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Dreaming Disability Musical Futurities

2025· book-chapter· en· W4411604434 on OpenAlexaff
Adam Patrick Bell, Molly Joyce

Bibliographic record

VenueOxford University Press eBooks · 2025
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsWestern University
Fundersnot available
KeywordsMusicalPsychologyCognitive scienceArtVisual arts

Abstract

fetched live from OpenAlex

Abstract This chapter employs Alison Kafer’s framing of disability futurities to consider how the field of music education could radically recalibrate its orientation toward disabled people. The discussion begins by examining some of the key concepts and ideas forwarded by the first wave of feminist researchers in disability studies before extending and expanding to more recent and ranging writings related to feminist disability theory to demonstrate how the idea of lived experience-as-epistemology has evolved up until the present time. Central to the chapter are the perspectives of four disabled women musicians on their experiences with music education. Musicians Gaelynn Lea, Lachi, Molly Joyce, and Sonia Allori were invited to discuss their learning backgrounds, music careers, instruments, identities, and lived experiences as disabled persons, as well as offer suggestions for music educators. Built upon their collective knowledge and wisdom, the chapter concludes by pointing out a trio of transformative practices that music educators can engage in: disability pride, access and care intimacy, and pliable pedagogy.

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 score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.021
Scholarly communication0.0080.011
Open science0.0010.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.027
GPT teacher head0.182
Teacher spread0.155 · 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
Published2025
Admission routes1
Has abstractyes

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