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Record W4408738103 · doi:10.1002/icd.70004

Five‐Year‐Old Children Identify Emotions in Music Along Valence and Intensity Dimensions

2025· article· en· W4408738103 on OpenAlexafffundabout
Haley E. Kragness, Arooba Mansoor, Areeba Qureshi, Rachel Peiris, Laura K. Cirelli

Bibliographic record

VenueInfant and Child Development · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyValence (chemistry)Developmental psychologyIntensity (physics)Cognitive psychologyOpticsChemistryPhysics

Abstract

fetched live from OpenAlex

ABSTRACT Music is a highly effective medium for communicating emotions among enculturated adults. In Western music, emotion perception is influenced by intensity cues (e.g., tempo and loudness ) and valence cues (e.g., major vs. minor mode ). Here, 5‐year‐old Canadian children ( N = 57, 26 boys, 31 girls, M age = ~5.5 years) and adults ( N = 59, 45 women, 9 men, 5 non‐binary/did not report, M age = ~18.5 years) rated music on valence or intensity. Children's ratings were positively correlated with adults' for both valence ( r = 0.914) and intensity ( r = 0.800) and both groups used similar features to make judgements. Results demonstrate that children perceive valence and intensity in music and point to the importance of testing children's emotion perception across the full valence–intensity dimensional space.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.518

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)0.0000.000

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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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.

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

Citations1
Published2025
Admission routes3
Has abstractyes

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