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Multiple Engagements and Network Bridging in Contentious Politics: Digital Media Use of Protest Participants

2011· article· en· W765492233 on OpenAlexaff
Stefaan Walgrave, W. Lance Bennett, Jeroen Van Laer, Christian Breunig

Bibliographic record

VenueMobilization An International Quarterly · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsICTSBridging (networking)Social movementPoliticsContentious politicsDigital mediaThe InternetSocial mediaPolitical sciencePublic relationsInformation and Communications TechnologyCore (optical fiber)Movement (music)SociologyEngineeringComputer science

Abstract

fetched live from OpenAlex

Based on three series of protest surveys across nations, issues, and time, this study examines to what extent the use of digital media permits activists to sustain multiple engagements in different protest events and different movement organizations. We find that digital media use stimulates multiple activisms. Through information and communication technologies (ICTs), activists can maintain multiple engagements and manage weak ties with diverse protest and movement communities. The data also suggest that these multiple engagements and overlapping activisms effectively provide linkages to and integration within social movement networks. Core activists who are closely linked to protest organizations rely more on ICTs to manage their multiple commitments. Even activists less closely tied to core protest organizations can link to more diverse communities through Internet use. These basic patterns systematically hold across nations, across issues, and across time.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0040.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.120
GPT teacher head0.328
Teacher spread0.208 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations152
Published2011
Admission routes1
Has abstractyes

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Same venueMobilization An International QuarterlySame topicSocial Media and PoliticsFrench-language works237,207