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Record W2319926365 · doi:10.1177/1077699014541786m

Book Review: <i>Social Movements and Their Technologies</i> , by Stefania Milan Social Movements and Their Technologies. MilanStefania. Basingstoke, UK: Palgrave Macmillan, 2013. 248 pp. $85 hbk.

2014· article· en· W2319926365 on OpenAlexaboutno aff
Lyell Davies

Bibliographic record

VenueJournalism & Mass Communication Quarterly · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsSocial movementSocial mediaSociologyMedia studiesPoliticsMovement (music)Subject (documents)Social sciencePolitical scienceLawAestheticsArtLibrary science

Abstract

fetched live from OpenAlex

Social Movements and Their Technologies. Stefania Milan. Basingstoke, UK: Palgrave Macmillan, 2013. 248 pp. $85 hbk.The use of electronic media by social movements has garnered considerable attention in recent years, with some commentators labeling recent upheavals in Arab world and elsewhere as Twitter- or Facebook-driven revolutions. But labels such as these offer slim insight into complex role that media communication technologies play in lives of social movements. For those who seek to more deeply understand this subject, Stefania Milan's Social Movements and Their Technologies is a good place to begin.A professor at Tilburg University in Netherlands and Citizen Lab at University of Toronto, Milan delivers two important innovations with regard to study of media and social movements. First, she uses sociology-based social movement theory as a framework with which to examine media organizing and activism she discusses, thereby breaking with tendency within media studies to study political media without studying social movement from which this media has emerged, and tendency within sociology-based social movement research of paying too little attention to media making that goes on within social movements. Second, she positions media making organizations, groups, and individuals she studies as constituents within a transnational media justice-driven social movement. Here, she argues, [f]ar from being considered only as tools, media and communication technologies have become a site of struggle in their own right.At center of Milan's research is a comparative examination of emancipatory communication practices (ECPs)-which she defines as ways of social organizing seeking to create alternatives to existing media and communication infrastructure- of two media constituencies, these being community radio practitioners and Internetbased activists. Using language of social movement theory, Milan states that goal of her research is to examine the emergence of media and technology activism, its features, mobilizing frames, identity building, and action repertories.To conduct her study, she interviewed and observed work of community radio practitioners in twenty-four countries and interviewed Internet activists from sixteen countries over a six-year period. From this work, Milan has delivered an insightful study regarding ideologies and organizational efforts that underwrite these alternative and oppositional media-making projects, with her study of Internet projects (which she bundles under term radical techies) being particularly compelling.Describing philosophies that underpin work of techies, Milan observes that these activists share a set of sources of inspiration-namely, DIY culture, cyberlibertarianism, hacker culture, anarchism, anarcho-syndicalism, Zapatista discourse, and autonomist thought. On a practical level, Internet activist groups typically aim to provide non-commercial web-based communication tools, such as website hosting and blogging platforms, e-mail accounts, list services, and chat rooms, to citizenry and activist community. In contrast to services provided by commercial systems, they seek to do this while preserving anonymity and privacy of users through encryption techniques. …

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2014
Admission routes1
Has abstractyes

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