The single lineup paradigm: A new way to manipulate target presence in eyewitness identification experiments.
Bibliographic record
Abstract
The suspect in eyewitness lineups may be guilty or innocent. These possibilities are traditionally simulated in eyewitness identification studies using a dual-lineup paradigm: All witnesses observe the same perpetrator and then receive one of two lineups. In this paradigm, the suspect's guilt is manipulated by including the perpetrator in one lineup and an innocent suspect in the other. The lineup is then filled with people matched to either the suspect (resulting in different fillers in perpetrator-present and perpetrator-absent lineups) or to the perpetrator (resulting in the same fillers in each lineup). An inescapable feature of the dual-lineup paradigm is that the perpetrator-present and perpetrator-absent lineups differ not only in the suspect's guilt, but also in their composition. Here, we describe a single-lineup paradigm: Subjects observe one of two perpetrators and then all subjects receive the same lineup containing one of the perpetrators. This alternative paradigm allows manipulation of the suspect's guilt without changing the lineup's composition. In three experiments, we applied the single-lineup paradigm to explore suspect-filler similarity and consistently found that increasing similarity reduced perpetrator identifications but did little to prevent innocent suspect misidentifications. Conversely, when fillers were matched to the perpetrator using a dual-lineup paradigm, increasing similarity reduced identification of perpetrators and innocent suspects. This finding suggests that the effect of filler similarity may depend on the person to whom the fillers are matched. We suggest that the single-lineup paradigm is a more ecologically valid and better controlled approach to creating suspect-matched lineups in laboratory investigations of eyewitness memory than existing procedures. (PsycINFO Database Record
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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 | 0.000 |
| 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 | 0.000 |
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".