Domestic Violence and the Newsprint Media: A Critical Discourse Analysis of Three Canadian Newspapers in a Covid-19 Context
Bibliographic record
Abstract
This paper seeks to explore the way the print news media reported on issues related to domestic violence (DV) in the Greater Toronto/Hamilton Ontario area in the context of Covid-19 from March 2020 to March 2021. Specifically, I drew on three newspapers to include the Hamilton Spectator, the Toronto Star, and the Globe and Mail. This research is primarily concerned with the discourses that emerged about gender-based violence in the newsprint media during a time when people were required to stay in their homes and when access to community-based services that support women experiencing DV became increasing challenging. Using a Critical Discourse Analysis (CDA) that was grounded in a feminist theoretical framework, three themes emerged as particularly dominant. These included: a) the media’s use of “victim” and “survivor” discourses, b) women’s experiences of DV and access to resources, and c) public health discourses that centered on responses to DV in light of Covid-19. This paper concluded that reinforcement of dominant narratives about the socio political and gendered landscape in which DV is reported on via newsprint media sources, depict DV as an individual rather than structural issue that shifts the blame away from historical and current day social, economic, and political forces that create the conditions in which DV occurs. Importantly, the newsprint media promote a homogenous definition of ‘woman’ thus elevating dominant DV discourses that tend to centre the experiences of white, heterosexual women and that result in silencing the voices of gender diverse and racialized women. Consequently, my research suggests that there is an ongoing need to build on existing feminist literature to critically examine DV as a systemic issue that requires a response that is inclusive of the diversity of women who experience DV, the needs for services to support a diversity of women, and to do so in ways that move away from individual solutions toward shifts in practice and policy.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.038 | 0.021 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".