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Record W2910247360 · doi:10.7202/1055465ar

On Teaching Kim’s Convenience: Asian American Studies, Asian Canadian Studies, and the Politics of Race in Asian Canadian Theatre and Performance Studies

2019· article· en· W2910247360 on OpenAlexvenueaboutno aff
Colleen Kim Daniher

Bibliographic record

VenueTheatre Research in Canada · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsWritPerformance studiesPoliticsGender studiesAsian americansAmerican studiesLatino studiesRacismMedia studiesHistoryPolitical scienceSociologyArtHumanitiesLawEthnic groupAnthropology

Abstract

fetched live from OpenAlex

This article offers a critical overview and rationale for why and to what ends Daniher put a comparative Asian North American method into practice in her classroom on Asian American Theatre and Performance Studies at Brown University in Spring 2016. In particular, Daniher focuses on pairing Ins Choi’s play-text Kim’s Convenience (2011) alongside a viewing of the made-for-PBS broadcast of Anna Deavere Smith’s Twilight: Los Angeles, 1992 (2001) in order to broach the topic of anti-Black racism in both Canada and the US in the Black Lives Matter moment . Although Daniher describes here a course and learning experience from within a US-American institutional setting, she directs the following emergent queries to the field of Canadian Theatre and Performance Studies in light of its recent inauguration of the new “sub-field” of Asian Canadian Theatre and Performance Studies: How should we frame Asian Canadian theatre and performance in the classroom? For what purpose and under what curricular conditions do we teach racialized “minority” repertoires of theatre and performance in Canada? Drawing on overlapping genealogies of Asian American and Asian Canadian Studies, Daniher contends that a more rigorous engagement with existing theories, methods, and critical analyses of racial power is urgently needed if Asian Canadian Theatre Studies hopes to coincide with the larger political-ethical stakes of “Asian Canadian studies projects” writ-large.

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)0.007
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.086
Threshold uncertainty score0.625

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0560.053
Scholarly communication0.0140.006
Open science0.0020.007
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0060.000

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 head0.038
GPT teacher head0.356
Teacher spread0.317 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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