Combating racism with critical race theory: Theorizing social movement learning from anti-racism movements in Canada
Bibliographic record
Abstract
Despite the success of critical race theory (CRT) in bringing about an intellectual movement that profoundly influenced the setting of a racial justice agenda in educational research since its inception 30 years ago, the material racial inequity still prevails and continues to subordinate people from racialized communities in and beyond the classroom. As such, it is time that we re-examine the way CRT has been interpreted and applied in educational research to better fulfill CRT’s promise of racial justice. The rise of the current wave of anti-racism movements presents a critical moment for such re-examination. This article therefore examines the current and potential engagement with CRT in educational research by analyzing and theorizing CRT-informed social movement learning to illustrate how we can fully realize the anti-racism potential of CRT in educational research. What we learn from the various forms of learning in the anti-racism movements suggest that a combination of anti-racism voices and practices is vital to mobilize learning as enactment of multiple forms of agency to combat racism through critical creative anti-racism struggles. Future CRT educational research can further recognize CRT as an integrated and evolving framework in which the centering of race and racism to illuminate multiple nexus of subordination serves as a starting point to develop anti-racism strategies and that CRT educational research can embrace a form of criticality against racism as practices of critique and creation of alternatives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".