Public crack cocaine smoking and willingness to use a supervised inhalation facility: implications for street disorder
Bibliographic record
Abstract
BACKGROUND: The health risks of crack cocaine smoking in public settings have not been well described. We sought to identify factors associated with public crack smoking, and assess the potential for a supervised inhalation facility to reduce engagement in this behavior, in a setting planning to evaluate a medically supervised crack cocaine smoking facility. METHODS: Data for this study were derived from a Canadian prospective cohort of injection drug users. Using multivariate logistic regression we identified factors associated with smoking crack cocaine in public areas. Among public crack smokers we then identified factors associated with willingness to use a supervised inhalation facility. RESULTS: Among our sample of 623 people who reported crack smoking, 61% reported recently using in public locations. In multivariate analysis, factors independently associated with public crack smoking included: daily crack cocaine smoking; daily heroin injection; having encounters with police; and engaging in drug dealing. In sub analysis, 71% of public crack smokers reported willingness to use a supervised inhalation facility. Factors independently associated with willingness include: female gender, engaging in risky pipe sharing; and having encounters with police. CONCLUSION: We found a high prevalence of public crack smoking locally, and this behavior was independently associated with encounters with police. However, a majority of public crack smokers reported being willing to use a supervised inhalation facility, and individuals who had recent encounters with police were more likely to report willingness. These findings suggest that supervised inhalation facilities offer potential to reduce street-disorder and reduce encounters with police.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".