Alibi corroboration: an examination of laypersons’ expectations
Bibliographic record
Abstract
Purpose The study aims to examine what laypersons expect those corroborating an alibi to remember about an interaction with an alibi provider. Design/methodology/approach Participants ( N = 314) were presented with a mock crime scenario and answered questions about an alibi provider (i.e. the criminal suspect) and alibi corroborators. Participants also completed a lineup task based on the scenario and rated the likelihood of their own ability to corroborate the suspect’s alibi. Findings Overall, participants believed that it was moderately likely that an alibi corroborator with no prior relationship with the suspect would be able to vouch for the suspect, provide a description and to remember his general physical characteristics. Those who were inaccurate in their lineup decision demonstrated lower expectations of their own ability to corroborate the suspect’s alibi relative to those who were accurate in their decision. Originality/value To the best of the authors’ knowledge, this is the first known study to assess what those judging an alibi expect when making a decision about the outcome of a case. Results demonstrate that laypeople have arguably unrealistic expectations of alibi corroborators, potentially jeopardizing innocent people’s ability to prove their innocence.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".