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Record W4400239392 · doi:10.18274/bl.v14i2.331

Identities in Drag: An Interview with King Sammy Silver on August 20, 2020

2023· article· en· W4400239392 on OpenAlexaff
Alexa Alice Joubin, Terri Power, King Sammy Silver

Bibliographic record

VenueBorrowers and Lenders The Journal of Shakespeare Appropriations · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsMasculinityNothingDragPower (physics)ViolaArtSociologyArt historyPsychoanalysisPsychologyGender studiesPhilosophyEngineering

Abstract

fetched live from OpenAlex

This interview with King Sammy Silver, conducted by Alexa Alice Joubin and Terri Power, explores drag as a stage practice. A London-based actor and YouTube personality, he represents a new generation of trans artists. He has worked with Power on multiple Shakespeare productions at Bath Spa University in the UK and elsewhere, and has been influenced by Power’s Drag King Richard III. He has played Valentine in Two Gentlemen of Verona, Viola in Twelfth Night, Capulet and Tybalt in Romeo and Juliet, and Benedict in Much Ado About Nothing. He reflects on Shakespeare’s role in trans theater today as well as how drag can deconstruct toxic masculinity.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.062
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0270.009
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0070.002

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 head0.048
GPT teacher head0.251
Teacher spread0.204 · 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 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
Published2023
Admission routes1
Has abstractyes

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