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Record W4400952645 · doi:10.25688/2619-0656.2020.14.12

LEXICAL AND GRAMMATICAL CHARACTERISTICS OF A CONTACT-INDUCED VARIETY: A CASE STUDY OF CHIAC

2020· article· ru· W4400952645 on OpenAlexaboutno aff
Lana R. Zurabova, Elena G. Borisova

Bibliographic record

VenueРусистика и компаративистика. · 2020
Typearticle
Languageru
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)LinguisticsLanguage contactNatural language processingPsychologyComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

В статье представлены грамматические и лексико-семантические особенности субдиалекта шиак в контексте языкового контакта в историческом регионе Акадия(Канада), выявленные в ходе корпусного исследования. Анализу подвергаются функциональные возможности предлогов, в том числе вынесение предлогов в конец предложения; семантические характеристики наречий-интенсификаторов; вариативное использование вопросительных частиц -ti / -tu при образовании вопросов; специфика диалектной глагольной системы, включая инфинитивные формы, а также правила спряжения глаголов. The article explores the dialectal features of Acadian French in New Brunswick (NB), Canada. Acadia has been developing as a region with distinctive linguistic and cultural characteristics since the early seventeenth century (1605) after Samuel de Champlain and Pierre Du Gua de Monts discovered Port-Royal (modern-day Nova Scotia). It encompasses the Atlantic provinces including New Brunswick, Nova Scotia, Prince Edward Island, and partially Quebec (Gaspesie, Cote-Nord and Iles de la Madeleine). The study focuses on a variety of French known as chiac (or chiaque), spoken in the province of New Brunswick. Despite its limited geographical distribution (south-east of NB), chiac proves to be of interest for research: it is highly variable, mostly spoken, and lexically, semantically, phonetically, and even grammatically influenced by English. Furthermore, it shows signs of language mixing. The author argues that the presented functional and lexical features are partially due to the longlasting language contact in Acadia and a specific sociolinguistic situation within the region. The source of evidence for the present study comes from the analysis of the oral corpus Chiac-Kasparian H99 and the mini-corpus Kasparian-Leger H2004 provided by Dr. Sylvia Kasparian, Head of the Textual Data Analysis Laboratory (Laboratoire d’analyse de donnees textuelles), University of Moncton. The corpus consists of transcribed spontaneous conversations of the inhabitants of the south-east of New Brunswick. The provided linguistic material comprises an unannotated text corpus, accompanied by partial sociolinguistic data about the speakers, including age, gender, place of study, place of residence, and status of participants to each other. Therefore, our first research step was to carry out the content analysis and subsequently interpret the results. At the initial stages of analysis, the authors annotated the text corpus which enabled them to highlight several distinctive characteristics of chiac, both as a subdialect of Acadian French and as a contact-induced variety, including signs of semantic transformation in both French and borrowed adverbs; dialectal interrogative morphemes -ti / -tu, and preposition stranding. Moreover, the authors postulate variability in verb forms, conjugation system, and functioning of auxiliaries. It must be noted, that the study relies on the theoretical and empirical body of work conducted by L. Peronnet, S. Kasparian, G. Chevalier, R. King, M. Roy, A. Thibault.

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)0.001
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.005
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.067
GPT teacher head0.335
Teacher spread0.268 · 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
Published2020
Admission routes1
Has abstractyes

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