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Record W2888781869 · doi:10.1101/403949

Does the strength of women’s attraction to male vocal masculinity track changes in steroid hormones?

2018· preprint· en· W2888781869 on OpenAlexaff
Benedict C. Jones, Amanda Hahn, Katarzyna Pisanski, Hongyi Wang, Michal Kandrik, Anthony J. Lee, Iris J. Holzleitner, David R. Feinberg, Lisa M. DeBruine

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMasculinityHormoneLuteinizing hormoneFormantSalivaPsychologyInternal medicineEndocrinologyMedicine

Abstract

fetched live from OpenAlex

Abstract Recent studies that either used luteinizing hormone tests to confirm the timing of ovulation or measured steroid hormones from saliva have found little evidence that women’s preferences for facial or body masculinity track within-subject changes in women’s fertility or hormonal status. Fewer studies using these methods have examined women’s preferences for vocal masculinity, however, and those that did report mixed results. Consequently, we used a longitudinal design and measured steroid hormones from saliva to test for evidence of hormonal regulation of women’s (N=351) preferences for two aspects of male vocal masculinity (low pitch and low formants). Analyses suggested that preferences for masculine pitch, but not masculine formants, may track within-woman changes in estradiol. Although these results present some evidence for the hypothesis that within-subject hormones regulate women’s attraction to masculine men, we do not discount the possibility that the effect of estradiol on pitch preferences in the current study is a false positive.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.283
Teacher spread0.256 · 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
Published2018
Admission routes1
Has abstractyes

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