Wrongful Remand: Miscarriages of Justice in the Canadian Bail System
Bibliographic record
Abstract
Some people detained pending trial are factually innocent. They committed no crime, as a matter of fact,but they spend weeks, months, or years in maximum security detention centers awaiting trial. Their cases have been largely overlooked in Canadian jurisprudence and legal scholarship. Consequently, little is known about how often these people are detained in custody or what features of the bail system permit or promote their detention. This dissertation presents previously unreported case studies, as revealed by transcripts and official court records, to explain how the bail system may treat the factually innocent. Building upon methodology and theory from wrongful conviction scholarship, the dissertation argues that pre-trial detention amounts to a miscarriage of justice (“wrongful remand”) when a person is detained for weeks, months, or years and the charges are stayed, withdrawn, or dismissed due to evidence tending to prove factual innocence. These miscarriages raise important questions about the theoretical and constitutional legitimacy of the current bail system. They reveal how the system may set the stage for a wrongful conviction, either at the guilty plea or trial phase. They display how the system may, in effect, devalue the trial process, by incarcerating and stigmatizing the wrongfully accused defendant before he or she can obtain access to justice at trial. And they reflect procedural and substantive bail principles that overemphasize law and order objectives while overlooking how detention may undermine the public interest. The dissertation also advocates a new approach to pre-trial release—an approach that would provide stronger protection for the factually innocent while promoting public safety and fair trials.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.041 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".