Examining the Types of Social Support and the Actual Sources of Support in Older Chinese and Korean Immigrants
Bibliographic record
Abstract
This study explored social support domains and actual sources of support for older Chinese and Korean immigrants and compared them to the traditional domains based on mainly White, middle class populations. Fifty-two older Cantonese and Korean speaking immigrants participated in one of eight focus groups. We identified four similar domains: tangible, information/advice, emotional support, and companionship. We also identified needing language support which is relevant for non-English speaking minority populations. Participants discussed not needing emotional support. These Chinese and Korean immigrants had a small number of actual sources of support, relying mainly on adult children for help with personal situations (e.g., carrying heavy groceries, communicating with physicians) and friends for general information/advice (e.g., learning how to speak English, applying for citizenship) and companionship. Immigrant Asians are caught between two different traditions; one that is strongly kinship oriented where needs and desires are subordinated to the interests of the family and one that values independence and celebrates individuality. Despite their reticence in asking for help outside the family, elders are seeking help from other sources, such as ethnic churches and the government.
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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 | 0.003 |
| 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) | 0.001 | 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".