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The subject of this research is the social relations that arise in terms of committing petty theft, as well as research means and methods for assessing optimization of the protective legal regulation. The author substantiates and tests the indicator of humanization of legal regulation, which is identified and used on the big data of judicial acts on administrative and criminal 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). The research is based on the original interdisciplinary methodology, which includes indicator approach and a set of legal and computer aided techniques (dogmatic, systemic analysis, expert assessment, data mining, correlation analysis, cluster analysis, classification, regression, etc.). The author substantiates the need to view humanization of protective legal regulation in the context of balanced interests of all parties involved in the legal conflict, namely: the state (society) interested in the effective preventive function of protective legal regulation; the victim interested in compensation for the caused harm; the wrongdoer interested in imposition of fair punishment adequate in its severity to facts in the case. These interests were compared to the empirical data and knowledge extracted from the vast arrays of judicial acts, as well as the corresponding methods of research. The use of humanization indicator for big data in cases of petty theft demonstrates that administrative responsibility in general is more humane than criminal responsibility (by three out of four indicators); there is disproportionality of repression in criminal cases; the level of humanism to the victim in cases of administrative offences is extremely low; individualization of criminal penalty is lower than of administrative penalty, despite the more complicated, time and cost consuming form of criminal proceedings.	

ûridičeskie issledovaniâ

The indicator of humanization of legal regulation: methodological study using big data of judicial practice on the 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)