Subsistence preference in practice: access decisions in salmon fisheries in the Alaskan Yukon River
Bibliographic record
Abstract
We examine Alaska Department of Fish and Game’s adherence to derived indicators of ecological and social sustainability. Ecological indicators rely on historical records of stock-status information and access decisions, while social indicators rely on a mix of historical records and semi-structured interviews with traditional subsistence users. Historical records are characterized by adherence to information requirements directing access and our operationalization of “subsistence preference,” the legal requirement to allow preferential access to traditional users. We find that decisions to close, restrict, or allow fishing are moderately adherent to general policies. Nonetheless, populations are still declining. We find little evidence of honoring the specific requirement of subsistence preference. Interviews eliciting traditional users’ perceptions of decision-making processes and outcomes revealed themes of heartbreak, anxiety, and frustration. Results suggest a need to rethink management approaches and indicators. Restricting access appears far better than closure for traditional users and more consistent with subsistence preference requirements.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".