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Titel: Classification Tree Model for Determining Society Unsafety Factors Convicted
Autor(en): Kovalchuk, Olha
Chudyk, Nataliia
Drakokhrust, Tetiana
Kaniuka, Valerii
Ivanytskyy, Roman
Khokhlova, Larysa
Körperschaft: Hochschule Anhalt
Erscheinungsdatum: 2024-11-30
Umfang: 1 Online-Ressource (6 Seiten)
Sprache: Englisch
Zusammenfassung: The global rise in crime rates is a result of the ineffectiveness of the traditional punishment system and the need to develop new approaches to applying relevant punitive measures to criminals, taking into account their level of danger to society. This paper presents a classification Decision Trees model to identify significant factors influencing the objective level of danger a convicted person poses to society. Applied research was conducted based on real data (individual characteristics and criminal history records) of 2,052 convicts serving sentences in correctional facilities in Ukraine. It was found that the most significant predictors for determining the level of danger to society were the number of previous incarcerations and the number of suspended sentences. Assessing the level of societal danger posed by convicts is one of the key aspects of upholding the principles of fair justice. The obtained results can serve as informational support for judicial decisions, ensuring a balance between societal protection and successful offender reintegration.
URI: https://opendata.uni-halle.de//handle/1981185920/120078
http://dx.doi.org/10.25673/118119
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY-SA 4.0) Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International(CC BY-SA 4.0) Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International
Enthalten in den Sammlungen:International Conference on Applied Innovations in IT (ICAIIT)

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