How to Make Individual Transferable Quotas Work Economically, Socially, and Environmentally
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 economic tool of individual transferable quotas (ITQs) gives their owners exclusive and transferable rights to catch a given portion of the total allowable catch (TAC) of a given fish stock. Authorities establish TACs and then divide them among individual fishers or firms in the form of individual catch quotas, usually a percentage of the TAC. ITQs are transferable through selling and buying in an open market. The main arguments by proponents of ITQs is that they eliminate the need to “race for the fish” and thus increase economic returns while eliminating overcapacity and overfishing. In general, fisheries’ management objectives consist of ecological (sustainable use of fish stocks), economic (no economic waste), and social (mainly the equitable distribution of fisheries benefits) issues. There is evidence to show that ITQs do indeed reduce economic waste and increase profits for those remaining in fisheries. However, they do not perform well in terms of sustainability or socially. A proposal that integrates ITQs in a comprehensive and effective ecosystem-based fisheries management system that is more likely to perform much better than ITQs with respect to ecological, economic, and social objectives is presented in this article.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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