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Record W2970859691 · doi:10.7202/1062565ar

L’art des (petites) différences

2019· article· fr· W2970859691 on OpenAlexvenueno aff
Pascale Criton, Sharon Kanach

Bibliographic record

VenueCircuit Musiques contemporaines · 2019
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Dans cet entretien, la compositrice française Pascale Criton retrace les grandes lignes qui sous-tendent son écriture et sa pensée musicales. Passionnée par le continuum sonore, ses rencontres avec Ivan Wyschnegradsky, Gérard Grisey – mais aussi avec le philosophe Gilles Deleuze – dans le courant des années 1970, confirment son intérêt pour les micro-intervalles et la variabilité du son. La compositrice livre les enjeux qui mobilisent son attention au fil des oeuvres qui jalonnent son parcours, des années 1980 à aujourd’hui. L’idée d’interaction écosensible émerge avec l’emploi de scordaturas en 1/4, 1/12e et 1/16e de ton associées à la synthèse du son (Thymes, 1988), ou en référence à des comportements acoustiques (Artefact, 2001) qui renouvellent l’écriture du geste (Objectiles, 2002). Pascale Criton interroge aussi bien les techniques instrumentales que la notation et l’interprétation (Circle Process, 2012). Son utilisation des petites différences vise l’élargissement de la perception et s’étend aujourd’hui à une écoute sensible aux phénomènes acoustiques et perceptifs (Wander Steps, 2018).

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)0.004
metaresearch head score (Gemma)0.009
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 score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.026
Scholarly communication0.0090.009
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0140.002

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 head0.260
GPT teacher head0.297
Teacher spread0.037 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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