Bibliographic record
Abstract
Australian victim-survivors of disability institutional violence have been unable to obtain public recognition and justice through conventional court-based processes and legal remedies. Redressing or ‘setting right’ the ongoing and structural phenomenon of disability institutional violence requires a new approach. This article introduces one dimension that might form part of such an approach: re-engaging through sites of conscience practices with former disability institutions. Sites of conscience practices engage the broader community in memories and histories of places of injustice in order to prompt collective action to prevent further injustice through broader social and legal change. The article proposes that through sites of conscience practices former disability institutions in Australia can be part of how we collectively recognise and ‘set right’ disability institutional violence. The article begins by explaining the approach to ‘disability institutions', ‘disability institutional violence’ and ‘redress'. Next, the article uses the example of Peat and Milson Island Hospital (New South Wales, Australia) to discuss how former disability institutions – through demolition/dereliction, repurposing or redevelopment – might sustain disability institutional violence. The article then introduces the concept of ‘sites of conscience’ and presents examples of sites of conscience practices in relation to former disability institutions across United States, Canada, United Kingdom and Denmark. Reflecting on these examples, the article makes preliminary suggestions of how we might re-position engagement with the memories, places and materiality of former disability institutions as integral to redressing disability institutional violence in Australia.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".