Adolescent males in out-of- home care: Past adversity and current functioning
Bibliographic record
Abstract
Adolescent males comprise a significant number of youth in out-of-home care, yet our understanding of their past adverse experiences and current functioning remains relatively limited. The current study relied on data from the Assessment and Action Record—second Canadian version for a representative sample of 508 12- to 17-year-olds in out-of-home care across the province of Ontario (Canada). Findings indicated high rates of maltreatment (especially emotional abuse) as the primary reason for child welfare entry, with an elevated occurrence of multiple exposure to different types of maltreatment (71.6% of youth). Once in care, male youth appeared vulnerable to continuing adverse experiences, with 23.8% experiencing maltreatment (emotional abuse and neglect) and non-maltreatment adversity primarily in the form of school changes and suspensions. Results on current functioning suggested some relative strengths (e.g., developmental assets) but also challenges in the areas of substance use, mental health, caregiver relationship, and academic performance. Past emotional abuse and neglect, as well as greater maltreatment exposure, significantly predicted greater substance use, while greater past-year individual adversities (e.g., school changes and suspensions) predicted poorer academic performance. Findings point to the importance of child welfare’s continued monitoring of adolescent males’ safety and well-being across home and school settings, as well as the reliance on trauma-informed practices to address the multiple needs of male youth in out-of-home care. Our findings also highlight the importance of using data in child welfare practice to regularly assess the well-being of youth in out-of-home care for purposes of service planning and delivery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".