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Record W2547525121 · doi:10.2298/medjp1603172b

Organized crime as a current security threat

2016· article· en· W2547525121 on OpenAlexfundno aff
Bóžidar Banović

Bibliographic record

VenueMedjunarodni problemi · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Sanctions and International Relations
Canadian institutionsnot available
FundersUniversity of TorontoUniversity of OxfordEuropean CommissionDartmouth CollegeUniversity of Missouri
KeywordsOrganised crimePoliticsPhenomenonPolitical scienceContext (archaeology)State (computer science)Position (finance)Cultural criminologyCriminologyIdentification (biology)Public relationsSociologyLawBusinessGeographyEpistemology

Abstract

fetched live from OpenAlex

Scientific and professional community, and political subjects, both at national and at the international level have a unique position that organized crime is now one of the most dangerous security threats. However, such consent does not exist in terms of conceptual determination, identification, dimensions and of choice of methods to counter organized crime. The first part of this article describes the main trends in the conceptual definition of organized crime, social and political context of the use of this term and the subjects who have contributed to it becoming one of the main concepts of modern scientific and professional discussions about crime. The second part indicates the dynamics of organized crime as a security threat in the territory of Europe, and the last part presents and analyzes the development of organized crime in Serbia and attitudes of scientists and experts, political entities and state bodies and institutions towards this phenomenon.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.006
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.245
Teacher spread0.214 · 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 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
Published2016
Admission routes1
Has abstractyes

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