Inequities in child protective services contact among First Nations and non-First Nations parents in one Canadian province: a retrospective population-based study
Bibliographic record
Abstract
BACKGROUND: Parental contact with child protective services (CPS) has been linked to deteriorating health among parents. Capturing rates of CPS contact among parents is therefore important for understanding inequities in exposure and their potential role in amplifying racial inequities in health and wellbeing. Though an extensive body of research in North America has provided population-level analyses of CPS contact among children, a disproportionate percentage of whom are Indigenous, no studies to date have extrapolated estimates to account for contact in parent populations, leading to a fragmented view of the system's reach and impact beyond the child-level. In order to advance health equity-oriented research in this domain, our study calculated previously unexplored population-level estimates of CPS contact among First Nations and non-First Nations parents. METHODS: We used whole-population linked data from Manitoba (Canada) to identify 119,883 birthing parents (13,171 First Nations; 106,712 non-First Nations) who had their first child between 1998 and 2019. We calculated prevalence rates, rate differences, and rate ratios of parental contact with different levels of CPS by First Nations status (categorization used in Canada for Indigenous peoples who are members of a First Nation), including ever had an open CPS file for child(ren), ever had out-of-home placement of child(ren), and ever had termination of parental rights (TPR). RESULTS: Overall, 49.6% of First Nations parents had a CPS file open for their child(ren) (vs. 13.1% among non-First Nations parents), 27.4% had out-of-home placement of their child(ren) (vs. 4.7% among non-First Nations parents), and 9.6% experienced TPR (vs. 1.8% among non-First Nations parents). CONCLUSIONS: CPS contact was high among parents and prevalence was almost 4 times higher among First Nations parents, where 1 out of 2 were intervened upon by CPS. Findings reinforce significant concerns about the system's scope and the crucial importance of considering its role in compounding health inequities and sustaining colonialism in Canada. First Nations-led interventions are needed to reduce CPS disruption to the lives of First Nations peoples.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".