Bibliographic record
Abstract
For many autistic performers in arts and entertainment, the stage can be an important site of self-advocacy and creative expression. Whereas everyday social interactions may be unpredictable, being onstage can allow autistic performers to work from a script and anticipate audience responses. This article explores the affordances and challenges of performance for young autistic adults in Canada through interviews with four autistic performers (two singers and two stand-up comics). While solo performance was the focus, participants discussed the creative employment of diverse media platforms, from the stage to screenwriting and children’s books, and emphasized the need for autistic people to be involved in all creative realms. This research follows a Critical Disability Studies (CDS) framework which challenges deficit models of autism (McGuire, 2016), “supercrip” tropes (Clare, 2015, p. 2), and narratives of overcoming autism (Cheng, 2017). While one participant noted being uncomfortable with the sense that they were a source of inspiration for non-autistic audiences, each found it encouraging that autistic audiences relate to their work and might be motivated to participate in similar forms of self-advocacy; in particular, they noted the value of performance in building confidence. As previous CDS literature is wary of disability as spectacle (Darke, 1994), this research provides insight into how young autistic adults use their work onstage and behind the scenes to promote and perform self-advocacy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".