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Record W2332921202 · doi:10.1017/s0008423914001152

Analyse écologique des déterminants de la participation électorale municipale au Québec

2014· article· fr· W2332921202 on OpenAlexaffabout
Jérôme Couture, Sandra Breux, Laurence Bhérer

Bibliographic record

VenueCanadian Journal of Political Science · 2014
Typearticle
Languagefr
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversité de MontréalUniversité Laval
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Résumé Au Canada, la participation électorale à l’échelle municipale est plus faible qu'aux autres échelles de gouvernement et les raisons susceptibles d'expliquer ce moindre engagement sont encore mal connues. À partir des taux de participation à la mairie aux élections de 2005 et de 2009 dans l'ensemble des municipalités du Québec (n = 949), la recherche teste 15 hypothèses explicatives de la participation électorale municipale. Les résultats montrent que quatre facteurs expliquent en grande partie la participation électorale municipale et ses variations. Il s'agit de la taille de l’électorat, de la présence d'un électorat âgé, de la marge victorieuse et du nombre de candidats en lice. Ces résultats permettent de mieux cerner le coût du vote à l’échelle municipale, tout en soulignant la nécessité de réaliser davantage d'enquêtes monographiques sur cet objet au Canada, notamment dans les plus grandes municipalités où la participation électorale y est plus faible.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.047
GPT teacher head0.384
Teacher spread0.338 · 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 designObservational
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

Citations15
Published2014
Admission routes2
Has abstractyes

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