Nativity Status and Access to Care in Canada and the U.S.: Factoring in the Roles of Race/Ethnicity and Socioeconomic Status
Bibliographic record
Abstract
We conducted cross-country comparisons of Canada and the U.S., and assessed the extent to which access to care varies by nativity status overall, as well as in conjunction with race/ethnicity and socioeconomic status. Data came from the Joint Canada-U.S. Survey of Health (n=6,620 non-elderly adults). Access measures included having a regular medical doctor, consultation with a health professional in the past year, dentist visit in the past year, Pap test in the past three years, and any unmet health care needs in the past year. Logistic regression was employed to estimate the relative odds of access to care, adjusting for potential confounders. Disparities in access to care based on nativity status overall, as well as nativity-by-race joint effects, were found in both countries. There was also a dose-response effect of education on access to care among the native-born but not among the foreign-born; there were few nativity-by-income joint effects.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".