Teaching As A Two-Way Mirror: Marginalized Pre-service Educators and The Impact Of Stereotype Threat in Canada’s Teacher Education
Bibliographic record
Abstract
This thesis examines how stereotype threat—a psychological phenomenon wherein individuals fear confirming negative stereotypes about their identity group (Steele & Aronson, 1995)—shapes the experiences and retention of racialized teacher candidates (TCs) in a Canadian teacher education program. While research has documented the cognitive and affective toll of stereotype threat on marginalized groups (Breese et al., 2023), few studies have explored its manifestation within Canadian teacher education. This study employed a qualitative phenomenological design to explore the experiences of racialized TCs at a predominantly White institution (PWI). Participants were recruited through demographic surveys and an adapted version of the Stereotype Vulnerability Scale (SVS; Bullock et al., 2020). Six individuals with elevated SVS scores were selected for in-depth, semi-structured interviews. Thematic analysis, conducted with the support of NVivo, uncovered four interrelated themes: the embodied realities of navigating disjunction between institutional Equity, Diversity, Inclusion, and Indigeneity (EDII) commitments and material conditions; experiences of marginalization across both program and practicum settings; the role of identity congruence in shaping belonging; and the challenges of achieving legibility as a teacher. Participants described a range of coping strategies—including emotional distancing, racial affinity grouping, and code-switching—as simultaneously necessary and emotionally taxing. This study offers a nuanced understanding of how racialized TCs internalize and resist stereotype threat, and highlights the emotional labour involved in asserting their place within a profession that often questions their legitimacy. The thesis concludes with actionable recommendations for transforming teacher education into a more equitable and affirming space.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.040 | 0.015 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".