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Record W4414989154 · doi:10.4000/14vus

Croisements chorégraphiques : opéras à la ville et à la cour au milieu du xviiie siècle

2025· article· fr· W4414989154 on OpenAlexaboutno aff
Rebecca Harris‐Warrick

Bibliographic record

VenueBulletin du Centre de recherche du château de Versailles · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBalletPlant canopyProcess analysis

Abstract

fetched live from OpenAlex

Lorsque l’Académie royale de musique sortait de Paris pour monter des opéras à la cour, elle faisait appel à son propre personnel, à l’exception du chorégraphe qui, lui, était directement employé par le roi. Cette particularité doit être interrogée : cet article vise à identifier, pour la période allant de 1748 à 1766, le travail effectué par les maîtres de ballet pour des opéras en fonction du lieu où ils étaient employés – à Paris (Jean-Barthélemy Lany) ou à la cour (Antoine Bandieri de Laval). Quelles différences artistiques ces changements de maître de ballet et de lieu auraient-ils pu engendrer ? Deux ouvrages de Rameau servent de cas d’étude : Pygmalion (Paris, 1748 et Fontainebleau, 1754) et la deuxième version de Castor et Pollux (Fontainebleau, 1763 ; Paris, 1764 ; Paris, 1765). Étant donné qu’il n’existe aucune chorégraphie de l’Opéra pendant cette période, notre étude s’appuie principalement sur les livrets des différentes reprises, les partitions, les comptes rendus parus dans le Mercure de France, et d’autres écrits de l’époque.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.011
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.040
GPT teacher head0.332
Teacher spread0.292 · 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 designQualitative
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
Published2025
Admission routes1
Has abstractyes

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