Cumulative and Cascading Impacts of Invisibility: An Intersectional Approach to Understanding the Housing Experiences of Canadians With Disabilities During COVID-19
Bibliographic record
Abstract
In this chapter, we examine the unique and heightened negative impacts of the COVID-19 pandemic through tracing how the preexisting social conditions of exclusion and precarity in which many disabled people live, effected access to safe, affordable, and accessible housing in Canada. We then illustrate the reverberating impacts housing choices have on how people with disabilities lived, lived well, and how they faced barriers to living well during the COVID-19 pandemic.,Using an intersectional livelihoods approach, we analyzed semi-structured interviews and focus groups with 32 diverse people with disabilities, 12 key informant semi-structured interviews, as well as academic and community literature and a social media scan of key disability advocacy organizations in Canada.,Pandemic-related policies in Canada often excluded people with disabilities, either overlooking barriers to access and safety, which exacerbated the already precarious livelihoods of people with disabilities or over-emphasized the usefulness of social adaptions such as work from home. These exclusions had more profound consequences for people with disabilities from historically marginalized groups, as they often faced increased barriers to livelihoods pre-pandemic, and disability- or care-specific policies failed to consider intersectional experiences of discrimination. People with disabilities formed communities of care to meet their needs and those of their loved ones.,To achieve a responsive policy response that addresses the cascading impacts of risk and care, it is necessary for governments to engage, early and often, with people with disabilities, disability leaders and organizations in emergency planning and beyond.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.042 | 0.025 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.014 |
| 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".