Generics license 30-month-olds’ inferences about the atypical properties of novel kinds.
Bibliographic record
Abstract
We examined whether the distinction between generic and nongeneric language provides toddlers with a rapid and efficient means to learn about kinds. In Experiment 1, we examined 30-month-olds' willingness to extend atypical properties to members of an unfamiliar category when the properties were introduced in 1 of 3 ways: (a) using a generic noun phrase ("Blicks drink ketchup"); (b) using a nongeneric noun phrase ("These blicks drink ketchup"); and (c) using an attentional phrase ("Look at this"). Hearing a generic noun phrase boosted toddlers' extension of properties to both the model exemplars and to novel members of the same category, relative to when a property had been introduced with a nongeneric noun phrase or an attentional phrase. In Experiment 2, properties were introduced with a generic noun phrase, and toddlers extended novel properties to members of the same-category, but not to an out-of-category object. Taken together, these findings demonstrate that generics highlight the stability of a feature and foster generalization of the property to novel within-category exemplars. (PsycINFO Database Record
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".