Encounters Between Violence and Media| Remembering January 29: The Québec City Mosque Shootings and the Struggle for Recognition
Bibliographic record
Abstract
On January 29, 2017, a gunman strode into the grand mosque in Québec City, Canada, and opened fire on the congregation, killing six and injuring 19 Muslims. The tragedy was widely covered in the local, national, and international media. In addition to providing details about the victims and the perpetrator, most of the immediate coverage focused on the outpouring of sympathy and empathy for the victims’ families and communities. The visibility of this performance of support contrasts sharply with the invisibility of state-sanctioned structural and interpersonal violence that Muslims continue to encounter in Québec on a daily basis. This article focuses on Muslim communities’ call for the recognition of the escalating violence of Islamophobia, paying particular attention to the Remember January 29 digital campaigns and memorial posts on various websites. The article argues that the digital campaigns contributed to the Canadian nation’s recognition of January 29 as a day of commemoration.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.034 | 0.010 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".