How phonological reductions sometimes help the listener.
Bibliographic record
Abstract
In speech production, high-frequency words are more likely than low-frequency words to be phonologically reduced. We tested in an eye-tracking experiment whether listeners can make use of this correlation between lexical frequency and phonological realization of words. Participants heard prefixed verbs in which the prefix was either fully produced or reduced. Simultaneously, they saw a high-frequency verb and a low-frequency verb with this prefix-plus 2 distractors-on a computer screen. Participants were more likely to look at the high-frequency verb when they heard a reduced prefix than when they heard a fully produced prefix. Listeners hence exploit the correlation of lexical frequency and phonological reduction and assume that a reduced prefix is more likely to belong to a high-frequency word. This shows that reductions do not necessarily burden the listener but may in fact have a communicative function, in line with functional theories of phonology.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| 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 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".