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Record W2951993015 · doi:10.1002/ajhb.23178

No clear evidence for correlations between handgrip strength and sexually dimorphic acoustic properties of voices

2018· article· en· W2951993015 on OpenAlexaff
Chengyang Han, Hongyi Wang, Vanessa Fasolt, Amanda Hahn, Iris J. Holzleitner, Junpeng Lao, Lisa M. DeBruine, David R. Feinberg, Benedict C. Jones

Bibliographic record

VenueAmerican Journal of Human Biology · 2018
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsMcMaster University
FundersH2020 European Research Council
KeywordsFormantVocal tractSexual dimorphismPsychologyPhysical strengthAudiologyAcousticsBiologyMedicinePhysical medicine and rehabilitationSpeech recognitionZoologyComputer sciencePhysics

Abstract

fetched live from OpenAlex

OBJECTIVES: Recent research on the signal value of masculine physical characteristics in men has focused on the possibility that such characteristics are valid cues of physical strength. However, evidence that sexually dimorphic vocal characteristics are correlated with physical strength is equivocal. Consequently, we undertook a further test for possible relationships between physical strength and masculine vocal characteristics. METHODS: We tested the putative relationships between White UK (N = 115) and Chinese (N = 106) participants' handgrip strength (a widely used proxy for general upper-body strength) and five sexually dimorphic acoustic properties of voices: fundamental frequency (F0), fundamental frequency's SD (F0-SD), formant dispersion (Df), formant position (Pf), and estimated vocal-tract length (VTL). RESULTS: Analyses revealed no clear evidence that stronger individuals had more masculine voices. CONCLUSIONS: Our results do not support the hypothesis that masculine vocal characteristics are a valid cue of physical strength.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.351
Teacher spread0.281 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations16
Published2018
Admission routes1
Has abstractyes

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