Teachers’ critical reflection: what are the practices for social justice in education?
Bibliographic record
Abstract
This article explores teachers’ participation in the school’s social justice system through the lens of the critical multicultural approach (May & Sleeter, 2010; May, 2000; 2003). Based on a research project about reconstruction and the theorization of teachers’ stories of practice (Desgagné, 2005) in a multiethnic context, data was collected from teachers in highly multiethnic primary schools in Québec. They were asked to narrate a story about a problem or an event with an immigrant or refugee student in their class. Four of these stories have been selected for this article. Our aim was to analyze the teachers’ cultural responses and their perception of their roles in supporting their students. Our analysis shows that although these teachers tend to make changes to their students’ reality, they cannot escape or contest “alone” the norms of an academic, societal and political system that governs its power relationships and privileges, its dominant norms and values.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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; a candidate call from one teacher head, 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".