Colour-Blind: Discursive Repertoires Teachers Used to Story Racism and Aboriginality in Urban Prairie Schools
Bibliographic record
Abstract
This qualitative study explores how teachers' constructions of racism consistently minimized its pervasiveness in the school. Teachers constructed racism as individual not systemic, construed it as a phenomenon of places outside the school, and attributed responsibility for addressing racism to other people, particularly Aboriginal populations. Based on written responses from 95 Canadian Prairie teachers from two schools, this research examines the discourses teachers employed to narrate racism, particularly with relation to Aboriginal students. While there were some differences between inner city and suburban teachers, teachers from both environments followed discursive repertoires that absolved themselves of responsibility for addressing racism and maintained the colour-blind image of education. Interrogating these discursive repertoires exposes the systems of denial that block meaningful action upon racialized inequalities and prevent the development of a truly inclusive educational environment. This underlines the need for expanded anti-racist professional development to support critical racial reflexivity among in-service teachers.Keywords: racism in education; critical whiteness studies; in-service teachers; Aboriginal education
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.033 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".