Clinical Characteristics of Alcohol Drinking and Acculturation Issues Faced by Korean Immigrants in the United States
Bibliographic record
Abstract
Koreans in the United States can be grouped based on their diverse immigration histories and levels of acculturation: 1st-generation (Il-Sei), 1.5 generation (Il-Jom-O-Sei), 2nd-generation (Yi-Sei), 3rd-generation (Sam-Sei), and so on. Generational differences often account for different norms and behaviors regarding alcohol consumption. Difficulties for 1st-generation Koreans arise when seeking treatment for mental health and alcohol or substance abuse problems because of language barriers and cultural differences. The purpose of this study is to explore the characteristics of alcohol consumption by Il-Sei Koreans who were born, raised, and educated in Korea and immigrated to the United States after age 18. Immigration stress, Korean drinking norms and traditions, the influence of Confucianism, acculturation, availability of Korean alcohol, and health treatment disparity issues are addressed.
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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 | 0.002 |
| 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 | 0.001 |
| 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".