When Conventionality isn’t Enough: Three-year-olds Overimitation of Action Sequences
Bibliographic record
Abstract
Imitation is a universal social learning mechanism. Children are so prone to imitation that they occasionally exhibit “overimitation” – imitation of actions that are superfluous to achieving a goal. One explanation for overimitation is that children believe that there is something causal about these actions. An alternative explanation is that children believe the superfluous actions reflect conventions. The first study addresses these possibilities by investigating whether the conventionality of actions affects children’s overimitation. 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. However, if children are more concerned about conventional ways of doing things, they might only overimitate superfluous actions when they are being presented as conventions. Participants were allowed to use a novel toy machine after a model performed causally relevant and superfluous actions on the toy. Results suggested that children overimitated more when the model was knowledgeable about the toy machine. This suggests that children do not simply overimitate any intentional actions that precede a goal. Instead, they selectively overimitate when there is evidence that those actions are conventional. The second study examined whether children would overimitate superfluous actions performed after the achievement of a goal. If children view all actions of a knowledgeable model as conventions and view the superfluous actions of an ignorant model as exploratory, they will overmitate more in the knowledgeable condition. Results suggest that children do not significantly overimitate the superfluous actions performed subsequent to goal achievement.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".