Preferences for Very Low and Very High Voice Pitch in Humans
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
Manipulations of voice pitch have been shown to alter attractiveness ratings, but whether preferences extend to very low or very high voice pitch is unknown. Here, we manipulated voice pitch in averaged men's and women's voices by 2 Hz intervals to create a range of male and female voices speaking monopthong vowel sounds and spanning a range of frequencies from normal to very low and very high pitch. With these voices, we used the method of constant stimuli to measure preferences for voice. Nineteen university students (ages: 20-25) participated in three experiments. On average, men preferred high-pitched women's voices to low-pitched women's voices across all frequencies tested. On average, women preferred men's voices lowered in pitch, but did not prefer very low men's voices. The results of this study may reflect selection pressures for men's and women's voices, and shed light on a perceptual link between voice pitch and vocal attractiveness.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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