Class matters: 12‐month‐olds’ word–object associations privilege content over function words
Bibliographic record
Abstract
A fundamental step in learning words is the development of an association between a sound pattern and an element in the environment. Here we explore the nature of this associative ability in 12-month-olds, examining whether it is constrained to privilege particular word forms over others. Forty-eight infants were presented with sets of novel English content-like word-object pairings (e.g. fep) or novel English function-like word-object (e.g. iv) pairings until they habituated. Results indicated that infants associated novel content-like words, but not the novel function-like words, with novel objects. These results demonstrate that the mechanism with which basic word-object associations are formed is remarkably sophisticated by the onset of productive language. That is, mere associative pairings are not sufficient to form mappings. Rather the system requires well-formed noun-like words to co-occur with objects in order for the linkages to arise.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".