More educated people are more WEIRD: Higher education predicts global cultural similarity to WEIRD countries
Bibliographic record
Abstract
Behavioral scientists increasingly recruit participants from less-WEIRD societies, but continue to oversample highly educated people, such as university students and online workers. Here we test how representative highly educated individuals are of the world’s cultural diversity. We used the cultural fixation index (CFST) to measure cultural distance between people with high and low education in 95 countries (N=268,992), across beliefs, values, and behaviors assessed by the World Values Survey (2005–2022). We find that more highly educated people are significantly more culturally similar to WEIRD countries, including the United States, Anglosphere, and Western Europe. Education did not predict cultural similarities to other large, culturally and politically influential countries, such as China, Russia, and India. Income and self-reported subjective status did not show the same pattern of WEIRD cultural similarity. Our results are consistent with hypotheses linking formal education with Western culture and suggest that cross-cultural samples of university-educated individuals underrepresent the world’s cultural variation.
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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 | 0.000 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".