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Record W4225998733 · doi:10.1177/87551233221085739

On Embedding Indigenous Musics in Schools: Examining the Applicability of Possible Models to One School District’s Approach

2022· article· en· W4225998733 on OpenAlexafffund
Anita Prest, J. Scott Goble, Héctor Vázquez-Cordoba

Bibliographic record

VenueUpdate Applications of Research in Music Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenousThe artsMusic educationCurriculumPresentation (obstetrics)Metropolitan areaSubject (documents)SociologyIndigenous educationTraditional knowledgePedagogyMathematics educationVisual artsGeographyPsychologyComputer scienceArtLibrary science

Abstract

fetched live from OpenAlex

Recent curriculum policy changes in British Columbia (BC) require that educators in all subject areas-including music-embed local Indigenous knowledge, pedagogies, and worldviews in their classes. Yet facilitating such decolonizing cross-cultural music education activities requires knowledge that music educators may not currently possess. We use four models created by an Indigenous Arts scholar to examine the interface of Indigenous and Western art musics in performing arts settings: (a) integration, (b) nation-to-nation music trading and reciprocal presentation, (c) a combination of the first two models, and (d) non-integrative encounters that are in relationship but have irreconcilable elements. We consider the applicability of these models in music education settings, using them to analyze our findings from a study in which we explored the ways teachers have embedded local First Nations songs and drumming in classes in a single metropolitan school district in BC.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.115
GPT teacher head0.408
Teacher spread0.293 · 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.

Study designQualitative
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

Citations7
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueUpdate Applications of Research in Music EducationSame topicIndigenous Health, Education, and RightsFrench-language works237,207