Children consider the probability of random success when evaluating knowledge
Bibliographic record
Abstract
To infer what others know, we must consider under what epistemic states their actions were both rational and probable. We test whether preschoolers can compare the probability of different actions (and outcomes) under different epistemic states—and use this to evaluate what others know. Specifically, four- to six-year-olds (n=90) were asked to help evaluate an agent’s knowledge state by asking the agent to complete either an “undiagnostic” task (where success was assured), or a “diagnostic task” (where the probability of random success was low). By age six, children understood that the “diagnostic” task would more likely reveal the agent’s knowledge state; four- and five-year-olds had no reliable preference, although children in all age groups understood that the “diagnostic” task was harder. These results suggest that, by the end of preschool, children understand how agents’ epistemic states and environment jointly determine success—considering whether agents’ actions imply knowledge, or just luck.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".