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Reconfiguration de l’État et renouvellement de l’action publique agricole : l’évolution des politiques agroenvironnementales au Québec et en France

2015· dissertation· W7147216397 on OpenAlexaboutno aff
Maude Benoit

Bibliographic record

Venuenot available
Typedissertation
Language
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Public policyPublic managementSugar industry

Abstract

fetched live from OpenAlex

L’avènement des enjeux environnementaux en agriculture est une tendance observable depuis les années 1990 dans l’ensemble des pays industrialisés, qui les intègrent pourtant de manière très différente à leurs politiques agricoles respectives. Cette thèse s’applique à expliquer l’institutionnalisation et l’évolution nationales différenciées de ces enjeux par le biais d’une analyse comparée entre le Québec et la France. Le cadre d’analyse proposé prend en compte à la fois les structures et les acteurs de la construction et du développement de la politique dite agroenvironnementale en étudiant spécifiquement deux variables explicatives : la configuration des politiques agricoles et le rôle des administrations publiques. L’enquête qualitative se déroule sur un temps long (1990-2013) et combine trois techniques de collecte de données : l’analyse documentaire, l’analyse de discours et l’entretien semi-dirigé. Au terme de cette thèse, force est de constater que les organisations fondatrices des politiques agricoles nationales (administration et profession agricoles) jouent un rôle de filtre des dynamiques réformatrices présentes à l’échelle globale et qu’elles « acclimatent » les référentiels de développement durable et du management public aux spécificités de leur pays et de leur secteur d’action publique.

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)0.003
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.438

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.003
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.045
GPT teacher head0.369
Teacher spread0.325 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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