—тать€ 'јдминистративна€ преюдици€ по делам о мелком хищении (ст. 7.27  ојѕ –‘ и ст. 158.1 ”  –‘): как большие данные судебных актов отражают гуманизацию и качество правосуди€' - журнал 'ёридические исследовани€' - NotaBene.ru
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Administrative prejudice in cases of petty theft (the Article 7.27 of the Code of the Russian Federation on Administrative Offenses and the Article 158.1 of the Criminal Code of the Russian Federation): how the big data of judicial acts reflect humanization and quality of justice

Trofimov Egor Viktorovich

ORCID: 0000-0003-4585-8820

Doctor of Law

Deputy Director for Science, St. Petersburg Institute (Branch) of the All-Russian State University of Justice

199178, Russia, g. Saint Petersburg, 10-ya liniya V.O., 19, lit. A, kab. 36

diterihs@mail.ru
ƒругие публикации этого автора
 

 
Metsker Oleg Gennad'evich

ORCID: 0000-0003-3427-7932

PhD in Technical Science

Researcher

199178, Russia, g. Saint Petersburg, 10-liniya V.O., 19 lit. A

olegmetsker@gmail.com
ƒругие публикации этого автора
 

 
Paskoshev David Dokkaevich

Master's Degree, National Research University ITMO

197101, Russia, g. Saint Petersburg, Kronverkskii pr., 49

david.d.paskoshev@gmail.com
ƒругие публикации этого автора
 

 

DOI:

10.25136/2409-7136.2021.9.36521

Review date:

24-09-2021


Publish date:

01-10-2021


Abstract: The subject of this article is the public relations arising in the context of committing petty theft, as well as research means and methods for assessing the optimization of legislation and law enforcement. Due to the specific structure of administrative prejudice, the article presents the methodology and results of the analysis big data of judicial acts in cases of petty theft (the Code of the Russian Federation on Administrative Offenses and the Article 158.1 of the Criminal Code of the Russian Federation) for assessing the quality of justice and optimization of legal regulation. The research is founded on the original interdisciplinary methodology, which contains the indicator approach along with the set of legal and computer aided techniques, including intellectual text and data mining, as well as machine learning. It is demonstrated that the judgments of conviction do not have considerable differences in the semantics and logical complexity of decision-making in comparison with the ruling on imposition of administrative penalty; the logic of making decisions on the choice of administrative or criminal penalty for petty theft varies, whereby the choice of administrative penalty is more differentiated. Despite the identity of acts related to administrative prejudice, their regulation by different laws leads to different enforcement results. Administrative-tort regulation is more optimal. Administrative responsibility for petty theft is rather humane for the society overall, although for victims, criminal responsibility appears to be more humane. Having analyzed the array of information, the author extracts certain knowledge on the administrative-tort and criminological characteristics of petty theft alongside peculiarities of court proceeding and imposition of penalties, as well as concludes on applicability of the developed methodology towards analyzing big data of case law on administrative and criminal offenses.


Keywords: machine learning, big data, digital state, improving the legal system, administrative prejudice, humanization, pilferage, text mining, data mining, indicators
This article written in Russian. You can find full text of article in Russian here .

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