Negligent Investigation: A New Remedy for the Wrongly Accused: Hill v. Hamilton-Wentworth Regional Police Services Board
Bibliographic record
Abstract
In Hill v. Hamilton-Wentworth Regional Police Services Board, the Supreme Court of Canada affirmed that the tort of "negligent investigation" exists in Canada. Chief Justice McLachlin, for the majority, noted that negligent police conduct is "a significant contributing factor to wrongful convictions," and argued that a negligence action was necessary to round out the available remedies for the wrongly accused (previously limited to malicious prosecution, false imprisonment, and misfeasance in a public office). Given the media and public support offered to the wrongly convicted in recent years, the decision in Hill will be generally welcomed. Few would oppose the expansion of compensation for those who have suffered a miscarriage of justice. However, the deferential standard adopted by the Court leaves room for doubt as to the efficacy of the new tort as a remedy for the wrongfully accused. Although the majority paid lip service to the cause of justice for the wrongly convicted, it is not clear that Hill will provoke a noticeable change in police practices or increase the probability of recovery for plaintiffs. Thus, while it is a step forward in the pursuit of police accountability, it is not the magic solution that society seeks. If anything, it points to the inadequacy of tort law as a means of addressing wrongs within the justice system.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.020 | 0.011 |
| 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".