Bibliographic record
Abstract
The perception of real-life aggressive episodes was studied, in order to (a) represent the cognitive dimensions used by judges to differentiate between such episodes, (b) to evaluate the perceived differences between different categories of episodes, and (c) to assess the effects of the judges' age, sex and attitudes on their cognitive representation of aggressive episodes. Judgements of 22 aggressive episodes selected from a free-response pilot study were analysed by Carroll & Chang's (1970) INDSCAL procedure, and differences between categories of episodes and groups of judges were evaluated by multiple discriminant analyses. Results indicated that (a) four cognitive dimensions, probability of occurrence, justifiability, emotional provocation, and control, defined the psychological map for aggressive episodes; (b) domestic against public, drunken and non-drunken, criminal against non-criminal episodes were significantly differentiated in this perceptual space; (c) the judges' age, sex and Machiavellism scores were related to their perception of such episodes. The results are discussed in terms of the importance of implicit perceptions of aggression and crime in the criminal justice system. Specifically, it is suggested that similar techniques could be used to (a) gauge popular perceptions of crime as an input to the legislative process, and (b) for the study of perceptions of aggressive episodes by such crucial groups in the criminal justice system as policemen, judges, jury members, victims and offenders.
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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 | 0.019 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".