Radical flanks of social movements can increase support for moderate factions
Bibliographic record
Abstract
Abstract Social movements are critical agents of social change, but are rarely monolithic. Instead, movements are often made up of distinct factions with unique agendas and tactics, and there is little scientific consensus on when these factions may complement—or impede—one another’s influence. One central debate concerns whether radical flanks within a movement increase support for more moderate factions within the same movement by making the moderate faction seem more reasonable—or reduce support for moderate factions by making the entire movement seem unreasonable. Results of two online experiments conducted with diverse samples (N = 2,772), including a study of the animal rights movement and a preregistered study of the climate movement, show that the presence of a radical flank increases support for a moderate faction within the same movement. Further, it is the use of radical tactics, such as property destruction or violence, rather than a radical agenda, that drives this effect. Results indicate the effect owes to a contrast effect: Use of radical tactics by one flank led the more moderate faction to appear less radical, even though all characteristics of the moderate faction were held constant. This perception led participants to identify more with and, in turn, express greater support for the more moderate faction. These results suggest that activist groups that employ unpopular tactics can increase support for other groups within the same movement, pointing to a hidden way in which movement factions are complementary, despite pursuing divergent approaches to social change.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".