Changes in social support and the emotional health of immigrant, refugee, and non-immigrant children across middle childhood: A three year follow up study.
Bibliographic record
Abstract
ObjectivesChildren who are new to Canada have unique circumstances that can be associated with their emotional health. Using linked immigration and child self-report data, we examined associations between changes in children’s social support and emotional health from ages 9 to 12, for immigrant, refugee, and non-immigrant children. ApproachA population sample of N = 4664 immigrant, refugee, and non-immigrant children reported on their peer support and school belonging, as well as their emotional health (life satisfaction, self-esteem, sadness), in Grades 4 and 7. Social support and emotional health were measured using the Middle Years Development Instrument (MDI). Migration background including age at arrival, migration class, generation status, and source region, was obtained from the Immigration, Refugees, and Citizenship Canada database, individually linked to MDI records using children’s Personal Education Number and child date of birth. Multi-level modelling assessed associations adjusting for confounders. ResultsIn the linked sample, 19% of children were first- or second-generation economic immigrants (themselves or their parents were born outside of Canada), 8% were family immigrants, and 5% were refugees. Children with refugee backgrounds reported lower life satisfaction and self-esteem and higher sadness in Grade 4 compared to all other groups. Children with immigration backgrounds reported lower life satisfaction and self-esteem and higher sadness compared to non-immigrants. Refugee children had significantly more positive changes in emotional health from Grades 4 to 7 compared to non-immigrants, and significantly more positive changes in social supports. Positive changes in social supports were associated with positive changes in emotional health of similar magnitude for all children, regardless of migration background. Children with refugee backgrounds on average experienced improved emotional health during middle childhood, and changes in peer support partially accounted for these changes. ConclusionResults suggest that children with migration backgrounds enter school with lower emotional health and are likely to benefit from increased social supports. Likewise, incorporating opportunities to build peer relationships and school belonging is likely to benefit all children, regardless of migration background.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".