Peer victimization and sympathy development in childhood: The moderating role of emotion regulation
Bibliographic record
Abstract
Abstract Although peer victimization is widely considered to be detrimental to children's well‐being, knowing what it feels like to be harmed is also thought to contribute to children's sense of concern for others. However, research has yet to establish a clear link between peer victimization and sympathy during childhood. Across two samples of Canadian 4‐ and 8‐year‐olds (total N = 504), we examined whether children's emotion regulation capacities (ER) moderated the victimization–sympathy link. Study 1 (n = 300; 33% European origin; 73% of caregivers held bachelor's degree or higher) examined the interactive effects of victimization and child‐ and caregiver‐reported ER on children's self‐reported sympathy assessed concurrently and 1 year later. Concurrently, victimization was positively associated with sympathy for children higher in self‐reported ER and for boys higher in caregiver‐reported ER. Longitudinally, victimization positively predicted changes in sympathy from 4 to 5 years of age for children higher in self‐reported ER. No longitudinal interaction effects emerged for caregiver‐reported ER or in older children. Using the same caregiver‐reported ER measure, Study 2 (n = 204; 30% European origin; 65% of caregivers held bachelor's degree or higher) replicated this pattern in a different cross‐sectional sample of 4‐ and 8‐year‐olds. These results provide initial support for the hypothesis that victimization experiences may facilitate other‐oriented concern in children who can effectively regulate their emotions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".