Adults’ perceptions of children’s ground rule applications during investigative interviews
Bibliographic record
Abstract
Ground rules are a recommended portion of investigative interviews with children. The current study examined how adults perceive children’s application of the I Don’t Understand (IDU) or I Don’t Know (IDK) rules during investigative interviews. Jury-eligible adults (N = 716) viewed a transcript of a child alleging sexual abuse in a 2 (Child Age: 6 v. 10) × 2 (Rule Applied: IDU v. IDK) × 2 (Rule Application Frequency: 1-time v. 6-times) design. Adults perceived the child who applied a rule 1 time as more credible, less likely to have intentionally lied, and more likely to have understood what her statements would be used for than the child who applied a rule 6 times. Child age and type of rule applied had more limited effects. Results have implications for those who interview children, design interview interventions, and provide expert testimony regarding child witnesses.
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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 | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".