Did the instigator intend to provoke? A key moderator in the relation between trait aggression and aggressive behavior
Bibliographic record
Abstract
Abstract The purpose of this study was to investigate the cross‐situational consistency of trait aggression in provoking situations where an instigator (1) clearly intended to provoke, (2) clearly intended not to provoke, or (3) where presence of intention was ambiguous. It was hypothesized that cross‐situational consistency would be substantial, and that trait aggression would have the greatest impact on aggressive behavior in ambiguous situations. Participants were 80 female and 38 male undergraduate students. They completed the Aggression Questionnaire [Buss and Perry, J Pers Soc Psychol, 1992, pp. 452], read a set of 24 vignettes depicting conflict situations and rated their perceived likelihood of becoming angry and aggressive in those situations. An overall cross‐situational consistency correlation coefficient of r=.47 was found. It was also found that trait aggression had a significantly greater effect on the likelihood of aggressive responses in the ambiguous and intentional situations than it did in the unintentional situations. These results are discussed in relation to trait activation and hostile attribution bias. Aggr. Behav. 30:409–424, 2004. © 2004 Wiley‐Liss, Inc.
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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 | 0.002 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".