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Record W2167279866

Developing a Precautionary Approach to Fisheries Management in Canada - the Decade Following the Cod Collapses

2003· article· en· W2167279866 on OpenAlexaboutno aff
Northwest Atlantic, P. A. Shelton, Oceans Canada, Denis Rivard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsPrecautionary principleStock (firearms)HarmFisheries managementFish stockFishingUncertaintyContext (archaeology)FisheryNatural resource economicsEconomicsEnvironmental resource managementGeographyEcologyPolitical scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.985

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0070.005
Scholarly communication0.0080.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.233
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2003
Admission routes1
Has abstractyes

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