Maternal and Paternal Attributions in the Prediction of Boys' Behavior Problems Across Time
Bibliographic record
Abstract
We examined the extent to which mother and father attributions for child behavior problems predict child behavior problems over time, accounting for the other parent's attributions, initial child problems and the child's attention-deficit/hyperactivity disorder (ADHD) status. Parents of 7- to 12-year-old boys with (n = 26) and without (n = 38) ADHD participated. Parents completed the Strengths and Difficulties Questionnaire (SDQ) as a measure of their son's behavior problems as well as the Written Analogue Questionnaire, reporting their attributions for child behavior problems. Parents completed the SDQ a second time 7 months later. Both mother and father attributions were associated with child behavior problems at Time 1 and again 7 months later. However, when ADHD status and the other parent's attributions for child behavior were controlled, only father attributions predicted child behavior problems, and continued to be uniquely predictive of child behavior problems at Time 2 even with initial child behavior problems controlled. Father attributions provide unique information above and beyond mother attributions when considering current and future child behavior problems.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".