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Record W2114976110 · doi:10.1111/infa.12114

Singing Delays the Onset of Infant Distress

2015· article· en· W2114976110 on OpenAlexafffund
Mariève Corbeil, Sandra E. Trehub, Isabelle Peretz

Bibliographic record

VenueInfancy · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of TorontoUniversité de MontréalInternational Laboratory for Brain, Music and Sound Research
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsSingingPsychologyActive listeningDistressAudiologyEntrainment (biomusicology)Developmental psychologyCommunicationRhythmMedicineClinical psychologyAcoustics

Abstract

fetched live from OpenAlex

Much is known about the efficacy of infant‐directed (ID) speech and singing for capturing attention, but little is known about their role in regulating affect. In Experiment 1, infants 7–10 months of age listened to scripted recordings of ID speech, adult‐directed speech, or singing in an unfamiliar language (Turkish) until they met a criterion of distress based on negative facial expression. They listened to singing for roughly twice as long as speech before meeting the distress criterion. In Experiment 2, they were exposed to natural recordings of ID speech or singing in a familiar language. As in Experiment 1, ID singing was considerably more effective than speech for delaying the onset of distress. We suggest that the temporal patterning of ID singing, with its regular beat, metrical organization, and tempo, plays an important role in inhibiting distress, perhaps by promoting entrainment and predictive listening.

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 score0.006

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.059
GPT teacher head0.309
Teacher spread0.250 · 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

Citations134
Published2015
Admission routes2
Has abstractyes

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