MétaCan
Menu
Back to cohort

ENGLISH BORROWINGS IN FRENCH IN THE ASPECT OF CANADIAN BILLINGVISM

2021· article· en· W3187941337 on OpenAlexaboutno aff
O. B. Alekseeva

Bibliographic record

VenueWritings in Romance-Germanic Philology · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsPhenomenonContext (archaeology)Neuroscience of multilingualismVocabularyGovernment (linguistics)FrenchGrammarComputer scienceSociologyHistory

Abstract

fetched live from OpenAlex

The article examines English borrowings into French in the context of Canadian bilingualism in connection with Canadian language policy, which combines several centralized language policies implemented by the federal government and regional policies pursued by provincial governments, including Quebec. To understand and analyze such a linguistic phenomenon, the article briefly discusses the historical causes of Canadian bilingualism. The study focuses on the lexical, grammatical and phonetic features of Canadian French and suggests that borrowing from both British and American versions of English into French has led to a unique combination that can only be identified as an independent phenomenon. The characteristics of Canadian French vocabulary, spelling, and grammar discussed in this article illustrate that Canadian French cannot be fully identified with any other type of French. The Canadian version of the French language is expressive, authentic, including through borrowings from the English language. The study emphasizes that the Canadian version of the French language, provided constant interaction with the English language, is learned naturally, and the rules naturally. Bilingual speakers agree on universal rules without knowing them, share and use these rules, but never clearly study them, because it seems impossible to teach how to change the code and maintain the structural integrity of the statement. The findings contradict the expectation that borrowed words harm the language that borrows them, so it was found that bilingual speakers who speak both English and French implicitly understand and use the rules of both languages, and borrowing and switching codes do not lead to language erosion.

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)0.003
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 score0.588
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.221
Teacher spread0.193 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueWritings in Romance-Germanic PhilologySame topicLinguistics, Language Diversity, and IdentityFrench-language works237,207