Caring for Pacific salmon: Reconsidering salmon‐human relationships
Bibliographic record
Abstract
Caring for Pacific salmon – one of the most iconic creatures of the North American West Coast – is not a straightforward task but is based on diverse understandings and relationships between salmon, people and the more‐than‐human environment. Local small‐scale interactions, in particular, shape individual motivations to care for these fish and understand how best to do this. This article emerges from a collaborative research project with the Heiltsuk Nation, whose territory is located on the Central Coast of British Columbia (BC), Canada. Through ethnographic engagement with both Indigenous and non‐Indigenous residents and visitors of this area, this article illustrates that close interactions are at the core of why and how people care for salmon. Drawing on theoretical engagements with the concept, care is understood not as an innocent notion but as a complicated set of practices that can also involve killing salmon. These salmon‐human interactions transcend unidirectional dominance, evolving into reciprocal exchanges that distribute responsibility across species boundaries.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.039 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| 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".