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Record W3215221987 · doi:10.1515/jcde-2021-0020

“My Skin Is Not Me”: The Transformations of William Shakespeare’s Othello in Ann-Marie MacDonald’s <i>Goodnight Desdemona (Good Morning Juliet)</i> and Djanet Sears’s <i>Harlem Duet</i>

2021· article· en· W3215221987 on OpenAlexaboutno aff
Imed Sassi

Bibliographic record

VenueJournal of Contemporary Drama in English · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsDramatizationAppropriationSpellCharacter (mathematics)VisionLiteratureArtHistoryPhilosophyTheologyEpistemology

Abstract

fetched live from OpenAlex

Abstract Both Goodnight Desdemona (Good Morning Juliet) (1990) and Harlem Duet (1997) are Canadian feminist appropriations of William Shakespeare. Both deal, at least partly, with Othello , and both can be considered subversive re-visions of Shakespeare’s play which aim to articulate oppositional intervention in the canon. These similarities notwithstanding, the plays have not often been studied concurrently. Also, while several critics have explored them, mostly separately, in terms of their adaptation/appropriation of Shakespeare, seeking to spell out the transformations they have brought to the “original” text, little has been said about how the iconic figure of Shakespeare still holds sway in these new dramas, albeit in different ways and to varying degrees. Likewise, their dramatization of the character of Othello remains rather understudied. This essay explores the “new” Othellos of the two plays, contending that their positioning in the two texts evinces some similarities while their characterization differs widely, given the plays’ generic difference, but mostly the two playwrights’ rather divergent feminist perspectives which, in turn, substantially shape the plays’ respective appropriation techniques.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.224
Teacher spread0.202 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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