Influence of eyewitness age and recall error on mock juror decision‐making
Bibliographic record
Abstract
The purpose of this research was to determine if child eyewitnesses are seen as more or less credible compared with older eyewitnesses and to determine whether the number of descriptive errors made while recalling the appearance of a perpetrator has an influence on perceived credibility of the witness. Mock jurors were given a mock trial that presented a positive identification by an eyewitness where age of the eyewitness (4‐, 12‐, 20‐year‐old) and the number of perpetrator descriptor errors (i.e., 0, 3, 6) made by the eyewitness were manipulated. Perceived levels of credibility, accuracy, and determinations of guilt were compared using a self‐report questionnaire. Results support the hypothesis that mock jurors perceive eyewitnesses who make fewer errors in descriptions with more integrity (i.e., more credible, reliable, and accurate) and perceive the evidence presented by them (i.e., description of perpetrator and description of events) as more reliable. Overall, adult eyewitnesses are perceived with more integrity than child eyewitnesses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".