What is at stake? Status and threats to South China Sea marine fisheries
Bibliographic record
Abstract
Governance of South China Sea (SCS) fisheries remains weak despite acknowledgement of their widespread overexploitation for the past few decades. This review incorporates unreported fish catches to provide an improved baseline of the current status and societal contribution of SCS marine fisheries, so that the socio-economic and ecological consequences of continued fisheries unsustainability may be understood. Potential fisheries contribution to food and livelihoods include 11–17 million t in fisheries catch and USD 12–22 × 10 9 in fisheries landed value annually in the 2000s, and close to 3 million jobs. However, overfishing has resulted in biodiversity and habitat loss, and altered ecosystem trophic structures to a ‘fished down’ state. The present situation reiterates the urgency for fisheries policies that simultaneously address multiple political, social, economic, and biological dimensions at regional, national, and local scales. Importantly, improved cooperation between SCS nations, particularly in overcoming territorial disputes, is essential for effective regional fisheries governance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".