South Asian-White health inequalities in Canada: intersections with gender and immigrant status
Bibliographic record
Abstract
OBJECTIVES: We apply intersectionality theory to health inequalities in Canada by investigating whether South Asian-White health inequalities are conditioned by gender and immigrant status in a synergistic way. DESIGN: Our dataset comprised 10 cycles (2001-2013) of the Canadian Community Health Survey. Using binary logistic regression modeling, we examined South Asian-White inequalities in self-rated health, diabetes, hypertension and asthma before and after controlling for potentially explanatory factors. Models were calculated separately in subsamples of native-born women, native-born men, immigrant women and immigrant men. RESULTS: South Asian immigrants had higher odds of fair/poor self-rated health, diabetes and hypertension than White immigrants. Native-born South Asian men had higher odds of fair/poor self-rated health than native-born White men and native-born South Asian women had lower odds of hypertension than native-born White women. Education, household income, smoking, physical activity and body mass index did little to explain these associations. The three-way interaction between racial identity, gender and immigrant status approached statistical significance for hypertension but not for self-rated health and asthma. CONCLUSION: Our findings provide modest support for the intersectionally inspired principle that combinations of identities derived from race, gender and nationality constitute sui generis categories in the manifestation of health outcomes.
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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 | 0.002 | 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 | 0.001 | 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".