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Record W4321463557 · doi:10.7202/1096477ar

Applying a Mad Studies Framework to Opera: Poulenc’s Dialogues des Carmélites

2023· article· en· W4321463557 on OpenAlexvenueno aff
Colette Simonot-Maiello

Bibliographic record

VenueIntersections Canadian Journal of Music · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Literary Analyses
Canadian institutionsnot available
Fundersnot available
KeywordsOperaMetaphorHistoryLiteratureArtVisual artsLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Multiple readings of madness are examined in Poulenc’s opera Dialogues des Carmélites (1957) through the framework of mad studies. Several layers of madness can be found in this work: individual lived experiences of madness, the history of mental illness in France during and after the French Revolution, and the cultural metaphor of hysteria as social degeneration, as articulated by Micale. Close readings of two scenes with a discussion of their musical features are included: the first prioress’s death (act 1, scene 4) and the final scene at the guillotine (act 3, scene 4).

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)0.006
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0190.044
Scholarly communication0.0120.006
Open science0.0020.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0050.000

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 head0.142
GPT teacher head0.288
Teacher spread0.146 · 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
Published2023
Admission routes1
Has abstractyes

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