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Record W2624065219

« Un-frenching » des Canadiennes françaises : histoires des Fransaskoises en situation linguistique minoritaire

2017· article· fr· W2624065219 on OpenAlexaffabout
Anna Von Staden, Andrea Sterzuk

Bibliographic record

VenueoURspace (University of Regina) · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicLinguistic and Sociocultural Studies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsHumanitiesSociologyContext (archaeology)ArtHistory
DOInot available

Abstract

fetched live from OpenAlex

Cette étude aborde le phénomène de la perte de la langue première chez cinq Fransaskoises. En examinant leur situation linguistique minoritaire, ainsi que leurs expériences particulières dans les domaines communautaires, scolaires et enfin familiaux, tout au long de leur vie, nous avons pu identifier certains éléments, selon les perceptions de nos participantes, qui ont contribué à cette perte de la langue française. L’étude suggère que les relations de pouvoir inéquitables entre les langues (Bourdieu, 1977, 1980, 1989 ; May, 2008 ; Norton, 2000) ont le plus influencé les perceptions, les attitudes et les actions linguistiques de ces femmes en ce qui concerne l’utilisation et la valeur de la langue française à travers le temps et l’espace.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.612

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.008
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.018
GPT teacher head0.246
Teacher spread0.227 · 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 designNot applicable
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

Citations3
Published2017
Admission routes2
Has abstractyes

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