Three-Year-Olds Overimitate when Actions are Presented as Conventions
Bibliographic record
Abstract
Imitation is a universal social learning mechanism, observed in all countries, across all ages. Three- to 5-year-olds are so prone to imitation that they occasionally exhibit “overimitation” – that is, they imitate actions that are apparently superfluous to achieving a particular goal. One explanation for overimitation is that children believe that there is something causal about the superfluous actions. An alternative explanation is that children believe that the superfluous actions reflect a particular “style” of performing the action that may be conventional within the community. The goal of the present study is to address these two possibilities by investigating whether children overimitate equally from knowledgeable and ignorant models. We reasoned that if children believe that the actor’s superfluous actions are causal, they might overimitate anytime those intentional actions precede the achievement of a goal. In contrast, if children are more concerned about conventional ways of doing things, they might only overimitate superfluous actions when it is clear that they are being presented as conventions. Sixty-eight 3-year-old children were allowed to use a novel toy machine after causally relevant and superfluous actions on the toy were demonstrated by a knowledgeable or ignorant model. Results suggested that children overimitated more when the model was present (versus only caregiver present) and when the model was knowledgeable (versus ignorant) of the toy machine. These findings suggest that children do not simply overimitate any intentional actions modelled by actors that precede a goal. Instead, they selectively overimitate when there is evidence that those actions are conventional.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".