Assortative Mating and Intergenerational Persistence of Schooling and Earnings
Bibliographic record
Abstract
Research on intergenerational mobility has often treated outcomes such as schooling and earnings as being imperfectly transmitted from one parent to a child. But because the characteristics of both parents are important in shaping children’s outcomes, the way in which a generation of parents is sorted into couples is likely to be a key determinant of intergenerational persistence. Mating patterns are assortative—that is, individuals tend to partner with people similar to themselves—and this is typically measured by similarity of educational attainment. I present the first estimates of the effect of assortative mating on intergenerational persistence of schooling and earnings. I measure assortative mating as the rank correlation of couples’ educational attainment, that is, the degree to which the most highly-educated men partner with the most highly-educated women. Using data on parents and children in the United States, I find that assortative mating explains about one quarter of the observed intergenerational persistence of schooling and earnings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".