An Analysis of Canada’s Approach to Addressing Gender-Based Violence: The Impact of Framings of Gender-Based Violence and Solutions in Policy and Funding
Bibliographic record
Abstract
Canadian governments have enacted policies and initiatives to address gender-based violence (GBV), a pressing public health and human rights concern. Despite these efforts, the epidemic of GBV continues, highlighting the urgent need for effective and preventative GBV policies. This research analyzed Canadian federal policies and initiatives to understand how GBV and actions to address it have been framed. Grounded in a critical methodological approach, I examined this topic using Foucault’s Post-structuralism, and Intersectional Feminism, with attention to social structures, power, gender inequality, and diverse survivor experiences. I analyzed 27 government documents, web pages, and advocacy reports and conducted nine interviews with GBV advocates and government officials in relevant roles. Critical discourse analysis and Bacchi’s “What’s the Problem Represented to Be” tool guided examination of texts, highlighting discourses and ideologies, silenced perspectives, the framing of GBV and solutions, and strengths and gaps in Canada’s policy approach to GBV. I found that multiple intersecting issues affect Canadian GBV policy. First, the historical progress of anti-GBV work exists alongside entrenched gendered discourses and systems of oppression such as patriarchy and colonialism. Inconsistencies in terminology use and persistent lack of clear definitions hindered the translation of complex GBV issues into concrete actions. Key frameworks (e.g., intersectionality) were not fully applied, impeding the effectiveness of policies, especially for systemically marginalized groups. Additionally, I found a strong emphasis on utilitarian values — situating GBV as a societal issue demanding collective responsibility — in tension with a lack of coordination among programs and policies, and enforced funding competition among agencies, which sometimes led to perceptions of government actions as performative. To highlight the significant impact of these discourses on policy, I closely examined Canada’s 2022 National Action Plan to End Gender-Based Violence (NAP) as an exemplar case. While the NAP was acknowledged as a positive step toward addressing structural roots of GBV, it remains constrained by longstanding jurisdictional issues, unclear terminology, and inconsistent accountability mechanisms. Overall, this research demonstrated that systemic challenges continue to impact the problematization of GBV in Canadian federal policy and programming. Recommendations are provided to address gaps for GBV action development and implementation in Canada.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.051 | 0.020 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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".