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Record W2951221045 · doi:10.1386/ijmec.14.1.9_1

Nurturing infants with music

2019· article· en· W2951221045 on OpenAlex
Sandra E. Trehub

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Music in Early Childhood · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSingingPsychologyGestureMelodyDevelopmental psychologyNature versus nurtureArousalAffectionMoodMusicalSocial psychology

Abstract

fetched live from OpenAlex

Primary caregivers throughout the world provide infants with life-sustaining care such as nutrition and protection from harm as well as life-enhancing care such as affection, contingent responsiveness and mentoring of various kinds. They nurture infants musically by means of one-on-one (i.e. infant-directed) singing accompanied by movement in some cultures and by visual gestures in others. Such singing, which is acoustically and visually distinct from solitary (i.e. self-directed) singing, is effective in engaging infants and regulating their mood and arousal. The repetition and stereotypy of caregivers’ performances contribute to their memorability and dyadic significance. Caregivers’ singing also influences infants’ social engagement more generally. Once infants become singers, their songs play an important role in social interaction and emotional self-regulation. Although caregivers sing to infants with playful or soothing intentions, their performances highlight the temporal and melodic structure of the music. In sum, caregivers lay the foundation for a lifelong musical journey.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.922
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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