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Record W2936898012 · doi:10.1386/jafp.11.3.315_1

Rubies in the crown: A conversation on racial representation in Canadian theatre with Karen Robinson

2018· article· en· W2936898012 on OpenAlexaboutno aff
Valentina Rapetti

Bibliographic record

VenueJournal of Adaptation in Film & Performance · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWhite (mutation)ConversationArtPower (physics)Gender studiesResistance (ecology)Black feminismArt historySociologyPerformance artBlack womenHistoryVisual artsCommunication

Abstract

fetched live from OpenAlex

Karen Robinson is one of Canada’s leading black actresses. Over the past twenty years, she has figured in more than 40 theatre productions, as well as in national and international TV series and films. A race-conscious artist actively engaged in portraying diverse representations of blackness on and beyond the Canadian stage, Robinson has acted in black-authored plays that have risen to canonical status, embodying memorable black female characters such as Billie in Djanet Sears’ Harlem Duet and Esther in Lynn Nottage’s Intimate Apparel. In this interview conducted in July 2016, Robinson shares some memories of the 2006 production of Harlem Duet at the Stratford Festival (Ontario, Canada), as well as her views on acting, colourblind casting, the revolutionary power of black women’s theatre, and the social relevance of individual and collective acts of resistance in a predominantly male, white-dominated cultural arena.

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)0.006
metaresearch head score (Gemma)0.013
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 score0.097
Threshold uncertainty score0.706

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0800.025
Scholarly communication0.0100.004
Open science0.0030.006
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0090.001

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 head0.031
GPT teacher head0.245
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 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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