Wetland resource management in Bangladesh: Implications for marginalization and vulnerability of local harvesters
Bibliographic record
Abstract
In Bangladesh, the state has the legal ownership and absolute control over natural resources, including the public land, forests, animals, water and fishes upon which local communities, consisting of fishers, farmers, daily labourers and other workers, rely heavily for their livelihoods. There is a system in place for fisheries or waterbodies, known as jalmohal administration. Under this system, the real control remains in the hands of the leaseholders. The evolution of wetland resource management approaches and their impact on actual harvesters are of particular interest in the study. By examining the implications of the top-down management regimes and the recent experimentation with the community-based resource management approach, this study analyses the trajectories of marginalization and consequential vulnerabilities of Hakaluki haor area local communities located in the northeastern region of Bangladesh. The framework of transfer of property rights, that is, leasing of wetlands as jalmohals (fishery estate), not only encourages individual gains and exploitations by the powerful elites, but also accelerates both the marginalization process and the vulnerability of local fishers to various types of shocks, including natural and health hazards.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| 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".