Words Get in the Way: Linguistic Effects on Talker Discrimination
Why this work is in the frame
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Bibliographic record
Abstract
A speech perception experiment provides evidence that the linguistic relationship between words affects the discrimination of their talkers. Listeners discriminated two talkers' voices with various linguistic relationships between their spoken words. Listeners were asked whether two words were spoken by the same person or not. Word pairs varied with respect to the linguistic relationship between the component words, forming either: phonological rhymes, lexical compounds, reversed compounds, or unrelated pairs. The degree of linguistic relationship between the words affected talker discrimination in a graded fashion, revealing biases listeners have regarding the nature of words and the talkers that speak them. These results indicate that listeners expect a talker's words to be linguistically related, and more generally, indexical processing is affected by linguistic information in a top-down fashion even when listeners are not told to attend to it.
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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 | 0.001 |
| 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 | 0.000 |
| 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 it