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Record W2164987490 · doi:10.1017/s0008423908081134

Gender and Elections: An Examination of the 2006 Canadian Federal Election

2008· article· en· W2164987490 on OpenAlexaffabout
Marie Rekkas

Bibliographic record

VenueCanadian Journal of Political Science · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPolitical scienceHumanitiesWelfare economicsFlexibility (engineering)Demographic economicsEconomicsArtManagement

Abstract

fetched live from OpenAlex

Abstract. The existing literature on gender effects in the electoral process offers little evidence of significant gender vote share differentials. In this paper it is shown that for the 2006 Canadian federal election, once candidate campaign spending is introduced into the model with appropriate flexibility in the vote share responsiveness across genders, significant differences are found to exist between male and female candidates. The findings suggest that, for equal levels of spending, male incumbents have a vote share advantage relative to female incumbents, though this vote share advantage is found to diminish with increased expenditures. Female non-incumbent candidates, on the other hand, have a vote share advantage over male non-incumbent candidates for higher levels of expenditure and this advantage was found to increase with increased expenditures. Résumé. Les écrits traitant des effets du genre dans le processus électoral offrent peu de preuves d'un écart significatif dans le pourcentage des voix selon le genre. Cet article montrera que, dans le contexte des élections fédérales canadiennes de 2006, une fois que les dépenses de campagne des candidats sont introduites dans le modèle avec la flexibilité adéquate sur la réceptivité du pourcentage des voix selon les genres, on découvre que des différences significatives existent entre les candidats masculins et féminins. Le résultat des recherches montre que pour des dépenses équivalentes, les titulaires masculins ont un avantage sur le pourcentage des voix par rapport aux titulaires de sexe féminin bien qu'il s'avère que cet avantage diminue lorsque les dépenses augmentent. D'autre part, les candidates féminines non-titulaires ont un avantage sur le pourcentage des voix par rapport aux candidats masculins non-titulaires quand les dépenses sont plus élevées et cet avantage s'avère augmenter lorsque les dépenses augmentent.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.274
Teacher spread0.246 · 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 teacher head, not a consensus.

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

Citations4
Published2008
Admission routes2
Has abstractyes

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