A large-scale corpus study of phonological opacity in Uyghur
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This article examines a case of phonological opacity in Uyghur resulting from an interaction between backness harmony and a vowel reduction process that converts harmonic vowels into transparent vowels. A large-scale corpus study shows that although opaque harmony with the underlying form of a reduced vowel is the dominant pattern, cases of surface-apparent harmony also occur. The rate of surface-apparent harmony varies across roots and is correlated with a number of factors, including root frequency. These data pose problems for standard accounts of opacity, which do not predict such variation. I propose an analysis where variation emerges from conflict between a paradigm uniformity constraint mandating that the harmonising behaviour of a root remains consistent, and surface phonotactic constraints. This is implemented in a parallel model by scaling constraint violations according to certainty in a root’s harmonic class. This aligns with past work suggesting some opacity is driven by paradigm uniformity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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