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Record W2970423848 · doi:10.33137/twpl.v41i1.32760

Asymmetry of Kazakh velar and uvular consonants

2019· article· en· W2970423848 on OpenAlexaffvenue
Heather Lynn Yawney

Bibliographic record

VenueToronto Working Papers in Linguistics · 2019
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVoiceVowelLinguisticsConsonantOptimality theoryMorphemeMathematicsSpeech recognitionComputer sciencePhonologyPhilosophy

Abstract

fetched live from OpenAlex

Little descriptive work has been done on the place and voicing restrictions of the asymmetrical velar and uvular consonant inventory in Kazakh. In Kazakh, velar and uvular consonants are restricted depending on their neighbouring vowel. Velars appear in front vowel environments and uvulars appear in back vowel environments (place restriction). Voiced and voiceless velars and uvulars are restricted depending on their position in the word. At the morpheme boundary, velars and uvulars are voiceless in the word-final position and voiced in the stem-final position, when followed by a vowel-initial suffix (voicing restriction). The results from elicitation-based production experiments with six native Kazakh speakers reveal that the place restriction is not productive from real words to nonce words but the voicing restriction is. The data suggests a derived-environment effect where the resulting voicing process is conditioned morphologically. A theoretical analysis within Optimality Theory captures the voicing pattern using an indexed-markedness constraint and Local Conjunction.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.319
Teacher spread0.301 · 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 designQualitative
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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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