Eyewitness accuracy rates in sequential and simultaneous lineup presentations: A meta-analytic comparison.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Most police lineups use a simultaneous presentation technique in which eyewitnesses view all lineup members at the same time. Lindsay and Wells (R. C. L. Lindsay & G. L. Wells, 1985) devised an alternative procedure, the sequential lineup, in which witnesses view one lineup member at a time and decide whether or not that person is the perpetrator prior to viewing the next lineup member. The present work uses the technique of meta-analysis to compare the accuracy rates of these presentation styles. Twenty-three papers were located (9 published and 14 unpublished), providing 30 tests of the hypothesis and including 4,145 participants. Results showed that identification of perpetrators from target-present lineups occurs at a higher rate from simultaneous than from sequential lineups. However, this difference largely disappears when moderator variables approximating real world conditions are considered. Also, correct rejection rates were significantly higher for sequential than simultaneous lineups and this difference is maintained or increased by greater approximation to real world conditions. Implications of these findings are discussed.
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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) | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it