Lie-Telling Behavior in Children With Autism and Its Relation to False-Belief Understanding
Bibliographic record
Abstract
Children’s lie-telling behavior and its relation to false-belief understanding was examined in children with autism spectrum disorders (ASD; n = 26) and a comparison group of typically developing children ( n = 27). Participants were assessed using a temptation resistance paradigm, in which children were told not to peek at a forbidden toy while left alone in a room and were later asked if they peeked. Overall, 77% of the total sample peeked at the toy, with no significant difference between the ASD and typically developing groups. Whereas 96% of the typically developing control children lied about peeking, significantly fewer children with ASD (72%) lied. Children with ASD were poorer at maintaining their lies than the control group. Liars had higher false-belief scores than truth-tellers. These findings have implications for understanding how theory of mind deficits may limit the ability of children with ASD to purposefully deceive others.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".