Managing fishing power: the case of Alaska red king crab (<i>Paralithodes camtschaticus</i>)
Bibliographic record
Abstract
Because of concern about the inability to manage the Bristol Bay red king crab (Paralithodes camtschaticus) fishery in Alaska and, in particular, to use in-season fishery performance to close the fishery at or near the preseason guideline harvest level, increasingly stringent pot limits were adopted to elongate the collapsing seasons. This paper provides a rigorous examination of the effect that pot limits had on season elongation and whether a redistribution of wealth occurred between large and small fishing vessels as a result of the policy. A simulation model of the fishery shows that pot limits did not elongate the season sufficiently to improve in-season management. Moreover, the policy allowed vessels to capture efficiency gains arising from an industry-wide reduction in fishing capacity. Both vessel size classes benefited from mutual gear reduction in all years except 1992. Redistribution of wealth was found to occur only in one year of the five years examined.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".