Detecting Children's Lies: Comparing True Accounts About Highly Stressful Injuries with Unprepared, Prepared, and Coached Lies
Bibliographic record
Abstract
In this investigation, 514 university students judged whether children were telling the truth about highly emotional events. Eight children (half female, half 8-9 and the remainder 12-14 years old) had been injured seriously enough to require emergency room treatment and were interviewed a few days later. Each was yoked to three other children matched in age and gender who fabricated accounts under one of three conditions: lies that were unprepared, prepared (24 hours to prepare), and coached by parents. Participants were at chance when judging true accounts as well as unprepared and prepared lies. However, 74% of the coached lies were judged as true. Participants' confidence in their judgments, age, experience with children, and relevant coursework/training did not improve judgments.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".