‘War talk’ engendering terror: race, gender and representation in Canadian print media
Bibliographic record
Abstract
Discourses of war centre on the objectification of the enemy and utilize Manichean oppositions to promote an explanation of events which make ‘common sense’ (Cooke and Woollacott 1993). In the aftermath of the events of September 11, 2001, with the collapse of the World Trade Center towers in New York City, those discourses assumed a heightened Orientalist mantle, coloured by the geographic, religious and cultural nature of the perceived enemy. In this short essay, I examine how the news media, and in particular, print media, covered the events of September 11, 2001.1 My focus is on the Canadian print media - The Gazette, a Montreal English daily, and The Globe and Mail, one of Canada’s two national papers. Both these papers play a pivotal role in shaping the ‘imagined community’ (Anderson 1983) that is Quebec and Canada, but more importantly, both are highly influential in shaping policy towards immigrants and cultural minority groups in the provincial and national landscape (Fleras and Kunz 2001). The analysis that follows is undoubtedly influenced by my standpoint (Durham 1998), as a woman, a Canadian of immigrant origins and as Muslim - a religious affiliation rendered salient because of its shared character with that of the ‘enemy’. In the sections that follow, I pay particular attention to the issue of gender - how it underpins, informs and shapes the discourses of war and how in so doing, it engenders terror such that the latter assumes a specific type of fear with differential repercussions for women and men.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.028 | 0.014 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".