Does lexical stress influence 17-month-olds’ mapping of verbs and nouns?
Bibliographic record
Abstract
English-learning infants attend to lexical stress when learning new words. Attention to lexical stress might be beneficial for word learning by providing an indication of the grammatical class of that word. English disyllabic nouns commonly have trochaic (strong-weak) stress, whereas English disyllabic verbs commonly have iambic (weak-strong) stress. We explored whether 17-month-old infants use word stress to resolve an ambiguous labeling event where objects and actions are equally plausible referents. Infants were habituated to 2 words paired with 2 objects, with each object performing a distinct path action. They were subsequently tested on (a) a change in object but not path action or (b) a change in path action but not the object. When infants were taught verb-friendly iambic labels, their looking times increased both when the action switched and when the object switched. Infants who were taught noun-friendly trochaic labels demonstrated an increase in looking time only when the object switched. These results demonstrate that in ambiguous labeling events infants map iambic labels to both actions and objects, and trochaic labels to the objects but not to the actions, suggesting a bias for words with trochaic stress to refer to objects. Seventeen-month-old infants can use trochaic lexical stress to guide their word learning in ambiguous situations, but iambic stress cues may not preferentially guide infants' mappings of actions or objects. (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) | 0.001 | 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 teacher head, 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".