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7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:0 | MLI | Mali | THA.17.13_1 | Muang Khon Kaen | TH | gadm2 | 0.5548 | 0.5279 | 0.5305 | 0.5544 | 0.5758 | 0.5947 | 0.6115 | 0.6267 | 0.6407 | 0.6535 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:1 | MLI | Mali | VNM.40.4_1 | Nam Định | VN | gadm2 | 0.5249 | 0.497 | 0.4915 | 0.5108 | 0.5324 | 0.5515 | 0.5678 | 0.5821 | 0.5945 | 0.6055 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:2 | MLI | Mali | MEX.21.161_2 | Tepanco de López | MX | gadm2 | 0.7561 | 0.7463 | 0.7568 | 0.7915 | 0.8232 | 0.8503 | 0.873 | 0.8929 | 0.9099 | 0.9241 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:3 | MLI | Mali | THA.72.25_1 | Warin Chamrap | TH | gadm2 | 0.5601 | 0.5333 | 0.5369 | 0.5598 | 0.5794 | 0.5969 | 0.6127 | 0.627 | 0.6403 | 0.6528 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:4 | MLI | Mali | TZA.14.1_1 | Gairo | TZ | gadm2 | 0.6263 | 0.6435 | 0.6773 | 0.729 | 0.7612 | 0.7842 | 0.802 | 0.8194 | 0.8303 | 0.8454 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:5 | MLI | Mali | GUY.6.2_1 | Bel Air / Woodlands | GY | gadm2 | 0.787 | 0.7561 | 0.7384 | 0.7654 | 0.7929 | 0.8181 | 0.8389 | 0.8595 | 0.876 | 0.8894 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:6 | MLI | Mali | VNM.15.7_1 | Ea Súp | VN | gadm2 | 0.5045 | 0.4763 | 0.4741 | 0.4929 | 0.5132 | 0.5317 | 0.5497 | 0.565 | 0.5794 | 0.5923 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:7 | MLI | Mali | MEX.13.68_2 | Tizayuca | MX | gadm2 | 0.7802 | 0.7593 | 0.7511 | 0.765 | 0.7845 | 0.8036 | 0.8214 | 0.8375 | 0.8515 | 0.8638 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:8 | MLI | Mali | KOR.8.21_2 | Pyeongtaek | KR | gadm2 | 0.2918 | 0.2959 | 0.3279 | 0.3711 | 0.3988 | 0.4164 | 0.429 | 0.4377 | 0.4443 | 0.4493 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:9 | MLI | Mali | BRA.10.144_2 | Pinheiro | BR | gadm2 | 0.7886 | 0.7761 | 0.7847 | 0.8131 | 0.8402 | 0.8647 | 0.8886 | 0.9096 | 0.9288 | 0.9463 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:10 | MLI | Mali | PHL.3.1_1 | Bayugan City | PH | gadm2 | 0.6572 | 0.6254 | 0.625 | 0.6489 | 0.6698 | 0.6885 | 0.7058 | 0.7215 | 0.7362 | 0.7499 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:11 | MLI | Mali | MYS.13.7_1 | Kota Marudu | MY | gadm2 | 0.4515 | 0.4347 | 0.4385 | 0.462 | 0.4835 | 0.5029 | 0.5199 | 0.5354 | 0.5487 | 0.5611 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:12 | MLI | Mali | USA.25.72_1 | Tunica | US | gadm2 | 0.6264 | 0.6226 | 0.6315 | 0.66 | 0.6793 | 0.6998 | 0.7146 | 0.7305 | 0.7435 | 0.7581 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:13 | MLI | Mali | MAR.11.3_1 | Salé | MA | gadm2 | 0.3939 | 0.3973 | 0.4152 | 0.4425 | 0.4629 | 0.4792 | 0.4922 | 0.5029 | 0.5117 | 0.5191 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:14 | MLI | Mali | PHL.63.6_1 | Saguday | PH | gadm2 | 0.6442 | 0.6051 | 0.5903 | 