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Record W2112650152 · doi:10.7202/1017153ar

La gouvernance multiniveau et la nouvelle gestion publique : des idées nouvelles à intégrer aux approches traditionnelles du fédéralisme dans le contexte de l’étude des relations intergouvernementales

2013· article· fr· W2112650152 on OpenAlexaffvenueabout
Lisa Turkewitsch, Michael Stein

Bibliographic record

VenueTélescope Revue d’analyse comparée en administration publique · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Le concept de gouvernance multiniveau peut aider àreconnaître et à comprendre de nouvelles tendances dansles relations intergouvernementales et l’élaboration depolitiques. Dans cet article, nous nous penchons sur les liens quiexistent entre la littérature sur l’administrationpublique, particulièrement celle portant sur la nouvelle gestionpublique, et la gouvernance multiniveau. Ces deux approches sontsusceptibles d’améliorer les approches traditionnellesutilisées pour comprendre le fonctionnement interne desrelations intergouvernementales dans les régimesfédéraux. Nous fournissons des exemples tirés detrois fédérations : l’Australie, le Canada etles États-Unis. Nous nous concentrons sur la façon dontla gouvernance multiniveau peut mettre en lumière leschangements dans les relations intergouvernementales (entre leséchelons supranational, fédéral,étatique/provincial et municipal) ainsi quel’élargissement horizontal de la gouvernance dans cesmêmes régimes à des organisations nongouvernementales et à d’autres acteurs.

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)0.006
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 score0.161
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0080.026
Scholarly communication0.0100.007
Open science0.0020.004
Research integrity0.0030.004
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 head0.026
GPT teacher head0.292
Teacher spread0.266 · 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

Citations0
Published2013
Admission routes3
Has abstractyes

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