Bibliographic record
Abstract
This article focuses on the transnational diffusion of social movement ideas. How do social movements in one country or region of the world diffuse to another country or region? How do social movement participants learn about other movements and ideas in faraway countries and mobilize around these same ideas? What are the channels and mechanisms of diffusion? These are the research questions the article addresses. I draw on the theoretical literature on social movements and recent research on diffusion to explore these questions. The discussion is applied to two recent cases of diffusion: The diffusion of the Transition movement from the United Kingdom to the United States and the diffusion of the solidarity economy movement from Latin America, France, and Canada to the United States. I argue that a combination of relational, nonrelational, and mediated diffusion explain the spread of the transition and solidarity economy movements. The article contributes to the literature on social movements in two ways. First, it contributes to the recent efforts to better understand the process of diffusion of social movements and their ideas. Second, it provides an account of two very recent social movements that have not been fully studied and documented yet.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.018 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".