Women Empowerment Status in the Coastal Fishing Communities of Bangladesh
Bibliographic record
Abstract
Socially ascribed gender norms are a significant barrier for women of the fishing communities in coastal Bangladesh. These norms limit women's income autonomy, access to productive resources, decision making capacity and mobility, which negatively affects their economic empowerment and overall well-being. The article delves into the topic of women's empowerment in these communities. The study employed a mixed method approach to collect data from ECOFISH II project intervention villages. Pro-WEFI, which is a modified and refined version of the Women's Empowerment in Agriculture Index (WEAI) was utilized for fishing community to determine women's empowerment and disempowerment status across three domains of empowerment (3DE): intrinsic, instrumental, and collective agency. The findings revealed that men experienced fewer inadequacies than women, with a weighted average 3DE score of 0.75 for men and 0.57 for women, and only 14% of women and 37% of men were found to be empowered. The Gender Parity Index (GPI) score was 0.79 and households with gender parity made up 31% of the total. This study developed a comprehensive set of Pro-WEFI indicators applicable for assessing and comparing women's empowerment across cultures in fisheries-related projects. Utilizing the disaggregated scores of each Pro-WEFI indicator, it is possible to identify areas of disempowerment for both genders and prioritize project interventions accordingly. Furthermore, employing the Pro-WEFI tool in a longitudinal panel design can capture the changes in women's empowerment over time in any fisheries project.
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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".