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Vivier, Claude (1948–1983)

2018· book-chapter· en· W4230854471 on OpenAlexaffabout
Paul Bazin

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLiterature, Musicology, and Cultural Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsImmortalitySoulThe artsArt historyArtOperaPianoPerformance artGeorge (robot)Chamber musicMusicalMOZARTHumanitiesVisual artsLiteraturePhilosophyTheology

Abstract

fetched live from OpenAlex

Claude Vivier is perhaps the best known of all Quebec composers, both in Canada and abroad. In 1967, after being removed from the religious establishment where he was preparing to become a priest, Vivier registered at the Montreal Conservatory of Music where he studied until 1970. He first attended composer Gilles Tremblay’s classes at the conservatory, and studied piano with Irving Heller there before traveling to Europe. A number of scholarships that Vivier received from the Canadian Arts Council (CAC) brought him to Utrect (1971–72) where he studied electroacoustic composition at the Instituut voor sonologie with composer Gottfried Michael Kœnig, and also to Cologne where he became a student of Karlheinz Stockhausen. Claude Vivier is the author of a catalogue bearing many traces of an intense journey of self-discovery. An opera, Kopernikus (1979) and three orchestral art songs (Lonely Child, 1980; Wo bist du Licht, 1981; Bouchara, 1981) are among his most affecting works. His major work for strings, Zipangu (1980), leaves an impression as lasting as his Pulau Dewata (1977) succeeds in invoking atmospheres typical of the Balinese gamelan sound world. Vivier was murdered in Paris in 1983, leaving behind a supposedly symbolic, unfinished work titled Glaubst du an die Unsterblichkeit der Seele? [Do you believe in the immortality of soul?].

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.234
Threshold uncertainty score0.465

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0380.013

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 head0.032
GPT teacher head0.285
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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes2
Has abstractyes

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