Rising Ethnic Diversity in the United States Accompanies Shifts Toward an Individualistic Culture
Bibliographic record
Abstract
We investigate the relationship between ethnic diversity and the rise of individualism in the United States during the 20th and 21st centuries. Tests of the historical rates of ethnic diversity alongside individualistic relational structures (e.g., adults living alone, single-/multi-child families) from the years 1950 to 2018 reveal that societal and regional rates of ethnic diversity accompanied individualistic relational structures. These effects hold above and beyond time-series trends in each variable. Further evidence from experimental studies ( N = 707) suggests that the presence of, and contact with, ethnically diverse others contributes to greater individualistic values (e.g., the importance of uniqueness and personal achievement). Converging evidence across societal-, regional-, and individual-level analyses suggests a systematic link between ethnic diversity and individualism. We discuss the implications of these findings for sociocultural livelihood in light of the rising rates of ethnic diversity across the globe.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".