Gender Based Utilization of Microfinance: An Empirical Evidence from District Quetta, Pakistan
Bibliographic record
Abstract
This study examines the impact of microfinance on gender based income generating activities of the Khushhalli Bank Ltd client’s in urban zone of district Quetta during year 2011. The Primary data was collected through structured questionnaire from 80 clients (60 beneficiaries and 20 non-beneficiaries) by adopting cross sectional experimental design. In order to analyze the collected data the t-tests were applied. The results show that the microfinance has a positive impact on both male as well female beneficiaries as compare to non-beneficiaries in term of increase in business performance. It has non-significant impact on average sale revenue of both male as well as female micro-entrepreneurs. Whereas it has a significant impact on average net profit, average fixed assets as well as average net worth of the male but having non-significant impact on female established micro-entrepreneurs. Comparison of gender based business performance reveals that the microenterprises operated by male are able to generate better revenue and net income performance also the same results are obtained in case of enhancement in fixed assets as well as net worth. So we may confidently say that male clients are able in utilizing the microfinance services more effectively as compared to female.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".