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Record W1992692854 · doi:10.1177/0010414005279320

Explaining The Gender Gap in Support for the New Right

2005· article· en· W1992692854 on OpenAlexaffabout
Elisabeth Gidengil, Matthew Hennigar, André Blais, Neil Nevitte

Bibliographic record

VenueComparative Political Studies · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPopulism, Right-Wing Movements
Canadian institutionsUniversity of TorontoUniversité de MontréalBrock UniversityMcGill University
Fundersnot available
KeywordsSalience (neuroscience)Gender gapSituational ethicsPoliticsVariety (cybernetics)Political scienceState (computer science)Social psychologyOrder (exchange)Positive economicsSociologyDemographic economicsPsychologyEconomicsLaw

Abstract

fetched live from OpenAlex

This article uses data from the 2000 Canadian Election Studyto examine a variety of possible explanations for the gender gap in support for the newright. The authors find structural and situational explanations to be of little help in accounting for the gap. What matters are values and beliefs. The gender gap in support for Canada's new right party reflects differences in views about the appropriate role of the state, lawand order, and traditional moral values. It also appears to reflect differences in the salience of politics in men's andwomen's lives. When all of these attitudinal factors are taken into account, the gender gap ceases to be significant. The implications of the findings are considered in light of comparative analyses of gender gaps in vote choice and support for radical right-wing populist political parties in Western Europe.

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)0.005
metaresearch head score (Gemma)0.014
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 score0.429
Threshold uncertainty score0.853

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.362
GPT teacher head0.487
Teacher spread0.125 · 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

Citations108
Published2005
Admission routes2
Has abstractyes

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