Children Use the Relative Confidence of People With Conflicting Perspectives to Form Their Own Beliefs
Bibliographic record
Abstract
We provide evidence that children sensibly integrate the judgments of different people who disagree according to their confidence. We asked children (ages 5-10 years, N = 92) to make judgments about what happened during unobserved events by relying on two informants who sometimes disagreed. Children integrated the reports of informants and formed novel beliefs endorsed by neither party by 8 years old when the informants reported equal confidence-for example, they selected a monster with six spots when one informant reported seeing one with four spots and another reported seeing one with eight. Unequal confidence across the informants biased children toward the judgment of the more confident party. That children can integrate social confidence judgments with conflicting information-considering and weighing the relative confidence of others to make up their own minds about what is most likely-represents a previously unappreciated mechanism of learning that is crucial to children's development as independent social agents. It allows children to become independent thinkers who can form beliefs that build on the knowledge of others without relying on identical belief adoption of one social agent over another.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".