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Record W1041701279 · doi:10.1163/22131418-00204013

The Matrix of Communication in Social Movements

2014· article· en· W1041701279 on OpenAlexaff
Roozbeh Safshekan

Bibliographic record

VenueSociology of Islam · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMainstreamAmateurCitizen journalismOpposition (politics)Social movementPublic relationsPoliticsSocial mediaSociologyPolitical communicationPolitical economyPolitical scienceMedia studiesLaw

Abstract

fetched live from OpenAlex

Communication technology has played a central role in the last two great socio-political uprisings in Iran’s history: The 1979 Revolution and 2009 Green Movement. By identifying three distinct elements of the communication process, this paper explores how the ability of the political opposition to communicate effectively contributed to the success or decline of these movements as one factor among a broader set of key factors. The first element is the ‘mainstream media’, which is professional, hierarchically structured and often funded by states, big corporations or major publicly funded organizations. ‘Alternative media’, in contrast, is amateur, has a participatory and horizontal working structure and often limited funding. The third, the ‘social network’, is a collection of actors who seek iterative and persisting exchanges among themselves based on common interests, beliefs, and other ties. This trinity constitutes what has been called the ‘matrix of communication’ in this paper.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0060.028
Scholarly communication0.0130.011
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.027
GPT teacher head0.373
Teacher spread0.345 · 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 designQualitative
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

Citations2
Published2014
Admission routes1
Has abstractyes

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