Examining the Critical Factors Affecting the Repayment of Microcredit Schemes in Amanah Ikhtiar Malaysia (AIM) in Malaysia
Why this work is in the frame
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Bibliographic record
Abstract
This study employs a cross sectional design with stratified random sampling method to examine how common household factors affect repayment performance of Amanah Ikhtiar Malaysia (AIM)’s hardcore poor microcredit program clients in Peninsular Malaysia. This study designed and tested a structural equation model to investigate how uses of loan, household income, number of gainfully employed members, number of sources of income and total savings affect repayment performance. Findings of this study showed a significant model fit and negative linear relationship between repayment problem with uses of loan in income generating activities, household income, number of gainfully employed members, and number of sources of income. AIM should therefore focus on designing and providing appropriate training and development programs to enable the hardcore poor households’ ability to use credit in income generating activities, grasp employment generating opportunities as well as find and invest in new income generating activities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it