Does diversity foster individualism? The relation of racial-ethnic diversity to individualism-collectivism across the 50 American States
Bibliographic record
Abstract
Recent longitudinal research by others analyzing the relation between racial-ethnic diversity and individualism-collectivism in the 50 American states over the period 2000–2018 suggests that racial-ethnic diversity promotes individualism. The present study used a cross-sectional approach based on 2013 data to determine whether a relation mirroring the longitudinal pattern exists between racial-ethnic diversity and individualism-collectivism across the 50 states. Two measures of state racial-ethnic diversity were related to four measures of state individualism-collectivism using Pearson correlation and partial correlation controlling for state socioeconomic status. All correlations between diversity and individualism were negative and all those between diversity and collectivism were positive. The absolute magnitudes ranged from .43 to .68 for the Pearson correlations and from .43 to .67 for the partial correlations. Contrary to the earlier longitudinal findings, the current results show that states with higher racial-ethnic diversity are less individualistic and more collectivistic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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 teacher head, 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".