Profiling and the Canadian Carceral State | Les profilages et l’État carcérale canadien
Bibliographic record
Abstract
The Canadian Carceral State routinely engages in profi ling of people pushed to the margins by colonialism, racism and white supremacy, capitalism and classism, patriarchy and heteronormativity, ableism, and other violent structures.This is evident in who is targeted, harmed, and killed by policing, imprisonment, immigration, child apprehension, health, social services and assistance, and other carceral institutions.The Journal of Prisoners on Prisons invites contributions by current and former prisoners, their loved ones, and grassroots community organizations that document, critique, and propose alternatives to profi ling evident in carceral practices and experiences.Prospective contributors can also submit pieces examining resistance eff orts behind and beyond bars to build decarceral futures.Les profi lages des personnes marginalisées par le colonialisme, le racisme et la suprématie blanche, le capitalisme et le classisme, le patriarcat et l'hétéronormativité, le capacitisme et d'autres structures violentes est une pratique récurrente chez l'État carcéral canadien.Cela est évident lorsqu'on observe qui est ciblé, blessé et tué par les services de police, l'emprisonnement, l'immigration, l'appréhension d'enfants, de santé, ainsi
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.027 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".