Confronting Race and Colonialism: Experiences and Lessons Learned From Teaching Social Studies
Bibliographic record
Abstract
Literature on teacher education and encounters with race highlight some of the difficulties that teacher candidates face when they confront their own racialized subjectivities. However, many of these projects focus exclusively on Whiteness studies, explicating how White teacher candidates come to witness their own racialized Whiteness in relation to their epistemological understandings of the world. In this paper, I diverge from this pattern of thought, exploring a subset of the tenets of critical race theory, that of silences and exclusions, pervading my own teaching in a primary/junior social studies methods class and exploring how these structured my lessons. Specifically, I look at how counternarratives, critiques against liberalism, and multiculturalism and encounters with racialized and colonial supremacy were involved in my pedagogical strategies. I conclude by suggesting that although these methods may seem daunting for the primary/junior classroom, they can provide valuable insights for teacher candidate orientations to their own pedagogies. Keywords: social studies pedagogy; anti-racism in practice
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.037 | 0.041 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".