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Record W4380925781 · doi:10.3138/ctr.109.013

Live and Kicking: A Disabled Audience Member Contemplates the Body in the Audience and on the Stage

2002· article· en· W4380925781 on OpenAlexvenueno aff
Joanne Buckley

Bibliographic record

VenueCanadian Theatre Review · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNothingMAGIC (telescope)Performing artsSightAestheticsNoticeVisual artsArtSpectacleFront (military)PsychologyMedia studiesSociologyEngineeringLawPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

As a person who loves live theatre and tries to get to as much of it as is humanly possible, and as a person who happens to be physically disabled (in a wheelchair with cerebral palsy), I have thought plenty about the role of the body – mine and theirs, the audience member and the practically double-jointed, rubber-bodied performer for whom physical risk seems nothing on stage. People notice that the physical reality of live theatre is a dominant force for me: I shriek at the sight of actors wrestling a life-like lizard in front of me in Night of the Iguana at the Tom Patterson Theatre in Stratford; I am astounded at Susan Strohman’s gifts as a choreographer, whether she is teaching folks to do some high stepping in the London production of Oklahoma or shepherding actors and actresses dressed as old ladies and wielding walkers on the Broadway stage of The Producers. For me, one of the perks of live theatre is that it involves real risk to the physical body – theirs, not mine. Granted, some of it – maybe most of it – is illusion, though not as much as in the World Wrestling Federation. Still, actors do fall off stages from time to time; there are often doctors standing in the wings, and, to top it off, they can do what I can’t, sometimes eight shows weekly, and that is at least part of the magic of performance.

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)0.001
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 score0.855
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.247
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 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
Published2002
Admission routes1
Has abstractyes

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