« Un-frenching » des Canadiennes françaises : histoires des Fransaskoises en situation linguistique minoritaire
Bibliographic record
Abstract
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".