Adults' judgments of children's coached reports.
Bibliographic record
Abstract
This study investigated adults' judgments of the honesty of children's coached true and fabricated mock testimony. Adults saw video clips of children testifying in a mock court about a true or fabricated event in their lives. They were asked to make an assessment of the truthfulness of the testimony, and respond to questions about their perception of children's credibility. Half of the adults saw children testifying after a competence examination, and the other half saw children testifying without a competence examination. Overall, girls were rated as more competent than boys, and their testimony was more likely to be believed. Younger children were more likely to be rated as incompetent than older children. A factor analysis of adults' responses revealed six factors which significantly predicted adults' overall assessment of children's credibility, and their evaluations of children's competence to testify. Adults' detection accuracy was at chance, with the majority of children rated as truthful. Viewing the competency examination and cross-examination did not improve the adults' detection accuracy. However, seeing the cross-examination made adults' less likely to believe children's testimony. The implications of these results for the judicial system are discussed.
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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 | 0.037 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".