Residential eviction and exposure to violence among people who inject drugs in Vancouver, Canada
Bibliographic record
Abstract
Background—People who inject drugs (PWID) experience markedly elevated rates of physical and sexual violence, as well as housing instability. While previous studies have demonstrated an association between homelessness and increased exposure to violence among PWID, the relationship between residential eviction and violence is unknown. We therefore sought to examine the association between residential eviction and experiencing violence among PWID in Vancouver, Canada. Methods—Data were derived from two open prospective cohort studies of PWID: the Vancouver Injection Drug Users Study (VIDUS) and the AIDS Care Cohort to evaluate Exposure to Survival Services (ACCESS). We used generalized estimating equations (GEE) to estimate the relationship between residential eviction and experiencing violence among male and female PWID, respectively. Results—Between June 2007 and May 2014, 1689 participants were eligible for the analysis, contributing a median of 5.5 years of follow-up. Of these, 567 (33.6%) were female. In total, 259 (45.7%) of females and 566 (50.4%) of males experienced at least one incident of violence over the study period. In multivariable GEE models, residential eviction was independently associated with greater odds of experiencing violence among both females (Adjusted Odds Ratio [AOR] =2.09; 95% confidence interval [CI]: 1.39–3.13) and males (AOR = 1.95; 95% CI = 1.49–2.55), after adjustment for potential confounders. Conclusion—Residential eviction was independently associated with an increased likelihood of experiencing violence among both male and female PWID. These findings point to the need for evidence-based social-structural interventions to mitigate housing instability and violence among PWID in this setting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".