SEX DIFFERENCES IN LIFE EXPECTANCY IN CANADA: IMMIGRANT AND NATIVE-BORN POPULATIONS
Bibliographic record
Abstract
A growing body of research often indicates that immigrant populations in Western countries enjoy a lower level of mortality in relation to their native-born host populations. In this literature, sex differences in mortality are often reported but substantive analyses of the differences are generally lacking. The present investigation looks at sex differences in life expectancy with specific reference to immigrant and Canadian-born populations in Canada during 1971 and 2001. For these two populations, sex differences in expectation of life at birth are decomposed into cause-of-death components. Immigrants in Canada have a higher life expectancy than their Canadian-born counterparts. In absolute terms, immigrant females enjoy the highest life expectancy. In relative terms, however, immigrant men show a larger longevity advantage, as their expectation of life at birth exceeds that of Canadian-born men by a wider margin than do foreign-born females in relation to Canadian-born females. It is also found that immigrants have a smaller sex differential in life expectancy as compared with the Canadian born. Decomposition analysis shows this is a function of immigrants having smaller sex differences in death rates from heart disease and cancer. Factors thought to underlie these differentials between immigrants and the Canadian born are discussed and suggestions for further research are given.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".