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Multimodal Music in Infancy and Early Childhood

2018· reference-entry· en· W2893804688 on OpenAlexaff
Sandra E. Trehub

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMelodySingingPsychologyRhythmGesturePleasureMusicalCognitive psychologyEarly childhoodMovement (music)CommunicationSound productionDevelopmental psychologyVisual artsArtAestheticsLinguisticsAcousticsNeuroscience

Abstract

fetched live from OpenAlex

Music in the early years is best understood as creative play with sound and body. Infants are highly responsive observers of mothers’ multimodal singing, which consists of expressive vocalizations in conjunction with facial and bodily gestures. Infants derive pleasure and solace from music, and they exhibit sensitivity to its pitch and temporal patterning. As toddlers, they engage in rudimentary singing and dancing, which ultimately become tools for emotional self-regulation. Preschoolers exhibit increasing sensitivity to culture-specific aspects of music. They sing as they play, producing conventional as well as invented songs and aligning their vocal patterns with their movements. By the early school years, children exhibit considerable understanding of musical forms and functions. Their melodic and rhythmic skills are more readily evident on the playground than in the classroom. Although music and movement are linked for adults, they are inseparable for infants and young children.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.239
Threshold uncertainty score0.997

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0330.001

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 head0.045
GPT teacher head0.240
Teacher spread0.195 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations12
Published2018
Admission routes1
Has abstractyes

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