Assessing Women’s Empowerment through Self-Help Groups: A Study of Personal and Economic Agency in Jabalpur, India
Bibliographic record
Abstract
Empowerment is a multi-dimensional social process that enables individuals, particularly women, to gain autonomy and control over their lives. Historically, women have faced both struggles and progress in achieving empowerment. Globally and in India, institutional and systemic interventions have been accelerating, with Self-Help Groups (SHGs) emerging as a significant avenue for promoting women’s empowerment. This study assesses women’s personal and economic empowerment associated with SHGs in Jabalpur, India. Primary data was collected from 62 women using a modified pro-WEAI (Women’s Empowerment in Agriculture Index) questionnaire that measures both intrinsic and instrumental agency among women. Statistical techniques, including t-tests and regression analysis, were employed to draw inferences from the data. The analysis revealed that women under the age of 35 exhibited higher levels of instrumental agency and total empowerment scores. This can be attributed to generational shifts, technological advancements, evolving gender roles, delayed marriage, and improved health and mobility. Additionally, women who had been associated with SHGs for more than 18 months and those educated to at least a high school level showed greater intrinsic agency, suggesting that government and educational programs can rapidly change mindsets. However, financial and asset-related impacts take longer to manifest. Regression analysis further indicated that the presence of more working individuals in a household is negatively associated with both intrinsic and instrumental agency among women. The findings highlight the need for targeted government initiatives to empower older and less educated women whose current programs may be underserved. Integrating financial literacy and asset management into SHG programs can further boost economic and personal empowerment. Tailored support for different demographic groups within SHGs can make interventions more inclusive and effective, promoting sustained empowerment and a more equitable society.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".