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Record W2433076537 · doi:10.1017/s095439451600003x

VOT merger in Heritage Korean in Toronto

2016· article· en· W2433076537 on OpenAlexaffabout
Yoonjung Kang, Naomi Nagy

Bibliographic record

VenueLanguage Variation and Change · 2016
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsSound changeVoice-onset timeVariation (astronomy)VowelHistoryLinguisticsHeritage languageContrast (vision)GeographyPsychologyComputer science

Abstract

fetched live from OpenAlex

Abstract Korean has a typologically unusual three-way laryngeal contrast in voiceless stops among aspirated, lenis, and fortis stops. Seoul Korean is undergoing a female-led sound change in which aspirated stops and lenis stops are merging in voice onset time (VOT) and are better distinguished by the F0 (fundamental frequency) of the following vowel than by their VOT, in younger speakers' speech. This paper compares the VOT pattern of Homeland (Seoul) and Heritage (Toronto) Korean speakers and finds that the same change is in progress in both. However, in the heritage variety, younger speakers do not advance the change, unlike their Seoul counterparts. Rather they have leveled off or are perhaps reversing the change, and there is very little sex difference among the younger heritage speakers' patterns. We consider possible accounts of the differences between the Seoul and Toronto patterns, building our understanding of how language-internal variation operates in bilingual speakers, a topic that has received relatively less attention in the variationist literature.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.035
GPT teacher head0.348
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations70
Published2016
Admission routes2
Has abstractyes

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