Bibliographic record
Abstract
16 savings groups in, 2 African Development Bank (AfDB), 14 African Development Foundation (ADF), 94 Aga Khan Foundation (AKF), 23, 183-184, 187 Agaliawamu, 261 Age International, 23, 27-28 Agence française de développement (AFD), 69-70 Agência de Promoção de Microfinanças (APM), 152 Agência de Supervisão de Actividade de Poupança e Microcrédito (ASAPM), 152 Agriculture, 151 Ajo, 208 Ajo Plus Account, 209 success and challenges, 210 Alajo, 196-197 Alliance du Crédit et de l'Epargne pour la Production (ACEP), 219-220 Amasachina, 139 Apoio à Emergência e Desenvolvimento da Microfinança ('APED-MF'), 152 Associação de Mulheres de Atividades Económicas (AMAE), 158 Association of Partially or Fully French-Language Universities (AUPELF), 218 Asun, 196 Asunafo, 136 Auction method, 77 Awach, 127 Botu, 87-88 Brong-Ahafo region, 136 Burial stokvels, 240-241 Burkina Faso case study, 70-72 cross-cutting themes, 69-70 economic effect, 65-67 ecosystem for financial inclusion, 68-69 savings groups in, 62-63, 68 social results, 67-68 Business, 263 Bwakisa carte, 100, 105 Cabo Verde economic outcomes, 91-92 formal finance and savings groups in, 89-91 social outcomes, 92-93 traditional forms of social solidarity in, 87 Cameroon economic impact of saving groups, 77 lessons from Cameroon case studies, 78-84 savings groups in, 75-77 social impact, 77-78 Canchungo, 151 Capital market, 135 C ÁRITAS, 89 Catholic Relief Services (CRS), 22-23, 62 Central Bank of Nigeria (CBN), 205, 208 Centre for Grassroots Economic Empowerment (CGEE), 204 economic outcomes, 208 Centre for Scientific Research (CNRS), 221-222 Chamapesa, 171 Chamas, 1, 164-166 objectives, 167-169 Chamasoft, 171 Chango app, 171 Chita, 239 Chitu, 239 CITY HABITAT, 89 Commercial banks, 69 Commercial tontine, 217 Communities, 78 memberships, 225 microfinance model, 97-98 Community Agents (CAs), 188 Community Development Trust Fund (CDTF), 202 Community of Savings and Internal Credit (CSIC), 62 Community Women Association of Nigeria (CWAN), 202 Company and Intellectual Property Records Office (CIPRO), 253 Competences, 33 additional competences in context of NGOs, 41 entrepreneurship, 40-41 ethical, 37 financial, 36-37 Congolese financial environment, 98 Consultative Group to Assist the Poor (CGAP), 163 Consumption, 13 Cooperative for Assistance and Relief Everywhere (CARE), 21, 135 International, 22-24, 262 MMD/VSLA Model, 23-25 Cooperative Regulations 9531, 261 Cooperatives, 126-127 Cooperatives Act CAP112, 261 Coordinating skills, 37-38 Corporate Affairs Commission (CAC), 205 Cotton producer groups (GPCs), 72 Council for Scientific and Industrial Research of the Savannah Agricultural Research Institute (CSIR-SARI), 141 Credit, 263-264
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.795 | 0.841 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".