Believe me, believe me not : investigating the possibility of a dual standard in the evaluation of alibi and eyewitness evidence
Bibliographic record
Abstract
The present study investigates the hypothesis that alibi evidence is interpreted as an excuse and so perceived and reacted to negatively. Participants read case summaries that included incriminating eyewitness and exculpatory alibi evidence, the latter labelled as an 'alibi', 'excuse' or 'statement', completed questionnaires evaluating their perceptions or the honesty and credibility of witnesses, and provided a ruling for the case (guilty/not guilty). The alibi evidence was provided before or after the eyewitness evidence. It was expected that ratings for the 'alibi' or 'excuse' would be lower than those for the 'statement'. Though there were no significant evaluations of alibi honesty/credibility and accuracy are not utilized in the formation of a verdict. The results are discussed in the context of using the 'excuse hypothesis' as an explanation for the underutilization of alibi evidence.
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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 | 0.017 | 0.147 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".