Racial/Ethnic Variation in the Relationship Between Educational Assortative Mating and Wives' Income Trajectories
Bibliographic record
Abstract
Prior work has examined the relationship between educational assortative mating and wives' labor market participation but has not assessed how this relationship varies by race/ethnicity. Using data from the National Longitudinal Survey of Youth 1979, we estimate group-based developmental trajectories to investigate whether the association between educational assortative mating and wives' income trajectories varies by race/ethnicity. The presence, prevalence, and shapes of prototypical long-term income trajectories vary markedly across racial/ethnic groups. Whites are more likely than Blacks and Hispanics to follow income trajectories consistent with a traditional gender division of labor. The association between educational assortative mating is also stronger for Whites than for Blacks and Hispanics. White wives in educationally hypogamous unions make the greatest contribution to the couple's total income, followed by those in homogamous and hypergamous unions. Black and Hispanic wives in hypogamous unions are less likely than their peers in other unions to be secondary earners. These findings underscore the need for studies of the consequences of educational assortative mating to pay closer attention to heterogeneity across and within racial/ethnic groups.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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 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".