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Record W2791145247 · doi:10.1002/j.cyo2.20171102.0001

Behind the Screen: the Syrian Virtual Resistance

2017· article· en· W2791145247 on OpenAlexaff
Billie Jeanne Brownlee

Bibliographic record

VenueCyberOrient · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsTyndale University
Fundersnot available
KeywordsDissentResistance (ecology)Political dissentPoliticsMiddle EastCollective actionCyberspacePolitical scienceContentious politicsSocial mediaPolitical economyResilience (materials science)Spanish Civil WarMedia studiesSociologySocial movementLawThe Internet

Abstract

fetched live from OpenAlex

Abstract Six years have gone by since the political upheaval that swept through many Middle East and North African (MENA) countries begun. Syria was caught in the grip of this revolutionary moment, one that drove the country from a peaceful popular mobilisation to a deadly fratricide civil war with no apparent way out. This paper provides an alternative approach to the study of the root causes of the Syrian uprising by examining the impact that the development of new media had in reconstructing forms of collective action and social mobilisation in pre-revolutionary Syria. By providing evidence of a number of significant initiatives, campaigns and acts of contentious politics that occurred between 2000 and 2011, this paper shows how, prior to 2011, scholarly work on Syria has not given sufficient theoretical and empirical consideration to the development of expressions of dissent and resilience of its cyberspace and to the informal and hybrid civic engagement they produced.

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)0.001
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.011
Scholarly communication0.0100.005
Open science0.0000.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.034
GPT teacher head0.335
Teacher spread0.301 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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