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Record W1539457794 · doi:10.7202/1027609ar

La saturation, métaphore pour la composition ?

2014· article· fr· W1539457794 on OpenAlexvenueno aff
Pierre Rigaudière

Bibliographic record

VenueCircuit Musiques contemporaines · 2014
Typearticle
Languagefr
FieldSocial Sciences
TopicLiterature, Musicology, and Cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

L’exploration par les compositeurs du courant spectral ou par Helmut Lachenmann de la face inharmonique du son aura assurément joué un rôle crucial dans l’acceptation par les générations suivantes de la composante acoustique bruiteuse comme un matériau entièrement légitime pour la composition. Pour des compositeurs comme Franck Bedrossian, Raphaël Cendo et Yann Robin, il ne s’agissait plus d’envisager le son saturé comme un son poussé dans ses derniers retranchements, ou comme l’outil d’une critique du « beau son » hérité du romantisme, mais bel et bien d’en faire la matière d’un discours articulé. Composer l’excès – de son, d’énergie – devenait pour eux un défi qu’il fallait relever par l’écriture. Constituer une palette de modes de jeu et de timbres était une chose, en assurer la dynamique et la cohérence en était une autre. L’une des visées principales de cet article est de montrer comment, sur la base d’un vocabulaire en grande partie commun, les trois compositeurs « saturationnistes » ont élaboré une grammaire qui les différencie aujourd’hui de façon manifeste.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.028
Scholarly communication0.0060.010
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.031
GPT teacher head0.280
Teacher spread0.250 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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