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Record W3196866202 · doi:10.1016/j.wocn.2021.101096

Systematic co-variation of monophthongs across speakers of New Zealand English

2021· article· en· W3196866202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Phonetics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of British Columbia
FundersMarsden Fund
KeywordsVariation (astronomy)Sound changeVowelContrast (vision)Set (abstract data type)LinguisticsComputer scienceSpeech recognitionArtificial intelligence

Abstract

fetched live from OpenAlex

The study of phonetic variation and change has tended to concentrate on particular variables in isolation, and it has proven challenging to move beyond an analysis of individual variables or small groups of variables, towards a better theoretical and empirical understanding of entire vowel systems. We develop a methodology that facilitates the study of co-variation, and introduce a large scale analysis of how elements of full sound systems co-vary across hundreds of speakers, demonstrating how constellations of vocalic variables operate together. Our data-set comprises F1 and F2 for 10 monophthongs of New Zealand English. We first obtain estimates of how advanced each speaker is with respect to changes in each of the vowels, irrespective of known predictors of sound change (i.e. year of birth, gender, speech rate). This is done by extracting by-speaker intercepts from Generalised Additive Models. We then use Principal Component Analysis on these intercepts to investigate the underlying structural co-variation that exists across the vocalic variables. Within a large subset of vowels, we see ‘leaders’ and ‘laggers’ of sound change; however, there are also groups of vowels which stand in opposition to each other, such that if a speaker is innovative in one, they tend to be conservative in the other. Some sets of covarying vowels could be linked by structural relationships (such as chain-shifting), but there are also covarying sets of vowels with no clear structural relationship, and which may be linked by shared social meaning. Our analysis provides novel insights into the structure of sound systems, demonstrating the existence of structured patterns in the realisations of specific vocalic variables across a large group of speakers. This approach offer a means to overcome long-standing methodological challenges in the study of phonetic co-variation, paving the way for research to move beyond the analysis of individual variables, towards an understanding of variation and co-variation in sound systems.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.335
Teacher spread0.312 · 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