Leveraging Man−Woman Romantic Relationships to Promote Men’s Awareness of Sexism and Gender Discrimination
Bibliographic record
Abstract
Despite decades of research and growing public awareness, sexism and gender discrimination remain pervasive, partly due to men’s lower awareness of sexism. Here, we explored whether man−woman romantic relationships can be leveraged to promote men’s awareness of sexism. In Study 1 ( N = 576), men who read about gender discrimination targeting their ostensible partner (versus a friend or stranger) were more likely to perspective-take and appraise the situation as sexist, and in turn, reported greater broader awareness of gender discrimination toward women and less sexist attitudes. In Study 2 ( N = 570), 76% of men reported that their partner had disclosed an experience of sexism. Greater perspective-taking was associated with recognizing these experiences as sexist and greater awareness of sexism and allyship behaviors ( n = 432). The findings suggest that man−woman romantic relationships offer a unique context to promote men’s awareness of sexism and gender discrimination, revealing both novel insights and challenges for reducing sexism.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".