A Global Meta-analysis of the Immigrant Mortality Advantage
Bibliographic record
Abstract
A large body of research on the “Healthy Immigrant Effect” (or “Paradox”) has reported an immigrant mortality advantage. However, other studies do not find such significant effects, and some even present contradictory evidence. This article is the first systematic meta-analysis that investigates the immigration-mortality relationship from a global perspective, examining 1,933 all-cause and cardiovascular mortality risk estimates from 103 publications. Our comprehensive analysis allows us to assess interactions between origin and destination regions and to reexamine, on a global scale, some of the most notable explanations for the immigrant mortality advantage, including suggestions that this paradox may be primarily the result of selection effects. We find evidence for the existence of a mild immigrant mortality advantage for working-age individuals. However, the relationship holds only for immigrants who moved between certain world regions, particularly those who immigrated from Northern Africa, Asia, and Southern Europe to richer countries. The results highlight the need in the broader migration literature for an increased focus on selection effects and on outcomes for people who chose not to migrate or who were denied entry into their planned destination country.
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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 | 0.020 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.026 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".