Evidence map›Paper›PMID 35477955›Full record

ArticleScientific reports2022

Universality of political corruption networks.

Alvaro F Martins, Bruno R da Cunha, Quentin S Hanley, Sebastián Gonçalves, Matjaž Perc, Haroldo V Ribeiro

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alvaro F MartinsDepartamento de Física, Universidade Estadual de Maringá - Maringá, Maringá, PR, 87020-900, Brazil.
Bruno R da CunhaRio Grande do Sul Superintendency, Brazilian Federal Police - Porto Alegre, Porto Alegre, RS, 90160-093, Brazil.
Quentin S HanleySchool of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK.
Sebastián GonçalvesInstituto de Física, Universidade Federal do Rio Grande do Sul - Porto Alegre, Porto Alegre, RS, 91501-970, Brazil.
Matjaž PercFaculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000, Maribor, Slovenia. matjaz.perc@gmail.com.
Haroldo V RibeiroDepartamento de Física, Universidade Estadual de Maringá - Maringá, Maringá, PR, 87020-900, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Corruption crimes demand highly coordinated actions among criminal agents to succeed. But research dedicated to corruption networks is still in its infancy and indeed little is known about the properties of these networks. Here we present a comprehensive investigation of corruption networks related to political scandals in Spain and Brazil over nearly three decades. We show that corruption networks of both countries share universal structural and dynamical properties, including similar degree distributions, clustering and assortativity coefficients, modular structure, and a growth process that is marked by the coalescence of network components due to a few recidivist criminals. We propose a simple model that not only reproduces these empirical properties but reveals also that corruption networks operate near a critical recidivism rate below which the network is entirely fragmented and above which it is overly connected. Our research thus indicates that actions focused on decreasing corruption recidivism may substantially mitigate this type of organized crime.

Indexed as

CrimeCriminalsBrazilCluster AnalysisHumansSpain

Identifiers

PMID35477955
PMCPMC9046414

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.