Microcredit and savings associations for building rural household resilience: A case study of selected village development fund and savings groups in Koh Kong and Mondul Kiri, Cambodia
Bibliographic record
Abstract
This case study was conducted to generate insights on the financial sustainability of selected VDFSGs and to gather information on members’ perceptions of the usefulness of these institutions in coping with household and climate change-related shocks or stresses. Financial sustainability was analyzed by conducting a detailed financial analysis of six selected VDFSGs to determine the sufficiency of interest payments as revenue to cover total costs as well as to evaluate loan recovery and equity build- up. Members’ perception of the usefulness of VDFSGs in helping them to cope with and adjust to family and climate change-related shocks/stresses was determined by conducting Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs) among selected representatives of VDFSG members. Useful feedback of the financial performance and areas for improvement were generated. The Pu Hong, Pu Chhob, and Prek Svay VDFSGs were considered financially sustainable based on the results of the study. The study also revealed that the VDFSGs are considered most useful when there are crop failures due to extreme weather events and when there are medical emergencies in the household. The FGD participants and key informants expressed confidence that they are in a better position to cope with their vulnerabilities due to the presence of a VDFSG in their village.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".