Testing What You’re Told: Young Children’s Empirical Investigation of a Surprising Claim
Bibliographic record
Abstract
Samuel Ronfarda* , Eva E. Chenb & Paul L. Harrisca University of Toronto, Mississauga, Canadab Hong Kong University of Science and Technology, Hong Kongc Harvard University, United StatesCONTACT Samuel Ronfard samuel.ronfard@utoronto.ca University of Toronto, Mississauga, 3359 Mississauga Road, CCT Building , Room 4059 Toronto, L5L 1C6, CanadaABSTRACTWe examined differences among children in their endorsement of an adult’s claim, their subsequent empirical investigation of that claim, and their resolution of any potential conflict between the claim and their empirical investigation. American and Chinese preschool (N = 171, M = 4.71 years) and elementary school (N = 128, M = 7.59 years) children were presented with five, different-sized, Russian dolls and asked to indicate the heaviest doll. Children typically selected the biggest doll. Children then heard either a false, counter-intuitive claim (i.e., smallest doll = heaviest) or a claim confirming their initial intuition (i.e., biggest doll = heaviest). Children frequently endorsed the experimenter’s claim even when it was counter-intuitive. The experimenter then left the room. During the experimenter’s absence, older children who had heard the counter-intuitive as opposed to the confirming claim explored the dolls more than younger children, especially when subtly prompted to explore. Moreover, only older children who heard the counter-intuitive claim simultaneously picked up the smallest and biggest doll, a more deliberate test of the experimenter’s claim. By implication, children engage in selective exploration following a surprising claim. Older children’s more systematic explorations of what they have been told may reflect improvements in their ability to test such claims and in their greater sensitivity to the fact that unexpected claims can and should be empirically investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".