Pacific Salmon: Ecology and Management of Western Alaska’s Populations
Bibliographic record
Abstract
Abstract.—The Arctic-Yukon-Kuskokwim Sustainable Salmon Initiative (AYK SSI) is a research program in Alaska focused on learning from the knowledge and understanding of local indigenous fishing communities. From the mid-1990s, Alaska Natives have urged that local and traditional/indigenous knowledge be recognized as a serious body of ecological insights and stewardship traditions. This paper provides a survey of milestones in Alaska, from the early definitional debates and the rise of systematic methods for documentation, to the growing body of substantive information. The discussion on local and traditional knowledge at the AYK SSI Symposium in February 2007 provided an opportunity to assess achievements and identify obstacles. Participants underscored the continuing challenges of the diverse cultural context for joint research by biologists and local communities, directing attention to foundational questions of trust and respect. Local residents celebrated the great promise for local and traditional/indigenous knowledge to contribute to our shared scientific understanding of salmon and to promote respectful and effective systems of stewardship, but they were also acutely perceptive of the barriers to improved synthesis and mutual learning. The concluding section of this paper explores implications for the on-going research agenda of the AYK SSI, particularly the need for an on-going consultative process to insure that local communities and researchers are mutually aware of methodologies available and the substantive contributions made by local and traditional knowledge research. In this way, the on-going development of research in this area can draw more fully on the struggles and accomplishments of the preceding decade.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".