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Record W2615474096 · doi:10.7202/1039670ar

Les compositeurs face au passé musical : l’attrait pour l’écriture orchestrale dans la trajectoire de quelques compositeurs québécois

2017· article· fr· W2615474096 on OpenAlexvenueaboutno aff
Danick Trottier

Bibliographic record

VenueCircuit Musiques contemporaines · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicLiterature, Musicology, and Cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

L’article porte sur l’écriture orchestrale comme choix naturel dans la trajectoire des compositeurs québécois nés vers la fin des années 1960 et après, l’orchestre étant devenu un outil d’expression privilégié depuis l’arrivée du nouveau millénaire. Cet investissement conduit à questionner la relation que les compositeurs québécois entretiennent avec le passé musical en s’attardant à la façon dont le champ d’expérience et l’horizon d’attente éclairent le régime d’historicité dans lequel ils se meuvent et pensent l’acte de création. Ce régime d’historicité étant gouverné désormais par les contraintes du présent qui sont celles liées à la difficulté de vivre de son art, d’être joué et de durer, le moment présent semble être la catégorie temporelle qui a force de loi. L’article fait référence à des compositeurs comme Simon Bertrand, Nicole Lizée, Julien Bilodeau, Éric Champagne et bien d’autres, et s’intéresse à la façon dont le rapport au temps s’est libéré d’une caricature du métier selon un récit déterministe du passé musical.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.526

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 studies0.0140.008
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.001

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 head0.064
GPT teacher head0.317
Teacher spread0.253 · 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 designQualitative
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

Citations2
Published2017
Admission routes2
Has abstractyes

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