Private Law Responses to Domestic Violence: The Intersection of Family Law and Tort
Bibliographic record
Abstract
This paper explores the progressive possibilities presented by two areas of private law – family law and tort law – in achieving economic justice for women who have been victims of domestic violence. The author first considers the role spousal support law might play in providing economic redress following abuse. While the Supreme Court of Canada’s decision in Leskun v. Leskun suggests that a court might consider the consequences of spousal misconduct when making a support order, courts remain reluctant to use support awards to address the economic impact of abuse. By contrast, tort law may appear to provide a more responsive framework for battered women. Women may use the tort of battery to seek damages to compensate for direct financial impact of the violence (e.g. medical expenses) and for indirect economic harm (e.g diminished employability). However, the challenges inherent in bringing a successful tort action mean that women rarely succeed in achieving compensation. The author concludes by considering other options (e.g. a public compensation scheme) which may be a solution for women seeking financial compensation for the harms suffered at the hands of a violent spouse.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.034 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".