How to Improve the Management of Renewable Resources: The Case of Canada's Northern Cod Fishery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The paper examines howan easy‐to‐apply optimal feedback rule can be used to solve for optimal levels of exploitation of a renewable resource. Using data from Canada's northern cod fishery, the optimal feedback rule is used to derive optimal levels of exploitation for the years 1962–91 under different discount rates, alternative model specifications, and parameter assumptions. The optimal feedback rule indicates that over much of the period the fishery was economically overexploited and, given the stock development that actually took place, a harvesting moratorium should have been instituted three years earlier than when it was introduced. The results show how the use of a simple and flexible optimal rule by managers of renewable resources can generate substantial gains.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it