Construction identitaire francophone en milieu minoritaire canadien : « Qui suis-je ? », « Que suis-je ? »
Bibliographic record
Abstract
En cherchant à se doter d’une identité sociale positive, les personnes tendent à adopter des identités multiples, variées et complexes, produits de leur socialisation et expressions de leur construction personnelle. Compte tenu de cette complexité, une conception de l’identité ethnolinguistique orientée uniquement sur l’autodéfinition ne tient pas compte de la valeur ni de la signification de l’identité. Nous avons alors proposé une conceptualisation de l’identité ethnolinguistique comportant deux composantes en interaction : l’autodéfinition et l’engagement identitaire. Dans le présent article, deux questions – « Qui suis-je ? » et « Que suis-je ? » – guident l’analyse de ces deux composantes de l’identité francophone et de leur processus de construction en situation francophone minoritaire au Canada. Sont pris en compte divers aspects de la socialisation ethnolangagière.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.019 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".