Conceptualizing a National Threat: Representations of “Homegrown Terrorism” in the News Media, Academia, and Grey Literature in Canada
Bibliographic record
Abstract
This article critically examines how the problem of “homegrown terrorism” is represented in a content analysis of news media, academic scholarship, and grey literature in Canada between 2013 and 2016. Findings centred around five primary themes: (1) homegrown terrorism is new to Canada and is growing in scope; (2) it represents a significant threat to national security; (3) it is a problem that tends to manifest in, and transform, “normal” youth; (4) it lacks any identifiable causes; and (5) it has culminated in a new regime of persistent threat and uncertainty in Canada. Based on the saturation of these themes, I argue that a narrative template has formed and proliferated across media, academic, and grey literatures, acting as a framework for understanding the homegrown terrorism problem’s key features that are legitimated by the repeated presence of a small group of expert and official sources. The second part of this article interrogates this conceptualization, including the criteria used in selecting cases and the underlying operation of racialized, orientalist discourses on Canadian Muslims that work to distinguish homegrown terrorism from other types of political violence in the country and to render it antithetical to Canadian values. This article provides a conceptual snapshot of homegrown terrorism around the time of highly publicized events (e.g., the 2014 Parliament Hill attack) that continue to impact Canadian politics and society. This analysis offers insight as ideas of radicalization and violent extremism gain further prominence in realms of public policy, service and program delivery, and multiple political contexts.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.016 | 0.024 |
| Science and technology studies | 0.039 | 0.039 |
| Scholarly communication | 0.027 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| 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".