Viewing relational aggression through multiple lenses: Temperament, personality, and personality pathology
Bibliographic record
Abstract
Dispositional trait frameworks offer great potential to elucidate the nature and development of psychopathology, including the construct of relational aggression. The present study sought to explore the dispositional context of relational aggression across three dispositional frameworks: temperament, personality, and personality pathology. Participants comprised a large community sample of youth, aged 6 to 18 years (N = 1,188; 51.2% female). Ratings of children's relational aggression, temperament, personality, and personality pathology traits were obtained through parent report (86.3% mothers). Results showed convergence and divergence across these three dispositional frameworks. Like other antisocial behavior subtypes, relational aggression generally showed connections with traits reflecting negative emotionality and poor self-regulation. Relational aggression showed stronger connections with temperament traits than with personality traits, suggesting that temperament frameworks may capture more relationally aggressive content. Findings at the lower order trait level help differentiate relational aggression from other externalizing problems by providing a more nuanced perspective (e.g., both sociability and shyness positively predicted relational aggression). In addition, there was little evidence of moderation of these associations by gender, age, or age2, and findings remained robust even after controlling for physical aggression. Results are discussed in the broader context of conceptualizing relational aggression in an overarching personality-psychopathology framework.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".