L’intersection du discours critique et d’ouverture dans le traitement des enjeux de la pluriethnicité par les étudiants en formation
Bibliographic record
Abstract
Dans cet article, nous présentons les résultats d’une recherche qualitative portant sur le traitement de la pluriethnicité dans des cours de deux programmes de formation des en‐ seignants en Colombie‐Britannique. L’analyse des données révèle le maillage de deux discours, l’un d’ouverture et l’autre critique, dans le traitement des enjeux de la pluriethni‐ cité en éducation, lesquels s’expriment avec plus ou moins d’intensité selon les acteurs et les enjeux discutés. Le maillage des discours témoigne de la difficulté à traiter la différence et de ses enjeux en termes d’opposition simplistes, sans tenir compte des contextes et des enjeux spécifiques. Toutefois, à maints égards, le traitement discursif d’enjeux sensibles en classe a créé un espace privilégié de « fusion des horizons » ayant permis d’explorer les paradoxes de la politique du multiculturalisme en éducation et de son traitement institu‐ tionnel. Afin de soutenir l’insertion professionnelle des enseignants, la formation des maîtres ne peut faire l’économie de l’exploration des zones d’inconfort que soulève l’articulation complexe des droits, des libertés et des responsabilités nécessaires au « savoir vivre ensemble » dans les sociétés démocratiques. Mots‐clés : formation des enseignants, éducation interculturelle, multiculturalisme, dis‐ cours, représentations sociales, identité, culture. We present the results of a qualitative research study about the ways two teacher education programs in British Columbia deal with multiethnicity. The data reveal two interwoven discourses in dealing with issues of multiethnicity in education, one of openness and the other critical. These discourses are expressed with more or less intensity depending on the actors and the issues being discussed. The mixing of the discourses shows the difficulty of dealing with difference and its challenges in simplistic terms of opposition, without taking context and specific concerns into consideration. However, in many respects, talking about sensitive issues in class created an ideal place for the merging of viewpoints, making it possible to explore the paradoxes of policies and institutional practices in multicultural education. To facilitate the transition from student teacher to fully fledged professional, teacher education cannot cut corners in exploring the zones of discomfort created by the complex interaction of the rights, freedoms and responsibilities essential to knowing how to live together in a democratic society. Keywords: teacher education, intercultural education, multiculturalism, discourse, social representations, identity, culture
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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 | 0.019 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.049 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".