What and Who Are “Essential”? A Disability Justice Perspective on COVID-19 Measures and the Diverse Disability Communities in Ontario
Bibliographic record
Abstract
Central to Ontario’s COVID-19 response was defining, supporting, and protecting essential services and, by extension, essential people – often through decision-making processes that were ad hoc and lacking in meaningful public engagement. This paper examines the Ontario government’s public health responses to the COVID-19 pandemic, from the early steps taken in 2020 by provincial officials to develop a triage protocol for hospitals that would discriminate against those who fall outside of the narrow view of essential people – especially disabled and older people – to the implementation of public health measures that also disadvantaged diverse disability communities in a multitude of settings and far-reaching, multiple, and intersecting ways. Selectively drawing on online local and national newspapers across Canada that mentioned COVID-19 and people with disabilities from March 2020 to June 2020, we examined the ways in which disabled people have been rendered invisible, invaluable, disposable, and “non-essential” as they struggle to survive the pandemic largely outside of provincial COVID-19 response frameworks. Through this analysis, we craft a contrasting understanding of “essential” that attends to the principles of disability justice, shifting interdependencies, and the diversity and mutuality of human needs. Drawing on examples of mutual aid and caregiving in diverse disabled communities, we also explore disability justice as an alternative framework that leaves no one behind.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.051 | 0.062 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 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".