Autism spectrum disorder, radicalization, and violence: a forensic perspective
Bibliographic record
Abstract
Some research suggests a higher prevalence of Autism Spectrum Disorder (ASD) among terrorist offenders in comparison to the general population. However, the literature does not achieve consistency in terms of an evidential and theoretical basis that individuals with ASD are especially susceptible to terrorism engagement. Through a case-series analysis, this paper discusses the interplay between ASD and radicalization. We examine how core ASD traits may increase one’s susceptibility to adopting radical ideology, and how internet exposure may contribute to the radicalization process. We comment on how vulnerability may lead to risk, distinguishing between these concepts, and argue that while individuals with ASD may not experience an increased risk of terrorism engagement, traits associated with ASD may increase one’s vulnerability to becoming radicalized when exposed to extremist material online. In considering psychiatric and legal issues, we then make recommendations by examining two notorious Canadian cases. Both individuals were reported to have ASD and received life sentences as a result of committing mass murder, with one individual targeting women, and the other targeting the Muslim population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".