Science1 distinct publisher3 min readUpdated
Hostility toward women separated supporters of extremist violence from everyone else across incel, far-right, religious and far-left categories alike, the research team reports.
The Scientist · Science desk
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An Australian research team surveyed 3,429 people, including teenagers as young as 13, about their attitudes across six distinct extremist movements: incel, far-right, white supremacist, religious, far-left and anti-feminist [1]. Across every one of those movements, the strongest predictor of support for extremist violence was not political ideology, religion, ethnicity or time spent online, but hostility toward women [2].
That single attitude did more to separate those who support extremist violence from those who do not than every form of online engagement the team measured put together [3]. And it held with roughly equal force whether the target ideology was incel, religious, far-right, white supremacist or left-wing [4]. The team's reading is that these are not six radicalisation stories sharing a risk factor; the shared belief is that men ought to dominate women, that breaching the gender order deserves punishment, and that violence to restore it is legitimate [5]. They argue movements inherit this from attitudes recruits already held before finding an ideology to attach them to [6].
The measurement was ordinary attitude-survey material: agreement with statements such as "sometimes women bother me just by being around," that a wife should be obedient to her husband, that a girl should give a guy what he wants sexually even if she does not feel like it, and that feminism is a hate movement [7].
The platform findings cut against where security attention has gone. Australian national security agencies have focused heavily on gaming, online forums and social media, but once the researchers accounted for what respondents believed about women, engagement with those platforms showed little independent link to extremist attitudes [8]. Three environments stood out instead: manfluencer content, online dating platforms and pornography [9]. Manfluencer engagement was the single strongest predictor of misogyny in the whole data set [10]; dating apps and pornography were the two behaviours most tightly connected to attitudes excusing violence against women [11]. When the team tested whether these spaces drive extremism directly or only through the gender attitudes they cultivate, nearly all lost their predictive power [12]. Pornography was the exception, retaining a small but real direct link [13].
The classroom account attached to the findings is the part practitioners will recognise. One teacher described students being funnelled into echo chambers via gaming and workout videos, then exposed to extreme misogyny, racism, homophobia and transphobia [14]. Andrew Tate, who is facing multiple criminal charges including rape and trafficking, is cited by students as an authority in class discussions, and teachers reported difficulty pushing back without being accused of bias [15][16]. Teachers call it the manosphere pipeline [17].
Two limits are worth holding. This is a first-person account of the team's own survey, published by the researchers [18], and a one-off attitude survey establishes co-occurrence, not direction: hostility toward women predicting support for violence is consistent with misogyny being the entry point and also with both being downstream of something the questionnaire did not ask about [1]. The available text also breaks off in the section on teenage attitudes, so the numbers for the 13-to-17 cohort, the study's novel contribution, are not yet in hand [19].
What to watch: whether the peer-reviewed paper reports per-movement effect sizes rather than the "almost equal force" summary [4]; whether the direct pornography effect survives replication [13]; and whether any prevention program actually re-cuts its intake and triage on gender attitudes instead of ideological category, which is the operational consequence of the finding and the hardest thing to fund.
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Ranked by verification strength, evidence, and original report placement.
Across every form of extremism measured, the strongest predictor was not political ideology, religion, ethnicity or how much time someone spent online; it was hostility toward women.
This one attitude did more to separate those who support extremist violence from those who don't than every form of online engagement put together.
The authors argue the movements are not six separate radicalization stories sharing a risk factor, and that what they share is an ideology that men ought to dominate women, that transgression of the natural gender order deserves punishment, and that violence in service of restoring that order is legitimate.
Manfluencer engagement was the single strongest predictor of misogyny in the entire data set.
An Australian teacher described students being funneled into echo chambers, lured into extremist content through innocent avenues such as gaming and workout videos, then exposed to extreme misogyny, racism, homophobia and transphobia.
Teachers call the phenomenon the manosphere pipeline.
Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
Specific numbers, single self-authored source, no methods
The account supplies unusually concrete anchors for a survey write-up: sample size (3,429), inclusion of 13-year-olds, six named movements, four verbatim instrument items, a companion teacher survey (511 respondents, 62%/57%) and a stated mediation test with one named exception. Against that, the entire cluster is one first-person piece by the researchers with no linked paper, no effect sizes, no model specification, no sampling detail, and a body that breaks off mid-section — so the central 'strongest predictor' ranking cannot be checked or replicated from what is supplied.
No adoption events in the supplied material
The cluster contains no release, deployment, benchmark, pricing, licensing, usage-disclosure or incident event to observe. Prevention frameworks and Australia's under-16 social media restrictions are referenced only as background the authors argue against, not as uptake of anything in this story, so no adoption reading is warranted.
Causal, totalising framing on correlational one-shot data
The headline and framing assert that hostile attitudes are 'driving extremism' and that misogyny is 'the ideological fount from which they all draw', and that movements 'inherited' pre-formed attitudes — claims of causation and temporal order that a single cross-sectional survey cannot establish, especially with no effect sizes or published methods supplied. The underlying descriptive findings are plausible and specifically stated, so the gap is one of overreach in interpretation rather than fabricated substance.
Researchers publicising their own study, unmediated
The only source is written in the first person by the team whose survey it describes and distributed through a research-communication outlet, so selection of which results to foreground, the 'ideological fount' framing and the policy-gap conclusion all serve the authors' interest in salience and uptake. No adversarial editing, peer review link, platform response or dissenting expert appears in the cluster to offset that. There is no evidence of commercial or vendor incentive.
Low: one publisher, one self-authored account
Confidence is limited by structure rather than by internal inconsistency. The narrative is coherent and quantitatively specific, but a single publisher carrying the researchers' own text, with no paper, statistics or corroborating coverage and a truncated body, supports only low confidence in the specific magnitudes and in the causal interpretation, and moderate confidence that a survey with the stated design and headline pattern exists.
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1 article · August 17, 2026