Hospital Knows Best: Court and Unfit Accused at the Mercy of Hospital Administrators: The Case of R. v. Conception
Bibliographic record
Abstract
This article analyzes the Supreme Court’s 2014 decision in R. v. Conception which considered the treatment order provisions of the Criminal Code, finding that a court may not make a forthwith treatment order without the consent of the hospital except in rare cases where a delay would breach the accused’s rights under the Canadian Charter of Rights and Freedoms (Charter). This article argues that the case represents a departure from three decades of legal developments in the sphere of civil and forensic mental health law unified by the principles of restraint and oversight. Further, the article suggests that the decision cedes court and tribunal oversight of the liberty interests of the unfit accused to unregulated hospital administrators, unless the unfit accused can establish a breach under the Charter, an eventuality which would appear to be legally impossible given that by definition the unfit accused is likely unable to instruct defence counsel. The article asserts that the unfit accused persons, who are to be the subject of a treatment orders, are unable legally to advance their Charter rights (having been found unfit). Drawing on the experiences of accused persons found not criminally responsible on account of mental disorder (NCR accused), the article suggests the Court’s expectation that the Charter will prevail and judges will maintain control over the unfit accused is unrealistic and practically impossible.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.025 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.033 | 0.032 |
| Insufficient payload (model declined to judge) | 0.003 | 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".