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Record W2325514100 · doi:10.1525/mp.2011.29.2.165

Effect of Music Training on Promoting Preliteracy Skills: Preliminary Causal Evidence

2011· article· en· W2325514100 on OpenAlexaff
Sylvain Moreno, Deanna C. Friesen, Ellen Bialystok

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsYork UniversityBaycrest Hospital
Fundersnot available
KeywordsPsychologyPhonological awarenessReading (process)Training (meteorology)Music educationCognitive psychologyPedagogyLinguisticsLiteracy

Abstract

fetched live from OpenAlex

the present study investigated whether music training fosters children's preliteracy skills. Sixty children were randomly assigned to participate in a 20-day training program in either music or visual art. Before and after training, children's phonological awareness and their ability to map visual symbols onto words (i.e., visual-auditory learning) were assessed. Equivalent improvement after training was observed for both groups on the phonological awareness measure, but the children with music training improved significantly more than the art-trained children on the visual-auditory learning measure. Music training appears to benefit certain skills necessary for reading.

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)0.002
metaresearch head score (Gemma)0.012
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.103
GPT teacher head0.364
Teacher spread0.261 · 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

Citations97
Published2011
Admission routes1
Has abstractyes

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