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Record W2326173386 · doi:10.1177/0160597613481799

Understanding the Transnational Diffusion of Social Movements

2013· article· en· W2326173386 on OpenAlex
Noha Shawki

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHumanity & Society · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsSolidaritySocial movementMovement (music)DiffusionLatin AmericansSociologySocial changeSocial solidarityPolitical sciencePolitical economyEconomic geographyEconomicsSocial sciencePoliticsLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.090
GPT teacher head0.301
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it