Bibliographic record
Abstract
This chapter briefly describes five fisheries in which ITQs or related systems have recently been instituted. (See Ocean Studies Board 1999 for other case studies of ITQ fisheries.) The five fisheries cover a variety of species and fishing techniques. In most cases fish stocks were severely depleted, or in imminent danger of becoming so, when the ITQ system was initiated. In all cases the new management regime has apparently stemmed or reversed the depletion of the stock. Economically speaking, the results are less clear. Vessel owners are notably reluctant to provide details about the profitability of their operations, and few of the cited references include detailed cost data or profit estimates. Profitability is sometimes inferred from the fact that quota prices have increased over time. An alternative explanation is that the price increase is mere speculation. Without actual financial data the two explanations cannot be separated. Georges Bank Sea Scallop Fishery The Atlantic sea scallop is distributed over the Northwest Atlantic continental shelf, from the Gulf of St Lawrence to Cape Hatteras, with a major population on Georges bank off New England. Scallops, caught by bottom dredging, are processed at sea, the product being fresh or frozen scallop “meats” typically sold in stores and restaurants. The description given here is condensed from Repetto (2001) and Edwards (2002). Repetto compares the management system for US and Canadian fisheries, calling this a “natural experiment in fisheries management.”
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".