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Record W4410563346 · doi:10.7202/1117958ar

Réflexions sur un amour de jeunesse – l’orchestre

2025· article· fr· W4410563346 on OpenAlexvenueaboutno aff
Parmela Attariwala

Bibliographic record

VenueCircuit Musiques contemporaines · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Les orchestres professionnels sont devenus des boucs émissaires dans les critiques postcoloniales de l’iniquité dans l’écosystème artistique canadien. L’orchestre, plus que toute autre structure de musique classique occidentale, garde le sens de la domination eurocentrique continue de la forme (y compris du comportement) et le coût fiscal corollaire nécessaire à son maintien. D’un point de vue perceptif, la forme et le coût des orchestres – lorsqu’ils sont comparés à des structures non occidentales – existent aux dépens d’autres pratiques musicales, une situation problématique compte tenu de la démographie ethnoculturelle canadienne actuelle. Dans cet article, l’auteure revient sur le rapport d’équité 2019 qu’elle a coécrit pour Orchestres Canada. Elle utilise l’autoréflexion pour se situer en tant que bénéficiaire du système orchestral, en tant que Canadienne racialisée et en tant que critique culturelle. Elle s’appuie ensuite sur cette multivalence pour analyser les questions sociales et éthiques qui préoccupent actuellement les orchestres canadiens, soit la résurgence autochtone et la prise en compte des colons, les différentes relations avec la colonialité et la problématique de la valeur culturelle dans le cadre du multiculturalisme légal et de la démocratie libérale.

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)0.003
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.292
Threshold uncertainty score0.581

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.029
Scholarly communication0.0100.004
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.204
GPT teacher head0.427
Teacher spread0.223 · 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
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

Citations0
Published2025
Admission routes2
Has abstractyes

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