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Record W2165433068 · doi:10.1017/s0952675706000741

<i>Low vowels and transparency in Kinande vowel harmony</i>

2006· article· en· W2165433068 on OpenAlexaff
Bryan Gick, Douglas Pulleyblank, Fiona Campbell, Ngessimo Mutaka

Bibliographic record

VenuePhonology · 2006
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVowel harmonyVowelMid vowelHarmony (color)NasalityTransparency (behavior)LinguisticsMathematicsSpeech recognitionMandarin ChineseAcousticsComputer scienceFormantPhysicsPhilosophy

Abstract

fetched live from OpenAlex

This paper addresses theoretical issues confronting cross-height harmony systems through an experimental study of Kinande, a Bantu language of the Democratic Republic of Congo. Using a combination of acoustic analysis and lingual ultrasound imaging, we evaluate previous proposals concerning the phonetic correlates of the harmonic vowel feature and the transparency of low vowels. Results indicate that (i) although a multivalued scalar acoustic feature in F1/F2 space is not adequate to distinguish all vowel categories in Kinande, the cross-height feature does correlate acoustically with F1, (ii) the cross-height feature of Kinande involves systematic tongue-root articulations and (iii) low vowels in Kinande are not neutral to harmony in the way reported in earlier work, but exhibit significant and systematic tongue-root advancement and retraction according to the dictates of harmony.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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

Citations69
Published2006
Admission routes1
Has abstractyes

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