Individualism: A Valid and Important Dimension of Cultural Differences Between Nations
Bibliographic record
Abstract
Oyserman, Coon, and Kemmelmeier's (2002) meta-analysis suggested problems in the measurement of individualism and collectivism. Studies using Hofstede's individualism scores show little convergent validity with more recent measures of individualism and collectivism. We propose that the lack of convergent validity is due to national differences in response styles. Whereas Hofstede statistically controlled for response styles, Oyserman et al.'s meta-analysis relied on uncorrected ratings. Data from an international student survey demonstrated convergent validity between Hofstede's individualism dimension and horizontal individualism when response styles were statistically controlled, whereas uncorrected scores correlated highly with the individualism scores in Oyserman et al.'s meta-analysis. Uncorrected horizontal individualism scores and meta-analytic individualism scores did not correlate significantly with nations' development, whereas corrected horizontal individualism scores and Hofstede's individualism dimension were significantly correlated with development. This pattern of results suggests that individualism is a valid construct for cross-cultural comparisons, but that the measurement of this construct needs improvement.
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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 | 0.031 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".