0.6091 | 0.6273 | 0.6429 | 0.6576 | 0.6696 | 0.6825 | 0.6946 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:15 | MLI | Mali | EGY.11.18_1 | As-Sayidah Zaynab | EG | gadm2 | 0.3301 | 0.3125 | 0.2857 | 0.2676 | 0.2616 | 0.2564 | 0.2534 | 0.2524 | 0.2514 | 0.2508 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:16 | MLI | Mali | USA.25.31_1 | Jasper | US | gadm2 | 0.6322 | 0.5965 | 0.579 | 0.5821 | 0.5911 | 0.6016 | 0.6123 | 0.6213 | 0.6305 | 0.64 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:17 | MLI | Mali | ARG.6.14_1 | Rió Cuarto | AR | gadm2 | 0.5777 | 0.5455 | 0.5295 | 0.5269 | 0.5311 | 0.5386 | 0.5475 | 0.557 | 0.5664 | 0.5757 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:18 | MLI | Mali | BRA.25.602_2 | Taquarituba | BR | gadm2 | 0.6091 | 0.5618 | 0.5241 | 0.5139 | 0.5141 | 0.5194 | 0.5279 | 0.5353 | 0.5433 | 0.5522 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:19 | MLI | Mali | SRB.21.2_1 | Batočina | RS | gadm2 | 0.4708 | 0.46 | 0.4563 | 0.4719 | 0.4698 | 0.4757 | 0.4908 | 0.4938 | 0.504 | 0.5227 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:20 | MLI | Mali | MEX.31.92_2 | Tixcacalcupul | MX | gadm2 | 0.6589 | 0.6138 | 0.6041 | 0.6273 | 0.6441 | 0.6678 | 0.6812 | 0.694 | 0.7074 | 0.7177 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:21 | MLI | Mali | USA.1.49_1 | Mobile | US | gadm2 | 0.628 | 0.594 | 0.5805 | 0.5864 | 0.5959 | 0.6066 | 0.6174 | 0.6279 | 0.6381 | 0.6478 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:22 | MLI | Mali | CAN.11.38_1 | La Haute-Yamaska | CA | gadm2 | 0.649 | 0.5942 | 0.5727 | 0.5728 | 0.5766 | 0.5803 | 0.584 | 0.5888 | 0.5929 | 0.5973 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:23 | MLI | Mali | THA.42.4_1 | Lom Kao | TH | gadm2 | 0.5735 | 0.549 | 0.5491 | 0.5709 | 0.5911 | 0.6091 | 0.625 | 0.6396 | 0.6529 | 0.6657 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:24 | MLI | Mali | NOR.13.7_1 | Hå | NO | gadm2 | 0.5031 | 0.4636 | 0.4274 | 0.4209 | 0.4266 | 0.4332 | 0.4394 | 0.4454 | 0.4525 | 0.4585 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:25 | MLI | Mali | BRA.10.119_2 | Miranda do Norte | BR | gadm2 | 0.7051 | 0.6857 | 0.6915 | 0.7169 | 0.7424 | 0.7659 | 0.7865 | 0.8055 | 0.8226 | 0.8378 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:26 | MLI | Mali | CAN.3.4_1 | Division No. 13 | CA | gadm2 | 0.5415 | 0.5131 | 0.5052 | 0.5123 | 0.5201 | 0.5273 | 0.5351 | 0.5423 | 0.5488 | 0.5544 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:27 | MLI | Mali | TUN.16.2_1 | Beni Khiar | TN | gadm2 | 0.4746 | 0.438 | 0.3942 | 0.3712 | 0.3614 | 0.357 | 0.3544 | 0.3537 | 0.3536 | 0.354 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:28 | MLI | Mali | BRA.25.154_2 | Diadema | BR | gadm2 | 0.6196 | 0.5887 | 0.5717 | 0.5696 | 0.5757 | 0.5852 | 0.5959 | 0.6069 | 0.6176 | 0.6275 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:29 | MLI | Mali | SLV.3.25_1 | San Francisco Morazán | SV | gadm2 | 0.7084 | 0.6846 | 0.6725 | 0.6914 | 0.7147 | 0.7353 | 0.7558 | 0.7713 | 0.7855 | 0.7984 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:30 | MLI | Mali | MOZ.4.7_1 | Mossurize | MZ | gadm2 | 0.5885 | 0.612 | 0.6589 | 0.7259 | 0.7692 | 0.803 | 0.8305 | 0.8468 | 0.8657 | 0.8781 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:31 | MLI | Mali | ROU.16.29_1 | Sanzieni | RO | gadm2 | 0.4514 | 0.433 | 0.4332 | 0.443 | 0.4515 | 0.4631 | 0.4729 | 0.4811 | 0.4868 | 0.4995 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:32 | MLI | Mali | MEX.20.105_2 | San Antonino Castillo Velasco | MX | gadm2 | 0.6438 | 0.6237 | 0.6304 | 0.6572 | 0.6855 | 0.7138 | 0.7397 | 0.7637 | 0.7824 | 0.8007 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:33 | MLI | Mali | THA.27.1_1 | Bang Len | TH | gadm2 | 0.5953 | 0.5606 | 0.5602 | 0.5843 | 0.605 | 0.6235 | 0.6398 | 0.6546 | 0.6677 | 0.6802 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:34 | MLI | Mali | BRA.24.28_2 | Balneário Camboriú | BR | gadm2 | 0.6068 | 0.5661 | 0.5513 | 0.5554 | 0.564 | 0.574 | 0.5846 | 0.5947 | 0.6045 | 0.6133 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:35 | MLI | Mali | USA.20.9_1 | Oxford | US | gadm2 | 0.6559 | 0.6026 | 0.5711 | 0.5657 | 0.5663 | 0.5692 | 0.5735 | 0.5791 | 0.5842 | 0.5896 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:36 | MLI | Mali | MEX.21.154_2 | Tecamachalco | MX | gadm2 | 0.7236 | 0.7038 | 0.7058 | 0.7341 | 0.7615 | 0.7866 | 0.8091 | 0.829 | 0.8463 | 0.8616 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:37 | MLI | Mali | USA.16.55_1 | Kossuth | US | gadm2 | 0.6181 | 0.5665 | 0.5337 | 0.5315 | 0.5332 | 0.5363 | 0.5399 | 0.5443 | 0.5485 | 0.5541 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:38 | MLI | Mali | ROU.4.26_1 | Faget | RO | gadm2 | 0.5015 | 0.4753 | 0.4563 | 0.4474 | 0.4508 | 0.456 | 0.4632 | 0.466 | 0.4763 | 0.4814 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:39 | MLI | Mali | BRA.13.742_2 | São José da Safira | BR | gadm2 | 0.597 | 0.5809 | 0.5693 | 0.5879 | 0.6112 | 0.6242 | 0.6393 | 0.6567 | 0.6684 | 0.687 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:40 | MLI | Mali | PHL.20.28_1 | Pamplona | PH | gadm2 | 0.6634 | 0.6355 | 0.633 | 0.6574 | 0.6803 | 0.6998 | 0.7185 | 0.7352 | 0.7516 | 0.7664 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:41 | MLI | Mali | MEX.15.57_2 | Metepec | MX | gadm2 | 0.7176 | 0.7086 | 0.7188 | 0.742 | 0.7638 | 0.7826 | 0.7997 | 0.8147 | 0.8279 | 0.8396 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:42 | MLI | Mali | BRA.25.581_2 | Severínia | BR | gadm2 | 0.6278 | 0.5796 | 0.5459 | 0.5358 | 0.5366 | 0.5437 | 0.5511 | 0.5603 | 0.5702 | 0.5793 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:43 | MLI | Mali | CHE.6.4_1 | Biel | CH | gadm2 | 0.527 | 0.5027 | 0.4923 | 0.5037 | 0.5186 | 0.5342 | 0.5461 | 0.5564 | 0.5665 | 0.5744 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:44 | MLI | Mali | NOR.3.9_1 | Grimstad | NO | gadm2 | 0.5388 | 0.4974 | 0.4643 | 0.4613 | 0.4674 | 0.474 | 0.4816 | 0.4885 | 0.4957 | 0.5021 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:45 | MLI | Mali | BRA.10.111_2 | Marajá do Sena | BR | gadm2 | 0.6333 | 0.6241 | 0.6271 | 0.6535 | 0.676 | 0.6973 | 0.7147 | 0.7304 | 0.7418 | 0.7528 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:46 | MLI | Mali | BRA.9.36_2 | Bonópolis | BR | gadm2 | 0.6386 | 0.618 | 0.6108 | 0.6166 | 0.6306 | 0.6503 | 0.6745 | 0.6874 | 0.6994 | 0.7126 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:47 | MLI | Mali | HND.12.17_1 | Santa María | HN | gadm2 | 0.7872 | 0.7819 | 0.7973 | 0.8412 | 0.8863 | 0.9241 | 0.9482 | 0.975 | 0.9961 | 1.018 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:48 | MLI | Mali | NOR.6.19_1 | Tolga | NO | gadm2 | 0.5287 | 0.4912 | 0.4498 | 0.458 | 0.4607 | 0.482 | 0.483 | 0.4888 | 0.4787 | 0.4844 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:49 | MLI | Mali | IRQ.16.10_1 | Tilkef | IQ | gadm2 | 0.1841 | 0.167 | 0.1416 | 0.1266 | 0.119 | 0.1153 | 0.1132 | 0.1119 | 0.1114 | 0.111 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:50 | MLI | Mali | BRA.27.48_2 | Dois Irmãos do Tocantins | BR | gadm2 | 0.6657 | 0.6505 | 0.6357 | 0.6492 | 0.6695 | 0.686 | 0.7003 | 0.7146 | 0.728 | 0.7446 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:51 | MLI | Mali | PHL.33.1_1 | Aguinaldo | PH | gadm2 | 0.649 | 0.6304 | 0.6309 | 0.6532 | 0.6768 | 0.6937 | 0.7099 | 0.7232 | 0.7362 | 0.75 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:52 | MLI | Mali | USA.6.31_1 | Jefferson | US | gadm2 | 0.6213 | 0.5856 | 0.5783 | 0.5845 | 0.5931 | 0.6026 | 0.6124 | 0.6221 | 0.6309 | 0.639 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:53 | MLI | Mali | NGA.14.5_1 | Enugu South | NG | gadm2 | 0.6441 | 0.6488 | 0.6764 | 0.7227 | 0.7611 | 0.7927 | 0.8201 | 0.8432 | 0.8627 | 0.8799 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:54 | MLI | Mali | PHL.69.7_1 | Gubat | PH | gadm2 | 0.63 | 0.5951 | 0.5886 | 0.613 | 0.6371 | 0.6585 | 0.6778 | 0.6952 | 0.7111 | 0.7256 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:55 | MLI | Mali | ROU.24.5_1 | Barnova | RO | gadm2 | 0.6197 | 0.5465 | 0.5026 | 0.495 | 0.4974 | 0.5031 | 0.5126 | 0.5182 | 0.5226 | 0.5315 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:56 | MLI | Mali | TUN.18.2_1 | Jelma | TN | gadm2 | 0.4193 | 0.3957 | 0.3663 | 0.3463 | 0.3391 | 0.335 | 0.3321 | 0.3308 | 0.3293 | 0.3289 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:57 | MLI | Mali | PHL.34.17_1 | Paoay | PH | gadm2 | 0.6099 | 0.5764 | 0.564 | 0.583 | 0.6009 | 0.6159 | 0.6293 | 0.6417 | 0.6539 | 0.6643 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:58 | MLI | Mali | HRV.12.4_1 | Kaptol | HR | gadm2 | 0.441 | 0.4088 | 0.3795 | 0.3667 | 0.3689 | 0.3694 | 0.3809 | 0.3799 | 0.3857 | 0.3941 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:59 | MLI | Mali | JPN.15.10_1 | Nakanoto | JP | gadm2 | 0.3904 | 0.3549 | 0.4093 | 0.448 | 0.4761 | 0.4657 | 0.4787 | 0.4897 | 0.4881 | 0.4873 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:60 | MLI | Mali | PER.23.6_1 | Moyobamba | PE | gadm2 | 0.7176 | 0.7018 | 0.7057 | 0.7341 | 0.7656 | 0.7959 | 0.8234 | 0.8477 | 0.8699 | 0.8901 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:61 | MLI | Mali | COL.11.38_2 | Timbiquí | CO | gadm2 | 0.7536 | 0.7622 | 0.8117 | 0.88 | 0.9328 | 0.9742 | 1.0057 | 1.0288 | 1.0539 | 1.0707 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:62 | MLI | Mali | USA.19.47_1 | Saint James | US | gadm2 | 0.5816 | 0.5526 | 0.5394 | 0.543 | 0.5489 | 0.5561 | 0.564 | 0.5724 | 0.5803 | 0.5881 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:63 | MLI | Mali | PHL.37.12_1 | Divilacan | PH | gadm2 | 0.7198 | 0.6967 | 0.6923 | 0.7095 | 0.7242 | 0.7408 | 0.7525 | 0.7656 | 0.7759 | 0.7886 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:64 | MLI | Mali | PER.6.11_1 | San Miguel | PE | gadm2 | 0.7177 | 0.7027 | 0.7073 | 0.7326 | 0.7605 | 0.7864 | 0.8088 | 0.8293 | 0.8474 | 0.8615 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:65 | MLI | Mali | BRA.13.175_2 | Chácara | BR | gadm2 | 0.6411 | 0.5956 | 0.5753 | 0.5858 | 0.5946 | 0.5991 | 0.6144 | 0.6291 | 0.637 | 0.6496 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:66 | MLI | Mali | ROU.19.40_1 | Piscu | RO | gadm2 | 0.5474 | 0.4961 | 0.4634 | 0.4487 | 0.4574 | 0.4593 | 0.4706 | 0.4774 | 0.4845 | 0.4883 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:67 | MLI | Mali | IRQ.6.7_1 | Soran | IQ | gadm2 | 0.2999 | 0.2879 | 0.2736 | 0.2643 | 0.2574 | 0.252 | 0.2485 | 0.2461 | 0.2443 | 0.2424 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:68 | MLI | Mali | AUS.5.82_1 | Lismore | AU | gadm2 | 0.5654 | 0.5281 | 0.5182 | 0.5246 | 0.5303 | 0.5367 | 0.5444 | 0.5508 | 0.5562 | 0.5618 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:69 | MLI | Mali | COL.23.3_2 | Bochalema | CO | gadm2 | 0.7616 | 0.7383 | 0.7402 | 0.755 | 0.7735 | 0.7945 | 0.8128 | 0.8314 | 0.8467 | 0.8616 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:70 | MLI | Mali | BRA.26.15_2 | Cedro de São João | BR | gadm2 | 0.6024 | 0.5844 | 0.5811 | 0.5925 | 0.608 | 0.6267 | 0.6366 | 0.6438 | 0.6595 | 0.6778 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:71 | MLI | Mali | USA.18.24_1 | Christian | US | gadm2 | 0.6556 | 0.6044 | 0.5726 | 0.5656 | 0.569 | 0.5743 | 0.5812 | 0.5884 | 0.5954 | 0.6023 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:72 | MLI | Mali | TZA.23.4_1 | Shinyanga Rural | TZ | gadm2 | 0.6871 | 0.6968 | 0.7282 | 0.7691 | 0.8082 | 0.8324 | 0.8532 | 0.8708 | 0.8913 | 0.8987 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:73 | MLI | Mali | BRA.4.15_2 | Caapiranga | BR | gadm2 | 0.7245 | 0.7079 | 0.7117 | 0.7321 | 0.7561 | 0.7725 | 0.7919 | 0.8089 | 0.8275 | 0.84 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:74 | MLI | Mali | MEX.5.86_2 | San Juan Cancuc | MX | gadm2 | 0.6979 | 0.7076 | 0.7668 | 0.8517 | 0.9151 | 0.9662 | 1.0021 | 1.0353 | 1.0645 | 1.0858 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:75 | MLI | Mali | TUN.1.5_1 | Raoued | TN | gadm2 | 0.4551 | 0.4262 | 0.3959 | 0.3801 | 0.3747 | 0.3733 | 0.3736 | 0.3744 | 0.3759 | 0.3772 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:76 | MLI | Mali | KHM.2.6_2 | Koas Krala | KH | gadm2 | 0.6613 | 0.6564 | 0.6865 | 0.7338 | 0.7677 | 0.7959 | 0.8176 | 0.8383 | 0.8558 | 0.8719 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:77 | MLI | Mali | JPN.2.25_1 | Yuzawa | JP | gadm2 | 0.3351 | 0.356 | 0.4095 | 0.4648 | 0.4923 | 0.508 | 0.5141 | 0.526 | 0.5272 | 0.5274 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:78 | MLI | Mali | ROU.3.96_1 | Vladesti | RO | gadm2 | 0.5481 | 0.5228 | 0.4908 | 0.4711 | 0.4712 | 0.4719 | 0.4802 | 0.486 | 0.4948 | 0.4997 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:79 | MLI | Mali | MEX.15.13_2 | Atizapán de Zaragoza | MX | gadm2 | 0.739 | 0.7286 | 0.7367 | 0.7572 | 0.7776 | 0.7966 | 0.8138 | 0.8289 | 0.8424 | 0.8543 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:80 | MLI | Mali | ITA.11.2_1 | Ascoli Piceno | IT | gadm2 | 0.5365 | 0.5041 | 0.4825 | 0.4793 | 0.4869 | 0.497 | 0.5079 | 0.5187 | 0.5291 | 0.5389 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:81 | MLI | Mali | MOZ.7.14_1 | Murrupula | MZ | gadm2 | 0.5724 | 0.5727 | 0.6199 | 0.6837 | 0.7268 | 0.7543 | 0.7831 | 0.8051 | 0.822 | 0.8344 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:82 | MLI | Mali | BRA.6.129_2 | Pacoti | BR | gadm2 | 0.653 | 0.6292 | 0.6186 | 0.6336 | 0.6546 | 0.669 | 0.6821 | 0.6964 | 0.7086 | 0.7208 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:83 | MLI | Mali | COL.11.14_2 | Jambaló | CO | gadm2 | 0.7578 | 0.7533 | 0.7888 | 0.8446 | 0.8905 | 0.9295 | 0.9641 | 0.9937 | 1.0202 | 1.0435 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:84 | MLI | Mali | BRA.10.152_2 | Presidente Médici | BR | gadm2 | 0.7042 | 0.702 | 0.7139 | 0.7469 | 0.7756 | 0.7948 | 0.815 | 0.8374 | 0.8568 | 0.8745 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:85 | MLI | Mali | PHL.70.6_1 | Polomolok | PH | gadm2 | 0.6371 | 0.6069 | 0.6043 | 0.6271 | 0.6482 | 0.6663 | 0.6822 | 0.6968 | 0.7103 | 0.7229 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:86 | MLI | Mali | PRY.7.8_1 | San Juan Nepomuceno | PY | gadm2 | 0.766 | 0.7392 | 0.7232 | 0.7377 | 0.7602 | 0.786 | 0.8113 | 0.8362 | 0.8584 | 0.8806 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:87 | MLI | Mali | TZA.16.1_1 | Ilemela | TZ | gadm2 | 0.6409 | 0.6501 | 0.688 | 0.7436 | 0.782 | 0.8107 | 0.8336 | 0.852 | 0.8681 | 0.8825 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:88 | MLI | Mali | SLE.2.1_1 | Bombali | SL | gadm2 | 0.5546 | 0.5621 | 0.5962 | 0.6518 | 0.6949 | 0.7277 | 0.7535 | 0.7742 | 0.7904 | 0.804 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:89 | MLI | Mali | COL.22.24_2 | Guaitarilla | CO | gadm2 | 0.723 | 0.7234 | 0.7599 | 0.8189 | 0.8674 | 0.9082 | 0.9444 | 0.9756 | 1.0024 | 1.03 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:90 | MLI | Mali | POL.12.20_1 | Myszków | PL | gadm2 | 0.531 | 0.5079 | 0.4958 | 0.5075 | 0.5209 | 0.5339 | 0.5457 | 0.5562 | 0.5663 | 0.5757 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:91 | MLI | Mali | BRA.15.100_2 | Juru | BR | gadm2 | 0.6118 | 0.57 | 0.5474 | 0.5392 | 0.5444 | 0.5498 | 0.559 | 0.5677 | 0.5764 | 0.5859 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:92 | MLI | Mali | TUR.3.1_1 | Başmakçı | TR | gadm2 | 0.2114 | 0.1851 | 0.1557 | 0.1391 | 0.131 | 0.1283 | 0.1252 | 0.1239 | 0.1244 | 0.1248 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:93 | MLI | Mali | BGR.25.10_1 | Zlataritsa | BG | gadm2 | 0.558 | 0.5402 | 0.5249 | 0.5256 | 0.5332 | 0.5322 | 0.5361 | 0.5504 | 0.5509 | 0.5564 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:94 | MLI | Mali | DZA.35.5_1 | Ben Daoud | DZ | gadm2 | 0.3523 | 0.3283 | 0.2933 | 0.2777 | 0.2699 | 0.2658 | 0.2649 | 0.2644 | 0.2639 | 0.2644 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:95 | MLI | Mali | JPN.9.23_1 | Mizuho | JP | gadm2 | 0.379 | 0.3796 | 0.4137 | 0.4572 | 0.4755 | 0.4862 | 0.4935 | 0.5024 | 0.5043 | 0.5044 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:96 | MLI | Mali | BRA.15.186_2 | São José de Espinharas | BR | gadm2 | 0.662 | 0.6506 | 0.6327 | 0.6409 | 0.647 | 0.662 | 0.6727 | 0.6772 | 0.6888 | 0.6986 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:97 | MLI | Mali | BRA.2.36_2 | Inhapi | BR | gadm2 | 0.6296 | 0.5984 | 0.5864 | 0.6019 | 0.6231 | 0.6418 | 0.6607 | 0.676 | 0.6905 | 0.7032 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:98 | MLI | Mali | COL.2.74_2 | Nechí | CO | gadm2 | 0.742 | 0.7359 | 0.7594 | 0.8041 | 0.8444 | 0.8772 | 0.9052 | 0.9297 | 0.9526 | 0.9728 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:99 | MLI | Mali | THA.8.9_1 | Khon Sawan | TH | gadm2 | 0.5992 | 0.5691 | 0.5634 | 0.5811 | 0.5993 | 0.6157 | 0.6309 | 0.6446 | 0.6574 | 0.6683 | 2,025 | 2,026 | 2025-2026 | AI for Good at Meta | Cross Gender Ties | gadm2_cgfr.csv | b138131c-52d0-48c0-8351-ee1c21cadf34 | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv | cc-by | 2026-08-12T23:12:09Z |
Cross Gender Ties | Africa (Mali official open data)
36,235 rows - 1 Africa country - 2025-2026 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official CSV resource from Mali as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
- Source: Cross Gender Ties
- Publisher: AI for Good at Meta
- Resource: gadm2_cgfr.csv
- Format:
CSV - License: CC BY 4.0
- Packaging mode:
tabular_resource
Geographic coverage
1 Africa country:
| Country | Rows | First year | Last year | Name |
|---|---|---|---|---|
MLI |
36,235 | 2025 | 2026 | Mali |
Indicators or Resource Contents
- This source file is packaged as a normalized tabular resource.
