Marital Conflict Trajectories and Associations With Children's Disruptive Behavior
Bibliographic record
Abstract
Abstract We seek to identify heterogeneous trajectories of marital conflict during the early childhood period, identify predictors associated with these trajectories, and examine associations between trajectory group membership and children's disruptive behavior. Participants were 469 families examined 4 times when the children were 2 to 54 months of age. Maternal reports of marital conflict, adverse childhood experiences, depressive symptoms, and sociodemographic characteristics were collected, and averaged maternal and paternal reports of child disruptive problems were used. Using growth mixture modeling, 3 trajectories of marital conflict were identified: high increasing (21.8%), high decreasing (7%), and low stable (71.2%). Maternal adverse childhood experiences predicted increased risk of belonging in the high‐increasing group, whereas depressive symptoms predicted increased risk of belonging in the high‐decreasing group. Importantly, children of mothers in the high‐increasing group exhibited higher levels of disruptive behavior at 54 months when compared with children of mothers in the high‐decreasing and low‐stable 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 | 0.000 | 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 | 0.000 | 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".