Is Fisheries and Oceans Canada policy receptive to a new Pacific salmon health perspective?
Bibliographic record
Abstract
The concept of health permeates priorities and policies for managing wild Pacific salmon ( Oncorynchus spp.). Regulatory agencies rely largely on salmon abundance and (or) the absence of pathogens to declare if a population is healthy. Our goal was to determine if there was a receptive policy environment within Fisheries and Oceans Canada (DFO) to adopt a cumulative effects perspective of health. We used a previously developed health model along with a multiple streams framework and a narrative review of DFO policy to see how fish health was situated in DFO’s salmon management problems, policy, and politics. We discovered that a cumulative effects perspective was consistent with policy goals and priorities. DFO’s guiding principles and responsibilities for aquatic animal health were spread across multiple policies and regulations. There were no processes or people responsible for integrating information and activities. The use of the word health in policies and planning without a consistent definition meant that DFO could not explicitly assess if it has reached its management target of healthy salmon. An option for transitioning to cumulative effects perspective is to adopt a healthy public policy perspective and processes to integrate the diverse information linked to social and environmental determinants of health.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".