Children Exposed to Intimate Partner Violence: Stability & Change in Sibling Aggression Over Time
Bibliographic record
Abstract
The purpose of our study was to investigate stability and change over time in sibling aggression in children exposed to intimate partner violence (IPV). We further investigated the role that maternal and sibling warmth might play, as well as sex differences in observed aggressive behavior. We expected that lower warmth would be associated with more aggression, both concurrently and over time. We also expected that more brother dyads would engage in aggression than sister or mixed sex dyads. Forty-seven families with two school-aged siblings were recruited from the community; thirty-two dyads returned for a second timepoint. Mothers reported on aggressive behavior by older and younger siblings, while each sibling provided a self-report. Unstructured sibling interactions were recorded for thirty minutes at each timepoint and physical and verbal aggression were coded. Results indicated that mean levels of aggression reported by mothers and siblings were stable over time, and the majority of siblings were stable in their observed aggressive behavior over time. Children’s reports of sibling, but not maternal warmth, significantly predicted later observed sibling aggression; older sibling perceptions of warmer sibling relationships at Time 1 predicted less observed sibling aggression at Time 2. More brother dyads engaged in observed aggression at Time 1, but not Time 2. Overall, our findings indicated that aggression between siblings exposed to IPV was stable over time, and that sibling warmth played a predictive role in aggressive behavior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".