Within-family processes: Interparental and coparenting conflict and child adjustment.
Bibliographic record
Abstract
Previous studies have found evidence that interparental conflict, parents' coparenting behavior, and children's adjustment are reciprocally related. Most prior research, however, has failed to empirically distinguish between-family differences from within-family changes, limiting our understanding of how within-family fluctuations in each construct may be interrelated over time. In the present study, we focused on within-family associations among interparental conflict factors (i.e., verbal aggression and withdrawing), coparenting conflict, and children's internalizing and externalizing problems. Longitudinal data were drawn from 5 annual waves of survey data from 537 German families (i.e., mothers, fathers, and a focal child) in the German Family Panel (pairfam) study (Brüderl et al., 2015; Huinink et al., 2011). Data were analyzed with random intercept cross-lagged panel models, which partition variance into between- and within-person (or family) components in longitudinal data. Cross-lagged analyses of within-family variance revealed that fluctuations in interparental conflict did not predict child problems, but higher than typical child externalizing problems increased fathers' withdrawal and coparenting conflict in the future. Higher than average coparenting conflict within a given family predicted reductions in interparental verbal aggression, less maternal withdrawal, and fewer child externalizing problems. The findings demonstrate that analyses of within-family associations may provide new insights on mutual influences that unfold across time within families and are of particular importance for informing practice. (PsycINFO Database Record
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".