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Record W2992130827 · doi:10.1051/nss/2019043

Une approche néo-institutionnaliste des systèmes de gestion des pêches en Europe et en Amérique du Nord

2019· article· fr· W2992130827 on OpenAlexaffabout
P. Le Floch, James R. Wilson

Bibliographic record

VenueNatures Sciences Sociétés · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

L’article retient comme problématique la portée et les limites de la régionalisation des pêches, en s’appuyant sur les expériences en Europe, aux États-Unis et au Canada. Après un rappel de la dimension historique de la politique commune de la pêche en Europe, l’article offre une synthèse des principaux concepts tirés de l’économie néo-institutionnaliste et des travaux sur les systèmes socio-écologiques. Une approche comparée en Europe, au Canada et aux États-Unis offre une diversité du caractère opérationnel des régimes de gestion des pêcheries. L’examen comparatif des trois grands systèmes de gestion des pêches est fondé sur des institutions guidées par la recherche d’un compromis entre critères écologiques et socio-économiques. La situation européenne se situe entre le mode décentralisé aux États-Unis et le régime canadien, le plus enraciné historiquement dans une conduite centralisée. En effet, la gestion des pêcheries, en Europe et en Amérique du Nord, est désormais intégrée à une approche écosystémique.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0030.006
Scholarly communication0.0070.005
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.084
GPT teacher head0.348
Teacher spread0.264 · 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 designTheoretical or conceptual
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

Citations2
Published2019
Admission routes2
Has abstractyes

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