Rupture, not injury: reframing repair for Black and Indigenous youth experiencing school pushout
Bibliographic record
Abstract
In this article, the authors describe their multi-year youth participatory action research project, Making Sense of Movements (MSOM), with Black and Indigenous high school students in Toronto. Youth co-researchers in MSOM designed a study on school pushout that reveals the pervasiveness of racism in schools and the inadequacy of responses to racist incidents by school personnel. School staff and teachers often treat racist incidents as isolated events that can be easily resolved. However, the authors situate Black and Indigenous students’ experiences of racism in their high schools within the ongoing legacies of settlement and slavery. Learning from Black and Indigenous feminist theories of rupture and refusal – see Hartman’s Scenes of Subjection: Terror, Slavery, and Self-Making in Nineteenth-Century America (1997); Simpson’s Mohawk Interruptus: Political Life across the Borders of Settler States (2014); and Tuck and Yang’s ‘Decolonization is not a metaphor’ (2012) – the authors invite readers to reframe the assumed ease and completeness of repair. They theorize racism and antiblackness as a rupture rather than an injury, which has important implications for school policy and how schools address racism. By moving beyond reparative frameworks, the authors engage rupture as a more meaningful starting place.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.028 | 0.025 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.009 |
| 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".