Child aggression and parenting behavior: Understanding the child-driven effects with parents’ emotion regulation as a moderator.
Bibliographic record
Abstract
= 5.51) and their parents recruited from five kindergartens. At Time 1 (T1), parents reported their own use of coercive parenting behaviors (i.e., physical coercion and psychological control) and emotion regulation strategies (i.e., suppression and reappraisal). A coloring task was administered to assess the child's aggression at the child's kindergarten. At Time 2 (T2; approximately 6 months later), mothers and fathers again reported their coercive parenting behaviors. Results indicate that suppression served as a moderator in the relations between child aggression and mothers' coercive parenting behavior. Specifically, (a) T1 child aggression was not directly predictive of T2 coercive parenting behaviors; (b) child overt aggression at T1 was associated with increased coercive parenting behaviors at T2 among mothers reporting higher use of suppression and was associated with decreased coercive parenting behaviors at T2 among mothers reporting lower use of suppression; (c) T1 child covert aggression was associated with increased T2 psychological control among mothers with more use of suppression and was associated with decreased psychological control among mothers reporting lower use of suppression. Reappraisal was not a moderator in the relations between child aggression and coercive parenting behaviors. These results shed light on the relations between child aggression and coercive parenting behavior as a function of parents' emotion regulation strategy. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".