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Record W291114972 · doi:10.3138/ijcs.47.187

Être bilingue à Sudbury (Ontario)Étude sur le contact des langues et lareprésentation des identités

2013· article· en· W291114972 on OpenAlexvenueaboutno aff
María Teresa Pisa Cañete

Bibliographic record

VenueInternational Journal of Canadian Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic and Sociocultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNeuroscience of multilingualismSociolinguisticsFrenchLingua francaSociologyLinguisticsLanguage contactNormativeMultilingualismVitalityEthnologyGender studiesAnthropologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

Abstract: In this article, we follow the theoretical sociolinguistics procedures used by Milroy, Heller and Mougeon on the choice of language in situations of bilingualism. Fieldwork among five bilingual francophone families in Greater Sudbury / Grand Sudbury (Ontario) enabled us to know the social factors that influence their choice of language in different situations of everyday life. In addition, these families represent two subgroups of the Franco-Ontarian minority population described by Duquette: on the one hand, an elite that promotes a normative French language and the traditional values of both the French culture and, on the other hand, the bilingual speakers for whom the English language offers attractive economic and cultural resources. Differences among Francophones weaken the vitality of their community, while English is required as a lingua franca, despite the historical struggles to achieve a certain level of education, to get jobs or to access a French sociocultural development in Ontario.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.072
GPT teacher head0.359
Teacher spread0.287 · 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".

Quick stats

Citations1
Published2013
Admission routes2
Has abstractyes

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Same venueInternational Journal of Canadian StudiesSame topicLinguistic and Sociocultural StudiesFrench-language works237,207