How liberalism accommodates far-right social movements: on “mainstreaming” and the need for critical theory in far-right studies
Bibliographic record
Abstract
Abstract Scholarship on social movements, racism, and nationalism increasingly falls under the purview of “extremism studies” and its subfield “far-right studies.” Prominent extremism scholars have developed generalist theories purportedly explaining far-right politics and power dynamics (or “mainstreaming”) across liberal societies. They define “far-right” as “illiberal” politics promoting dehumanization, exclusion, and inequality. Their theory of mainstreaming suggests that “the” far-right is a coherent entity that “enters” mainstream institutions or discourse from the outside. For these scholars, strengthening liberal-civic principles prevents far-right political power (mainstreaming). I call these approaches “grand theory templates,” which I critique for simplistic interpretations of power and for overlooking critical theory scholarship showing how liberalism accommodates far-right politics. Using the Canadian nationalist movement as a case study, I show how liberal chauvinism can be crucial to empowering right-wing populist movements. My data include over 40 hours of participant-observation at 20 right-wing events and 35 interviews with 42 current leaders and members of on-the-ground nationalist groups. Right-wing nationalists foregrounded liberal-civic ideas, such as “security,” “rights,” “objectivity,” and “tolerance,” to advance anti-Muslim sentiment and populist conspiracism. My findings suggest that far-right movements can gain power by embracing liberalism’s ambiguity and contradictions. In other words, mastering liberal messaging can be essential to the growth of far-right movements, challenging any easy dismissal of these politics as “illiberal.” Altogether, “top–down” grand theory templates oversimplify political distinctions and power, compromising research design and analysis. I advocate for more granular and “bottom–up” inductive approaches that prioritize sociological traditions over theories recently popularized by extremism scholars.
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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 | 0.071 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.017 | 0.194 |
| Scholarly communication | 0.030 | 0.044 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".