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Record W197709451 · doi:10.7202/702130ar

Les pêches canadiennes, objet de relations internationales complexes et conflictuelles

2005· article· en· W197709451 on OpenAlexaffvenueabout
Marcel Daneau

Bibliographic record

VenueÉtudes internationales · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversité LavalMinistère des Ressources naturelles et des ForêtsGDG Environnement
Fundersnot available
KeywordsFishingStock (firearms)Fisheries managementAppropriationFisheryBusinessEconomicsEconomyGeography

Abstract

fetched live from OpenAlex

Canada's fisheries have always been the subject of complex and conflicting international relations. Until January 1977, the fishing grounds off the Canadian coasts were there to be exploited by any nation with the means to do so. Interstate competition had a disastrous effect on the stock. With the extension of Canadian responsibilities to 200 miles offshore, a national System was laid down for stock exploitation and appropriation. From 1976 to 1982, Canada set up plans for the strict management of its fisheries, and numerous agreements were signed which allowed for the allocation of surplus stock from the Canadian waters in return for a market for Canadian sea products. From 1982 to 1985, with its stock increasing, Canada's policy appeared more generous since it allowed for the allocation of its non-surplus stock to signatory countries with a growing market for Canadian goods or with lower tarriff barriers. Since 1985, the emphasis in Canada has been mainly on conservation : Non-surplus stocks are allocated to countries who buy Canadian sea products, though especially those who respect the Canadian territorial limits and who respect the quotas, set by the North West Atlantic Fishing Organisation, outside Canada's 200-mile zone in the Atlantic. Due to its proximity to the US and to France (St-Pierre and Miquelon), Canada has sustained relations with those two countries. There are major differences between them regarding the demarcation of maritime boundaries and the sharing of transnational fisheries.

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)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.215
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.011
Science and technology studies0.0220.033
Scholarly communication0.0320.007
Open science0.0020.006
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0130.002

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 head0.060
GPT teacher head0.357
Teacher spread0.297 · 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 designNot applicable
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

Citations0
Published2005
Admission routes3
Has abstractyes

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