The Role of Microfinance in Poverty Alleviation: Empirical Evidence from South-West Nigeria
Bibliographic record
Abstract
Microfinance programme has been generally regarded as a development strategy that can enhance the economic performance of the poor. The government of Nigeria has made concerted efforts to alleviate poverty in the country. One of such efforts is Poverty alleviation through Microfinance loan but poverty still remains pervasive and widespread in the country especially in the rural communities. This study examines the role of microfinance vis-à-vis poverty reduction particularly in the South- West Zone of Nigeria. Data were collected through survey questionnaire in the study area. Descriptive Statistics together with Binary Logit Regression Model were employed to analyse the data collected. The result of the analyses revealed that microfinance loan made significant impact on the loan beneficiaries in the study area which lead to poverty reduction. The government is advised to provide more enabling environment to make Microfinance operations more effective in the country particularly in the rural areas. Microfinance Institutions are implored to create more awareness on their operations and make less stringent conditions for the loan accessibility.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".