Bibliographic record
Abstract
Some models of cognitive development postulate qualitative change in the fundamental nature of mental structure, whereas others stress more invariant constraints on the form of mental organization. This article explores the implications of these two perspectives for characterizing the ontogeny of causal reasoning. Recent work on the development of causal reasoning over the preschool years has confirmed that children follow systematic constraints in identifying and labelling causes and effects. These observations have led many researchers to grant the preschooler an underlying knowledge of the defining principles of causality. This poses a challenge to the traditional view that the young child is precausal and must learn what features of occurrences distinguish causal from correlated events. The literature on causal reasoning in the preschool years is reviewed, and it is concluded that the hypothesis of an invariant causal scheme is only partially correct. Whereas preschoolers appear to share some principles of causal reasoning with adults, there are developmental changes in the extent to which these principles are held as necessary features of events, and in how they can be manipulated in the service of causal judgments and explanations. The issue of whether observed differences are due to change in specific knowledge or in the operational domain is raised, and it is argued that there is a reorganization in the interrelationship (although not the components) of the underlying causal scheme.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 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".