In-depth Analysis on the Access to and Suitability of the Loans
Bibliographic record
Abstract
This paper examines the borrowing behavior of the households and the suitability of the loans obtained from the community oriented financial intermediary (COFI) and reinforces the significance of using a household approach in evaluating the effects of microfinance. Using descriptive and statistical analyses, results show that the effects of credit in household income and expenses are positive and statistically significant with client households experiencing greater positive effects than nonclient households. Moreover, nonclient households, unlike client households, allot a greater percentage of their loans in proportion to their income on food and nonfood consumptions suggesting that they are more engaged in borrowing for smoothing their consumptions. It has also been shown that the access to COFI loans is relatively easy for the client household members since the requirements and processing are fast and reasonable. This indicates that credit cooperatives rarely disapprove loan applications and if there are numbers of pending loan applications, they usually reduce the amount of loan approved instead of disapproving the application. In general, COFI loans reasonably suit the needs of the COFI clients. Given that both household types obtained their credits from various lenders, those who have access to the COFI system have a reliable source of loans indicating that the COFI performs a particularly important role in providing services, especially credit lines.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".