Masculinity, femininity, and support for climate policy
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.
Bibliographic record
Abstract
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it