Bibliographic record
Abstract
BACKGROUND: The relationship between health status and Hispanic ethnicities, language, and nativity is poorly understood, due to the limitations and conflicting findings of previous studies. OBJECTIVES: To examine the effects of language and nativity on health status in Hispanic ethnic subgroups and non-Hispanic whites (whites). RESEARCH DESIGN: Cross-sectional analyses of data from the 1998-2004 National Health Interview Survey linked to the 1999-2005 Medical Expenditure Panel Survey. Health status was regressed on race/ethnicity, interview language, and nativity, with adjustment for demographic and socioeconomic variables. SUBJECTS: A total of 16,489 Hispanics (13,522 Mexicans, 778 Cubans, 1360 Puerto Ricans, and 829 Dominicans) and 45,422 whites. MEASURES: SF-12 mental (MCS-12) and physical (PCS-12) component summary scores. RESULTS: In adjusted analyses, Mexicans had significantly higher MCS-12 scores than other Hispanics and whites, with the largest advantage noted for Spanish-speaking Mexicans. Ethnic origin * nativity interaction effects were significant for both MCS-12 [adjusted Wald test, F (3236) = 7.27, P = 0.0001] and PCS-12 [F (3236) = 4.75, P = 0.0031]. Continental US-born Mexicans had worse mental and physical health status than non-US-born Mexicans. By contrast, continental US birth was associated with better mental health status for Cubans and Dominicans, and better physical health status for Puerto Ricans. CONCLUSIONS: Complex interactions exist among language, nativity, ethnicity, and health status among Hispanics. Mexicans have better health status than whites and other Hispanics, and the moderating effects of nativity and language differ for Mexicans compared with other Hispanics. Future research should approach Hispanics as a diverse grouping rather than a monolithic entity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".