Schema
| Column | Type | Description | Example |
|---|---|---|---|
source_record_id |
string |
Stable row identifier for tabular resources. | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd:0 |
country_iso3 |
category |
ISO3 country code. | MLI |
country_name |
category |
Country name. | Mali |
region_id |
string |
Source column. | THA.17.13_1 |
region_name |
string |
Source column. | Muang Khon Kaen |
country |
string |
Source column. | TH |
level |
string |
Source column. | gadm2 |
cgfr_5 |
float64 |
Source column. | 0.5548 |
cgfr_10 |
float64 |
Source column. | 0.5279 |
cgfr_25 |
float64 |
Source column. | 0.5305 |
cgfr_50 |
float64 |
Source column. | 0.5544 |
cgfr_75 |
float64 |
Source column. | 0.5758 |
cgfr_100 |
float64 |
Source column. | 0.5947 |
cgfr_125 |
float64 |
Source column. | 0.6115 |
cgfr_150 |
float64 |
Source column. | 0.6267 |
cgfr_175 |
float64 |
Source column. | 0.6407 |
cgfr_200 |
float64 |
Source column. | 0.6535 |
source_period_start_year |
Int64 |
First year inferred from source resource metadata. | 2025 |
source_period_end_year |
Int64 |
Last year inferred from source resource metadata. | 2026 |
source_period_label |
category |
Human-readable period inferred from source resource metadata. | 2025-2026 |
source_provider |
category |
Publishing organization. | AI for Good at Meta |
source_dataset |
category |
Source package title. | Cross Gender Ties |
source_resource |
category |
Source resource title. | gadm2_cgfr.csv |
source_package_id |
category |
CKAN package UUID. | b138131c-52d0-48c0-8351-ee1c21cadf34 |
source_resource_id |
category |
CKAN resource UUID. | 7eb541a4-d22b-4fc6-b7ed-769cb4df06dd |
source_url |
category |
Original source resource URL. | https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/re |
license_id |
category |
Source license identifier. | cc-by |
retrieved_at |
category |
UTC retrieval timestamp. | 2026-08-12T23:12:09Z |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mali-cross-gender-ties-eb3709ca")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
sample_country = df[df["country_iso3"] == "MLI"]
Work with indicators
if "indicator_id" in df.columns:
print(df["indicator_id"].value_counts().head())
sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
Citation
@misc{electric_sheep_africa_africa_mali_cross_gender_ties_eb3709ca_2026,
title = {Cross Gender Ties | Africa (Mali official open data)},
author = {AI for Good at Meta},
year = {2026},
url = {https://data.humdata.org/dataset/cross-gender-ties},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-cross-gender-ties-eb3709ca}}
}
License
Released under CC BY 4.0.
Original data (c) AI for Good at Meta. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified,
ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
open sources, normalize the schemas, package as Parquet, and publish with
consistent dataset cards so researchers and developers can use load_dataset()
to start working in seconds.
Browse the full collection: huggingface.co/electricsheepafrica
Provenance: ingested 2026-08-13 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/7eb541a4-d22b-4fc6-b7ed-769cb4df06dd/download/gadm2_cgfr.csv
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