Pathogen disgust predicts women’s preferences for masculinity in men’s voices, faces, and bodies
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
Recent studies suggest that pathogen-related factors may contribute to systematic variation in women’s preferences for masculinity in men’s faces. However, there is very little evidence for similar correlations between pathogen-related factors and women’s preferences for masculinity in other domains (e.g., men’s voices or bodies). Consequently, we conducted a series of studies to examine whether pathogen disgust (assessed using Tybur et al’s Three Domains of Disgust Scale) predicts individual differences in women’s preferences for masculine characteristics in men’s voices, bodies, and faces. We also tested if pathogen disgust predicts individual differences in measures of women’s actual mate choices in the same way. We observed positive correlations between women’s pathogen disgust and their preferences for masculinity in men’s voices (Study 1) and faces and bodies (Study 2). We also observed positive correlations between women’s pathogen disgust and their masculinity ratings of both their current and ideal romantic partners (Study 3). Each of these correlations was independent of the possible effects of women’s sexual and moral disgust. Together, these findings suggest that individual differences in pathogen disgust predict individual differences in women’s masculinity preferences across multiple domains and may also predict individual differences in their actual mate choices.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 it