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Record W2036842153 · doi:10.7202/1000483ar

Identité linguistique et poids des langues : une étude comparative entre des jeunes de milieu scolaire francophone au Nouveau-Brunswick et anglophone au Québec

2011· article· fr· W2036842153 on OpenAlexaffvenueabout
Annie Pilote, Marie‐Odile Magnan, Karine Vieux-Fort

Bibliographic record

VenueNouvelles perspectives en sciences sociales · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesFrenchSociologyPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article porte sur la construction identitaire en milieu linguistique minoritaire au Canada. Partant d’une démarche qualitative comparative entre des jeunes d’un milieu scolaire francophone au Nouveau-Brunswick et anglophone au Québec, il examine les processus à travers lesquels les jeunes construisent leur identité linguistique, c’est-à-dire à travers une négociation entre leur définition subjective de Soi et des identités transmises par Autrui (en particulier la famille et l’école). Les résultats sont présentés à partir de configurations identitaires liées au type de familles dont sont issus les jeunes interrogés : endogames majoritaires, endogames minoritaires et exogames (français et anglais). L’analyse démontre que si l’identification « bilingue » est présente chez les deux groupes de jeunes étudiés, les enjeux qui s’y rattachent varient en fonction du poids relatif de l’anglais et du français dans l’environnement nord-américain.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.159

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 studies0.0110.005
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.092
GPT teacher head0.434
Teacher spread0.342 · 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 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

Citations22
Published2011
Admission routes3
Has abstractyes

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