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Record W2021616902 · doi:10.1177/1750635211434366

Uncovering the French-speaking jihadisphere: An exploratory analysis

2012· article· en· W2021616902 on OpenAlex
Benjamin Ducol

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedia War & Conflict · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversité Laval
FundersDublin City University
KeywordsIdeologyGermanThe InternetPolitical scienceMedia studiesArabicPublic relationsIslamSociologyLawHistoryPoliticsWorld Wide WebComputer scienceLinguistics

Abstract

fetched live from OpenAlex

Terrorist groups have exploited the internet and other information technologies to advance their strategies since the mid-1990s. Violent jihadi groups are no exception. They have located the internet at the core of their media strategies, which has given birth to a vibrant global jihadisphere: an online community of militants and sympathizers united by their common adherence to a global Salafi jihadi ideology. Not only do jihadi groups devote increasing energy to attempting to connect with global audiences, but jihadi sympathizers from all around the world are more involved than ever in widening the spread of jihadi online content through para-personal media. The expanding use of non-Arabic languages such as French, English, German, Russian and Dutch by jihadi groups and ideologues has not yet been adequately examined in the academic literature. This article represents a preliminary effort at delineating the nature of the French-speaking jihadisphere, including discussion of the major websites and forums composing it, the real and virtual links between these, and how forum users originally learned of the forums’ existence.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.321
Teacher spread0.273 · 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