Preschoolers’ extension of familiar adjectives
Bibliographic record
Abstract
In two experiments, we examined the role of labels in guiding preschoolers' extension of three types of familiar adjectives: emotional state adjectives, physiological state adjectives, and trait adjectives. On each trial, we labeled a target animal with one of the three different types of adjectives and asked whether these terms could apply to a subordinate-level match, a basic-level match, a superordinate-level match, or an inanimate object. In Experiment 1, participants extended trait adjectives, but not emotional or physiological adjectives, to members of the same basic-level category, regardless of whether an explicit basic-level label was provided for the target animal. Similarly, children in Experiment 2 also extended trait adjectives to the members of the same basic-level category, even when explicit superordinate- and subordinate-level labels were provided for the target animals. Together, these results demonstrate that children appreciate that emotional and physiological adjectives cannot be generalized to the same extent as can trait adjectives, and the results document the privileged status of basic-level categories in preschoolers' extension of trait adjectives.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".