Parole in Canada: gender and diversity in the federal system
Bibliographic record
Abstract
Book snopsis: Just as Canada’s population has changed in the past four decades, so too has its prison population. The increasing diversity among prisoners raises important questions about how we punish those who break the law. Parole in Canada is the first book to explore how concerns about aboriginality, gender, and the multicultural ideal of “diversity” have been interpreted and used to alter federal parole policy and practice. \n \nUsing the Parole of Board of Canada as a case study, this book shows how certain facets of offender differences are selectively included for “accommodation,” while fundamental institutional structures, practices, and power arrangements remain unchanged. Sarah Turnbull argues that, as the current approach fails to challenge outdated notions about gender, race, and Aboriginality within the penal system, instead of addressing concerns around diversity, these measures end up contributing to further exclusion and discrimination within the system. By tracing the organizational approaches to gender and diversity in Canada’s federal parole system, this important book advances our understanding of penal change and highlights the challenges and complexities of accommodating offender diversities in the pursuit of a more “fair” and “appropriate” penality. \n \nScholars and upper-level students in the fields of law, criminology, sociology, gender studies, and Aboriginal studies will appreciate this analysis of diversity initiatives in parole policy and practice.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".