The influence of number of A trials on 2-years-old’s behavior in Two A-Not-B-Type search tasks: A test of the hierarchical competing systems model
Bibliographic record
Abstract
Age-appropriate modifications of the A-not-B task were used to examine 2-year-olds’ search behavior. Several theories predict that A-not-B errors will in-crease as a function of number of A trials. However, the hierarchical competing systems model (Marcovitch & Zelazo, 1999) predicts that although the ratio of perseverative to nonperseverative errors will increase, the likelihood of perseveration will be an inverted U-shaped function. In Experiment 1, children received 1, 6, or 11 A trials in a multistep multilocation search task. In Experiment 2, children received 3, 7, 11, or 15 A trials in a sandbox task. Results from Experiment 1 showed that the ratio of perseverative to nonperseverative errors increased with number of A trials, and results from both Experiments 1 and 2 indicated that the likelihood of perseverative errors was highest following a moderate number of A trials. These findings are consistent with the suggestion that search behavior provides an index of the development of conscious control.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".