Negotiating risk and poverty in mangrove fishing communities of the Bangladesh Sundarbans
Bibliographic record
Abstract
Small-scale fishers in Bangladesh face substantial risks due to their occupation and their geographical setting. Without any effective buffer against crises, recurring shocks and on-going risk exposure are major factors pushing fishers into poverty. Not all fishers experience these events in the same way, however, with some of them showing higher capacity to negotiate risks. In this study, we ask how fishers cope with shock, what factors differentiate them in their risk negotiations, and what implications these factors may have on poverty alleviation policy. On the basis of the study’s findings, we posit that poverty alleviation in small-scale fishing communities in Bangladesh requires interventions that target not only risk minimization, but also the endowment of fishers with socio-economic capitals to help them handle varying degrees of risk and shocks. Such policies as, for instance, providing employment for fisherwomen or providing a basic social safety net will increase the overall resilience and well-being of fisher communities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".