Reflections on operationalizing an anti-racism pedagogy: teaching as regional storytelling
Bibliographic record
Abstract
Responding to rising social tensions and ongoing theoretical and political changes in the study of geography, we advocate for greater operationalizing of anti-racism pedagogies within the field. Such pedagogies undermine long-standing geographic knowledge systems that marginalize and misrepresent people of color while also distorting and misinforming the worldviews of a White society. Drawing from classroom successes and uncertainties, five educators explore the anti-racist possibilities of geography education as a form of “regional storytelling.” Regions, one of geography’s formative constructs, play a central role within popular and academic understandings of racial differences and identities. Making exclusionary moral judgements about regions and associated populations has long been at the core of the colonization and racialization process. Contributors use reflexive storytelling – understood here as both a classroom instructional method and a way to create supportive spaces for educators to reflect on their praxis – to identify and discuss strategies for carrying out anti-racist, regionally-based teaching, the instructional decisions and challenges faced in the classroom, and perceptions of student response and anxieties. We also reflect on how the wider regional and racial positionalities of teachers and students shape the way an anti-racist pedagogy is enacted, interpreted, and realized within the higher education classroom.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".