Prosocial behaviour between siblings exposed to intimate partner violence
Bibliographic record
Abstract
Abstract Children's prosocial behaviour is a core feature of their social development as well as their resilience, but it has not yet been examined in siblings exposed to intimate partner violence (IPV). The goals of the present study were: (1) To describe prosocial behaviour between siblings exposed to IPV by exploring linkages with exposure to violence, sibling spacing, child age, and self‐esteem; (2) To investigate if prosocial behaviour varied as a function of sibling relationship quality; and (3) To assess if child adjustment problems were related to sibling prosocial behaviour. Forty‐seven families with two school‐aged siblings aged eight and eleven years on average were recruited from the community. Observations of unstructured sibling interaction were coded for prosocial behaviour as well as declined prosocial offers and requests. Children reported on their self‐esteem and on the quality of their sibling relationships. Mothers reported on internalizing and externalizing problems for each child. Results showed that prosocial behaviour was positively associated with greater sibling warmth and sibling spacing, but not related to exposure to IPV or child self‐esteem. Declined prosocial behaviours were positively associated with maternal reports of physical IPV and negatively associated with child age. Prosocial behaviour differed significantly across relationship typologies; it was more frequent in intense relationships, and when sibling spacing was larger. By examining sibling prosociality, this exploratory study shed new light on resilience in children exposed to IPV. Results were discussed within a resilience framework.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".