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Record W2094141372 · doi:10.1177/8755123314548043

The Challenges of Imitation for Children with Autism Spectrum Disorders with Implications for General Music Education

2014· article· en· W2094141372 on OpenAlexaff
Sheila Scott

Bibliographic record

VenueUpdate Applications of Research in Music Education · 2014
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsBrandon University
Fundersnot available
KeywordsImitationAutismPsychologyVariety (cybernetics)Rote learningPsychological interventionMusicalDevelopmental psychologyTeaching methodMathematics educationComputer scienceCooperative learningSocial psychologyVisual arts

Abstract

fetched live from OpenAlex

With emphasis on inclusive education, many music teachers interact with children on the autism spectrum within regular classroom settings. Many of these teachers rely on rote learning to teach a variety of musical skills. This creates difficulties for children on the autism spectrum who respond differently to imitation than their typically developing peers. By understanding this phenomenon, music teachers are better prepared to interact with children on the autism spectrum. To this end, learning through imitation as a foundational strategy for teachers in primary music education is summarized here. This is followed by a review of research findings to build a profile for how children on the autism spectrum respond to imitation. Implications for music teaching explains how strategies currently used by music teachers support interventions suggested in psychological literature and how these strategies may be adapted to better meet the needs of students on the autism spectrum.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.370
Teacher spread0.318 · 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 designTheoretical or conceptual
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

Citations13
Published2014
Admission routes1
Has abstractyes

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