Compensating the Harms of Sexual and Domestic Violence: Tort Law, Insurance and the Role of the State
Bibliographic record
Abstract
In Canada, the measurable health-related social and economic costs to society of domestic and sexual violence are estimated to exceed over $1.5 billion a year. Most victims of such violence are not adequately compensated by the current legal regime. In this paper, the authors draw parallels between the societal costs of domestic and sexual violence and of workplace and automobile accidents. In both of the latter environments, the government has intervened to create statutorily governed schemes that ensure adequate victim compensation. The same reasons that drove reform for industrial and automobile accidents - the high cost of tort litigation, restrictions on claims, low rate of actual compensation and the acceptance of social responsibility - should now be applied to the widespread problem of domestic and sexual violence. The authors argue that a publicly funded system is the only viable solution. The authors explore the (im-)possibility of private insurance. Neither the no-fault automobile insurance model nor the workers' compensation model is workable due to differences in the nature of harm and the relationship between tortfeasor and victim. Extending existing liability insurance is also unworkable as most policies contain exclusion clauses that prevent coverage for harms caused intentionally. Clearly, the best approach to compensate victims is a substantially enhanced public compensation scheme. As a starting point, the authors suggest combatting the current problems with Ontario's Criminal Injuries Compensation Program - such as underfunding and low awareness. They also argue in favour of establishing a clear compensation rationale for the program. The purpose of the new publicly funded program should be anchored in an attempt to acknowledge, through compensation, the need for solace; and the current approach of attempting to put a cost on individual pain and suffering of claimants should be abandoned. As a potential source of funds, the authors point to the ongoing budgetary surpluses of the Victims' Justice Fund, which they argue is currently not being used effectively.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".