Stimulus variability and perceptual learning of nonnative vowel categories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT English-speakers' learning of a French vowel contrast (/ə/–/ø/) was examined under six different stimulus conditions in which contrastive and noncontrastive stimulus dimensions were varied orthogonally to each other. The distribution of contrastive cues was varied across training conditions to create single prototype, variable far (from the category boundary), and variable close (to the boundary) conditions, each in a single talker or a multiple talker version. The control condition involved identification of gender appropriate grammatical elements. Pre- and posttraining measures of vowel perception and production were obtained from each participant. When assessing pre- to posttraining changes in the slope of the identification functions, statistically significant training effects were observed in the multiple voice far and multiple voice close conditions.
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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 | 0.000 |
| 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 it