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Record W3096211270 · doi:10.3138/md.63.3.1087

Space, Symbols, and Speech in Gurpreet Kaur Bhatti’s <i>Behzti</i> and Its Reception

2020· article· en· W3096211270 on OpenAlexvenueno aff
Rehana Ahmed

Bibliographic record

VenueModern Drama · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsnot available
Fundersnot available
KeywordsOffensiveMulticulturalismInterpretation (philosophy)SociologyCensorshipRepresentation (politics)Space (punctuation)AestheticsGender studiesLawPoliticsPolitical scienceArtLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

In December 2004, the staging of Gurpreet Kaur Bhatti’s play Behzti at the Birmingham Repertory Theatre triggered protests by some members of the Sikh community who considered it offensive. By unearthing and exploring tensions in the play’s representation of a Sikh community, this article sheds light on some of the tensions in multicultural Britain in order to complicate and challenge an interpretation of the dispute in terms of a reductive binary of creative freedom versus religious censure and censorship. While, for the liberal secularist critic and proponent of free expression, the explosion of taboos is vital to an expansion of freedom, a hard-line adoption of this position that fails to account for the material specificities of a religious response to a creative work, including the demography of the protestors, can result in a curtailment of the freedom of a religious minority. Reading the play in dialogue with the controversy it generated, this article seeks to ground the outbreak of religious minority offence in its local material conditions and, by doing so, to underline the unequal access to social, cultural, and spatial capital that shaped the controversy. It focuses in particular on religious symbols, space, and speech, exploring how they figure in both the literary and social texts.

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)0.002
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 score0.015
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.028
Scholarly communication0.0070.003
Open science0.0010.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.036
GPT teacher head0.220
Teacher spread0.184 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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