The Healthy migrant effect on depression: variation over time?
Bibliographic record
Abstract
English Growing international evidence supports the epidemiological paradox thatimmigrants have better overall health than non-immigrants, including lowerlevels of depression. But whether length of residence in the host populationmodifies this effect on depression is not well understood. We examine a large,heterogeneous sample of Canadians to investigate three possible trajectories ofdepression within the immigrant population. We present hypotheses testing ifthe depression rate among immigrants improves, deteriorates, or undergoes nonlinearchange over time. Our results confirm the so-called 'healthy migranteffect' and show that visible minority immigrants are especially healthy.However, soon after arrival in Canada, depression among immigrants increasesfor several decades. Policy implications of the findings are discussed. French De plus en plus d'études internationales importantes supportent le paradoxeépidémiologique qui démontre que les immigrants sont en général en meilleuresanté et souffrent moins de dépression que les non-immigrants. Mais nous necomprenons pas encore bien si le nombre d’années de résidence au sein de lanouvelle population modifie cet effet. Nous avons examiné un large échantillonhétérogène de Canadiens pour étudier trois trajectoires d’évolution possibles dela dépression au sein de la population immigrante. Nous présentons différenteshypothèses pour évaluer si la dépression chez les immigrants s’améliore, sedétériore ou continue de façon non-linéaire au fil des années. Nos résultatsconfirment ce qui est appelé « l’effet de l’immigrant en bonne santé etdémontrent que la santé des immigrants appartenant aux minorités visibles estencore meilleure que celle des autres immigrants. Cependant, peu après leurarrivée au Canada, le taux des dépressions chez les immigrants augmentependant plusieurs décennies. Les implications des ses résultats au niveau despolices sont discutées.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".