Cross-Examination Fails to Safeguard Against Feedback Effects on Eyewitness Testimony
Bibliographic record
Abstract
The legal system relies heavily on eyewitness evidence to identify and prosecute criminal perpetrators, but wrongful convictions resulting from eyewitness misidentification have led many to conclude that eyewitness memory is unreliable. Advances in eyewitness identification research have produced a more nuanced understanding of eyewitness reliability, however. Whereas pristinely collected eyewitness identification evidence provides diagnostic information about a suspect’s guilt or innocence, numerous contaminants of eyewitness memory can undermine the reliability of eyewitness identification evidence. One such contaminant is confirming post-identification feedback—feedback given to or inferred by an eyewitness that communicates that their identification decision was correct. Confirming feedback is inevitable in real cases involving eyewitness identification and compromises the diagnostic value of eyewitness memory to such an extent that it undermines evaluators’ abilities to differentiate between accurate and mistaken eyewitnesses (Smalarz & Wells, 2014). The current research tested whether cross-examination, a fundamental legal safeguard for preventing wrongful conviction based on eyewitness misidentification, can help remedy the contaminating effects of feedback on eyewitness testimony. Evaluators (N = 128) viewed direct examination testimony or direct- and cross-examination testimony of accurate and mistaken eyewitnesses, some of whom had received confirming feedback following their identification. Although the majority of eyewitnesses admitted during cross-examination that some or all of their recollections may have been influenced by the feedback, viewing the cross-examination did not improve evaluators’ abilities to differentiate between accurate and mistaken eyewitness testimony. Cross-examination appears to be an insufficient safeguard for preventing wrongful convictions based on contaminated eyewitness evidence.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 0.005 |
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".