How Collective-Action Failure Shapes Group Heterogeneity and Engagement in Conventional and Radical Action Over Time
Bibliographic record
Abstract
Extensive research has identified factors influencing collective-action participation. However, less is known about how collective-action outcomes (i.e., success and failure) shape engagement in social movements over time. Using data collected before and after the 2017 marriage-equality debate in Australia, we conducted a latent profile analysis that indicated that success unified supporters of change ( n = 420), whereas failure created subgroups among opponents ( n = 419), reflecting four divergent responses: disengagement (resigned acceptors), moderate disengagement and continued investment (moderates), and renewed commitment to the cause using similar strategies (stay-the-course opponents) or new strategies (innovators). Resigned acceptors were least inclined to act following failure, whereas innovators were generally more likely to engage in conventional action and justify using radical action relative to the other profiles. These divergent reactions were predicted by differing baseline levels of social identification, group efficacy, and anger. Collective-action outcomes dynamically shape participation in social movements; this is an important direction for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".