Altruistic Lying in an Alibi Corroboration Context: The Effects of Liking, Compliance, and Relationship between Suspects and Witnesses
Bibliographic record
Abstract
Police investigators, judges, and jurors are often very skeptical of alibi witness testimony. To investigate when and why individuals lie for one another, we conducted two studies in which witnesses' support of a false alibi was observed. We varied the level of social pressure exerted on witnesses and the level of affinity between suspect-witness pairs. During a study session purportedly intended to investigate dyadic problem-solving ability, a mock theft was staged. When questioned, participants were provided the opportunity to either corroborate or refute a confederate's false alibi that the latter was with them when the theft occurred. Participants were more likely to lie for the confederate when the latter explicitly asked participants to conceal his/her whereabouts during the time of the theft (Study 1). How much participants liked the suspect did not impact lying; however, participants lied for a confederate more often when the latter was a friend rather than a stranger (Study 2). Results show that alibi witnesses often lie and that investigators and jurors may not accurately estimate the likelihood that such witnesses will lie for one another. Witnesses who lied also reported doing so more often because they believed that the suspect was innocent rather than guilty. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 | 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".