Philosophy of Disability, Conceptual Engineering, and the Nursing Home-Industrial-Complex in Canada
Bibliographic record
Abstract
In this article, I indicate how the naturalized and individualized conception of disability that prevails in philosophy informs the indifference of philosophers to the predictable COVID-19 tragedy that has unfolded in nursing homes, supported living centers, psychiatric institutions, and other institutions in which elders and younger disabled people are placed. I maintain that, insofar as feminist and other discourses represent these institutions as sites of care and love, they enact structural gaslighting. I argue, therefore, that philosophers must engage in conceptual engineering with respect to how disability and these institutions are understood and represented. To substantiate my argument, I trace the sequence of catastrophic events that have occurred in nursing homes in Canada and in the Canadian province of Ontario in particular during the pandemic, tying these events to other past and current eugenic practices produced in the Canadian context. The crux of the article is that the COVID-19 pandemic has thrown into vivid relief the carceral character of nursing homes and other congregate settings in which elders and younger disabled people are confined.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.046 | 0.052 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".