Government response to the increase in gender-based violence during the pandemic in Canada: Lessons for addressing inequity in emergency management practice
Bibliographic record
Abstract
A harmful untended consequence of the protective public health orders issued during the coronavirus disease 2019 pandemic was an increase in gender-based violence (GBV). This study examined the response of federal, provincial, and territorial governments in Canada to GBV during the peak of the pandemic (between February 2020 and October 2021) through a review of relevant media releases. These documents were then assessed for evidence of effective crisis leadership and compared to established international guidance for addressing GBV in disasters and other humanitarian emergencies. Five major themes emerged from the media review with respect to government communications and actions. First, governments announced funding to organizations working in the domestic violence sector to help support their ability to adapt their services during the pandemic. Second, media releases described efforts undertaken by governments to expand several different types of support services for victims of GBV. Third, governments promoted awareness of the ongoing problem of GBV, as well as its increase during the pandemic. Fourth, government communications acknowledged heightened risk for some populations, including Indigenous women, lesbian, gay, bisexual, transgender, queer, and intersex populations, and those at risk of human trafficking. Fifth, legislative and policy changes were announced by some governments during the pandemic. An analysis of the timing of communications suggests that only the federal government and one third of provinces and territories took early action to address the increase in GBV during the pandemic, which is consistent with international guidance that calls for the use of the precautionary principle. Most of the governments responded to the GBV crisis late or not at all. Although the analysis of media releases alone is insufficient to establish the scope of government actions taken to address GBV during the pandemic, public communication related to ongoing threats is an expected crisis communication competency. This study offers recommendations for practice, which might help address gender inequity in 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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".