High prevalence of exposure to the child welfare system among street-involved youth in a Canadian setting: implications for policy and practice
Bibliographic record
Abstract
Background: Street-involved youth are more likely to experience trauma and adverse events in childhood; however, little is known about exposure to the child welfare system among this vulnerable population. This study sought to examine the prevalence and correlates of being in government care among street-involved youth in Vancouver, Canada. Methods: From September 2005 to November 2012, data were collected from the At-Risk Youth Study, a prospective cohort of street-involved youth aged 14–26 who use illicit drugs. Logistic regression analysis was employed to identify factors associated with a history of being in government care. Results: Among our sample of 937 street-involved youth, 455 (49%) reported being in government care at some point in their childhood. In a multivariate analysis, Aboriginal ancestry (adjusted odds ratio [AOR] = 2.07; 95% confidence interval [CI]: 1.50 – 2.85), younger age at first “hard” substance use (AOR = 1.10; 95% CI: 1.05 – 1.16), high school incompletion (AOR = 1.40; 95% CI: 1.00 – 1.95), having a parent that drank heavily or used illicit drugs (AOR = 1.48; 95% CI: 1.09 – 2.01), and experiencing physical abuse (AOR = 1.90; 95% CI: 1.22 – 2.96) were independently associated with exposure to the child welfare system. Conclusions: Youth with a history of being in government care appear to be at high-risk of adverse illicit substance-related behaviours. Evidence-based interventions are required to better support vulnerable children and youth with histories of being in the child welfare system, and prevent problematic substance use and street-involvement among this population.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".