‘Man can’t give birth, woman can't fish’: gender dynamics in the small-scale fisheries of Bangladesh
Bibliographic record
Abstract
Going beyond the myths prevalent in the socio-cultural embeddedness of rural Bangladesh, this article examines the diverse visible and invisible roles of fisherwomen in small-scale fisheries. This research considered two ethnic groups situated in two different ecosystems: the floodplain freshwater ecosystem is represented by new-entrant Muslim fishers ‘Maimal’ and the coastal ecosystem is represented by caste-based Hindu fishers ‘Jaladas’. From the basic ontological worldview of human dignity, moral individualism, and the social recognition of women’s rights, we argue that fisherwomen’s roles need to be recognized, focused, and valued to develop a horizontal understanding that is a prerequisite to the process of democratization, and the proper functioning of a just society. In the rural societies, a host of attributes, such as the deep-rooted socio-cultural constructions of the motherly myth, extreme tolerance, family teaching, religious antagonism, poverty, lack of education, internalization of a subordinate position, lack of supportive institutions, and fear of loss of societal patronage, profoundly undermine the capacity of women to aspire and raise their voice. Fisherwomen are accrued an inferior social position although they perform unique roles in the areas of childcare, household upkeep, livelihoods, and psycho-social support for the seafaring fishers. Conducive to the ecotone of marine fisheries, this article also portrays how a rigid patriarchal form of society is seasonally transformed to matrifocality when fishermen are away for fishing for half the year.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".