The Methods of Digital Forecasting of Inmate Misconduct in Penal Institutions

Abstract

The authors use the analysis of existing research ideas regarding the structure and content of the criminological prediction methodology to examine modern approaches to predicting illegal activities in penitentiary institutions. They analyze and classify the objects of prevention — those inmates in places of confinement who need to be controlled while serving their sentence because they have a range of unlawful behavior. In the diagnostic sub-task the object is viewed as a source of information whose attributes and features are studied as they manifest its essence and condition. The authors present a large-scale review of Russian and foreign publications to research the evolution of scientific ideas regarding the contents of the hypothesis as a basis of criminological prediction. While recognizing the value of theoretical criminological achievements, the authors set the goal of analyzing the possible ways of integrating criminology and operative search activities for the identification of pre-criminal behavior in places of confinement. Using the theory of criminological prediction and empirical materials, the authors analyze the possibilities of designing a multi-factor prediction model for individual unlawful behavior by transforming this model into a system of corresponding indicators and risk factors of pre-criminal behavior. They conduct a systemic analysis of the contents of socio-demographic, penitentiary, psychological variables, as well as variables connected with the criminal past as an aggregate of risk factors of pre-criminal behavior. They also describe the essence of digital prediction methods - predictive analytics, analytical intelligence, initiative analytics, - which are used to build a system of indicators for studying and assessing the behavior of certain categories of inmates. The authors show the necessity of using digital analytical methods of making managerial decisions regarding the preventive measures of rapid response in cases of the destructive behavior of inmates. Using the regularities that form the basis of criminological prediction, the authors state that it is necessary to develop the methods of digital prediction and to adapt key features of the digital environment and newest information and telecommunication technologies to solving the tasks of preventing offences among inmates.