Links Between Parental Psychological Violence, Other Family Disturbances, and Children's Adjustment
Bibliographic record
Abstract
In a sample of 143 parent-child dyads from two-parent and separated families, this investigation documented the links between parental psychological violence and separation or divorce, severity of parental conflict, triangulation of the child in this conflict, and polarized parent-child alliances. The unique and combined contributions of all these variables to children's behavior problems were also assessed. Participants were parents, mostly mothers, and their 10-12-year-old child. They were recruited through schools, community organizations, and newspapers. Questionnaires were administered at home. Findings suggest that separated families undergo more relational disturbances than two-parent families (more severe conflicts, more triangulation, stronger parent-child alliances), but the amount of parental psychological violence was similar in both groups. Psychological violence was associated with the severity of parental conflict, especially in two-parent families. Triangulation of the child in parental conflict was another correlate of psychological violence. Once all variables were controlled for, psychological violence remained the only significant correlate of children's externalized behavior problems. These findings raise the importance of preventing psychological violence toward children, especially in families plagued with severe parental conflicts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".