Relaxed Performance: Exploring University-based Training Across Fashion, Theatre, and Choir
Bibliographic record
Abstract
Over the course of the 2019—2020 academic year, the British Council and Bodies in Translation (BIT) at the Re•Vision Centre for Art and Social Justice at the University of Guelph partnered with three universities in Turtle Island, in the province known as Ontario, to introduce Relaxed Performance (RP) training modules into existing fashion studies, theatre, and choral studies curriculums. Through this RP Curriculum Pilot project, up to 240 students at X University, York University, and the University of Guelph, respectively, learned best practices and how to incorporate RP principles into their mid-term and final projects, which were open to the public. \n \nThis report chronicles the RP Curriculum Pilot, a project built on findings from the 2019 "Relaxed Performance: Exploring Accessibility in the Canadian Theatre Landscape" report, which pointed to the promise of disability justice–led RP training and delivery for improv- ing accessible performances. Over the course of this training, BIT researchers employed a mixed methods framework using surveys, interviews, participant observation, and analysis of materials produced through the RP training. Through this data generation, we gained insight into RP as a vibrant, creative intervention with roots in European theatre–based disability activism. Each discipline engaged in RP for different reasons and developed its own set of strategies around making a crip fashion show, a relaxed theatre production, and a choral ensemble performance more accessible; all of these performances reflect RP’s growing application across sectors. \n \nThe work of RP is community-based and must be community-led, beginning with the meaningful inclusion of disabled people as RP trainers, also known as Access Activators. Following the guiding principles of disability justice, RP’s community-based approach must preserve and nurture its vitality by expanding its context-specific relationships with those who report being underrepresented in RP, specifically Deaf and Indigenous communities. Additionally, it is clear that as a justice-oriented praxis, RP must continue to strive to respond to and develop context- and industry-specific “vital practices” that will vary across performances as RP continues to grow, becoming transdisciplinary and increasingly transnational in scope.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.018 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".