Bibliographic record
Abstract
In the current study the impact of victim age, crime seriousness, and social influence on perceptions of alibi believability, victim responsibility, confidence, and emotions was examined. Participants (N = 141) read a brief crime-scenario vignette and a summary of the suspect's alibi, followed by a series of closed-ended questions. The alibi was held constant across all conditions. Eighty percent of participants rated the suspect's alibi as moderately believable or less than moderately believable. A significant interaction of Victim Age × Crime Seriousness on perceptions of alibi believability was found. Additionally, those individuals who reported greater feelings of certain negative emotions tended to rate the crime as being more serious and the suspect's alibi as less believable. Furthermore, participants’ self-reported feelings of sadness, pleasure, and fear could significantly predict participants’ alibi believability ratings. These results offer additional support for the legal relevance of emotions, particularly with respect to alibi assessment.
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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 | 0.002 | 0.002 |
| 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; 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".