Gayzing Women’s Bodies: Criticisms of Labia Depend on the Gender and Sexual Orientation of Perceivers
Bibliographic record
Abstract
The heterosexual male gaze is often credited with producing bodily anxieties among women, yet empirical and popular cultural evidence suggest gay men have especially negative views toward women’s bodies, particularly women’s genitalia. Across two studies (N = 6,129; Mage = 27.58; 2,047 women, 4,082 men) we conducted secondary analyses of existing datasets to test the hypotheses that gay men would evaluate labia more negatively than heterosexual men, and that lesbian women would evaluate labia more positively than heterosexual women. We conducted fixed-effects mini meta-analyses to estimate summary effect sizes for perceptions of normalcy and fit with societal ideals; we additionally assessed an outcome of disgust in Study 2. We found support for our hypotheses: For normalcy and societal ideal, we found small summary effects such that gay men evaluated labia more negatively than heterosexual men, and medium summary effects such that lesbian women evaluated labia more positively than heterosexual women. Gay men also rated labia as more disgusting than any other demographic group, and lesbian women rated the stimuli as less disgusting than heterosexual women, supporting our hypotheses. The current findings suggest a pressing need to acknowledge and incorporate gay men’s perceptions of women’s bodies into literatures on misogyny, objectification, and body image more generally.
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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 | 0.044 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".