Disfluencies signal reference to novel objects for adults but not children
Bibliographic record
Abstract
Speech disfluencies can guide the ways in which listeners interpret spoken language. Here, we examined whether three-year-olds, five-year-olds, and adults use filled pauses to anticipate that a speaker is likely to refer to a novel object. Across three experiments, participants were presented with pairs of novel and familiar objects and heard a speaker refer to one of the objects using a fluent ("Look at the ball/lep!") or disfluent ("Look at thee uh ball/lep!") expression. The salience of the speaker's unfamiliarity with the novel referents, and the way in which the speaker referred to the novel referents (i.e., a noun vs. a description) varied across experiments. Three- and five-year-olds successfully identified familiar and novel targets, but only adults' looking patterns reflected increased looks to novel objects in the presence of a disfluency. Together, these findings demonstrate that adults, but not young children, use filled pauses to anticipate reference to novel objects.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".