Investigating Investigators: Examining Witnesses' Influence on Investigators.
Bibliographic record
Abstract
This research examined the influence of eyewitness identification decisions on participants in the role of police investigators. Undergraduate "investigators" interviewed confederate "witnesses" and then searched a computer database of potential suspects. The database included information on each suspect's physical description, prior criminal record, alibi, and fingerprints. Participants selected a suspect and estimated the probability that the suspect was guilty. Investigators subsequently administered a photo lineup to the witness and re-estimated the suspect's guilt. If the witness identified the suspect probability estimates increased dramatically. If the witness identified an innocent lineup member or rejected the lineup, investigators' probability estimates dropped significantly, even when pre-lineup objective evidence (e.g., fingerprints) was strong. Performance of participants acting as witnesses in two baseline studies was at chance. Therefore, participant-investigators greatly overestimated the amount of information gain provided by eyewitness identifications.
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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".