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Record W4224986372 · doi:10.1515/phon-2022-2019

Northern Raglai voicing and its relation to Southern Raglai register: evidence for early stages of registrogenesis

2022· article· en· W4224986372 on OpenAlexafffund
Marc Brunelle, Jeanne Brown, Phạm Thị Thu Hà

Bibliographic record

VenuePhonetica · 2022
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsVoiceRegister (sociolinguistics)Relation (database)LinguisticsPsychologyCommunicationComputer sciencePhilosophyData mining

Abstract

fetched live from OpenAlex

Northern and Southern Raglai are two closely related Austronesian dialects (Chamic branch) spoken in south-central Vietnam. Although they are mutually intelligible, Northern Raglai is described as having a voicing contrast in onset stops, while Southern Raglai is assumed to have replaced the Chamic voicing contrast with a register contrast realized on the whole syllable (but primarily on its vowel). A production study of the two dialects confirms that Northern Raglai preserves a voicing contrast, even if most women exhibit partial devoicing of their voiced stops, and that Southern Raglai has developed a register contrast based on F1 and phonation cues at the beginning of vowels. The weights of the acoustic properties of voicing and register are similar across ages and genders, suggesting that the two laryngeal contrasts are phonetically stable. Even if there is little evidence of change in progress, a close inspection of the Northern Raglai voicing contrast reveals voicing-conditioned modulations of F1 and perturbations of phonation after partially devoiced stops that could be precursors of a register system similar to that of Southern Raglai. We argue that this is a pathway to registrogenesis and speculate about the articulatory laryngeal mechanisms that could trigger registrogenetic changes. Our data also show that the Northern Raglai voicing contrast is unstable in aspirated stops and that voiced aspirated stops typically have a partially voiceless and partially voiced aspiration.

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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.102
GPT teacher head0.373
Teacher spread0.271 · 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

Citations73
Published2022
Admission routes2
Has abstractyes

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