The influence of disability-related dwelling adaptations on household dwelling satisfaction
Bibliographic record
Abstract
Much existing housing stock is inaccessible and does not adequately meet the needs of households with disabled members. As a result, households must often seek dwelling adaptations to improve the accessibility of their existing housing. However, adaptations can be costly, particularly in the context of limited state subsidies. This study examines the extent to which households with disabled members in Ontario, Canada’s most populous province, have access to needed dwelling adaptations and the impact of these adaptations on dwelling satisfaction. Using data from the Canadian Housing Survey, we find that close to ten percent of Ontario households need one or more disability-related dwelling adaptations, but close to half of these households do not have all the adaptations they need. Households led by older adults are more likely to have needed dwelling adaptations, as are renter households in the social housing sector. With respect to dwelling satisfaction, households with needed adaptations reported similar levels of satisfaction to households without disabled members, while households who did not have needed adaptations reported significantly lower satisfaction with their dwellings. These findings signal the importance of improving state supports for dwelling adaptations as one part of a broader commitment to inclusive housing policy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".