Bibliographic record
Abstract
This study compares the monophthongal vowels /a ɛ e i ʌ ɨ o u/ of two North Korean dialects as spoken by ethnic Koreans in China (24 Phyeongan and 21 Hamkyoung) with the vowels of Seoul Korean (25 younger and 32 older). Younger and older speakers of Seoul Korean are compared to examine the sound change in progress in Seoul. The most striking difference among the dialects is in the realization of /o/ and /ʌ/. In Seoul, /o/ is produced higher than /ʌ/. In Phyeongan, /o/ is lower than /ʌ/, while in Hamkyoung, the two are comparable in height and the main contrast is along F2. Also, /e/-/ɛ/ contrast is lost in Seoul but robust in the Northern dialects. Within Seoul Korean, the back vowel shift observed in recent literature is confirmed (Cho S. 2003, Han J. and Kang H. 2013, and Kang Y. to appear)—/o/ is raised toward /u/ while /ɨ/ is fronted away from /u/ in younger speakers’ speech. In contrast to recent reports of /u/-/ɨ/ and /o/-/ʌ/ merger in homeland North Korean dialects (Kang S. 1996, 1997, Kwak 2003, and So 2010), in our Northern data, these contrasts remain distinct.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".