Sureties as Civilian Jailers: Understanding the Role of the Court in the Lives of Accused Released on Surety Bail in Ontario
Bibliographic record
Abstract
Changes to Ontario's bail system (2017) are intended to keep accused out of custody and in the community as they await trial. For the Ministry of the Attorney General, living in the community while on bail is a vast improvement to remand because there is minimal state involvement in the lives of accused, resulting in fewer personal and administrative disruptions. Yet, most accused in the province require a surety to be released. Justices of the peace, Crowns, and even defense counsel expect sureties to act like civilian jailers, which questions the level of state intervention at this stage in the legal process. Previous scholarship on bail attributes the overuse of surety releases to a culture of risk aversion whereby the courts offload responsibility and blame for the accused's actions onto the surety. By exploring how court officials describe and determine who an appropriate surety is and the types of powers afforded to them, this paper argues that although sureties are legally obligated to supervise the accused, the court is still heavily involved in defining what this role looks like and how it should unfold outside the courtroom. The qualitative findings provide important insight into how criminally suspect individuals are governed in the province more generally.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.040 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".