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Record W4255696326 · doi:10.31234/osf.io/q9zwa

Rhythm and melody as social signals for infants

2020· preprint· en· W4255696326 on OpenAlexaff
Laura K. Cirelli, Sandra E. Trehub, Laurel J. Trainor

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsBaycrest HospitalMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMelodyProsocial behaviorPsychologyRhythmSingingInterpersonal communicationPerceptionCognitionSocial cognitionCognitive psychologySocial relationDevelopmental psychologySocial psychologyMusicalNeuroscience

Abstract

fetched live from OpenAlex

Infants typically experience music through social interactions with others. One such experience involves caregivers singing to infants while holding and bouncing them rhythmically. These highly social interactions shape infant music perception and may also influence social cognition and behavior. Moving in time with others-interpersonal synchrony-can direct infants' social preferences and prosocial behavior. Infants also show social preferences and selective prosociality toward singers of familiar, socially learned melodies. Here, we discuss recent studies of the influence of musical engagement on infant social cognition and behavior, highlighting the importance of rhythmic movement and socially relevant melodies.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.052
GPT teacher head0.356
Teacher spread0.305 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

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