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Musical Lives of Infants

2012· reference-entry· en· W247794542 on OpenAlexaff
Mayumi Adachi, Sandra E. Trehub

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMusicalNatural (archaeology)Psychological interventionPsychologyIntervention (counseling)Music educationSpeculationDevelopmental psychologyHistoryVisual artsPedagogyArt

Abstract

fetched live from OpenAlex

In recent years there has been increasing interest in and speculation about infants' natural propensity for music, their ease of learning, and their musical environment. This interest has fueled a new frontier of music education or intervention aimed at infants, parents, and, in some cases, expectant parents. This article summarizes the available information on responsiveness to music and on music learning both before and after birth. It also considers the limited data on emerging music production skills and early musical environments provided by contemporary urban parents. In addition, the article provides a glimpse of interventions designed to alter the natural musical landscape. Current evidence is consistent with the view that infants are naturally receptive to music and are capable of learning from incidental as well as intentional exposure to music. What remains unresolved is the utility or merit of prenatal and early postnatal musical interventions aimed at enriching the lives of infants and their parents.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.099
GPT teacher head0.269
Teacher spread0.170 · 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 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

Citations54
Published2012
Admission routes1
Has abstractyes

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