Trust and social movements: A new research agenda
Bibliographic record
Abstract
Social movement studies clearly suggest that trust matters for processes of social mobilization: When engaging in costly, and potentially risky, contentious collective action on a common goal, activists and groups rely on the expectation that fellow protestors and allies will not fail them. To date, however, we lack research that explains which types of trust shape the emergence and evolution of social movements. Trust, we argue, is not simply an independent variable influencing mobilization, but is itself shaped—built, stabilized, weakened, or even destroyed—over the course of collective contentious action. To set the stage for a corresponding research agenda, this introduction to the special issue “Trust and Social Movements” bridges the gap between research on trust and social movement studies and clarifies the complex conceptual relationship between various types of trust and the dynamics of social mobilization. Furthermore, we identify overarching research questions, summarize the contributions to the special issue, and discuss key findings.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.012 | 0.039 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 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".