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Multiculturalism in International Music Education

2004· book-chapter· en· W4388354692 on OpenAlexaboutno aff
Terese M. Volk

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismMusic educationIndigenousCurriculumIndependence (probability theory)Music GeographyPerspective (graphical)Multicultural educationGender studiesSociologyPedagogyPolitical scienceMusic historyVisual artsArt

Abstract

fetched live from OpenAlex

Abstract The topic of multiculturalism has become one of worldwide concern, and many countries have addressed this issue both in education and in music education. Sometimes it is focused on the need to reestablish indigenous musics in the music education curriculum. Many countries (Zambia, Malaysia, and Nigeria among them) had their own musics supplanted by the study of Western art music during colonization and since independence have been trying to find ways to incorporate their own various music traditions in the schools. Some places (the United Kingdom, Australia, and Canada) are dealing with incorporating the music cultures of immigrant populations, much as in the United States. Still others, like Germany, are just beginning to incorporate a perspective that includes world musics in their curriculum. The development of multicultural music education in some cases runs parallel to that of the United States; in other cases, it provides contrasts.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0070.003
Open science0.0000.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.067
GPT teacher head0.244
Teacher spread0.178 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2004
Admission routes1
Has abstractyes

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