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Record W4225313170 · doi:10.24908/iqurcp15485

Shakespeare's The Bachelorette

2022· article· en· W4225313170 on OpenAlexvenueno aff
Haley Forgacs, Patrick Cunningham

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsQueerPresentation (obstetrics)Power (physics)LiteratureHuman sexualityArtDramaEliteAestheticsPopular cultureAppealHistorySociologyGender studies

Abstract

fetched live from OpenAlex

Our joint presentation combines performance and parody to create a playful and accessible approach to understanding Shakespearean texts and the power of adaptation. We intend to populate the TV show “The Bachelorette” with Shakespeare’s characters, thus using popular culture to reveal the problematic aspects of Shakespeare’s plays. We want to appeal to up and coming generations and include those who may not have the background or elite education to understand Shakespeare on their own. One possibility we hope to explore is Ophelia choosing among several Shakespearean tragic heroes vying for her hand. Additionally, we will deconstruct Shakespearean gender norms and notions of sexuality, and probe the queer experience, or the lack thereof, in Shakespearean adaptations. Many Shakespearean popular media adaptations skirt around the queer undertones of the texts from which they derive their material. Our exploration is facilitated by the critical and parodic nature of our presentation, drawing on influences from Shakespeare’s own works and popular adaptations like Baz Luhrmann’s 1996 film Romeo + Juliet and Iqbal Khan’s 2015 theatrical production of Othello to challenge and subvert Shakespearean conventions. While many Shakespearean adaptations exalt and revere Shakespeare, our experiment hopes to discover what a queer and irreverent eye might make of Shakespeare.
 Mediums:
 
 Presentation
 Mini essay

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.750
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.166
GPT teacher head0.341
Teacher spread0.175 · 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.

Study designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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