Neurodivergency and Interdependent Creation: Breaking into Canadian Disability Arts
Bibliographic record
Abstract
Disability arts has traditionally been understood as that which is led, created, and/or curated by disabled artists. While disability arts and culture in Canada has continued to grow and develop over the last number of decades, I have perceived a notable lack of neurodivergent artists being included at disability arts events and community gatherings. I question if this lack of representation may be due in part to this perception of disability arts as having to be led exclusively by those with lived experience of disability. In this paper, I will critically engage with concepts of inter-abled artistic collaboration, interdependency and the need to re-imagine disability arts leadership structures to better include neurodivergent artists and their allies. I will further position my ideas around this topic within the context of the roundtable discussion on the future of disability arts leadership that took place at the Cripping the Arts Symposium in 2019.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.056 | 0.037 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".