Trajectories of coparenting quality across ethnically diverse and interethnic parents
Bibliographic record
Abstract
The Interracial Couples’ Life Transitions (ICLT) model proposes that: i) interethnic parents experience more coparenting difficulties upon the birth of a child compared to same-ethnicity parents; and ii) there exists heterogeneity in interethnic parents’ coparenting quality, thus the coparenting experience cannot be generalized across all interethnic unions. In the present work, we examined these two propositions using a large-scale database of elevated risk, fragile families. In Study 1, we compared the longitudinal trajectories of coparenting in interethnic parents ( n = 574 mother-father unions) and their matched same-ethnicity counterparts ( n = 574 each mothers and fathers) and found that interethnic parents of Asian, Black, Hispanic, and White backgrounds consistently experienced lower and decreasing trajectories of coparenting compared to their counterparts across the first 9 years of a child’s life. In Study 2, we examined heterogeneity in coparenting trajectories for only interethnic mothers and fathers ( n = 1148) and found a three-trajectory profile in which the majority (75.5%) of parents fall into a contented (stable and high) coparenting profile. Our findings confirm and extend on the ICLT model, showing that most interethnic parents experience more coparenting difficulties across time compared to their counterparts, and although there is some heterogeneity in interethnic parents’ coparenting trajectories, most interethnic parents appear to experience stable and content coparenting across time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".