MEDIATING SERIAL VIOLENCE : NORMATIVITY, DEVIANCE & FRAMING IN THE MCARTHUR MURDERS
Bibliographic record
Abstract
How do the media react in the face of a violent phenomenon involving actors both embraced and marginalized by society? One such phenomena – the McArthur murders – encapsulates this dynamic considering how the media explained the murders to their audiences. McArthur, a white LGBTQ+ man, murdered over a seven-year period specifically targeting male victims of South Asian or Middle Eastern descent associated with the LGBTQ+ community and geographic area in Toronto, Canada. The victims embodied a variety of marginalized identities including race, ethnicity, sexual orientation, immigration status and houselessness. It is in this context that this qualitative study finds itself, investigating media coverage of the McArthur murders in two mediums/Canadian outlets. The Toronto Star, Canada’s largest daily newspaper representing newspaper coverage, and a podcast produced by the Canadian Broadcasting Corporation (CBC), Uncover: The Village representing podcast (or audio) media. Considering the context of the McArthur murders and the identities of the actors involved, the study is focused on how normativity and deviancy are constructed through mediatized eyes (or frames). Through a blend of deductive and inductive framing analysis relying on a queer phenomenologically-inspired theoretical framework, the study’s aim is threefold: (1) to uncover what frames are most prevalent across both outlets, (2) to understand, using deductively applied frames, how both outlets construct the events of the McArthur murders and, (3) to understand the interplay between mediatized reification or mitigation of normativity. The analysis found that both newspaper and podcast were most concerned with attributing responsibility in their coverage, which introduced the queer phenomenological understanding of institutions into the analysis, a pattern which continued throughout each deductively applied frame. Moreover, connections to analogous sets of murders in 1970s Toronto broadened the implications of the study across time. Finally, the analysis showed that rather than solely reifying or mitigating normativity, both outlets’ coverage despite similarities and differences, are illustrative of normativity and deviancy’s ongoing orientation towards one another. The conflict between societally standard and aberrant is shown to be a constant over time, after death, and across contexts – a dynamic relationship which has significance for how media scholars might approach cross-medium analyses of complex phenomena in further research.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.043 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".