bank Climate Knowledge Portal | 980 | 1,015 | named | named | system | GCM models from the ⟦World Bank Climate Knowledge Portal⟧ indicate that monthly temperatures in Jordan will increase | true | null | |
jdc_operational:000029 | 10 | 1 | ILOSTAT database | 1,516 | 1,532 | named | named | database | International Labor Organization, ⟦ILOSTAT database⟧. Data retrieved in Sept 2019. | true | null | |
jdc_operational:000029 | 10 | 1 | World Development Indicators | 1,780 | 1,808 | named | named | database | ⟦World Development Indicators⟧. Data retrieved in June 2019 | true | null | |
jdc_operational:000029 | 10 | 2 | World Development Indicators | 219 | 247 | named | named | database | ⟦World Development Indicators⟧. Data retrieved in June 2019 | true | null | |
jdc_operational:000029 | 11 | 0 | Jordan Labor Market Panel Survey | 720 | 752 | named | named | survey | ⟦Jordan Labor Market Panel Survey⟧ (JLMPS) 2016 data indicated that 91 percent of those who work do so informally. | true | null | |
jdc_operational:000029 | 11 | 2 | World Bank National Accounts Data | 549 | 582 | named | named | database | ⟦World Bank National Accounts Data⟧, 2018 | true | null | |
jdc_operational:000029 | 11 | 2 | Labor Force Survey | 595 | 613 | named | named | survey | ⟦Labor Force Survey⟧, 2018 (DoS) | true | null | |
jdc_operational:000029 | 12 | 1 | 2016 Labor Market Study | 528 | 551 | named | named | survey | The findings of a ⟦2016 Labor Market Study⟧ conducted by the ICT Association of Jordan (Intaj) revealed five core weaknesses | true | null | |
jdc_operational:000029 | 13 | 0 | survey of digital firms in Jordan | 1,349 | 1,382 | descriptive | descriptive | survey | A World Bank (WB) ⟦survey of digital firms in Jordan⟧ in January 2019 suggested that 48 percent of firms perceive finding technical talent an obstacle in the local market. | true | null | |
jdc_operational:000029 | 18 | 1 | database of all trainees/ graduates | 1,273 | 1,308 | descriptive | descriptive | database | creating a Customer Relationship Management System (CRM) to maintain a ⟦database of all trainees/ graduates⟧ | true | null | |
jdc_operational:000029 | 20 | 0 | National Aid Fund (NAF) database | 999 | 1,031 | named | named | database | identified through the ⟦National Aid Fund (NAF) database⟧ across project components | true | null | |
jdc_operational:000029 | 24 | 1 | address records | 739 | 754 | descriptive | descriptive | administrative | a bank providing information on ⟦address records⟧, tax authority on annual income | true | null | |
jdc_operational:000029 | 34 | 1 | results data | 682 | 694 | vague | vague | other | The PMU and the World Bank will also use ⟦results data⟧ to build awareness of project results | true | null | |
jdc_operational:000029 | 34 | 1 | data gathered on Syrian refugees | 1,685 | 1,717 | descriptive | descriptive | other | any ⟦data gathered on Syrian refugees⟧ will be disaggregated by sex | true | null | |
jdc_operational:000029 | 36 | 0 | labor force data | 1,524 | 1,540 | descriptive | vague | other | ⟦labor force data⟧ was used to estimate various wage and employment rates among youth ages 18 to 30. | true | null | |
jdc_operational:000029 | 37 | 1 | Eligible Expenditure Program (EEP) table | 1,017 | 1,057 | named | descriptive | other | As per the ⟦Eligible Expenditure Program (EEP) table⟧, the details are below | true | null | |
jdc_operational:000029 | 59 | 1 | list of certified training service providers | 1 | 45 | descriptive | descriptive | other | ⟦list of certified training service providers⟧; DLI 1.3 | true | null | |
jdc_operational:000029 | 65 | 0 | Training Records and Social Security Database | 1,381 | 1,426 | named | named | database | **Data source/ Agency**|⟦Training Records and Social Security Database⟧ | true | null | |
jdc_operational:000029 | 65 | 1 | Training Records and Social Security Database | 34 | 79 | named | named | database | **Data source/ Agency**|⟦Training Records and Social Security Database⟧ | true | null | |
jdc_operational:000029 | 65 | 1 | records from TSPs | 561 | 578 | descriptive | descriptive | administrative | IVA will receive ⟦records from TSPs⟧ and verify through | true | null | |
