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Record W4318275421 · doi:10.1017/9781009241212.006

Cross-Dressing in Restoration Shakespeare: Twelfth Night and The Tempest

2023· book-chapter· en· W4318275421 on OpenAlexaboutno aff
Fiona Ritchie

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsTempestTransvestismWindsorArtPerformance artLiteratureGeorge (robot)Art historyPsychologyPsychoanalysis

Abstract

fetched live from OpenAlex

This chapter analyses cross-dressing in Restoration Shakespeare – in the main, female characters dressed in male attire – exploring the key question of how this theatrical device was influenced by the advent of the professional actress on the English stage. The approach is twofold. Firstly, the chapter examines the use of cross-dressing in specific Restoration-era adaptations of Shakespeare. One of the earliest of these, Dryden and Davenant’s The Tempest (1667), provides additional opportunities for transvestite performance as the play’s new male role of Hippolito was performed as a travesty part by an actress (either Mary Davis or Jane Long) and the female part of Sycorax (also added to the play by the adapters) was likely played by a man. Furthermore, it explores how other adapters treated the cross-dressing already inherent in the Shakespearean texts they chose to rewrite, considering, for example, George Granville’s The Jew of Venice (1701) and Charles Burnaby’s Love Betrayed (1703), a version of Twelfth Night . Secondly, the chapter investigates the Restoration performance history of Shakespearean ‘originals’ that feature transvestism, including Twelfth Night and The Merry Wives of Windsor. The chapter nuances our understanding of gender in Restoration Shakespeare through a detailed consideration of cross-dressing.

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

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 studies0.0140.012
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.046
GPT teacher head0.218
Teacher spread0.172 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooks→Same topicShakespeare, Adaptation, and Literary Criticism→French-language works237,207→