When do people lie, for whom, and why? : Altruistic lying in an alibi corroboration context
Bibliographic record
Abstract
Three studies were conducted in order to identity factors that impact the likelihood that a witness will lie for a suspect in an alibi corroboration context. Specifically, the level of affinity between a suspect and a witness, the level of social pressure, and gender were investigated as factors impacting the likelihood that a witness would knowingly support a false alibi. During a study session purportedly intended to investigate dyadic problem-solving ability, a mock theft was staged in an adjacent office. When questioned by the experimenter, undergraduate students were provided the opportunity to either corroborate or refute a confederate’s false alibi that the latter had been in the testing room during the time of the theft, which participants knew was false. In study 1, participants who were explicitly asked to conceal the confederate’s whereabouts during the time of the theft were more likely to lie for him or her by corroborating the false alibi (61% vs. 26% of those who were not asked to lie). In study 2, there was a higher percentage of male participants who corroborated a male confederate’s false alibi (41%) compared to female participants who corroborated a female confederate’s false alibi (23%). In study 3, participants were found to be more likely to lie for a confederate when the latter was their friend (41%) than when he or she was a stranger (18%). How much a participant liked the suspect (study 1) and whether or not the suspect had previously helped the participant (study 2) did not affect the rates of false alibi corroboration. The results confirm that alibi witnesses often lie, but suggest that investigators and jurors may underestimate the frequency with which strangers and acquaintances lie for one another, and that witnesses who lie do so more often because they trust that the suspect is innocent rather than guilty.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".