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Record W4391413203 · doi:10.1515/9781787442528

Debussy's Resonance

2018· book· en· W4391413203 on OpenAlexaboutno aff

Bibliographic record

VenueBoydell and Brewer eBooks · 2018
Typebook
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Some of Debussy's most beloved pieces, as well as lesser-known ones from his early years, set in a rich cultural context by leading experts from the English- and French-speaking worlds. The music of Claude Debussy has always been widely beloved by listeners and performers alike, more perhaps than that of any of the other pioneers of musical modernism. However rich in itself, his creative output also participated,and continues to participate, in a network of cultural connections, the scope and meaning of which can only be gleaned through multiple interpretive frameworks. Debussy's Resonance offers twenty new studies by some of themost active and respected English- and French-language scholars of French music. The book treats a large swath of the composer's music, from previously unexplored mélodies of his early years to late pieces such as the ballet Jeux and the Douze Études , and takes into consideration the numerous contexts that helped shape the works and the different ways that musicologists and critics have explained them. CONTRIBUTORS: Katherine Bergeron, Matthew Brown, David J. Code, Mark DeVoto, Michel Duchesneau, David Grayson, Denis Herlin, Jocelyn Ho, Roy Howat, Steven Huebner, Julian Johnson, Barbara L. Kelly, Richard Langham Smith, Mark McFarland, François de Médicis, Robert Orledge, Boyd Pomeroy. Caroline Rae, Marie Rolf, August Sheehy FRANÇOIS DE MÉDICIS is Professor of Music at the Université de Montréal. STEVEN HUEBNER is Professor of Music at McGill University.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.193
Teacher spread0.168 · 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 teacher head, not a consensus.

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

Citations2
Published2018
Admission routes1
Has abstractyes

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