Bibliographic record
Abstract
McCarthy and associates observe that analyses of racial/ethnic health disparities in countries with substantial recent immigrant populations must consider the effects of nativity, for this factor influences health differences. We acknowledge this crucial observation, and indeed we are familiar with the literature on healthy migrants. For example, an up-to-date Statistics Canada report indicates that foreign-born individuals report fewer chronic conditions than nonimmigrants.1 This foreign-born advantage persists after the introduction of controls for age, education, and income. Of interest to McCarthy and others, this report also observes that health risk behaviors (e.g., tobacco consumption) differ between immigrants and nonimmigrants, but that these differences cannot account for the differences in health outcomes. We have completed research—also using nationally representative data—into the healthy migrant (or immigrant) effect, specifically testing whether this phenomenon applies to depression and whether the effect on depression varies with length of residence.2 Our results confirmed that the healthy migrant advantage with regard to depression appears to be concentrated among recent, non-European immigrants, especially Asians, and therefore may not be generalizable. Other research shows a similar pattern for chronic conditions and disabilities.3 In other words, the so-called healthy migrant effect may be spurious and could actually represent a socio-cultural health effect. McCarthy and colleagues remark that we should be more cautious in our speculative explanation for the superior functional health of Canadian Blacks compared with US Blacks, considering that national differences in immigration histories may confound our findings. We agree that differences in health care policies may not hold the answer, but data and space limitations prevented us from giving a more satisfying explanation. In any case, modeling the healthy migrant effect is virtually impossible without data from source countries, which are necessary to determine whether individual health status is a consistent selection factor in the international migration process. Our results do, however, confirm that the reported functional health of Canadian Blacks is better after control for immigrant status. We therefore rule out the healthy migrant effect as a valid explanation for why Canadian Blacks are healthier than the Canadian average. Moreover, US research demonstrates that Black–White health differences are attenuated after control for socioeconomic status.4 This finding lends indirect support to our argument that Canada’s single-payer health insurance system is a plausible reason for health differences between Canadian and US Blacks. In the United States, in contrast to Canada, there is obviously a robust correlation between health care access and socioeconomic status.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.527 | 0.322 |
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".