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Record W4385971473 · doi:10.1080/13670050.2023.2242562

Exploring attitudes towards French, English, and code-switching in Manitoba (Canada)

2023· article· en· W4385971473 on OpenAlexafffundabout
Maria Rodrigo-Tamarit, Verónica Loureiro-Rodríguez

Bibliographic record

VenueInternational Journal of Bilingual Education and Bilingualism · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Manitoba
FundersUniversity of ManitobaResearch Manitoba
KeywordsSolidarityCode-switchingPrestigeFirst languageNeuroscience of multilingualismPsychologySociologyFeelingSociolinguisticsLinguisticsSociocultural evolutionImmigrationSocial psychologyHistoryPolitical scienceAnthropologyPolitics

Abstract

fetched live from OpenAlex

This study contributes to the understanding of attitudes towards monolingual and code-switched varieties by examining the perceptions of 95 bilinguals towards Manitoban French, Canadian English and code-switching in Manitoba, a Canadian province where French is a minority language with official federal status. By means of a matched-guise test, we explore French-English bilinguals’ social evaluations of the three linguistic varieties and examine how these social evaluations vary according to participant characteristics (i.e. age, gender, mother tongue, origin, and sociocultural identity). In our experiment, participants listened to a speaker using Manitoban French, Canadian English and code-switching and rated each guise on several solidarity and status traits. Results from the cumulative link mixed effects models reveal that French and English are rated similarly for status. Overall, both French and English elicit feelings of attachment, but a preference towards French emerges among participants born in Manitoba. Code-switching is rated lower than the monolingual varieties in most status and solidarity traits, which indicates that our participants implicitly value linguistic purism. However, results also show that participants born in Manitoba and those with French as their mother tongue ascribe covert prestige to code-switching.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.884

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 head0.102
GPT teacher head0.371
Teacher spread0.269 · 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 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".

Quick stats

Citations6
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Bilingual Education and BilingualismSame topicLinguistic Variation and MorphologyFrench-language works237,207