COVID-19, the Shadow Pandemic, and Access to Justice for Survivors of Domestic Violence
Bibliographic record
Abstract
The COVID-19 pandemic has co-existed alongside a far less visible “shadow pandemic” of violence against women, with COVID-19 impacting the number and complexity of domestic violence cases and enabling new tactics for coercive control. This article provides a preliminary assessment of the extent to which Canada’s responses to the COVID-19 pandemic have prioritized the safety of women and children, with a focus on the courts and women’s access to justice. We examine court directives and judicial decisions triaging which cases would be heard as “urgent,” as well as courts’ decisions on the merits in cases involving domestic violence and COVID-19, spanning the areas of family, child welfare, criminal law, and civil protection orders. In the sixty-seven reported decisions in our sample, we find very little awareness overall of the heightened risks for survivors during COVID-19, in keeping with the pre-pandemic tendency of decision makers to focus on incident-based physical violence instead of patterns of coercive control. Our analysis also suggests that survivors’ ability to prove domestic violence and secure court orders that would help to ensure their safety was hampered not only by procedural complexity but also by the reduced availability of a range of services—health, counselling, housing, and supervised access centres, for example—as a result of COVID-19. The cases further reveal significant differences in judicial interpretation of the risks of COVID-19 relative to the risks of domestic violence, often depending on the area of law in question. This again aligns with observations of the judicial treatment of domestic violence prior to the COVID-19 pandemic, with different and sometimes conflicting norms and assumptions prevailing in different legal contexts. We conclude that despite some positive government responses and judicial decisions, COVID-19 has further exposed many of the gaps in knowledge about domestic violence and in the supports and resources necessary to make women and children safe that long pre-dated COVID-19. In addressing the ongoing pandemic of violence against women, we offer some suggestions of measures to improve access to justice during this and future disasters.
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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 | 0.022 |
| 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 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".