Individual Differences in Children’s Preference to Learn From a Confident Informant
Bibliographic record
Abstract
Past research has demonstrated that children can use an informant’s confidence level to selectively choose from whom to learn. Yet, in any given study, not all children show a preference to learn from the most confident informant. Are individual differences in this preference stable over time and across learning situations? In two studies, we evaluated the stability of preschoolers’ performance on selective learning tasks using confidence as a cue. The first study (N=48) presented children with the same two informants, one confident and one hesitant, and the same four test trials twice with a one-week delay between administrations. The second study (N=50) presented two parallel tasks with different pairs of informants and test trials one after the other in the same testing session. Correlations between administrations were moderate in the first study and small in the second study, suggesting that children show some stability in their preference to learn from a confident individual but that their performance is also influenced by important situational factors, measurement error or both. Implications for the study of individual differences in selective social learning are discussed.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".