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Record W3101900825 · doi:10.29173/connections8

Diffraction Patterns of Homoeroticism and Mimesis between Twelfth Night and She's the Man

2020· article· en· W3101900825 on OpenAlexafffundvenue
Xavia A. Publius

Bibliographic record

VenueConnections A Journal of Language Media and Culture · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsQueerSpectacleDramaHollywoodMovie theaterHuman sexualityLiteratureArtRealismAestheticsSpace (punctuation)Queer theorySociologyHistoryGender studiesPhilosophyArt historyLawPolitical science

Abstract

fetched live from OpenAlex

Shakespeare’s Twelfth Night (1602) is well-known for its homoeroticism, whereas the critical consensus concerning She’s the Man (dir. Andy Fickman), a 2006 film based on Twelfth Night, seems to be that it dampens the play’s homoerotic strategies and meanings in the translation to film. This paper argues that while specific elements are indeed dampened, homoeroticism is still firmly present in the movie, and the perceived curtailing of much of the play’s subversive energy does not explain the film’s queer legacy. Because of the different codes surrounding homoeroticism for Elizabethan drama and Hollywood cinema, the different contours of homosocial space within the two societies, and the Western invention of the homosexual as a distinct category in the time between the two eras, the queer potential of She’s the Man resides in different moments of the story, and is filtered through capitalist strategies of queerbaiting. Therefore, I aim to show the diffraction patterns of queer and trans desire between the two works. Specifically, the different approaches to mimesis shape this intra-action, including the place of women in mimetics; the specters of realism and psychoanalysis; shifting notions of gender and sexuality; and changes in audience tastes regarding bodily spectacle in cross-dressing stories.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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 teacher head, 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

Citations0
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueConnections A Journal of Language Media and CultureSame topicFolklore, Mythology, and Literature StudiesFrench-language works237,207