Comment on Fishing Effort Allocation in the Turks and Caicos Islands
Bibliographic record
Abstract
"There is no doubt that social structure and norms play an important role in economic efficiency but to downplay the crucial role that economic factors play in artisanal fisher decision making can lead to faulty policy recommendations and could potentially jeopardize efforts to conserve important reef species and habitats. Like terrestrial farmers and forest users in developing countries, the decisions of artisanal fishers tend to be uncompromisingly economic in nature when all factors ? information availability, risk preferences, and wealth (or lack thereof) ? are considered. Fishers in the Turks and Caicos Islands tend to be marginalized ethnically or socially, and the fishery acts as the de facto social safety net. In circumstances such as these, fishers tend to be highly cognizant of risk and rewards even if the dockside banter centers on diving skill. Artisanal fishers? economic decision-making capacity should not be underestimated."
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".