The More (Social Group Memberships), the Merrier: Is This the Case for Asians?
Bibliographic record
Abstract
While previous studies have consistently shown that belonging to multiple groups enhances well-being, the current research proposes that for Asians, multiple group memberships (MGM) may confer fewer well-being benefits. We suggest that this is due, in part, to Asian norms about relationships and support seeking, making Asians more reluctant to enlist social support due to concerns about burdening others. Overall, MGM was associated with enhanced well-being in Westerners (Study 2), but not Asians (Studies 1-3). Study 2 showed that social support mediated the relationship between MGM and well-being for Westerners only. In Study 3, among Asians, MGM benefited the well-being of those who were least reluctant to enlist support. Finally, reviewing the MGM evidence-base to date, relative to Westerners, MGM was less beneficial for the well-being of Asians. The evidence underscores the importance of culture in influencing how likely individuals utilize their group memberships as psychological resources.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".