Adults’ Detection of Deception in Children: Effect of Coaching and Age for Children's True and Fabricated Reports of Injuries
Bibliographic record
Abstract
A total of 1,074 undergraduates judged the truthfulness of children's interviews (from verbatim transcripts) about experiencing injuries serious enough to require hospital emergency room treatment. Ninety-six children (three age groups: 5-7, 8-10, and 11-14 years, 50% girls) were interviewed. At each age, 16 children told truthful accounts of actual injury experiences and 16 fabricated their reports, with half of each group coached by parents for the previous 4 days. Lies by 5- to 7-year-olds, whether coached or not, were detected at above-chance levels. In contrast, 8- to 10-year-olds' accounts that were coached, whether true or not, were more likely to be believed. For 11- to 14-year-olds, adults were less likely to accurately judge lies if they were coached. The believability of children aged 8 or above who were coached to lie is particularly disturbing in light of the finding that participants were more confident in the accuracy of their veracity decisions when judging coached reports.
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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 | 0.006 | 0.059 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".