5-year-olds' Use of Disfluency and Speaker Identity in Referential Communication
Bibliographic record
Abstract
Filled pauses, once thought to be an extraneous aspect of language, play an important role in communication by serving as a signal of speaker difficulty. If children can make such attributions, then their interpretation of filled pauses should be speaker-specific. Using an eye-tracking paradigm, listeners were introduced to two characters with gender-typed colour preferences. These characters instructed children to look at pink or blue objects in a display using fluent (“Look at the X”) and disfluent (“Look at thee, uh, X”) instructions. Experiment 1indicated that 5-year-olds did not make any referential predictions. With the addition of filler trials, Experiment 2 indicated that 5-year-olds and adults anticipated reference to gender-typed objects during the baseline interval (“Look at”), and disfluent instructions led listeners to amend this prediction. These results suggest that children use disfluency as a marker to adjust their speaker-specific referential predictions.
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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 | 0.001 |
| 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".