Fisheries and the COVID-19 pandemic: A global scoping review of the early pressures, impacts, and responses in least developed, emerging, and developed countries
Bibliographic record
Abstract
The COVID-19 pandemic disrupted fisheries at every step of the global seafood supply chain, through such challenges as trade stoppages, lockdowns, and restaurant closures. We performed a scoping review of the literature published during the first two years of the pandemic to examine the challenges of new and unpredictable shocks to fisheries in countries around the world, with a specific focus on development status. We identified a robust body of published work that illustrates a rapid mobilization around COVID-19 research by scholars around the world. Pressures were governmental, economic, and societal in nature. Across developed and emerging countries, we found the greatest number of reports of impacts on fish harvest/production and fish trade. In least developed countries, impacts reported were often more cross cutting, affecting multiple aspects of the supply chain simultaneously. Individuals were most frequently reported as bearing the burden of responses to COVID-19 pressures in lower development status nations, while a larger proportion of responses reported for developed nations happened at the fishery and farm/firm level. In developed nations the pandemic also created new opportunities for people to respond innovatively and capitalize on supply chain disruptions. Importantly, while the literature offers robust details on fishers and fisheries from geographically and economically diverse locales, it fails to provide the necessary baseline information or other quantitative details that would be required to evaluate the magnitude and extent of harms experienced that may create long-term legacies for fisheries and small-scale fishing communities in least developed and emerging economies.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| 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".