Group Differences in Intermarriage with Whites between Asians, Blacks, and Hispanics: The Effects of Assimilation and Structural Constraints
Why this work is in the frame
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Bibliographic record
Abstract
This study examines the reasons for differences in the prevalence of intermarriage with Whites between racial minorities in 283 U.S. metropolitan areas. The analysis demonstrates that Asians have the highest and Blacks the lowest rate of intermarriage with Whites, with Hispanics falling in between. We tested two theories for these group differences. First, the structural explanation, which posits that differences in the relative size of each racial group in marriage markets affects their chances for intermarriage. Second, the assimilation explanation, which suggests that differences in social distance with Whites influences the propensity for intermarriage. The decomposition analysis shows that the cultural assimilation explanation is the primary reason for the Hispanic–Black gap in intermarriage. However, both explanations predict Black–Asian and Asian–Hispanic differences in intermarriage with Whites.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it