Exhibiting activist disability history in Canada:<i>Out from under</i>as a case study of social movement learning
Bibliographic record
Abstract
This article introduces the exhibit called Out from Under: Disability, History and Things to Remember and positions it as a focal point for exploring questions of disability, museum exhibition and adult education. Created by the School of Disability Studies at Ryerson University in Toronto, Out from Under was the first public exhibit of disability history in Canada (2007–2014) and the first to be displayed at the prestigious Royal Ontario Museum. With adult education in mind, we unravel some of the strands of teaching and learning woven through this lengthy, creative project. Highlighting a complex blend of actors and forms of knowing, we consider the knowledge activated through exhibit creation as well as a subsequent formal study of visitor responses. We situate the whole project as a robust and rare example of social movement learning through practices that crossed the borders between disability/mad rights movements, an undergraduate programme of Disability Studies and a major Canadian museum.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.052 | 0.024 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".