Shadows of the Past: The Effects of Movements' Past Strategy on Third-Parties' Support for its Current Strategy
Bibliographic record
Abstract
Social movements benefit from third-party support in waging social change.The budding literature on the effects of social movements' strategy (violent vs. nonviolent) on third-parties' willingness to support and join the social movement has mainly regarded social movements' strategy as something fixed and unrelated to its past strategy.Using varied contexts, I investigated how social movements' past strategy may affect, if any, third parties' moral perception of the current strategy of social movements and how this perception translates into third parties' (un)willingness to support and join social movements.In the context of the conflict between hate groups and counter-protestors in a lesser-known country, Bhutan (Studies 1 & 4), and an ally country (Study 2) American participants were more willing to support and join a violent movement that was previously nonviolent as opposed to a historically violent movement.Perceived moral continuity of movements' strategy (Studies 1-5) and perceiving violent strategies as the last resort (Studies 2-4) mediated the relationship between change in movements' strategy and third parties' willingness to support and join the movement.However, using a conflictual context in which a movement, Liberation of Tamil Ealam, sought to gain independence from a government, Sri Lankan government (Study 3), and a domestic anti-Fascist movement in the United States, Antifa, that aims to combat hate groups led to partial replication of findings of Studies 1-2 & 4. While there was no significant difference between conditions (shifting from nonviolence to violence vs. continuing violence) in third parties' willingness to support and join the movement, perceived moral continuity of movements' strategy (Studies 3 & 5) and perceiving violence as the last resort (Study 3) mediated the relationship between conditions and third parties' willingness to support and join the movement.Theoretical and practical implications for social movements are discussed.Specifically, social movements that have exhausted nonviolent avenues to achieve their goals are likely to find support among third-parties for a shift toward SHADOWS OF THE PAST iii violent strategies-support that may ultimately lead to either desired social change or conflict escalation.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".