FACTORS ASSOCIATED WITH UNMET HEALTHCARE NEEDS IN OLDER ASIAN AMERICANS
Bibliographic record
Abstract
Abstract Older Asian Americans are the fast-growing but understudied population in health disparities research. Using a sample that reflects cultural/linguistic diversity, the present study explored general (health insurance, usual place for care, income) and immigrant-specific (nativity, length of stay in the US, English proficiency, acculturation) risk factors of unmet healthcare needs in older Asian Americans. Data were drawn from the Asian American Quality of Life survey (N = 533). With the inclusion of a considerable number of non-English-speaking individuals, the present sample presented a high rate of unmet healthcare needs. Those with a shorter stay in the US, limited English proficiency, and lower level of acculturation had increased odds of having unmet healthcare needs than their counterparts after controlling for background characteristics. Challenging the myth of model minority, findings highlight the importance of immigrant-specific factors in identifying risk groups of unmet healthcare needs and demonstrate vulnerability in access to healthcare.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".