In-group trust and self-rated health in East Asia using quadri-national survey data
Bibliographic record
Abstract
This study aims to examine the relationship between types of interpersonal trust and health in East Asia. We doubt that generalized trust toward “most people” is a valid and reliable measure of interpersonal trust in East Asia. We thus employ specific measures of in-group and out-group trust to test whether and how each type of trust is associated with self-rated health. We use data from the 2012 East Asian Social Survey administered in China ( n = 5819), Japan ( n = 2335), South Korea ( n = 1396), and Taiwan ( n = 2314) with response rates of 71%, 59%, 56%, and 52%, respectively. Empirical test produces three major findings. First, in-group trust is consistently associated with self-rated health in all four countries, whereas out-group trust is related to health only in Taiwan. By contrast, generalized trust is related to health only in Korea. Second, perceived social support mediates partially of the relationship between in-group trust and self-rated health in China, Japan, and Taiwan. Third, the health benefit of in-group trust is more pronounced in Korea than in China. This study thus calls for the need to use measures of specific types of trust because they are more sensitive in detecting both international and intra-regional variations of health.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".