MétaCan
Menu
Back to cohort
Record W2895013564 · doi:10.3366/drs.2018.0221

Parisian Music-Hall Ballet through the Eyes of its Critics

2018· article· en· W2895013564 on OpenAlexaff
Sarah Gutsche-Miller

Bibliographic record

VenueDance Research · 2018
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBalletSpectacleDanceChoreographyArtViewpointsVisual artsMusicalPeriod (music)Classical balletConcert dancePerformance artArt historyAesthetics

Abstract

fetched live from OpenAlex

In the 1890s, Paris's three pre-eminent music halls – the Folies-Bergère, the Olympia, and the Casino de Paris – staged ballets on a nightly basis alongside circus acts and song-and-dance routines. As music-hall ballet librettos and scores show, these productions were closely related to ballets staged by the Paris Opéra, with similar large-scale structures, scene and dance types, and dramatic, choreographic, and musical conventions. What music-hall ballets looked like, however, is less clear: they have left few visual traces, and virtually no prose descriptions of choreography or staging. The one plentiful source of information is press reviews, but relying on reviews poses many problems for the historian. Critics’ various culturally situated viewpoints and interpretations may be used to create a composite picture of what might have been happening on stage, but they can also leave us with a hazy understanding of the genre. This paper examines the multiple and sometimes contradictory critical responses to 1890s music-hall ballets both to highlight what effect such contradictions might have on our perception of music-hall ballet (in particular as art or salacious spectacle) and to call attention to the problems inherent in using the press as a documentary source.

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)0.005
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0090.025
Scholarly communication0.0120.005
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.288
GPT teacher head0.496
Teacher spread0.208 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDance ResearchSame topicDiversity and Impact of DanceFrench-language works237,207