The health of homeless immigrants
Bibliographic record
Abstract
BACKGROUND: This study examined the association between immigrant status and current health in a representative sample of 1189 homeless people in Toronto, Canada. METHODS: Multivariate regression analyses were performed to examine the relationship between immigrant status and current health status (assessed using the SF-12) among homeless recent immigrants (< or = 10 years since immigration), non-recent immigrants (>10 years since immigration) and Canadian-born individuals recruited at shelters and meal programmes (response rate 73%). RESULTS: After adjusting for demographic characteristics and lifetime duration of homelessness, recent immigrants were significantly less likely to have chronic conditions (RR 0.7, 95% CI 0.5 to 0.9), mental health problems (OR 0.4, 95% CI 0.2 to 0.7), alcohol problems (OR 0.2, 95% CI 0.1 to 0.5) and drug problems (OR 0.2, 95% CI 0.1 to 0.4) than non-recent immigrants and Canadian-born individuals. Recent immigrants were also more likely to have better mental health status (+3.4 points, SE +/-1.6) and physical health status (+2.2 points, SE +/-1.3) on scales with a mean of 50 and a SD of 10 in the general population. CONCLUSION: Homeless recent immigrants are a distinct group who are generally healthier and may have very different service needs from other homeless people.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".