Racial Realism in Canadian Teacher Education: The Potential of Cross-Racial Critical Professional Mentorship
Bibliographic record
Abstract
Critical professional development (CPD) facilitates creative empowering teacher practice and racial justice accountability. This paper extends United States’ CPD literature through a qualitative critical race analysis of a one-year Canadian teacher education anti-racist cross-racial mentorship project. Focus groups with 13 teacher candidate (TC) members of the project suggest cross-racial CPD mentorship enhanced the TCs’ anti-racist 1) experiences with their teacher education program, 2) engagement with conversations, and 3) pedagogical comprehension. A fourth finding revealed the TCs recognized their lack of comprehension regarding whiteness and a desire to learn more. Through a critical race theory racial realist lens, the findings suggest practical ways in which Canadian anti-racist teacher educators can contribute to the democratic racial equity and decolonization commitments of education systems.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.050 | 0.030 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".