Census-taking and theater-making: Real and imagined perceptions and experiences of school and neighborhood safety for racialized and white youth
Bibliographic record
Abstract
This article explores the unexpected discovery of a significant divergence between the strong feelings of safety and belonging reported in a school and neighborhood safety survey, and the discursive, contradictory, and complex narratives about safety revealed by students’ storytelling through theater and narratives shared with researchers in a Toronto classroom. The authors highlight how institutionalized definitions of safety most often reflect normative, white experiences, while reproducing patterns of oppression in the lives of racialized students (and teachers) by sending clear messages about the kinds of safety narratives that do, and do not, belong. Our analysis opens a line of inquiry between what the pursuit of being a ‘safe school’ is meant to do, what it does, and what it may fail to do, with implications for how school boards might differently evaluate student safety, endeavor to create “safe spaces” within schools, and enact school policies better able to improve the lives of racialized and white youth.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".