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Record W2785778263 · doi:10.4018/ijcwt.2018010101

#TerroristFinancing

2018· article· en· W2785778263 on OpenAlexaff
Michael L. Tierney

Bibliographic record

VenueInternational Journal of Cyber Warfare and Terrorism · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTerrorismThe InternetOrder (exchange)State (computer science)BusinessFinanceIslamPolitical scienceComputer securityPublic relationsComputer scienceLaw

Abstract

fetched live from OpenAlex

This article describes how the internet has come to play a central role in terrorist financing endeavours. Online channels allow terrorist financiers to network with like-minded individuals, in order to increase support, raise funds, and move wealth across the international system. For instance, the Islamic State, Hezbollah, and other groups have become adept at using these channels to finance their activities. Therefore, increased examination is required of the ways in which terrorists use the internet to raise and move funds. This study assesses some of the current trends and risks associated with online terrorist financing. Some policy options are also outlined, in order to reduce the threat of terrorist financing via the internet moving into the future.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.247
Teacher spread0.234 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2018
Admission routes1
Has abstractyes

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