MétaCan
Menu
← Back to cohort
Record W7071486683

Six French composers’ homage to Haydn : an analytical comparison enlightening their conception of tombeau

2009· dissertation· en· W7071486683 on OpenAlexafffund

Bibliographic record

VenueeScholarship@McGill (McGill) · 2009
Typedissertation
Languageen
FieldSocial Sciences
TopicRace, Identity, and Education in Brazil
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
FundersSocial Sciences and Humanities Research Council of CanadaMcGill University
KeywordsFeature (linguistics)Ridiculous
DOInot available

Abstract

fetched live from OpenAlex

In 1909, the Revue musicale mensuelle de la Societe lnternationale de Musique (RSIM) asked six French composers (Debussy, Dukas, Hahn, d’Indy, Ravel and Wid or) to commemorate Haydn’s centennial anniversary of death by each creating a piano piece that incorporated a theme built with a letter-note correspondence on the word “Haydn”. In the context of the French fin-de-siecle search for musical identity, this collective tombeau represents a unique opportunity to discover what characteristics were important to them. My analysis of the pieces reveals five common elements: enharmonic reinterpretation as a means of exploration of foreign keys, large scale registral connections, dissonant chords for colour, ingenious means of creating unity, and use of past genres and form. The influence of Italian and German culture, as well as French music history and politics are also evaluated. The tom beaux reveal how central the concept of the music of the past was to French composers at the tum of the century and how it pointed the way to post-war neoclassicism.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.208
Threshold uncertainty score0.413

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0130.007
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.037
GPT teacher head0.344
Teacher spread0.307 · 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

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueeScholarship@McGill (McGill)→Same topicRace, Identity, and Education in Brazil→French-language works237,207→