Exploring housing instability through a gender lens among people who inject drugs in Montreal, Canada
Bibliographic record
Abstract
INTRODUCTION: Housing instability contributes to harm among people who inject drugs (PWID). We examined determinants of varying levels of housing instability and explored gender differences in housing instability and associated determinants among PWID. METHOD: We used baseline data from HEPCO, a community-based cohort of PWID in Montreal, Canada (2011-2022). Housing (past 3 months) was categorised as stable, precarious (i.e., temporary accommodation) or unsheltered. Multinomial logistic regression was used to assess relationships between sociodemographic factors, recent drug use, and housing instability. A multivariable model was constructed using the full sample. Gender differences were explored via stratified and unadjusted analyses given the relatively small number of women. RESULTS: A total of 911 PWID (748 men and 163 women) were included. In the multivariable model, not living in a marriage-like relationship, recent incarceration, and not reporting recent heroin use were associated with both precarious housing and being unsheltered, relative to stable housing. Employment, consumption of cocaine, amphetamines, and other opioids were only associated with being unsheltered. In stratified analyses, precarious and unsheltered housing was reported by 14.1% and 23.3% of women and 20.9% and 30.9% of men. Sociodemographic factors and drug use patterns also differed by gender. Although most associations with housing instability were in similar directions for men and women, several estimates differed in magnitude, denoting some signals of gender differences. DISCUSSION AND CONCLUSION: Almost half the sample was unsheltered or precariously housed. Studies with larger samples of women should formally examine the relevance of developing gender-specific responses to housing instability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".