Intergenerational valuation of fisheries resources can justify long-term conservation: a case study in Atlantic cod (<i>Gadus morhua</i>)
Bibliographic record
Abstract
Where the conventional model of discounting advocates aggressive harvest policies, intergenerational discounting could have been used to render the historic gross overfishing of Atlantic cod (Gadus morhua) economically unappealing compared with a more conservative long-term strategy. Under these discounting approaches, we compare the historic harvest trend from 1985 (and projected postcollapse earnings) with theoretical optimal harvest profiles determined by an ecosystem model. The optimal scenarios generate less initial harvest than the historic profile but maintain the resource and provide greater yields over the long term. At a discount rate equal to market interest, we demonstrate that it was more economic under conventional valuation to harvest the cod stock to collapse than it would have been to sustain the population. However, under intergenerational valuation, the sustainable optimal scenarios outperform the actual harvest profile. Application of conventional discounting by fishing consortiums may be partly to blame for depletion, yet management fell short of even that ideal.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".