The Healthy or Chronically Ill Immigrant
Bibliographic record
Abstract
Utilizing the longitudinal component of the National Population Health Survey (NPHS) (1994/1995-2000/2001), designed to collect comprehensive information on the health status of the Canadian population and related socio-demographic information, differences in health status between immigrants and non-immigrants (i.e., native-born individuals) were explored. Specifically, the analysis investigated how chronic conditions influence the health of immigrants, the role of stress and mental health upon immigrant health status, and the influence and role of previously underrepresented variables such as age and arrival cohorts on foreign-born health status. The conceptual approach of this project draws upon a 'population health' perspective, which suggests that the most influential determinants of human health status are non-medical in nature, but rather can be identified as the social and economic characteristics of individuals. Analysis was completed through the use of ordinary least squares stepwise regression and logistic stepwise regression in association with descriptive stochastic methodologies. Analysis of the mental health and stress variables suggests that, contrary to what has been expressed in literature in the past, both immigrants and the native-born do not perceive stress, distress, or depression to be major problems or health concerns in their lives. Furthermore, the analysis indicated, as was expected, that older immigrants are at greater risk of developing more chronic conditions relative to younger groups, and that arrival cohorts, the period in which an immigrant entered the nation, do exert a considerable influence on the health status of the foreign-born. Surprisingly, this analysis indicates that the Healthy Immigrant Effect (HIE), which proposes that recent immigrants, regardless of country of birth, tend to be in better health than the Canadian-born population upon entering the nation, may be more apparent than real, especially when investigating mental health and stress conditions amongst the foreign-born.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".