On the categorical nature of Korean /pk/ place assimilation
Bibliographic record
Abstract
Korean exhibits regressive place assimilation in /pk/ clusters, which has been described as gradient and rate dependent. However, this assumption has empirically only been tested on the basis of air pressure data [Jun, 1996] which does not provide a direct record of articulator movement. The present study examines articulator movement using EMMA. For three Seoul-dialect speakers, stimuli containing /pk/ clusters were elicited word-medially (for words and nonwords) and in a phrase-boundary condition; two rates were employed. Results show that the labial can indeed reduce word medially, rendering [kk]. However, contrary to previous claims, the data demonstrate that reduction in /pk/ is always categorical, although it is optional or stochastic in its occurrence. Substantial interspeaker variation is observed, with the frequency of reduction being higher at fast rate and ranging overall from 6 at both rates and is never gradient. The lack of reduction in nonsense words and in the phrase boundary condition shows that the process is sensitive to lexical properties. The observed tendency for more gestural overlap word medially compared to the phrase-boundary condition supports the hypothesis that gestural overlap plays a role in the origins of place assimilation. [Work supported by NIH.]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".