Impulsive behaviour in interpersonal encounters: Associations with quarrelsomeness and agreeableness
Bibliographic record
Abstract
Associations between impulsivity and interpersonal behaviours have rarely been examined, even though impulsivity may disrupt the flow of social interactions. For example, it is unknown to what extent the commonly used Barratt Impulsiveness Scale (BIS-11) predicts impulsive behaviour in social situations, and how behaving impulsively during interpersonal encounters might influence levels of quarrelsomeness and agreeableness. In this study, 48 healthy working individuals completed the BIS-11 and recorded their behaviour in social situations using event-contingent recording. Record forms included items representing quarrelsome, agreeable, and impulsive behaviours. BIS-11 motor impulsiveness scores predicted impulsive behaviour in social situations. Impulsive behaviour was associated, in different interactions, with both agreeableness and quarrelsomeness. Behaving impulsively in specific interactions was negatively associated with agreeableness in participants with higher BIS-11 motor impulsiveness and positively associated with agreeableness in participants with lower BIS-11 motor impulsiveness. Impulsive quarrelsome behaviour may cause interpersonal problems. Impulsive agreeable behaviour may have positive effects in individuals with low trait impulsivity. The idea that there are between-person differences in the effects of state impulsivity on the flow of social interaction deserves further study.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".