Bibliographic record
Abstract
A meta-analysis of published cross-cultural studies of self-enhancement reveals pervasive and pronounced differences between East Asians and Westerners. Across 91 comparisons, the average cross-cultural effect was d = .84. The effect emerged in all 30 methods, except for comparisons of implicit self-esteem. Within cultures, Westerners showed a clear self-serving bias (d = .87), whereas East Asians did not (d = -.01), with Asian Americans falling in between (d = .52). East Asians did self-enhance in the methods that involved comparing themselves to average but were self-critical in other methods. It was hypothesized that this inconsistency could be explained in that these methods are compromised by the "everyone is better than their group's average effect" (EBTA). Supporting this rationale, studies that were implicated by the EBTA reported significantly larger self-enhancement effect for all cultures compared to other studies. Overall, the evidence converges to show that East Asians do not self-enhance.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".