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Record W4285369747 · doi:10.1386/ijmec_00031_1

Neurologic music therapy: Supporting school-readiness skills in children with hearing loss

2021· article· en· W4285369747 on OpenAlex
G Dubois, Michael H. Thaut, Corene Hurt-Thaut, Joanne DeLuzio, Stephanie Nixon

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Music in Early Childhood · 2021
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsActive listeningPsychologyHearing lossCurriculumSpoken languageLiteracyLanguage developmentAudiologyDevelopmental psychologyPedagogyComputer scienceMedicineCommunication

Abstract

fetched live from OpenAlex

Children with hearing loss (HL) who use listening and spoken language as their methods of communication are now being integrated into classrooms with typically hearing peers upon school entry due to the development of sophisticated hearing technology. However, areas in overall development may lag as the delay in accessibility to speech and language makes it difficult to reach age-appropriate levels in time for kindergarten. Supporting development in these areas of the challenge requires explicit teaching of, and experience with, listening, language, social and executive function, literacy and balance. Participating in a group music and movement class with a focus on areas of challenge for children with HL using neurologic music therapy techniques allows for goal-directed therapy and practice, along with the opportunity to interact with peers in a supportive environment. An overview of the specific techniques for each area of interest and how they can be used is discussed along with a sample curriculum.

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.

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 score0.031
Threshold uncertainty score0.814

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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