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Record W2040500951 · doi:10.3138/ecf.26.4.537

A Comedian on Tragedy: Colley Cibber’s <i>Apology</i> and <i>The Rival Queans</i>

2014· article· en· W2040500951 on OpenAlexvenueno aff
Vivian Davis

Bibliographic record

VenueEighteenth-Century Fiction · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTragedy (event)ComedyBurlesquePleasureContext (archaeology)ComicsLiteratureLaughterAestheticsArtWhite (mutation)NarrativeHistoryPsychology

Abstract

fetched live from OpenAlex

While eighteenth-century actor and theatre manager Colley Cibber is most frequently discussed within the context of sentimental comedy, this article addresses the comedian’s writing for and about the tragic stage. The neoclassical establishment consistently argued for the propriety of tragedy; however, actor and manager Cibber in his 1740 autobiography makes a case for the ludic qualities of successful tragic performance which, he insists, produces pleasure not tied to moral improvement. Moreover, Cibber embraces, rather than bemoans, the destabilization of social hierarchies that attends confessed generic hybridity. In an analysis of the comic burlesque The Rival Queans, a parody of Nathaniel Lee’s earlier tragedy The Rival Queens, I show how Cibber’s tragic stage was less concerned with categories of masculinity and femininity than in the sheer fluidity of gender. Experimenting with gender and genre in light of the period’s changing notions of sexual difference, the comedian revalues mixed genres and gender confusion as a site of illicit pleasure, providing an affective yet ephemeral other against which tragedy’s formidable narratives about gender and nation took shape.

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)0.003
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: none
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0180.017
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.179
Teacher spread0.171 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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Same venueEighteenth-Century FictionSame topicLiterature: history, themes, analysisFrench-language works237,207