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Record W4401633459 · doi:10.21083/nrsc.v2023i17.7187

Regional variation in high vowel deletion in New Brunswick French: Preliminary observations

2023· article· en· W4401633459 on OpenAlexafffundvenueabout
Władysław Cichocki

Bibliographic record

VenueNouvelle Revue Synergies Canada · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversité LavalUniversité du Québec à MontréalUniversity of GuelphUniversité de MontréalUniversity of New Brunswick
FundersUniversité de Moncton
KeywordsVowelVariation (astronomy)Regional variationLinguisticsGeographyPolitical scienceAstrophysicsPhilosophyPhysics

Abstract

fetched live from OpenAlex

This paper presents findings of a descriptive study that suggest that the deletion of high vowels, a process that is generally associated with Laurentian French, may have begun to spread across francophone regions of New Brunswick. The study examines the pronunciation of /t, d/ + /i, y/ sequences in a small number of lexical items, with a focus on vowel deletion. Based on acoustic phonetic analyses of sentences read by 136 speakers from the five main French-speaking regions in New Brunswick, results indicate that /i, y/ deletion rates are relatively high in the NorthWest, a region that is located adjacent to Quebec, but lower in other regions, with the lowest rates occurring in the SouthEast. Deletion rates are significantly higher among younger speakers than older speakers, indicating that this may be a sound change in progress. The results highlight an interaction between high vowel deletion and /t, d/ affrication. These preliminary observations provide guidelines for future dialectological and phonetic research on this process.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.804
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.035
GPT teacher head0.255
Teacher spread0.220 · 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 teacher head, 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

Citations0
Published2023
Admission routes4
Has abstractyes

Explore more

Same venueNouvelle Revue Synergies CanadaSame topicLinguistic Variation and MorphologyFrench-language works237,207