Bibliographic record
Abstract
Salmon are inherently resilient species.However, this resiliency has been undermined in British Columbia by a century of centralized, command-and-control management focused initially on maximizing yield and, more recently, on economic efficiency.Community and cultural resiliency have also been undermined, especially by the recent emphasis on economic efficiency, which has concentrated access in the hands of a few and has disenfranchised fishery-dependent communities.Recent declines in both salmon stocks and salmon prices have revealed the systemic failure of the current management system.If salmon and their fisheries are to become viable again, radically new management policies are needed.For the salmon species, the emphasis must shift from maximizing yield to restoring resilience; for salmon fisheries, the emphasis must shift from maximizing economic efficiency to maximizing community and cultural resilience.For the species, an approach is needed that integrates harvest management, habitat management, and habitat enhancement to sustain and enhance resilience.This is best achieved by giving fishing and aboriginal communities greater responsibility and authority to manage the fisheries on which they depend.Co-management arrangements that involve cooperative ownership of major multistock resources like the Fraser River and Skeena River fisheries and community-based quota management of smaller fisheries provide ways to put species conservation much more directly in the hands of the communities most dependent on the well-being and resilience of these fisheries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.002 |
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".