Official language proficiency and self-reported health among immigrants to Canada.
Bibliographic record
Abstract
BACKGROUND: New immigrants to Canada initially report better health than does the Canadian-born population. With time, this "healthy immigrant effect" appears to diminish. Limited ability to speak English or French has been identified as a possible factor in poor health. This analysis explored the relationship between self-reported official language proficiency and transitions to poor self-reported health. DATA AND METHODS: Statistics Canada's Longitudinal Survey of Immigrants to Canada tracked a sample of the 2001 immigrant cohort for four years (6, 24 and 48 months after arrival). Data from each of the three survey waves were available for 7,716 respondents. Bivariate and multivariate analysis were used to examine associations between official language proficiency and self-reported health, by sex, controlling for selected pre-migration and post-migration factors. The prevalence of poor health among immigrants was compared with rates among the Canadian-born population, based on data from the Canadian Community Health Survey. RESULTS: Among a representative sample of recent immigrants, the prevalence of poor self-reported health had risen substantially, especially among women, after four years in Canada. Prolonged limited official language proficiency was strongly associated with a transition to poor health among male and female immigrants who had earlier reported good health. Other factors significantly associated with an increase in the prevalence of poor self-reported health differed by sex. Refugee status, self-reported discrimination, and living in Vancouver were significant for men. Age, health care access problems, and limited friendliness of neighbours were significant for women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".