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Record W2800916706 · doi:10.7202/1044445ar

« Just allow the space to tell us what we should be… what we should be doing » : l’expérience cinématographique de la musique improvisée

2018· article· fr· W2800916706 on OpenAlexvenueno aff
Frédéric Dallaire

Bibliographic record

VenueRevue musicale OICRM · 2018
Typearticle
Languagefr
FieldArts and Humanities
TopicVisual Culture and Art Theory
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtArt history

Abstract

fetched live from OpenAlex

Cet article explore l’hypothèse suivante : le cinéma peut nous faire voir et entendre la dimension éthique et politique de l’improvisation musicale. Il décrit concrètement les éléments de cette politique de l’improvisation en analysant plusieurs séquences du film Step Across the Border (1990) de Nicolas Humbert et Werner Penzel. Il étudie deux principes relationnels qui structurent la pratique de l’improvisation musicale et cinématographique explorée dans le film. L’implication (intégration du créateur dans l’espace sonore) et la résonance (transformation mutuelle du son, du contexte, de l’auditeur) modifient la dynamique du tournage et souligne le potentiel musical des espaces quotidiens (la rue, le café, la mer, l’usine). De plus, le montage cinématographique a un pouvoir de mise en relation, il crée un espace de résonance qui brouille les frontières entre les musiciens (Fred Frith et ses amis), les cinéastes et les spectateurs. Cette « expérimentation de nouvelles formes sociales de création » (Saladin 2014, p. 205) produit une expérience cinématographique libre et singulière : dans ce film, la musique est un phénomène pluriel qui peut déplacer notre regard, notre écoute, et ainsi interroger nos manières d’interagir avec les autres.

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)0.004
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.019
Scholarly communication0.0090.007
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.063
GPT teacher head0.305
Teacher spread0.242 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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