Ethnicity and Postmigration Health Trajectory in New Immigrants to Canada
Bibliographic record
Abstract
OBJECTIVES: In this prospective cohort study, we examined the trajectory of general health during the first 4 years after new immigrants' arrival in Canada. We focused on the change in self-rated health trajectories and their gender and ethnic disparities. METHODS: Data were derived from the Longitudinal Survey of Immigrants to Canada and were collected between April 2001 and November 2005 by Statistics Canada. We used weighted samples of 3309 men and 3351 women aged between 20 and 59 years. RESULTS: At arrival, only 3.5% of new immigrants rated their general health as poor. Significant and steady increases in poor health were revealed during the following 4 years, especially among ethnic minorities and women. Specifically, we found a higher risk of poor health among West Asian and Chinese men and among South Asian and Chinese women than among their European counterparts. CONCLUSIONS: Newly arrived immigrants are extremely healthy, but the health advantage dissipates rapidly during the initial years of settlement in Canada. Women and minority ethnic groups may be more vulnerable to social changes and postmigration settlement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".