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Record W1865725062 · doi:10.7202/1030872ar

Littérature et vocalité chez Xenakis ou comment traiter des abîmes

2015· article· fr· W1865725062 on OpenAlexaffvenue
Nicolas Darbon

Bibliographic record

VenueIntersections Canadian Journal of Music · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsCanadian University Music Society
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Le mythème du Chaos est étudié à travers les oeuvres vocales de Xenakis. Il est représentatif de l’histoire, des préoccupations et de la sensibilité « contemporaines » (de la fin du XXe siècle) : bien que s’inspirant de l’Antiquité grecque, le traitement du texte oscille entre les pôles de l’abstraction pure et de l’expression signifiante. Furieux, tempétueux, le chaos xenakien peut résulter du traumatisme, de la folie, de la guerre, désigner l’état de ce qui n’a pas de forme, la béance, le déluge, la genèse, la perdition, être transition, processus, représenter l’Origine ou la Fin du monde. Ainsi le compositeur a-t-il voulu « traiter des abîmes » par la vocalité soliste ou chorale, remonter à « toute la richesse cosmique, mais chaotiquement ». Cet article ouvre un diptyque dont le second volet s’intitule « La Grande Mère néolithique dans Serment-Orkos » (publié par le Centre Iannis Xenakis, Université de Rouen). Le postulat est le suivant : les sciences dites du « chaos » et de la « complexité » relèvent elles-mêmes d’une anthropologie de l’imaginaire. Par ailleurs, il s’inscrit dans un champ de recherche sur la transdiction (notion explicitée sur le site du CEREdI, Université de Rouen), c’est-à-dire sur le son et la corporéité des transferts musico-littéraires.

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)0.002
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
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 head0.067
GPT teacher head0.282
Teacher spread0.215 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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