The Overlap Between the Child Welfare and Youth Justice Systems in Manitoba, Canada
Bibliographic record
Abstract
IntroductionManitoba has one of the highest rates of children taken into care of child welfare services (Child and Family Services; CFS) in the world, and also one of the highest youth incarceration rates in Canada. Policy-makers recognize there is overlap between these systems; the extent of that overlap is unknown. Objectives and ApproachWe linked CFS, Justice, and Population Health Registry data to quantify the overlap between having a history of CFS during childhood (0-17 years) and being charged with a crime as a youth (12-17 years). Using a cohort approach, we selected all individuals in Manitoba who were born in 1988 (N=28,178); those not in the province at any time from 12-17 years were excluded, leaving a final cohort of 18,182. The cohort was divided into 3 groups according to CFS involvement: CFS out-of-home care (1,148); CFS in-home services (3,395); no CFS (13,639). Criminal charges between 12-17 years were identified. Results6.3% of our cohort had CFS out-of-home care, 18.7% received CFS in-home services, and 75% had no CFS involvement. 10.5% of the cohort were charged of a crime between 12-17 years. Almost half (46.6%) of youth who had CFS out-of-home care had criminal charges, compared to 19.4% of youth who had CFS in-home services, and 5.3% of youth with no CFS. Despite accounting for only 6.3% of the cohort, youth who had out-of-home care accounted for 28.0% of youth with criminal charges. Indigenous (First Nations (FN) and Metis) children/youth were over-represented in both systems; for example, 24.5% of FN youth had been in care compared to 3.1% of non-Indigenous; and 32.2% of FN youth were charged with a crime compared to 6.6% of non-Indigenous youth. Conclusion/ImplicationsThere is substantial overlap between the child welfare and youth justice systems, with overrepresentation of Indigenous youth in both systems. Culturally appropriate programs and policies aimed at supporting parents, families and communities to care for their own children will likely have long-term positive impacts on the youth justice system.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".