Fisheries subsidies exacerbate inequities in accessing seafood nutrients in the Indian Ocean
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Harmful, capacity-enhancing subsidies distort fishing activities and lead to overfishing and perverse outcomes for food security and conservation. We investigated the provision and spatial distribution of fisheries subsidies in the Indian Ocean. Total fisheries subsidies in the Indian Ocean, estimated at USD 3.2 billion in 2018, were mostly harmful subsidies (60%), provided to the large-scale industrial sector by mainly a few subsidising countries, including Distant Water Fishing countries. We also explored possible socio-economic drivers of the composition of subsidies, and show that the extent of harmful subsidies provided by Indian Ocean Rim (IOR) countries to their industrial sector can be predicted by the seafood export quantities of these countries. These results illustrate the inequity in accessing fisheries resources for the small-scale sector of nutrient insecure and ocean-dependant IOR countries. The present study can benchmark future assessments and implementation of fisheries subsidy disciplines in the region following the World Trade Organisation Agreement on Fisheries Subsidies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it