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Record W2165356024 · doi:10.1017/s000842390606015x

Electoral Participation in Municipal, Provincial and Federal Elections in Canada

2006· article· en· W2165356024 on OpenAlexaffabout
M. Reza Nakhaie

Bibliographic record

VenueCanadian Journal of Political Science · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTurnoutSocial capitalMicrodata (statistics)VotingPolitical scienceDemographicsGovernment (linguistics)Demographic economicsPoliticsPolitical capitalSociologyEconomicsDemographyCensusPopulation

Abstract

fetched live from OpenAlex

Abstract.The purpose of this paper is to highlight the importance of social relations or social capital for voting turnout at three levels of Canadian government, paying particular attention to social contexts, socio-demographics and socio-economic forces. The data source is the Public Use Microdata File from theNational Survey of Giving, Volunteering and Participation, administered by Statistics Canada (2001). Results provide support for social capital theory. Those who donate to charities and/or volunteer have a stronger propensity to vote than their counterparts. Two other measures of social capital, social networks and participation in religious activities, are also related to turnout. However, their effects are comparatively modest. Among the social bases of social capital, community rootedness is an important predictor of turnout. Civic engagement or attentiveness to current affairs also significantly increases voter turnout at all levels of Canadian government. Finally, standard socio-economic and demographic predictors of political participation do show independent effects on turnout. However, with the exception of age, these predictors are not as consistent or as strong as social capital measures in explaining turnout. Theoretical and policy implications of the findings are discussed. Résumé.L'objectif de cette étude est de souligner l'importance des relations sociales ou “ capital social ” en ce qui concerne la participation aux élections municipales, provinciales et fédérales au Canada, en prêtant une attention particulière aux contextes sociaux et aux forces socio-démographiques et socio-économiques. Nos données proviennent du fichier de microdonnées à grande diffusion del'Enquête nationale sur le don, le bénévolat et la participation, administré par Statistique Canada (2001). Les résultats vérifient la théorie du capital social. Les gens qui font des dons aux organismes de bienfaisance ou font du bénévolat ont une tendance plus marquée à voter que les autres. Deux autres mesures de capital social, l'appartenance à des réseaux sociaux et la participation à des activités religieuses, ont aussi une corrélation positive avec la participation électorale. Leur impact est cependant relativement limité. Parmi les composantes du capital social, l'enracinement dans la communauté est un indicateur important de participation. L'engagement dans la vie civique ou un intérêt marqué pour les affaires courantes augmentent aussi d'une façon significative la participation aux élections à tous les niveaux gouvernementaux. Finalement, il s'avère que les variables explicatives socio-économiques et démographiques standard de la participation politique ont des effets indépendants sur le vote. Toutefois, à l'exception de l'âge, ces variables ne sont ni aussi constantes ni aussi déterminantes que les mesures du capital social pour expliquer la participation. Nous discutons dans cet article les implications théoriques et politiques de nos conclusions.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.022
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.292
Teacher spread0.276 · 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

Citations30
Published2006
Admission routes2
Has abstractyes

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