High Seas Fisheries: Troubled Waters, Tangled Governance and Recovery Prospects
Bibliographic record
Abstract
Global fisheries are in a perceived state of crisis. Despite growing technological effort and an unprecedented global expansion of fisheries, total landings (85-100 million MT per year) have stagnated and probably entered a period of slow decline. This trend may destabilize ocean ecosystems and undermine world seafood supplies, which provide the major source of protein for 2.3bn people, and international cooperation to address this issue has been slow. This is particularly true for highseas fisheries that occur in international waters encompassing some 61% of the world's ocean. These have been plagued by a fragmented and weak legal framework, poor enforcement of existing regulations, and the problem of illegal, unreported, and unregulated (IUU) fishing. On the positive side, individual States have introduced measures that have been successful in recovering overexploited resources. Turning the tide on the high seas requires strong government cooperation to enforce conservative harvest levels (quotas), as well as measures that protect biological diversity, such as protected areas, bycatch regulations, and the conservation of critical habitats. This article provides a short overview of the biological, institutional and legal dimensions of high-seas fisheries. It emphasizes that this is a unique time in history, where unprecedented awareness, scientific advances, and a growing willingness to collaborate internationally are setting the stage for a dynamic transformation of high-seas governance. What is missing is a visionary master plan on how to integrate fragmented efforts towards the common goal of sustainable development on the high seas.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".