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Towards a (Self-)Compassionate Music Education: Affirmative Politics, Self-Compassion, and Anti-Oppression

2020· article· en· W3039474118 on OpenAlexaboutno aff
Hess

Bibliographic record

VenuePhilosophy of Music Education Review · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsOppressionPoliticsSociologyAestheticsIdentity (music)Gender studiesContext (archaeology)Power (physics)White (mutation)PsychologyPolitical scienceLawHistoryArt

Abstract

fetched live from OpenAlex

In Red Skin, White Masks: Rejecting the Colonial Politics of Recognition, Glen Coulthard argues that since 1969, colonial power relations in Canada have shifted from an unconcealed structure of domination to a mode of colonial governance that operates through state recognition and accommodation. He instead looks to identify a type of recognition based on self-affirmation and self-recognition rather than state acceptance. Following Coulthard, I examine movements created to affirm oppressed groups in the context of anti-Semitism and anti-Blackness in the mid-twentieth century and explore possible limitations of such movements, including the erasure or elision of complex intersections of identity. I then draw upon self-compassion, a mental health and wellness approach, as a potential framework for the affirmative politics Coulthard theorizes. Subsequently, I consider whether such a framework offers a mechanism to provide the self-affirmation and recognition that Coulthard identifies as vital to resisting oppression. I ultimately explore how understanding music as cultural production in music education might engender this affirmative politics to facilitate rich affirmation and validation of students and educators to musically imagine different possible futures.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.078
GPT teacher head0.283
Teacher spread0.205 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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