Perceptions of Canadian Federal Policy Responses to COVID-19 among People with Disabilities and Chronic Health Conditions
Bibliographic record
Abstract
This study examines how people with disabilities and chronic health conditions—members of a large and diverse group often overlooked by Canadian public policy—are making sense of the Canadian federal government’s response to COVID-19. Using original national online survey data collected in June 2020 ( N = 1,027), we investigate how members of this group view the government’s overall response. Although survey results show broad support for the federal government’s pandemic response, findings also indicate fractures based on disability type and specific health condition, political partisanship, region, and experiences with COVID-19. Among these, identification with the Liberal party and receipt of CERB stand out as associated with more positive views. Further examination of qualitative responses shows that these views are also linked to differing perspectives surrounding government benefits and spending, partisan divisions, and other social and cultural cleavages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".