A fresh look at inland fisheries and their role in food security and livelihoods
Bibliographic record
Abstract
Abstract The role of inland fisheries in livelihoods, food security and sustainable development is often overshadowed by the higher profile interest in ocean issues. Whilst inland fisheries' catch and contribution to global nutrition, food security and the economy, are less than that of marine fisheries, global‐level comparisons of fish production obscure considerable livelihood impacts in certain countries and sub‐national areas. To highlight these contributions, this paper synthesizes recent data and innovative approaches for assessing such livelihood contributions and their importance in countries with limited access to ocean resources and aquaculture. Inland fisheries are crucial for many socially, economically and nutritionally vulnerable groups of people around the world, but the challenges in monitoring inland fisheries preclude a complete understanding of the magnitude of their contributions. This situation is rapidly improving with increasing recognition of inland fisheries in development discourses, which has also encouraged research to enhance knowledge on the importance of inland fisheries. We review this work, including collated information published in a recent Food and Agriculture Organization report, to provide an up to date characterization of the state of knowledge on the role of inland fisheries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".