Country‐level and individual‐level predictors of men's support for gender equality in 42 countries
Bibliographic record
Abstract
Abstract Men sometimes withdraw support for gender equality movements when their higher gender status is threatened. Here, we expand the focus of this phenomenon by examining it cross‐culturally, to test if both individual‐ and country‐level variables predict men's collective action intentions to support gender equality. We tested a model in which men's zero‐sum beliefs about gender predict reduced collective action intentions via an increase in hostile sexism. Because country‐level gender equality may threaten men's higher gender status, we also examined whether the path from zero‐sum beliefs to collective action intentions was stronger in countries higher in gender equality. Multilevel modeling on 6,734 men from 42 countries supported the individual‐level mediation model, but found no evidence of moderation by country‐level gender equality. Both country‐level gender equality and individual‐level zero‐sum thinking independently predicted reductions in men's willingness to act collectively for gender equality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".