Rental Housing Type and Self-Reported General Health and Mental Health Status: Evidence from the Canadian Housing Survey 2018–2019
Bibliographic record
Abstract
Using the Canadian Housing Survey, 2018-2019, we examined self-reported general and mental health among tenants residing in various housing types, including cooperative, non-profit, government, and private housing. Adjusting for confounders, we discovered that tenants in not-for-profit housing reported the highest odds, over four and half times (odds ratio 4.63), of poor general health compared to tenants in privately owned housing in Canada. On the other hand, the odds were reversed for tenants in cooperative housing and government housing, with 24% and 33% lower odds of poor general health, respectively, compared to tenants in privately owned housing. Moreover, we found that tenants in not-for-profit (1.26) and government housing (1.43) reported higher odds of poor mental health. On the other hand, tenants in cooperative housing reported 42% lower odds of poor mental health than tenants in privately owned housing. Furthermore, we observed variations in the odds of poor general and poor mental health among tenants from different equity-seeking groups across different housing types. These findings highlight the importance of considering housing type and equity factors in understanding health outcomes among tenants.
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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 | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".