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Record W4380881000 · doi:10.3138/ctr.122.012

Building Communities: Disability Arts Festivals in Canada

2005· article· en· W4380881000 on OpenAlexvenueaboutno aff
Kirsty Johnston

Bibliographic record

VenueCanadian Theatre Review · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsVisual artsWork (physics)SociologySpace (punctuation)ArtAestheticsEngineering

Abstract

fetched live from OpenAlex

Disability arts festivals showcase and celebrate the voices of a distinct and talented community of artists. Several such festivals have been held in Canada since 2001, and theatre has played a prominent role in each. Together, the festivals have built connections with, and contributed to, a growing international disability arts culture. The term “disability arts” is drawn from the work of several artists, artistic facilitators and leaders in the movement. They use it to describe and connect art work created by people who determine a strong link between disability experience and their art. Many are careful to explain that such work is not the mere by-product of art therapy. Rather, it is intentional artistic work. Disability arts festivals provide a forum for community building by allowing artists who work in different locations and operate in different artistic media to connect their works around the concept of disability. Although the range of ways in which artists interpret, involve and experience disability and disability arts is vast, festivals create venues in which artists and audiences can express and connect their ideas. In short, they organize time and space in which communities can form and gather momentum.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.570

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0180.004
Scholarly communication0.0050.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.057
GPT teacher head0.287
Teacher spread0.230 · 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 designObservational
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
Published2005
Admission routes2
Has abstractyes

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