Premarital Characteristics, Selection into Marriage, and African American Marital Disruption
Bibliographic record
Abstract
African Americans have long experienced high marital disruption rates relative to other groups in the United States. Attempts to explain those differences using economic and demographic factors have met with limited success. Using longitudinal data from two waves of the National Survey of Families and Households, I examine the relationship between pre-marital attitudinal factors and the racial gap in marital disruption. I first compare the attitudes of initially unmarried African Americans who went on to marry with those of their non-African American counterparts. I find certain important differences, but on the whole they do not contribute to the African Americans' higher rates of marital disruption. As a group, African Americans who marry are highly religious and hold relatively traditional attitudes towards pre-marital sex and cohabitation. The prevalence of such traits results, in part, from high selectivity into marriage. African Americans who marry differ substantially from those who remain single in ways that are generally associated with a lower risk of marital disruption. Stated otherwise, African American singles who would tend to face the highest risk of divorce disproportionately decide not to marry. Among non-African Americans, by contrast, individuals who marry are much more representative of the initial marriage pool as a whole. Were African Americans who marry not such a highly selected group with respect to their attitudinal characteristics, the racial gap in marital disruption would be substantially larger than it is.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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 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".