Bibliographic record
Abstract
Abstract Rice, J. 2014. Evolution of international commitments for fisheries sustainability. – ICES Journal of Marine Science, 71: 157–165. The basic standards for the sustainability of fisheries were set by international policy in the UN Fish Stocks Agreement (FSA). However, each year since the FSA was ratified, the United Nations General Assembly has negotiated and agreed to resolutions on Ocean Law of the Sea and on Sustainable Fisheries. This paper reviews chronologically how the interpretation of “sustainability” has evolved in those resolutions, as well as been addressed in the decadal world summits on sustainable development. Although the basic biological benchmarks for sustainability have not been altered by these resolutions, commitments for the standards to be met by all ecosystem components impacted by fishing have become increasingly strong. The annual resolutions have increasingly stressed that environmental sustainability is critically important, but is not more important than social well-being aspects of sustainability, with fisheries having a vital role in sustainable development in many parts of the world. In addition, agreements on biodiversity conservation made largely in Oceans and Law of the Sea resolutions are increasingly influencing the nature and pace of evolution of how “sustainability” is interpreted in fisheries.
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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".