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Record W4318485445 · doi:10.3390/sexes4010008

Intrasexual Competition in Women’s Likelihood of Self-Enhancement and Perceptions of Breast Morphology: A Hispanic Sample

2023· article· en· W4318485445 on OpenAlexaff
Ray Garza, Farid Pazhoohi

Bibliographic record

VenueSexes · 2023
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSexual selectionPsychologyAttractivenessMate choiceDemographyDevelopmental psychologySocial psychologyMatingBiologyEcology

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.015
GPT teacher head0.301
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2023
Admission routes1
Has abstractyes

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