Private Law, the State and the Duty to Protect: Tort Actions for Police Failures in Gendered Violence Cases
Bibliographic record
Abstract
In this paper I address the possibilities for using private law to redress wrongs in which the state itself is implicated, involving the negligence of public authorities. Focusing specifically on police failures to protect in relation to gendered violence, the complex issues thrown up by the legal actions I examine allow for broader reflections on the possibilities for law's engagement with problems of social justice, and in particular, the possibilities for demanding state accountability for remedying these problems. I comparatively analyse recent Canadian caselaw which suggests a move towards a slowly expanding conception of the existence of a private law duty owed by the state, and specifically, the police, to women known to be at particular risk, or, at “special distinctive risk” of violence. Both the decisions in Jane Doe v. Metropolitan Toronto (Municipality) Commissioners of Police and in B.M. v. British Columbia (Attorney General) exemplify this modest and incremental expansion of a recognition of a duty owed by the police to women harmed by violence perpetrated by third parties. In discussing these two key cases in which negligence actions have been brought forward for police failure to protect (or failure to protect through warning), I assess the nature of the judicial reasoning undertaken in the judgments, and address the public-private fault line which is expressly engaged in these decisions. More broadly, I explore what these cases tell us about the possibilities and perils of using tort and constitutional law to impose state accountability for so-called “private” violence against women.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.042 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.014 | 0.010 |
| 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".