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Record W2584592457 · doi:10.3138/tric.37.2.263

Infrequently Asked Questions, or: How to Kickstart Conversations Around Inclusion and Accessibility in Canadian Theatre and Why it Might be Good for Everybody

2016· article· en· W2584592457 on OpenAlexvenueaboutno aff
Jan Derbyshire

Bibliographic record

VenueTheatre Research in Canada · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsConversationInclusion (mineral)Diversity (politics)PedagogySociologyPsychologyPublic relationsMedia studiesVisual artsPolitical scienceArtGender studiesLawCommunication

Abstract

fetched live from OpenAlex

I have a habit of liking to flip the familiar. In theatre this manifests as a driving obsession to look for artistic practices and models that work well for institutes, companies, and creators and ask: is this the way you’ve always done things? It’s a good question to start the rock rolling on issues of diversity, inclusion, and accessibility. No matter what the answer is, I like to invite people to start a conversation, to ask who is involved in these successful systems and who isn’t? Not everyone is interested. Heidi Taylor, Artistic and Executive Director of the Playwrights’ Theatre Centre (PTC) in Vancouver, is. Together we developed ACK Lab, an investigation on how to make the PTC Playwright’s Colony, a yearly writing intensive at PTC, more inclusive and accessible to persons with perceived or self-identified disabilities. It was graciously funded by the Bly Capacity grant, a LAMDA initiative and a Canada Council “Leadership for Change” grant. It involved six months of intense conversations and a ten-day workshop during December 2015.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.790

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 studies0.0010.000
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 head0.079
GPT teacher head0.330
Teacher spread0.251 · 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 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

Citations2
Published2016
Admission routes2
Has abstractyes

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