Intrasexual Competition in Women’s Likelihood of Self-Enhancement and Perceptions of Breast Morphology: A Hispanic Sample
Bibliographic record
Abstract
Women’s breasts are considered sexually attractive because they may infer a woman’s residual reproductive value. Given that men find women’s breasts attractive, women may compete with other women to enhance their physical attractiveness when primed with an intrasexual competitive cue. The current study investigated women’s intrasexual competition when viewing variations in breast morphology. Women (N = 189) were randomly assigned to a partner threat condition and shown images of women’s breasts that included variations in breast size, ptosis (i.e., sagginess), and intermammary distance (i.e., cleavage). Women were more likely to report an increase in enhancing their appearance, wearing revealing clothing, dieting and exercising, and perceiving the breasts as a sexual threat as a function of larger breast sizes with low ptosis and intermediate distances. The partner threat prime did not play a role in ratings. Interestingly, there was a moderating role for women’s dispositional levels in intrasexual competition. Women with higher levels of intrasexual competition were more likely to enhance their appearance when viewing large breast sizes. The study points to the role that breast morphology indicative of residual reproductive value has on increasing enhancement strategies.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".