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Record W2164058512 · doi:10.1177/0305735607068885

Exposure to music and cognitive performance: tests of children and adults

2006· article· en· W2164058512 on OpenAlexaffabout
E. Glenn Schellenberg, Takayuki Nakata, Patrick G. Hunter, Sachiko Tamoto

Bibliographic record

VenuePsychology of Music · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMOZARTPsychologyCognitionSingingActive listeningDevelopmental psychologyMoodArousalEffects of sleep deprivation on cognitive performanceAudiologyCognitive psychologyCommunicationSocial psychologyArt

Abstract

fetched live from OpenAlex

This article reports on two experiments of exposure to music and cognitive performance. In Experiment 1, Canadian undergraduates performed better on an IQ subtest (Symbol Search) after listening to an up-tempo piece of music composed by Mozart in comparison to a slow piece by Albinoni. The effect was evident, however, only when the two pieces also induced reliable differences in arousal and mood. In Experiment 2, Japanese 5-year-olds drew for longer periods of time after singing or hearing familiar children's songs than after hearing Mozart or Albinoni, and their drawings were judged by adults to be more creative, energetic, and technically proficient. These results indicate that (1) exposure to different types of music can enhance performance on a variety of cognitive tests, (2) these effects are mediated by changes in emotional state, and (3) the effects generalize across cultures and age groups.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.288
Teacher spread0.263 · 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

Citations317
Published2006
Admission routes2
Has abstractyes

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