Practicing Professional Discomfort as Self-Location: White Teacher Experiences With Race Bias Mitigation
Bibliographic record
Abstract
This study is among the first in Canada to research implicit race bias mitigation in secondary teacher practice. The findings emerge from data collected from a ten-month engagement period with 12 Ontario teachers who, alongside the research team, codesigned a race bias mitigation plan based on four to six varied mitigation strategies. These included technical and dialogical activities and a required reading of one anti-racist and/or anti-colonial book. Throughout the project, teachers engaged in ongoing reflection, journaling, email exchanges and an in-person interview. A thematic analysis of this data was completed (Ryan & Bernard, 2003). The design of this study was underpinned by a braiding of social psychology with critical race theory, second wave White teacher identity studies and other approaches. This multimodal approach brings a critical and dynamic reading of whiteness in education. Three broad preliminary findings have emerged from this study. First, teacher perceptions of efficacy of implicit race bias mitigation strategies relied on their noticing of conscious changes in their perceptions of and experiences with race, racism and Black, Indigenous and People of Colour (BIPOC) students. Second, the concurrent use of critical anti-racist strategies, alongside implicit race bias mitigation strategies, seemed to instigate participants’ deepest reflections on race. Finally, this synergy and the long duration of the project contributed to the participants’ evolving understandings of racism in education as a phenomenon that goes beyond the domain of the individual. The results may deepen our understandings of the challenges and opportunities surrounding implicit race bias mitigation work in terms of teacher practices and theoretical considerations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".