It’s time to sharpen our definition of sustainable fisheries management
Bibliographic record
Abstract
We review and evaluate the sustainability paradigm as it applies to wild capture fisheries in the context of a recently developed harvest strategy framework that, if implemented, will meet Canada’s national and international obligations with regard to sustainable fisheries. This framework is based on an operationally explicit definition of sustainability that includes a commitment to managing for maximum sustainable yield. Although Canadian policy strongly supports sustainable fisheries management in principle, usage of the term has been vague and implementation of sustainable fisheries management strategies has lagged. Fisheries managed under the recently developed framework would be better able to meet new ecocertification and ecolabelling standards. An emerging governance structure discussed herein with respect to fisheries management is conducive to implementing sustainable management practices that meet long-term public good objectives.
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 | 0.034 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.015 | 0.036 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.010 | 0.032 |
| Insufficient payload (model declined to judge) | 0.005 | 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".