Voice Pitch Influences Perceptions of Sexual Infidelity
Bibliographic record
Abstract
Sexual infidelity can be costly to members of both the extra-pair and the paired couple. Thus, detecting infidelity risk is potentially adaptive if it aids in avoiding cuckoldry or loss of parental and relationship investment. Among men, testosterone is inversely related to voice pitch, relationship and offspring investment, and is positively related to the pursuit of short-term relationships, including extra-pair sex. Among women, estrogen is positively related to voice pitch, attractiveness, and the likelihood of extra-pair involvement. Although prior work has demonstrated a positive relationship between men's testosterone levels and infidelity, this study is the first to investigate attributions of infidelity as a function of sexual dimorphism in male and female voices. We found that men attributed high infidelity risk to feminized women's voices, but not significantly more often than did women. Women attributed high infidelity risk to masculinized men's voices at significantly higher rates than did men. These data suggest that voice pitch is used as an indicator of sexual strategy in addition to underlying mate value. The aforementioned attributions may be adaptive if they prevent cuckoldry and/or loss of parental and relationship investment via avoidance of partners who may be more likely to be unfaithful.
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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 | 0.001 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".