Impact of Microfinance on Poverty: Qualitative Analysis for Grameen Bank Borrowers
Bibliographic record
Abstract
Poverty is economic, social, political and even moral issue all over the world. Microfinance has been designed to eliminate poverty and may help marginal people to materialize their dreams. Microfinance has been formalized primarily in Bangladesh with this concept. Grameen Bank (GB) has been serving large number of people below poverty level here. Initially, microfinance institutions have been supported by the Government or Donor assuming its positive impact on borrowers. However, ambiguous impacts have been reported in several studies that make microfinance questionable. Therefore, this study intent to measure the impact of microfinance on GB borrowers through the process of qualitative changes in borrowers lives. The process has been measured by some case studies for participant and non-participant borrowers using Modified Household Economic Portfolio Model (M - HEPM). Our qualitative analysis shows that microfinance makes positive changes in the process of borrowers lives observed through financial and activity diaries of the borrowers.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".