A global review of species‐specific shark‐fin‐to‐body‐mass ratios and relevant legislation
Bibliographic record
Abstract
In this review, shark-fin-to-body-mass ratios, which have been legislated by several countries as a means of regulating and monitoring shark fisheries, have been compiled and reviewed. Observed and legislated wet-fin-mass-to-round-mass (M(fw) :M(r) ) ratios have been collected for 50 species and eight countries. Wet to dry-fin mass conversion factors have also been reviewed. Existing shark fishery legislation was compiled by political entity and regional fishery management organizations (RFMO). The mean observed M(fw) :M(r) ratio for all species was 3·0%, but actual fin to body-mass ratios varied considerably by species and location. Species-specific mean ratios ranged from 1·1 to 10·9%, and estimated mean ratios ranged from 1·5 to 6·1% by country, depending on fin-cutting practices and the mix of exploited species. The mean conversion factor for wet to dry-fin mass was 0·43. Shark-related legislation was found to exist in 37 countries and the 22 maritime members of the European Union, and shark-related regulations have been designated by nine RFMOs. Results suggest that currently regulated ratios may not be appropriate for all species and fin-cutting practices, and regulations based on generalized ratios for all sharks may be inadequate. Alternative policies may be necessary for the effective management of global shark fisheries.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".