Incel Ideology, Radicalization and Mental Health
Bibliographic record
Abstract
Incels (involuntarily celibates) are an online community of men who feel disenfranchised because they are unable to find a romantic and sexual partner. Incels tend to blame society for placing too much value in physical appearance and for endowing women with too much power in mate selection, a grievance that sometimes translates into violent misogyny. Mass-casualty Incel attacks have led the security services in the U.S., Canada, and the U.K. to classify Incels as a violent extremist threat. However, little empirical research is available to inform the understanding of Incels, or to qualify their potential danger to the public. Filling this gap, this study presents an important empirical datum by reaching beyond media headlines and online activity, to assess Incel ideology, mental health, and radical intentions through in-depth surveys of 274 active Incels. Most Incels in our study reported mental health problems and psychological trauma of bullying or persecution. Incel ideology was only weakly correlated with radicalization, and ideology and radicalization were differentially correlated with mental health measures. Most Incels in the study rejected violence. The discussion considers implications of these findings for detection, policing, and non-criminal interventions focused on the Incel community.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".