jdc_operational:000029 | 65 | 1 | social security database | 598 | 622 | descriptive | descriptive | administrative | verify through ⟦social security database⟧ | true | null | |
jdc_operational:000029 | 66 | 0 | training records of the G7-12 teachers | 1,167 | 1,205 | descriptive | descriptive | administrative | IVA to check the ⟦training records of the G7-12 teachers⟧ and confirm the percentage | true | null | |
jdc_operational:000029 | 66 | 1 | training records of the G7-12 teachers | 134 | 172 | descriptive | descriptive | administrative | IVA to check the ⟦training records of the G7-12 teachers⟧ and confirm the percentage of teachers trained | true | null | |
jdc_operational:000029 | 68 | 1 | results data | 426 | 438 | vague | vague | other | The World Bank team will also use ⟦results data⟧ to build awareness of project results | true | null | |
jdc_operational:000029 | 71 | 0 | National Aid Fund (NAF) database | 629 | 661 | named | named | database | including those registered in the ⟦National Aid Fund (NAF) database⟧ | true | null | |
jdc_operational:000029 | 73 | 0 | survey on social media and education reform | 863 | 906 | descriptive | descriptive | survey | In a ⟦survey on social media and education reform⟧ across 13 MENA countries | true | null | |
jdc_operational:000029 | 73 | 1 | mapping of global digital skills frameworks | 388 | 431 | descriptive | descriptive | other | Injaz conducted a ⟦mapping of global digital skills frameworks⟧ to identify the gaps in the existing curriculum. | false | null | |
jdc_operational:000029 | 77 | 1 | social security records | 568 | 591 | descriptive | descriptive | administrative | The project will ask for the ⟦social security records⟧[1] of new employees to process payments. | true | null | |
jdc_operational:000029 | 80 | 1 | service inventory | 1,565 | 1,582 | descriptive | descriptive | other | Each MDA has completed a ⟦service inventory⟧[2] which was used to | true | null | |
jdc_operational:000029 | 86 | 0 | address records | 230 | 245 | descriptive | descriptive | administrative | For example, a bank providing information on ⟦address records⟧[3], Tax authority on annual income etc. in the form of a federated architecture. | true | null | |
jdc_operational:000029 | 88 | 0 | labor force survey data | 420 | 443 | descriptive | descriptive | survey | The ⟦labor force survey data⟧[4] shows stark contrast in the wages and employment rates. | true | null | |
jdc_operational:000029 | 89 | 1 | individual-level survey data | 1,160 | 1,188 | descriptive | descriptive | microdata | estimated through regression analysis (in the form of Mincerian equations) of ⟦individual-level survey data⟧[5]. | true | null | |
jdc_operational:000029 | 89 | 1 | individual survey data | 1,921 | 1,943 | descriptive | descriptive | microdata | it is not possible to estimate the differential from the ⟦individual survey data⟧[6] available | true | null | |
jdc_operational:000029 | 89 | 2 | individual survey data | 85 | 107 | descriptive | descriptive | microdata | it is not possible to estimate the differential from the ⟦individual survey data⟧[7] available | true | null | |
jdc_operational:000029 | 90 | 0 | labor force survey data | 1,049 | 1,072 | descriptive | descriptive | survey | The assumptions are mainly based on evidence from the literature, ⟦labor force survey data⟧[8] (⟦JLMPS 2016⟧[9]), or our expectations of outputs for the program | true | null | |
jdc_operational:000029 | 90 | 0 | JLMPS 2016 | 1,074 | 1,084 | named | named | survey | The assumptions are mainly based on evidence from the literature, ⟦labor force survey data⟧[8] (⟦JLMPS 2016⟧[9]), or our expectations of outputs for the program | true | null | |
jdc_operational:000029 | 90 | 0 | labor force date | 1,668 | 1,684 | descriptive | descriptive | survey | Note that all statistics from ⟦labor force date⟧[10] (wages and employment rates) are taken for the population of 18 to 30 years old. | true | null | |
jdc_operational:000029 | 95 | 0 | automated HR database system | 1,083 | 1,111 | descriptive | descriptive | system | entry into the ⟦automated HR database system⟧[11]. | true | null | |
