One is Not Enough: Multiple Exemplars Facilitate Infants' Generalizations of Novel Properties
Bibliographic record
Abstract
Across three experiments, we examined 9‐ and 11‐month‐olds' mappings of novel sound properties to novel animal categories. Infants were familiarized with novel animal–novel sound pairings (e.g., Animal A [red]–Sound 1) and then tested on: (1) their acquisition of the original pairing and (2) their generalization of the sound property to a new member of a familiarized category (e.g., Animal A [blue]–Sound 1). When familiarized with a single exemplar of a category, 11‐month‐olds showed no evidence of acquiring or generalizing the animal–sound pairings. In contrast, 11‐month‐olds learnt the original animal–sound mappings and generalized the sound property to a novel member of that category when familiarized with multiple exemplars of a category. Finally, when familiarized with multiple exemplars, 9‐month‐old infants learnt the original animal–sound pairing, but did not extend the novel sound property. The results of these experiments provide evidence for developmental differences in the facilitative role of multiple exemplars in promoting the learning and generalization of information.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".