Access to markets for small-scale fisheries: challenges and opportunities during and after the COVID-19 pandemic
Bibliographic record
Abstract
This study views markets as social institutions and examines whether they enable or hinder access for small-scale fisheries, especially in the context of the COVID-19 pandemic at a global and a national scale (Bangladesh), with a local case study in the Bangladesh Sundarbans. On a global scale, the study reveals that the COVID-19 pandemic has disrupted the supply chains of fish and fisheries products worldwide, with serious consequences for small-scale fishers’ livelihoods and socio-economic conditions. However, the pandemic has also brought new opportunities for small-scale fisheries, including product and income diversification, alternative market arrangements, and flexibility in direct sales. At a country level in Bangladesh, similar effects are found in the production, distribution and supply, processing, markets, and food and nutritional security for small-scale fisheries. Finally, a case study was conducted in the Bangladesh Sundarbans to investigate the market structure and the governance of access to markets for the small-scale mud crab (Scylla serrata) fishery. The findings show that local traders or depo owners are the main actors governing both the domestic and the export mud crab supply chains, while small-scale fishers are invisible due to weak market arrangements and the absence of government policy to support them. The study recommends modifying the market governance structure based on the social dynamics of the stakeholders, institutional capacity, and interactions between the key actors to enhance the small-scale fisheries’ access to markets. Overall, the COVID-19 pandemic has created an opportunity for countries around the world, especially for developing countries like Bangladesh, to build back the market structure better and stronger, also by addressing the pre-pandemic distortions made by the powerful players in the supply chains. Governing bodies and the stakeholders of the fisheries supply chains around the world could also learn from the present situation and use it as a basis for building viable and resilient small-scale fisheries when facing future crises.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".