The prevalence and social-structural correlates of housing status among women living with HIV in Vancouver, Canada
Bibliographic record
Abstract
BACKGROUND: Women living with HIV (WLWH) experience numerous social and structural barriers to stable housing, with substantial implications for access to health care services. This study is the first to apply the Canadian Definition of Homelessness (CDOH), an inclusive national guideline, to investigate the prevalence and correlates of housing status among WLWH in Metro Vancouver, Canada. METHODS: Our study utilized data from a longitudinal open cohort of cisgender and trans WLWH aged 14 years and older, in 2010-2019. Cross-sectional descriptive statistics of the prevalence of housing status and other social and structural variables were summarized for the baseline visits. Bivariate and multivariable logistic regression analyses were conducted using generalized linear mixed models (GLMM) for repeated measures to investigate the relationship between social and structural correlates and housing status among WLWH. RESULTS: The study included 336 participants with 1930 observations over 9 years. Housing status derived from CDOH included four categories: unsheltered, unstable, supportive housing, and stable housing (reference). Evidence suggested high levels of precarious housing, with 24% of participants reporting being unsheltered, 47% reporting unstable housing, 11.9% reporting supportive housing, and 16.4% reporting stable housing in the last six months at baseline. According to the multivariable models, living in the Downtown Eastside (DTES) neighbourhood of Metro Vancouver, hospitalization, physical/sexual violence, and stimulant use were associated with being unsheltered, compared to stable housing; DTES residence, hospitalization, and physical/sexual violence were associated with unstable housing; DTES residence and stimulant use were associated with living in supportive housing. CONCLUSION: Complex social-structural inequities are associated with housing instability among WLWH. In addition to meeting basic needs for living, to facilitate access to housing among WLWH, housing options that are gender-responsive and gender-inclusive and include trauma- and violence-informed principles, low-barrier requirements, and strong connections with supportive harm reduction services are critical.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 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".