Conflicting stakes and governance relating to the co-management of salmon in the Columbia river basin (U.S.A.)
Bibliographic record
Abstract
In the U.S. portion of the Columbia Bassin, salmon populations are five times lower than 150 years ago. They are co-managed by federal, state and tribal protagonists in order to restore them. On this territory larger than France, the federal government dominates the governance relating to the co-management of endangered and threatened species of salmon. The NOAA Fisheries Service writes up recovery plans and biological opinions that guide the actions on the ground. State and tribal agencies carry out multiple tasks on the ground, including the reintroduction of local salmon populations, the restoration of riparian areas, the management of salmon hatcheries or the enforcement of fishing rules. At the same time, a federal court in Oregon has authority to change the federal plans and biological opinions if the latter do not comply with the 1973 Endangered Species Act. During the 2000s, this court notably contributed to reduce the lethal impact of dams on salmon. If some local salmon populations have been partially restored, major problems remain unresolved: large dams keep hindering the overall recovery, just like continuing pollution and environmental degradation in parts of watersheds. Conflicts of interest between different groups go on. Environmental and fishing groups as well as Indian tribes call for more ambitious recovery targets. They come up against major agricultural and industrial interests generally protected by federal and state governments. These two governmental protagonists are opposed to the development of elements of tribal projects related to salmon hatcheries. The adoption of the United Nations Declaration on the Rights of Indigenous Peoples by the Obama administration in 2010 could defuse conflicts and bring about changes in the governance.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".