Measuring Potential Rents in the North Sea Herring 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 This paper assesses the potential for rent generation in the North Sea herring fishery. The assessment distinguishes between rents and intra‐marginal profits—the sum of which constitutes variable profits in the fishery. A bioeconomic model combining fish population dynamics and the economics of the fishery is constructed to allow the computation of these different components of profits. In order to assess the dynamics of both rents and intra‐marginal profits, the model is computed under various assumptions with regard to price, costs, and discount rates. Potential total profits are measured at £88 to £89 million annually, of which rents make up about £87 million with intra‐marginal profits measured in the order of only £2 million. The study further shows that, in this fishery, rent is dissipated mainly due to excess effort but also due to suboptimal stock size.
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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 | 0.000 | 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 it