The dynamics of exploited marine fish populations and Humpty Dumpty: similarities and differences
Bibliographic record
Abstract
Marine fish populations of the global oceans and particularly large‐bodied, continental shelf‐dwelling groundfish species of the North Atlantic, such as cod (Gadus morhua), have been strongly perturbed by over‐fishing, frequently beyond levels that may have altered their capacity to recover. Age and size structure, spatial structure, reproductive potential, and other traits that convey fitness advantages are commonly lost when prolonged and excessive fishing pressure is exerted. Fisheries management protocols implemented to recover collapsed populations have been numerous and varied with all attempting to reduce or eliminate fishing pressure. Such measures, employed singly or in multiple combinations, typically involve quota reductions or fishing moratoria, area closures and other technical measures, as well as enhanced enforcement of fishing practices. A striking geographic pattern exists in the efficacy of such measures to regain lost population attributes and hence recovery. Some regional populations have recovered while others, despite management interventions lasting decades, notably, but not exclusively, those aimed at cod populations of the Northwest Atlantic, have yet to fully recover, an endpoint analogous to the conclusion of the famous nursery rhyme of Humpty Dumpty. Here we examine the dynamics of multiple collapsed populations exhibiting varying responses to recovery initiatives from the perspective of the Humpty Dumpty metaphor.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".