Parent-Child Separations and Mental Health among First Nations and Métis Peoples in Canada: Links to Intergenerational Residential School Attendance
Bibliographic record
Abstract
First Nations children are over 17 times more likely to be removed from their families and placed in the child welfare system (CWS) than non-Indigenous children in Canada. The high rates of parent-child separation have been linked to discriminatory public services and the Indian Residential School (IRS) system, which instigated a multi-generational cycle of family disruption. However, limited empirical evidence exists linking the IRS to subsequent parent-child separations, the CWS, and mental health outcomes among First Nations, Inuit, and Métis populations in Canada. The current studies examine these relationships using a nationally representative sample of First Nations youth (ages 12-17 years) living in communities across Canada (Study 1), and among First Nations and Métis adults (ages 18+ years) in Canada (Study 2). Study 1 revealed that First Nations youth with a parent who attended IRS had increased odds of not living with either of their biological parents, and both IRS and not living with biological parents independently predicted greater psychological distress. Similarly, Study 2 revealed that First Nations and Métis adults with familial IRS history displayed greater odds of spending time in the CWS, and both IRS and CWS predicted elevated depressive symptoms. The increased distress and depressive symptoms associated with parent-child separations calls for First Nations-led interventions to address the inequities in the practices of removing Indigenous children and youth from their families.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".