Identité professionnelle et rôle des enseignantes et des enseignants dans les écoles de langue française en Ontario
Bibliographic record
Abstract
In addition to transmitting academic knowledge and socializing students, teachers working in a linguistic minority context must be a linguistic and cultural model for these young people. Their task is complex and comes with many challenges not faced by their counterparts in English-language schools. This research aims to understand how teachers in French-language schools in Ontario perceive themselves personally and professionally. Based on the life stories of seven teachers, we are interested in exploring how their rapport to identity will have an influence on how they perceive their role in fulfilling the mandate of French-language schools, particularly with regard to the transmission of French language and culture, given the close link between personal and professional identity. Analysis of the results reveals that teachers understand their role as agents of linguistic reproduction, but have a poor understanding of their role in the transmission of French culture. Despite the many policies and initiatives implemented by the government to support their work and help them fulfill the mandate of French-language schools, teachers tend instead to interpret their role according to their representations of their own linguistic and cultural identity, as well as their representations of the culture of expression, interpreted according to a traditional and folkloric vision of this notion.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".