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Record W2587989664 · doi:10.3138/tric.37.2.239

<i>May I have this dance?</i> Teaching, Performing, and Transforming in a University-Community Mixed-Ability Dance Theatre Project

2016· article· en· W2587989664 on OpenAlexaffvenue
Lisa Doolittle, Callista Chasse, Corey Makoloski, Pamela C. Boyd, Annalee Yassi

Bibliographic record

VenueTheatre Research in Canada · 2016
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of British ColumbiaUniversity of Lethbridge
Fundersnot available
KeywordsDanceDramaDance educationContext (archaeology)CurriculumEmbodied cognitionPedagogyGeneral partnershipSociologyConcert dancePsychologyVisual artsArtPolitical scienceGeography

Abstract

fetched live from OpenAlex

Combining disability and dance may not be new, yet enacting inclusive dance/drama education in a university remains rare. This article reflects on the integration of people with developmental disabilities in dance theatre, particularly in institutions of higher education, and shares insights that emerged in the context of an inclusive dance-theatre project. Over two years, the project progressed from a community-based art for social change partnership, to a post-secondary drama course, to a large-scale, university-produced theatrical production. Drawing on qualitative, embodied, and quantitative data the authors critically reflect on the potential for integrated dance theatre work to contribute to training future professional artists with disabilities, to enrich curriculum for students without disabilities, to inform theory and practice in the field of art for social change, and to positively affect the perceptions and experiences of people living with disabilities.

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)0.004
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 score0.669
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 science0.0010.000
Research integrity0.0000.002
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 head0.072
GPT teacher head0.348
Teacher spread0.276 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

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