The Influence of Shape Similarity and Shared Labels on Infants’ Inductive Inferences about Nonobvious Object Properties
Bibliographic record
Abstract
This study examined the influence of object labels and shape similarity on 16- to 21-month-old infants' inductive inferences. In three experiments, a total of 144 infants were presented with novel target objects with or without a nonobvious property, followed by test objects that varied in shape similarity to the target. When objects were not labeled, infants generalized the nonobvious property to test objects that were highly similar in shape (Experiment 1). When objects were labeled with novel nouns, infants relied both on shape similarity and shared labels to generalize properties (Experiment 2). Finally, when objects were labeled with familiar nouns, infants generalized the properties to those objects that shared the same label, regardless of shape similarity (Experiment 3). The results of these experiments delineate the role of perceptual similarity and conceptual information in guiding infants' inductive inferences.
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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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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".