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Record W2920078065 · doi:10.7202/1055843ar

Proses Lyriques in Context

2019· article· en· W2920078065 on OpenAlexvenueno aff
Paul E. Dworak

Bibliographic record

VenueRevue musicale OICRM · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsComposition (language)Context (archaeology)LiteratureArtPoetryScholarshipNarrativeHistory

Abstract

fetched live from OpenAlex

In Proses lyriques, Debussy developed new methods for setting text to music. The music critics in Paris and Brussels who reviewed this composition between 1894 and 1914 were in most cases highly critical of the work. Rather than admitting that they did not understand the goals that Debussy had set for this composition, some of the critics spoke of it in derogatory terms because they believed that it abandoned traditional principles for writing poetry and for setting the text to music. Debussy wrote the text for the four songs of Proses lyriques. He used the innovations in writing verse that were begun by Charles Baudelaire and culminated in works of Stéphane Mallarmé. In particular, Debussy used the literary genre of prose lyrique that was cultivated by the Belgian writer Arnold Goffin and some of his contemporaries. Prose lyrique was a synthesis of poésie lyrique and developments in vers libre that were prominent in poèmes en prose. Mallarmé and Remy de Gourmont, in particular, encouraged writers to be aware of the harmonic and rhythmic aspects of the words that they selected in their verse. This article presents selected reviews of Proses lyriques written during the two decades after its composition. It also discusses the development of verse during the second half of the 19th century. This discussion provides a context for understanding both the artistic environment in which Debussy composed these songs and the innovations that he implemented in this composition, so that future scholarship can explore his innovations in the design of his verse, its rhythm and word selection, and its melodic and harmonic realization.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0040.008
Scholarly communication0.0090.004
Open science0.0000.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0100.002

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 head0.023
GPT teacher head0.207
Teacher spread0.185 · 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 designTheoretical or conceptual
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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueRevue musicale OICRMSame topicMusicology and Musical AnalysisFrench-language works237,207