11: The Mental Health and Wellbeing of Refugee Children in Detention in Canada: A Pilot Study
Bibliographic record
Abstract
In Canada asylum seekers may be detained in prison-like institutions. This includes children. The official statistics of the CBSA suggest that between 2005 and 2010, >650 children were detained each year. While international studies acknowledge the negative health consequences of detention on children, until now there has been no research on the detention of children in Canada. This study aimed to generate an understanding of the well-being, health and experiences of migrant children who have been detained in Canada by documenting their perspectives during or after detention. This was a qualitative study anchored in an ethnographic methodology. Data was collected using two methods: 1) in-depth interviews with 18 families, who had been detained or were detained at the time of interview; and 2) participatory observation in the field (at the detention centres in Montreal and Toronto). Detention impacts on children mental health, wellbeing and sense of identity was documented. Results suggest that even very brief periods of detention are distressing for children, with potentially longstanding sequelae. During detention, children are often separated from one or both parents, which appears to compound suffering. Children's narratives show that detention may negatively impact their sense of self and safety in Canada. Children experience detention as highly stressful, frightening and even, in some cases, traumatizing. Our findings suggest that detention may be significant determinant of health for this subgroup of children and that future policy and advocacy efforts should address this.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".