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Record W1800444551 · doi:10.14288/acme.v2i1.705

Performing Nursing: BC Nurses’ Union Theatre Project

2015· article· en· W1800444551 on OpenAlexaffabout
Geraldine Pratt, Elia E. Kirby

Bibliographic record

VenueOpen Collections · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEmbodied cognitionSpace (punctuation)Context (archaeology)PoliticsRepresentation (politics)Political theatreTheatre studiesSociologyVisual artsArtPolitical scienceHistoryDramaLawComputer scienceArchaeology

Abstract

fetched live from OpenAlex

We examine a collaborative theatre project, between Vancouver theatre artists and the British Columbia Nurses’ Union (BCNU). We consider conflict that emerged in and around the project in an effort to understand some of the potentials of theatre as a technology for social change and broader debates about the politics of representation. Theatre is a rich site for thinking about epistemologies that blur the line between context and text, and text and embodied practice. The space of theatre does not hold still but works with and moves into other spaces. This can be understood through the concept of 'interspatiality.' We end by considering how theatre might move into the space of academic writing and practice.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.550
Threshold uncertainty score0.906

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0290.013
Scholarly communication0.0080.001
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0140.002

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 head0.074
GPT teacher head0.310
Teacher spread0.236 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations29
Published2015
Admission routes2
Has abstractyes

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