MétaCan
Menu
Back to cohort
Record W4246869491 · doi:10.1017/cnj.2016.39

Supralaryngeal implementation of length and laryngeal contrasts in Japanese and Korean

2017· article· en· W4246869491 on OpenAlexaff
Alexei Kochetov, Yoonjung Kang

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2017
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsObstruentDuration (music)PsychologyLinguisticsDegree (music)Voice-onset timeAudiologyMathematicsVoiceAcousticsMedicinePhysics

Abstract

fetched live from OpenAlex

Abstract This article investigates supralaryngeal characteristics of Japanese and Korean length and laryngeal contrasts in stops and affricates. Electropalatography data collected from five Japanese and five Korean speakers revealed similar differences among the consonants in the degree of linguopalatal contact and duration of the closure. Japanese (voiceless) geminate and Korean fortis obstruents were most constricted and had the longest duration (although considerably longer in Japanese). Japanese voiced and Korean lenis obstruents were least constricted and had the shortest duration. Japanese voiceless (singleton) and Korean aspirated obstruents showed intermediate degree of contact and duration. Both stops and affricates showed a positive correlation between degree of contact and duration. The results show that the two very different sets of phonological contrasts are implemented similarly at the supralaryngeal level. These cross-language similarities and cross-category differences are proposed to result from the application of independently-motivated phonetic enhancement rules to distinct phonological representations of laryngeal/length contrasts in the two languages.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.335
Teacher spread0.314 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Linguistics / La revue canadienne de linguistiqueSame topicPhonetics and Phonology ResearchFrench-language works237,207