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Record W4400607719 · doi:10.1353/tt.2024.a932204

Disorganizing Representation in Theatresports: A Case Study in Improv Comedy

2024· article· en· W4400607719 on OpenAlexaboutno aff
Keira Mayo

Bibliographic record

VenueTheatre topics · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComedyRepresentation (politics)Race (biology)AestheticsIdentity (music)Event (particle physics)ArtSociologyVisual artsEpistemologyGender studiesPhilosophyLawPolitical science

Abstract

fetched live from OpenAlex

Abstract: This article offers a model of analyzing improv comedy by minoritarian improvisers that refuses to reduce the performance to being about race and gender. This work draws on critiques of identity and representation advanced by queer of color performance studies scholars to show how race and gender can matter in improv without their being the only aspects of significance. Examining a scene from Toronto’s fortieth anniversary of Theatresports, I highlight how the form of the “Dubbing Game”—where improvisers speak for one another—combines with the improvisers’ creative choices to produce a lively and laughable piece of improvised theatre. Exploring how the Dubbing Game separates voice from body shows how race and gender can be sensed as an event rather than strictly adhering to bodies. Through this exploration, I argue that part of what makes this dubbing scene funny is the disorganization of the representational logic. Importantly, disorganizing representational logic is only part of the scene’s comedy. This article shows the many ways that the scene’s comedy emerges through particular creative choices rather than from information about the “what is” of race and gender.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.295
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.

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
Published2024
Admission routes1
Has abstractyes

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