Phantoms and Fabrications: Young Children's Detection of Implausible Lies
Bibliographic record
Abstract
The present study investigated whether young children are gullible and readily deceived by another's lies. Specifically, this study examined whether young children believe a lie teller's statement when the statement violates their developing knowledge of a distinction between reality and fantasy. In the first three experiments 3- to 6-year-olds (N = 293) were presented with either a story or a live staged event in which an individual made an implausible statement about a misdeed (claiming that a ghost jumped out of a book and broke a glass). A significant age effect was obtained: 5- and 6-year-olds tended to report that the individual who made the implausible statement had actually committed the misdeed, whereas 3- and 4-year-olds tended to accept the claim of the protagonist. Experiment 4 revealed that 5- and 6-year-olds (N = 43) not only disbelieved an individual's implausible statement but also inferred that the individual was lying and had a deceptive intent. In contrast, Experiment 5 revealed that 3- and 4-year-olds (N = 41) had difficulty disbelieving an individual's implausible claim about an inanimate object (i.e., the claim that a chair came alive and broke the glass). The findings suggest that 5- and 6-year-olds are not so gullible as previously thought, and that they use their well-developed real-world knowledge to detect scapegoating lies. In contrast, many younger children tend to believe another's implausible lies, perhaps due to the fact that the knowledge needed to detect such lies has not yet been consolidated.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".