Six-Year-Olds, but Not Younger Children, Consider the Probability of Being Right by Chance When Inferring Others' Knowledge
Bibliographic record
Abstract
When determining what others know, we intuitively consider not only whether they succeed but also their probability of success in the absence of knowledge (e.g., random guessing). Across three experiments (n = 240 North American 4-6-year-olds, data collected between 2020-2023) we find that 4-year-olds understand that tasks with a lower probability of chance success are harder. However, it is not until age 6 that children use this understanding to gauge (Experiment 1) and infer (Experiments 2-3) what others know. These results suggest that, although basic probabilistic reasoning and representations of knowledge are well in place by age 4, children do not integrate the two to make mental-state inferences until much later, pointing to an area of important developmental change in Theory of Mind.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".