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Record W4392263397 · doi:10.1353/tt.2024.a920469

Critical Conversations: Emerging BIPOC Critics Reimagine Theatre Criticism through the Digital

2024· article· en· W4392263397 on OpenAlexaboutno aff
Michelle MacArthur

Bibliographic record

VenueTheatre topics · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCriticismTheatre criticismArtSociologyAestheticsLiteratureLiterary criticismLiterary science

Abstract

fetched live from OpenAlex

Abstract: Theatre criticism in the Global North currently finds itself at a pivotal point, as the internet eclipses legacy media as the central space for critical discourse and as ongoing antiracist and anticolonial activism highlights the underrepresentation of BIPOC artists across the theatre industry. Within this context, stakeholders in the theatre community, recognizing the importance of a vibrant critical discourse, are faced with finding more sustainable and equitable models. This article considers the future of theatre reviewing through a case study of Taking on the World (TotW), a mentorship program for emerging BIPOC critics run in conjunction with Toronto's Soulpepper Theatre Company and Intermission magazine. TotW participants' innovative critical practice demonstrates that de-hierarchizing theatre criticism necessitates reimagining the form, and specifically centering conversation as a key quality of process and product. Exploiting the capabilities of the digital, TotW participants embed conversation within their work and model a mode of criticism that challenges traditional notions of expertise and is ultimately more inclusive. Applying recent scholarship on theatre criticism to examples of work produced in the program and participant interviews, this article advances new ways of practicing and teaching theatre criticism at this crucial moment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.999

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.285
Teacher spread0.256 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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