Outcomes of children involved with child protection in Manitoba, Canada: a demonstration project for working in partnership across government, community organizations, and academia.
Bibliographic record
Abstract
ObjectivesSPECTRUM is a unique multi-disciplinary, cross-sector collaborative research partnership between academics, government, and community organizations in Manitoba working together to address complex social problems. In our first research project, partners identified the need for quantitative evidence around outcomes of children involved with Child Protection Services (CPS), using linked administrative data. ApproachFrom the SPECTRUM partnership, a research team with CPS expertise was established, including government policy-makers, community organizations representing First Nations families, and academics from multiple disciplines. The research is guided by an Advisory Circle of First Nations Knowledge Keepers. Linking health, education, CPS, and justice data we developed a matched cohort identifying children involved with CPS (2007-2018) for whom there was discretion in the decision to 1) place them in out-of-home care (n=19,718), or 2) keep them in their family home while providing services (n=28,154). Instrumental Variable analysis, with CPS agency as the instrument, will be used to compare outcomes. ResultsFollowing the trajectories of these two groups of CPS-involved children over time, we will compare their mental and physical health, educational achievement, and justice system involvement while accounting for individual-level (e.g., age, sex, chronic health conditions) and family-level (e.g., family income, maternal mental health, number of siblings) factors that may contribute to these outcomes. Preliminary findings will be workshopped with the SPECTRUM partnership to facilitate discussions on framing the evidence for policy makers. The SPECTRUM policy team will then prepare policy recommendations for government to consider. The Advisory Circle and a youth advisory squad will facilitate contextualizing and mobilizing findings. Actions taken by government in response to material provided will be monitored and will inform the development of subsequent research projects conducted by SPECTRUM. ConclusionGovernment and community stakeholder involvement throughout bolsters the likelihood of evidence translating into program and policy changes. This is not a situation where academics are telling government how to do their jobs – this is government, community organizations, and academics working together with the shared goal of better outcomes for children.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".