Initiation of drug dealing among a prospective cohort of street-involved youth
Bibliographic record
Abstract
BACKGROUND: Street-involved youth who use drugs may have limited income-generation options and are known to commonly become immersed in illicit drug markets to generate funds. However, little attention has been given to factors that may drive drug dealing initiation among this vulnerable population. OBJECTIVES: This longitudinal study examines drug dealing initiation among street-involved youth. METHODS: Data were derived from the At-Risk Youth Study from September 2005 to November 2014; a prospective cohort of 194 street-involved youth who use drugs aged 14-26, in Vancouver, Canada. Extended Cox model was used to identify factors independently associated with time to first drug dealing. RESULTS: Among street-involved youth who had never dealt drugs at baseline, 56 (29%) individuals initiated drug dealing during the study period for an incidence density of 13.0 per 100 person-years (95% confidence interval [CI]: 9.9-17.2). In multivariable Cox regression analysis, male gender (adjusted hazard ratio [AHR] = 1.90, 95% CI: 1.06-3.42), homelessness (AHR = 1.88, 95% CI: 1.05-3.35), crystal methamphetamine use (AHR = 2.48, 95% CI: 1.47-4.20), and crack cocaine use (AHR = 2.35, 95% CI: 1.38-4.00) were positively and independently associated with initiating drug dealing. CONCLUSION: Homelessness and stimulant drug use were key risk factors for drug dealing initiation among street-involved youth. Findings indicate that evidence-based and innovative interventions, including youth-centric supportive housing, low threshold employment programs, and stimulant addiction treatment should be implemented and evaluated as strategies to help prevent this vulnerable population from engaging in risky illegal income generation practices.
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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 | 0.000 |
| 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".