Developing a Precautionary Approach to Fisheries Management in Canada - the Decade Following the Cod Collapses
Bibliographic record
Abstract
We review the evolution of the precautionary approach in a Canadian context over the decade following major collapses of a number of cod stocks. The collapses of these cod stocks in the late-1980s and early-1990s precipitated evaluations of alternative scientific and fisheries management approaches. Over the 10 years following the collapses, Canada has been engaged in a process of developing a precautionary framework that is consistent with UNFA. This framework adopts a notion of “serious harm” as the definition of a conservation limit reference point. Several approaches for defining conservation limits consistent with serious harm have been applied to three Canadian cod stocks of concern and used in the provision of scientific advice in the most recent assessments. While much has been achieved, work is ongoing to develop robust limit reference points in terms of both spawner biomass and fishing mortality, and to explicitly take into account uncertainty associated with these reference points in relation to uncertainty in the current state of the stock and uncertainty in the projected future states. Approaches for linking a harvest strategy framework to the limits, the current state of the stock, and projected future states, accounting for the associated uncertainties, still need to be developed. However, a broad Canadian framework for the PA is now in place which is consistent with UNFA, and which could provide the basis for management decisions at the present time.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".