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Record W4416926483 · doi:10.36939/cjur/vol34no/art439

Les maires des petites municipalités québécoises font-ils des politiques publiques ?

2025· article· W4416926483 on OpenAlexaffvenueabout
Yann Fournis, Nathalie Lewis

Bibliographic record

VenueCanadian journal of urban research · 2025
Typearticle
Language
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsContext (archaeology)Action (physics)Jurisprudence

Abstract

fetched live from OpenAlex

La réforme du modèle régional québécois en 2015 a bousculé les municipalités, qui jusque-là trouvaient à l’échelle régionale des ressources importantes pour leur développement. En 2017, une nouvelle loi reconnaît leur statut de gouvernement de proximité, ce qui leur permet d’acquérir une certaine reconnaissance administrative et politique. Mais ce modèle renouvelé change peu le sort des petites municipalités rurales, aux capacités politique et administrative limitées. Il offre cependant une occasion d’observer concrètement comme agissent ces acteurs aux moyens limités. En effet, à travers une méthodologie s’appuyant sur une revue de presse et des entretiens semi-directifs conduits au Bas-Saint-Laurent, cet article interroge la nature de l’action publique produite par ces « petites » municipalités de la périphérie québécoise : en examinant trois étapes du processus décisionnel municipal, il démontre que le maire est le porteur d’une action municipale fragile et limitative, soumise systématiquement à un jeu de double contrainte, juridique et communautaire. Ce municipalisme pragmatique pourrait être associé à un conservatisme propre aux communautés rurales ; mais il peut aussi être pensé comme une sorte de micro-politique du contrôle communautaire des institutions municipales en milieu rural.

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)0.011
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 score0.097
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0050.003
Scholarly communication0.0090.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.208
GPT teacher head0.453
Teacher spread0.245 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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