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Record W4210792287 · doi:10.1086/718046

Introducing Music in a Saudi Arabian Elementary School

2022· article· en· W4210792287 on OpenAlex

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

VenueThe Elementary School Journal · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsQueen's University
Fundersnot available
KeywordsExpatriateMusic educationCurriculumProfessional developmentSchool teachersPedagogyPsychologyMathematics educationMedical educationPolitical scienceMedicine

Abstract

fetched live from OpenAlex

This article describes the challenges and triumphs in introducing music in the primary division of a private elementary school in Riyadh, Saudi Arabia. Data sources included classroom observations, field notes, lesson plans, professional development materials, photographs, audio-recordings, videos, surveys, and interviews. Data were analyzed using standard qualitative protocols. Most of the teachers who were new to music teaching (both Saudi and non-Saudi) were eager to begin teaching music. They took advantage of professional development opportunities offered by an expatriate curriculum consultant. A school improvement team, made up of expatriate and Saudi teachers, guided the school-based music activities as well as professional development in the broader community. By the end of the year, music was present in all primary classes. The article closes with implications for the evolution of music teaching in Saudi Arabia, as well as how lessons learned through the Saudi experience might enrich music teaching in other settings.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.3140.000

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 head0.034
GPT teacher head0.238
Teacher spread0.203 · 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