Assessing the Impact of Financial Knowledge on Financial Inclusion among Muslim Women in Urban Gaya District: An Empirical Analysis
Bibliographic record
Abstract
Abstract This study investigates the influence of financial knowledge on financial inclusion among Muslim women residing in the urban region of Gaya district, Bihar. Using a structured questionnaire administered to 650 respondents, the research applies descriptive statistics, exploratory factor analysis (EFA), and multiple regression analysis to evaluate how financial knowledge affects access to, usage of, and perception about formal financial services. The questionnaire included items measuring basic financial concepts, digital finance usage, and culturally specific financial preferences such as interest-free banking. The findings suggest a statistically significant positive relationship between financial knowledge and financial inclusion, even after controlling for education, income, and employment status. The model explains over a quarter of the variation in inclusion outcomes. These results highlight the urgent need for culturally contextualized and gender-sensitive financial education programs in minority-dominated urban regions. The paper concludes with actionable policy recommendations aimed at bridging gendered financial gaps in marginalized urban communities and suggests directions for future research. The results also underscore the potential for these interventions to create a replicable model for other socio-religious minority groups facing financial exclusion.
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How this classification was reachedexpand
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 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".