jdc_operational:000029 | 95 | 0 | automated attendance register | 1,879 | 1,908 | descriptive | descriptive | administrative | Daily time attendance sheets based on an ⟦automated attendance register⟧[12] are maintained by the attendance supervisor | true | null | |
jdc_operational:000029 | 95 | 0 | computerized payroll data base | 2,068 | 2,098 | descriptive | descriptive | database | All payroll records are kept in a secure, centralized ⟦computerized payroll data base⟧[13] that is updated daily | true | null | |
jdc_operational:000029 | 95 | 1 | automated attendance register | 31 | 60 | descriptive | descriptive | administrative | attendance sheets based on an ⟦automated attendance register⟧[14] are maintained by the attendance supervisor | true | null | |
jdc_operational:000029 | 95 | 1 | computerized payroll data base | 220 | 250 | descriptive | descriptive | database | All payroll records are kept in a secure, centralized ⟦computerized payroll data base⟧[15] that is updated daily | true | null | |
jdc_operational:000030 | 10 | 1 | inequality-adjusted 2013 Human Development Index | 1,269 | 1,317 | named | named | indicator | As revealed by the World Bank’s ⟦inequality-adjusted 2013 Human Development Index⟧[16] (HDI) | true | null | |
jdc_operational:000030 | 10 | 1 | World Bank EdStats | 1,521 | 1,539 | named | named | database | World Bank’s ⟦World Bank EdStats⟧[17] accessed 10.7.14 | true | null | |
jdc_operational:000030 | 11 | 1 | Trends in International Mathematics and Science Study | 1,264 | 1,317 | named | named | survey | the 2011 ⟦Trends in International Mathematics and Science Study⟧[18] (TIMSS) results | true | null | |
jdc_operational:000030 | 11 | 1 | 2004 household survey | 1,356 | 1,377 | descriptive | descriptive | survey | Indeed, based on the ⟦2004 household survey⟧[19], poverty and education are highly correlated in Lebanon. | true | null | |
jdc_operational:000030 | 11 | 1 | 2013 Human Capital Index | 1,631 | 1,655 | named | named | indicator | World Economic Forum’s ⟦2013 Human Capital Index⟧[20] | true | null | |
jdc_operational:000030 | 11 | 1 | World Bank Ed Stats | 1,795 | 1,814 | named | named | database | ⟦World Bank Ed Stats⟧[21] | true | null | |
jdc_operational:000030 | 35 | 0 | D-RASATI survey | 846 | 861 | named | named | survey | Statistics provided by the ⟦D-RASATI survey⟧[22] (2011) | true | null | |
jdc_operational:000030 | 35 | 1 | database | 594 | 602 | descriptive | vague | database | Project preparation included the preparation of a ⟦database⟧[23] which accounts for many of the school facilities characteristics | true | null | |
jdc_operational:000030 | 5 | 0 | Institutional Data | 471 | 489 | descriptive | vague | other | ||**⟦Institutional Data⟧[24]**|| | false | null | |
jdc_operational:000030 | 9 | 0 | available but incomplete data | 1,615 | 1,644 | vague | vague | other | Based on ⟦available but incomplete data⟧[25], significant progress was made in reducing poverty prior to the civil war. | true | null | |
jdc_operational:000030 | 9 | 1 | available but incomplete data | 34 | 63 | vague | vague | other | Based on ⟦available but incomplete data⟧[26], significant progress was made in reducing poverty prior to the civil war. | true | null | |
jdc_operational:000031 | 2 | 1 | large-scale learning assessments in Chad | 1,102 | 1,142 | descriptive | descriptive | survey | Results from ⟦large-scale learning assessments in Chad⟧[27] indicate that 97 percent of | true | null | |
jdc_operational:000031 | 2 | 1 | Refugee Protection Assessment for Chad | 1,231 | 1,269 | named | named | report | United Nations High Commissioner for Refugees (UNHCR) ⟦Refugee Protection Assessment for Chad⟧[28], January 2020. | true | null | |
jdc_operational:000031 | 6 | 1 | household survey | 494 | 510 | descriptive | descriptive | survey | This sub-component will mainly target vulnerable households using data from the recent ⟦household survey⟧[29]. | true | null | |
jdc_operational:000032 | 11 | 0 | Economic and Social Impact Assessment | 944 | 981 | named | named | report | According to the ⟦Economic and Social Impact Assessment⟧[30] (ESIA) carried out by the World Bank (WB) | true | null |
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