MétaCan
Menu
Back to cohort
Record W2141895619 · doi:10.1017/s1743923x11000079

Gender Affinity Effects in Vote Choice in Westminster Systems: Assessing “Flexible” Voters in Canada

2011· article· en· W2141895619 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePolitics & Gender · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversity of CalgaryQueen's University
Fundersnot available
KeywordsRepresentation (politics)VotingIncentivePoliticsConsciousnessPolitical scienceProportional representationStyle (visual arts)Social psychologyGeneral electionPsychologyEconomicsLawMicroeconomicsDemocracyGeography

Abstract

fetched live from OpenAlex

Under certain conditions, women are more likely than men to vote for women candidates, a phenomenon referred to as a “gender affinity effect.” Causal mechanisms connecting women voters to women candidates are gender consciousness, desire for descriptive representation, support for liberal social policy, the use of gender as a shortcut to vote choice among low-information voters, and a “party-sex overlap.” Existing work is focused on American elections, which tend to be candidate centered, so little is known about gender affinity effects between voters and candidates in other contexts. This article focuses on Westminster-style parliamentary systems, using the Canadian federal elections of 2000 and 2004 as test cases. Women in these systems have the same motivations to gravitate toward women candidates, for they are gender conscious and desire descriptive representation. But they do not have the same incentives to cast ballots for women because political institutions and practices tend to discourage candidate-based voting. The article pays particular attention to a segment of the electorate we call “flexible” voters, which is comprised of independents, leaners, and defectors. In Westminster systems, it is this group of voters who should be most sensitive to candidate-based considerations.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.064
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.107
GPT teacher head0.338
Teacher spread0.231 · 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