Once considered a “disruptive science”, biotelemetry is now among the most trusted and relevant approaches informing salmon fisheries management
Bibliographic record
Abstract
New scientific approaches that prompt a rethink in resource policy or management, and that lead to “worldviews” being challenged, are considered to be “disruptive”. This paper explores (i) the complex 30-year history of a biotelemetry science “disruption” with the management of Fraser River salmon fisheries, (ii) the transformation of biotelemetry science from a disruptive to an accepted science, and (iii) the circumstances that have now made it one of the most important tools for managing Pacific salmon fisheries. We conclude with an overview of a successful case study involving the co-production of biotelemetry science to inform the management of the British Columbia marine recreational fishery. The approach we advocate for provides a pathway for all telemetry practitioners to avoid potential pitfalls and take advantage of what we have learned to ensure biotelemetry science continues to have the potential to generate relevant knowledge to inform management of all socio-economically important fishes.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".