Representations of Sexual Assault in News Media Coverage of Canada’s Extreme Intoxication Defence
Bibliographic record
Abstract
The extreme intoxication defence (EID) is a provision in Canada’s Criminal Code that protects offenders who are ‘morally innocent’ by means of intoxication. Barred in 1994 by s. 33.1, three recent Supreme Court cases (Brown, Chan, and Sullivan) have overturned this decision, declaring the law unconstitutional in 2022. Concerns over the potential implications of this defence were raised by women’s rights groups and the public alike, prompting the Canadian legislator to rush Bill C-28, which includes a new standard for criminal liability requiring extreme intoxication to the point of automatism to enact the defence. Some advocates for women’s rights say that this is not enough, while policymakers stand by the legitimacy of the provision. News coverage of the Supreme Court rulings and the passing of Bill C-28 represented the interests of legislators, as well as women’s rights groups with concerns over the potential applications of the EID in sexual assault cases. Utilising media-framing theory and Critical Discourse Analysis (CDA), this study analyses the media discourse across three major Canadian newspapers; the Globe and Mail, Toronto Star, and the National Post between June 2020 and February 2023. The findings of this study were consistent with the academic literature regarding news media representations of sexual assault since the #Metoo movement. There has been greater inclusion of feminist perspectives, and the concerns for womens’ rights are better represented. Although, much of the coverage becomes encumbered with analysing the confusing legal language of the EID and discounting its potential implications for sexual assault case processing. Overall, new representations of the defence tend to hyper-politicise the issue and distract the reader from the social issues that contribute to the perpetuation of sexual violence against women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".