Immigrant child health in Canada: a scoping review
Bibliographic record
Abstract
INTRODUCTION: Understanding the health of immigrant children from birth to 18 years of age is important given the significance of the early childhood years and complexity of factors that may influence the health status of immigrant populations. Thus, the purpose of this review was to understand the extent and nature of the literature on the health of immigrant children in Canada. METHODS: We conducted a scoping review of the literature. The review was focused on studies of first-generation and second-generation immigrant children aged 0-18 years. We completed standardised data extraction of immigration status, immigration route, age of children, data source, health or clinical focus, country of origin and major findings. RESULTS: In total, 250 published papers representing data from 237 studies met the inclusion criteria for this study. A total of 178 articles used quantitative methodologies (mostly survey and cross-sectional study designs), 54 used qualitative methodologies and 18 used mixed methodologies. The articles considered in this review included 147 (59%) focusing on physical health, 76 (30%) focusing on mental health and 37 (15%) focusing on the social aspects of health for refugee and first-generation and second-generation immigrant children across the provinces and territories of Canada. CONCLUSIONS: Several literature gaps exist with respect to child immigrant health in Canada. For instance, there are no exclusive studies on immigrant boys and limited studies on children of international students.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.020 | 0.029 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".