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Record W3181448949 · doi:10.22215/etd/2016-11573

Influence of Intensive Ensemble Music Training on Children from a Lower Socioeconomic Status: An ERP Study

2016· dissertation· en· W3181448949 on OpenAlexaff
Nina Hedayati

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologySocioeconomic statusAudiologyPsychological interventionEvent-related potentialPerceptionAuditory stimuliStimulus (psychology)Developmental psychologyAuditory perceptionCognitionCognitive psychologyMedicineNeurosciencePopulation

Abstract

fetched live from OpenAlex

Low socioeconomic status (SES) children may experience positive outcomes through interventions.OrKidstra, an intervention program, provides musical training to low SES children in an intensive, ensemble, and social setting.This study examined the effect of OrKidstra training on children through an auditory Go/No-Go task with tone-locked (1100 and 2000Hz) Event-Related Potentials (ERPs).OrKidstra children demonstrated higher auditory discrimination than the comparison group for tones at 500, 1000, and 2000Hz during a hearing test, but accuracy and reaction times did not differ for the Go/No-Go task.ERP analyses revealed that OrKidstra children showed a greater spread of neural activity for auditory perception (pre-P300), they had earlier but smaller P300 peaks (associated with stimulus evaluation), and the late potentials (associated with inhibitory control) were more widely distributed.This study suggests that OrKidstra children tend to experience faster and more efficient neural processing to auditory stimuli, and emphasizes the importance of such interventions.

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)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.041
GPT teacher head0.306
Teacher spread0.265 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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