Reasonable Bail or Bail at All Costs? Defence Counsel Perspectives on a Coercive Environment
Bibliographic record
Abstract
Abstract Bail decisions are largely shaped by private, out-of-court negotiations between Crown attorneys and defence lawyers. While accused persons rely on the professional expertise of defence lawyers to navigate bail negotiations and secure them the best possible outcome, much remains unknown about how lawyers prepare for and negotiate bail. This study examines the process of bail preparations and negotiations from the defence’s perspective based on data from 18 semi-structured interviews with defence lawyers. The findings show that, while defence lawyers argue for reasonable bail terms, their ultimate goal is to obtain a release for their client. Defence lawyers also prioritize collecting and strategically using information about the case and the Crowns and justices with whom they work. They often adopt a risk-averse and cooperative approach with Crowns to avoid delaying or preventing their client’s release, even if that means agreeing to additional conditions. Our findings inform efforts to reform bail processes.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".