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Modernist Opera’s Stigmatized Subjects

2016· book· en· W2475634808 on OpenAlexaff
Sherry D. Lee

Bibliographic record

VenueOxford University Press eBooks · 2016
Typebook
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOperaSubjectivityAestheticsPersonhoodRepresentation (politics)MetaphorInterpretation (philosophy)Sociocultural evolutionArtMusicalLiteratureSociologyPhilosophyEpistemologyLinguisticsAnthropology

Abstract

fetched live from OpenAlex

Abstract While nineteenth-century opera saw its share of damaged and acutely afflicted bodies, and its music more frequently aestheticized suffering than it either objectified or sympathized with it, the early twentieth century saw a shift in emphasis with regard to the staged and musical representation of subjects stigmatized by congenital or permanent physical disabilities. This essay considers the ways in which the musicodramatic framework for interpretation, spectatorship, and identification in modernist opera (including depictions by Strauss, Schreker, and Zemlinsky of dwarves and hunchbacks) is subtly reconfigured according to shifting modernist aesthetic and sociocultural contexts, such that the visual and sonic signification of physical disability is conceptualized as a kind of metaphor for damaged subjectivity or personhood—a status not infrequently understood as encapsulating the broader fate of the modern self.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.024

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 studies0.0050.029
Scholarly communication0.0050.004
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.196
Teacher spread0.158 · 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
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

Citations13
Published2016
Admission routes1
Has abstractyes

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