Comparative Patterns of Interracial Marriage: Structural Opportunities, Third-party Factors, and Temporal Change in Immigrant Societies
Bibliographic record
Abstract
Using census data, we compare patterns of interracial marriage in six different contexts where immigration has played a central role in population composition. We use Kalmijn’s (1998) general theoretical perspective that emphasizes how opportunity structures and third-party factors affect inter-group marriage rates. More specifically, we hypothesize that rates of intermarriage are influenced by: (1) structural opportunities as reflected by the history of inequality, segregation, and racial oppression, (2) third-party interests such as cultural and linguistic differences, and (3) societal trends that reflect choices in the formation of intimate relationships and racial equality. We use age as a surrogate for the trends over time. We first estimate log-linear models to gauge the extent of overall homogamy and race specific homogamy in each cultural setting. We then use multinomial logistic regression to evaluate age differences. Cross- cultural differences in rates of intermarriage are substantial. Intermarriage is more common in societies where structural opportunities for contact are high and third-party interests low (Hawaii and New Zealand), almost non-existent among some groups in societies where the strong inter-group tensions remain, (Xinjiang Province, China and South Africa), and intermediate in societies with moderate degrees of opportunities and third-party interests (United States and Canada). Age is generally negatively associated with intermarriage, with some interesting exceptions. Interracial marriage in general is becoming more common in the arenas we examine.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".