Temporal changes in harvesting dynamics of Canadian inshore fisheries for northern Atlantic cod, <i>Gadus morhua</i>
Bibliographic record
Abstract
We quantified temporal changes in catch rate, fishing effort, and catch misreporting for two sectors of the fixed-gear fishery for Newfoundland's northern Atlantic cod, Gadus morhua, from 1980 to 1991, the year preceding the stock's commercial fishing moratorium. Over the 12-year period, fishermen reported catch rate declines of 40 and 75% in the trap and gillnet fisheries, respectively, associated with significant increases in nominal fishing effort. Additional changes to effort included smaller gillnet and trap mesh sizes, larger traps, longer soak times, and modifications to trap design to increase catch retention probabilities. Compared with the early 1980s, unreported catches among inshore fishermen may have trebled by the late 1980s and early 1990s due to longer gillnet soak times, increased gear selectivity for small fish, and declining availability of fish of marketable size. These patterns in harvesting dynamics are consistent with the hypothesis that the decline of northern cod was gradual and that increased rates of catch misreporting contributed to increases in fishing mortality. The concomitants of declining fixed-gear catch rate, increasing quantitative and qualitative fishing effort, increased selectivity for smaller fish, and increasing levels of unreported catches may represent general correlates of imminent fish stock collapses.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".