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Record W4411353055 · doi:10.1080/23251042.2025.2517426

Masculinity, femininity, and support for climate policy

2025· article· en· W4411353055 on OpenAlexafffund
Tony Silva, Carly Hamdon, Emily Huddart Kennedy

Bibliographic record

VenueEnvironmental Sociology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFemininityMasculinityClimate changeEcofeminismSociologyGender studiesPolitical scienceEnvironmental ethicsGeology

Abstract

fetched live from OpenAlex

Prior work has examined relationships among gender, political ideology, and climate attitudes. Yet little quantitative research in this area has examined measures of gender beyond identification as a woman or man. Using a probability sample of Canadians (n = 2,503), we analyze the associations between support for climate policy and self-rated masculinity, self-rated femininity, and gender polarization, measured as the absolute difference between masculinity and femininity. We do so among six subsets characterized by gender identity (woman, man) and political ideology (left, center, and right). Masculinity and femininity were not associated with climate attitudes in any subset, and gender polarization was associated with climate attitudes only among right-wing men. The results indicate that scholars should operationalize masculinity and femininity in relation to one another, since this relational measure may be independently associated with important outcomes. Additionally, taken-for-granted assumptions about the relationship between masculinity and environmental attitudes need to be reconsidered.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.211
GPT teacher head0.454
Teacher spread0.243 · 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 designNot applicable
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

Citations5
Published2025
Admission routes2
Has abstractyes

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