The Cognitive Revolution in Children’s Understanding of Mind
Bibliographic record
Abstract
Bruner, in reassessing the cognitive revolution, argues for the centrality of ‘meaning-making’ in human activity, claiming that children learn to give meaning to what people do as they learn the language and social practices of their culture. The role played by the attribution of mental states to others has been studied intensely in the past decade in a new research area that has come to be known as children’s ‘theory of mind’. Researchers in this field who, unlike Bruner, see psychology as a natural empirical science, view the child as constructing a causal theory to explain and predict human action. They base their arguments largely on experimental observation of children’s performance in laboratory tasks, especially the ‘false-belief’ task. In contrast, many researchers who take Bruner’s view study the development of social understanding in naturalistic observation of children’s interaction with peers and family members. In this article we examine the relations between these views and suggest that the real challenge of the cognitive revolution is to unite the two approaches, to achieve a causal, naturalistic account of the acquisition and elaboration of meaning-making.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.023 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".