Profit and Price Effects of Multi-species Individual Transferable Quotas
Why this work is in the frame
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Bibliographic record
Abstract
Regulators in many countries have adopted individual transferable quotas as a means of dealing with the open access problem inherent in fisheries. Using individual vessel data prior to and after the introduction of ITQs in Canada's multi-species Scotia-Fundy mobile gear fishery, the paper uses an index number profit decomposition to compare vessel performance over time and across individual vessels. The approach allows us to undertake both an ex post evaluation of short-term impacts of ITQs and an ex ante evaluation of longer term impacts. With respect to short-term impacts, the results suggest that larger vessels have benefited the most from the introduction of ITQs, but that all vessels have enjoyed increases in the prices received for those fish species that are included in the quota program. With respect to longer-term impacts, the transferability provisions of the ITQ program have encouraged exit and more efficient operations to prevail.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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