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Disjunctured Feminisms

2016· book-chapter· en· W4233926578 on OpenAlexaff
Roberta Lamb, Niyati Dhokai

Bibliographic record

VenueOxford University Press eBooks · 2016
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsQueen's University
Fundersnot available
KeywordsFeminismSociologySocial justiceGender studiesNegotiationRelevance (law)Diversity (politics)EthnographyMulticulturalismPedagogySocial sciencePolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Abstract This chapter explores feminism in the classroom to contribute to the discussion of music education and social justice in the volume. Through a dual-authored, cross-generational and cross-cultural approach, it follows the disjunctured past of feminism in North American music education, and advocates for the study of feminist histories within music education and its social and historical relevance to current music educators. It also deliberates the negotiation of North American academic feminisms concurrently with global feminisms. Furthermore, it considers the emergence of multicultural feminist perspectives within the music education classroom and offers ethnographic possibilities for encouraging diverse perspectives within the classroom. The chapter offers possibilities for encouraging inclusive and comprehensive music education that recognizes how each individual’s experience contributes to feminist diversity and social justice.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.024
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0020.004
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 head0.052
GPT teacher head0.196
Teacher spread0.145 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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