Bibliographic record
Abstract
Using primary source material obtained through archives and other open sources, this working paper examines, through a series of qualitative case studies, nineteen lone-actor terrorist attacks that occurred in Canada across a 150-year period, specifically between 1868 and 2018. The next section addresses methodological issues, including in connection to definitions. That is followed by an historical overview of lone-actor terrorism in which the nineteen case studies are introduced (full details appear in the appendix). Finally, focusing on commonalities of the attacks and the backgrounds of the perpetrators, along with their motivations and tactics, techniques and procedures, analysis is provided, including through the use of templates from other work on lone-actor terrorism. This working paper is significant for two reasons. First, it historicizes lone-actor terrorism as a practice and shows that it is not a contemporary phenomenon, even if there has been a greater prevalence of such attacks since 9/11. By applying a longue durée to lone-actor terrorism, the paper reveals that a range of motivations have sparked violence over the 150 years examined and that no single explanation accounts for such an outcome, let alone simple “individual life stories.” The paper supports sociologist Ramón Spaaij’s contention that the violent extremism of lone-actor terrorists “tends to result from a combination of individual processes, interpersonal relations and socio-political and cultural circumstances.” More significantly, by deploying a longer temporal exploration of lone-actor terrorism, the paper illustrates that violent actors emerge from a variety of communities and backgrounds. This decentring of the present counters the dangers of a short-term approach in which marginalized groups face overrepresentation among perpetrators, consequently fuelling wider political discourses that encourage discrimination and the securitization of “suspect communities.” Ultimately, however, the paper argues that one key variable connects eighteen of the nineteen attacks: the perpetrators were men. Although this paper does not argue that masculinities as a social construct led directly to the attacks discussed, it proposes that there is some correlation between certain masculinities and lone-actor terrorism, specifically when extreme violence is viewed as an acceptable reply to an intersection of personal and societal grievances. This relationship needs additional and urgent attention, not only by academics, but by politicians, the media and security agencies as well.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.024 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".