The Association Between Emotion, Social Information Processing, and Aggressive Behavior: A Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. Aggressive individuals are thought to process social information in such a manner that the likelihood of engaging in aggressive acts increases drastically. Additionally, emotion and emotion regulation skills are implicated in aggressive and violent behavior as well. However, little attention has been paid to the reciprocal relations between emotion and emotion regulation and Social Information Processing (SIP) in explaining aggression. Therefore, the present study systematically examined extant research on the role of emotion and SIP in aggressive behavior. The results supported substantial overlap between emotion and emotion regulation processes and SIP in explaining aggression. Due to the paucity and nature of available studies, no firm conclusion can be drawn about the nature of their reciprocal relationships. However, the integration of cognition and emotion seems a promising avenue of research for explaining the development and manifestation of aggressive behavior, as well as to inform its prevention and treatment. Future research is needed to elucidate the likely intertwined roles of emotion and the entire SIP process in offender or at-risk populations.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it