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Record W4206804395 · doi:10.1038/s41598-021-04311-7

Trilled /r/ is associated with roughness, linking sound and touch across spoken languages

2022· article· en· W4206804395 on OpenAlexaff
Bodo Winter, Márton Sóskuthy, Marcus Perlman, Mark Dingemanse

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversity of British Columbia
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekChildren's Liver Disease FoundationUK Research and InnovationUniversity of Pennsylvania
KeywordsSound (geography)Computer scienceAcousticsSpeech recognitionPhysics

Abstract

fetched live from OpenAlex

Cross-modal integration between sound and texture is important to perception and action. Here we show this has repercussions for the structure of spoken languages. We present a new statistical universal linking speech with the evolutionarily ancient sense of touch. Words that express roughness-the primary perceptual dimension of texture-are highly likely to feature a trilled /r/, the most commonly occurring rhotic consonant. In four studies, we show the pattern to be extremely robust, being the first widespread pattern of iconicity documented not just across a large, diverse sample of the world's spoken languages, but also across numerous sensory words within languages. Our deep analysis of Indo-European languages and Proto-Indo-European roots indicates remarkable historical stability of the pattern, which appears to date back at least 6000 years.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.038
GPT teacher head0.353
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations64
Published2022
Admission routes1
Has abstractyes

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