The Some Good and Mostly Bad about Maximum Sustainable Yield as a Management Target
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.An American historian, Dr Carmel Finley, has described in detail how Maximum Sustainable Yield (MSY) was used, during the post-World War II negotiation of a US-Japan Peace Treaty, as a quasi-legal, pseudo-scientific concept to force Japanese fishermen to ‘abstain’ from fishing for halibut and salmon in waters adjacent to the coasts of North America, (while not restricting US tuna fishing close to South and Central Ameroca).1 It was said that the fish resources in that region were ‘fully utilised’, under joint governmental management, of Canadian and US fishing operations. The claim was based mainly on studies by North American scientists, particularly Milner ‘Benny’ Schaefer, who applied a logistic model to the yellowfin tuna of the Eastern Pacific and thereby launched what we now know as ‘Surplus Production’ theory. This followed in the footsteps of the Norwegian scientists Johan Hjort, Per Ottestad and Gunnar Jahn who published in 1933 their classic study of whaling
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.045 | 0.017 |
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".