Parents’ Attributions for Negative and Positive Child Behavior in Relation to Parenting and Child Problems
Bibliographic record
Abstract
Previous research has stressed the importance of parents' attributions and parenting for child problems. Based on social cognitive models, studies have focused on the interrelations among parents' child-responsibility attributions for negative behavior, harsh parenting, and child problems. Little is known about the extent to which child-responsibility attributions for positive behavior and other types of parenting play a role in these models. The purpose of this study was to examine whether parents' child-responsibility attributions for positive and negative child behaviors are related to child problems, and whether these relations are mediated by harsh, lax, and positive parenting. Mothers' and fathers' attributions and parenting were examined separately. A community sample of 148 couples and their 9- to 12-year-old child (50% boys) participated in the study. Mothers and children participated by completing questionnaires and a laboratory interaction task. Fathers participated by completing the same questionnaires as mothers. Harsh parenting was the only parenting variable that uniquely mediated the relations between more child-responsibility attributions for (a) negative child behaviors and child problems for both parents and (b) the inverse relation between attributions for positive child behaviors and child problems for fathers. Findings confirm the importance of harsh parenting and demonstrate the importance of parents' attributions for positive child behaviors in relation to decreasing harsh parenting and child problems. Clinically, it may be useful not only to reduce child-responsibility attributions for negative behaviors but also to increase the extent to which parents give their child credit for positive behaviors.
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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 | 0.018 |
| 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 | 0.001 |
| 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".