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Record W2510548201 · doi:10.4000/conflits.19292

La gouvernance polycentrique du cybercrime : les réseaux fragmentés de la coopération internationale

2016· article· fr· W2510548201 on OpenAlex

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

VenueCultures & conflits/Cultures et conflits · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsUniversité de MontréalSNC-Lavalin (Canada)
Fundersnot available
KeywordsHumanitiesPolitical scienceCybercrimeThe InternetComputer scienceWorld Wide WebPhilosophy

Abstract

fetched live from OpenAlex

L’une des caractéristiques fondamentales de la délinquance numérique est sa nature transnationale, qui semble constituer un obstacle majeur à l’harmonisation et la coordination de ressources policières, par définition locales. L’étude empirique de la gouvernance internationale du cybercrime nous offre cependant une image bien différente de la situation. Cet article utilise la méthode de l’analyse des réseaux sociaux (ARS) afin de modéliser la structure polycentrique des acteurs et des initiatives qui incarnent la coopération anti-cybercriminalité. En se basant sur un corpus de 657 acteurs organisationnels participant à 51 initiatives, on applique la technique des réseaux d’affiliation (ou réseaux à deux dimensions) pour mesurer la cohésion du réseau global, identifier les acteurs publics et privés occupant un rôle central dans ce dispositif, ainsi que ceux jouant un rôle d’intermédiaire (ou de broker) entre des sous-groupes géographiques ou fonctionnels relativement segmentés.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.330
Teacher spread0.308 · 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