Embodying Difference: A Case for Anti-Racist and Decolonizing Approaches to Multiliteracies
Bibliographic record
Abstract
This paper asks what pedagogies are needed as Canadians are invited to reconcile colonial pasts with contemporary forms of racism and enduring colonial structures. Sharing discourses of race from youth who participated in a year-long ethnography, and moments from a drama-based pedagogical collaboration, this paper suggests ways of updating multiliteracies frameworks so as to better account for the networks of power that circulate in classrooms. This project had the dual aims of exploring discourses of difference used by students, as well as drama as a multimodal, embodied, and (post)critical pedagogy for unpacking differences embedded in the Grade 9 social studies curriculum. Drawing on feminist pedagogies, critical race studies, and Indigenous critiques of education, the author argues that embodiment and subjectivity are central to teaching and learning, and illustrates through excerpts from interviews and fieldnotes, how race, intersectionality, and White supremacy influence interactions in the classroom. The paper concludes by proposing that multiliteracies and multimodal pedagogies would benefit from centralizing anti-racist and decolonizing approaches to learning, in addition to the networks in which literacy practices occur and through which meaning is made.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.036 | 0.117 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.004 | 0.008 |
| 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".