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Modeling the risks of the confession process of the accused of criminal offenses based on survival concept

НазваModeling the risks of the confession process of the accused of criminal offenses based on survival concept
Назва англійськоюModeling the risks of the confession process of the accused of criminal offenses based on survival concept
АвториOlha Kovalchuk
ПринадлежністьWest Ukrainian National University, Ternopil, Ukraine
Бібліографічний описModeling the risks of the confession process of the accused of criminal offenses based on survival concept / Olha Kovalchuk // Scientific Journal of TNTU. — Tern.: TNTU, 2022. — Vol 108. — No 4. — P. 27–37.
Bibliographic description:Kovalchuk O. (2022) Modeling the risks of the confession process of the accused of criminal offenses based on survival concept. Scientific Journal of TNTU (Tern.), vol 108, no 4, pp. 27–37.
DOI: https://doi.org/10.33108/visnyk_tntu2022.04.027
УДК

51-7

Ключові слова

survival analysis, Kaplan-Meier model, Cox proportional hazards model, confession.

Based on statistical survival analysis, the assessment and forecasting of the risks of pleading guilty to criminal offenses in conditions of incomplete data are carried out. Risk function is constructed to estimate the probability of confession of suspects at certain stages (time periods) of the trial. The Kaplan-Meier model is applied to calculate the chances of obtaining confession evidence after the end of the trial in criminal proceedings. Differences in the decision to admit guilt for two groups of defendants: in the commission of a criminal offense by one person and a group of persons are investigated. Cox regression model is constructed to establish the interconnection between the stages of the pre-trial investigation, at which the accused gives confessions, with the duration of the investigation and the method of prosecution.

 

ISSN:2522-4433
Перелік літератури
  1. Involuntary Confessions by Criminal Suspects. JUSTIA. American website specializing in legal information retrieval. 2022. URL: https://www.justia.com/criminal/procedure/miranda-rights/involuntary-confessions/ (accessed: 11.11.2022).
  2. Berezka K. M., Kovalchuk O. Ya., Banakh S. V., Zlyvko S. V., Hrechaniuk R. A Binary Logistic Regression Model for Support Decision Making in Criminal Justice. Folia Oeconomica Stetinensia. 2022. Vol. 22. No. 1. P. 1–17. Doi: https://doi.org/10.2478/foli-2022-0001.
  3. Kovalchuk O., Banakh S., Masonkova M., Burdin V., Zaverukha O., Ivanytskyy R. A Scoring Model for Support Decision Making in Criminal Justice, 12th International Conference “Advanced Computer Information Technologies”. Spišská Kapitula. Slovakia. 2022. P. 116–120. Doi: 10.1109/ACIT54803. 2022.9913182.
  4. Kovalchuk O., Banakh S., Masonkova M., Berezka K., Mokhun S., Fedchyshyn O. Text Mining for the Analysis of Legal Texts, 12th International Conference “Advanced Computer Information Technologies”. Spišská Kapitula. Slovakia. 2022. P. 502–505. Doi: 10.1109/ACIT54803.2022.9913169.
  5. Babii A. Important aspects of the experimental research methodology. Scientific Journal of TNTU. 2020. Vol. 97. No. 1. P. 77–87. URL: https://doi.org/10.33108/visnyk_tntu2020.01.
  6. Lupenko S., Lytvynenko Ia., Stadnyk N. Method for reducing the computational complexity of processing discrete cyclic random processes in digital data analysis systems. Scientific Journal of TNTU. 2020.
    Vol. 97. No. 1. P. 110–121. URL: https://doi.org/10.33108/visnyk_tntu2020.01.
  7. Aliluiko A., Ruska R. Robust stability and evaluation of the quality functional for linear control systems with matrix uncertainty. Scientific Journal of TNTU. 2020. Vol. 99. No. 3. P. 55–65. URL: https://doi.org/ 10.33108/visnyk_tntu2020.03.
  8. Krishnamurthi G. The Case for the Abolition of Criminal Confessions. SMU Law Review. 2022. Vol. 75. No. 1. P. 15–71. Doi: 10.2139/ssrn.3730499.
  9. Ho H. L. Confessions in the Criminal Process. Modern Law Review. 2020. Vol. 84. No. 1. P. 3–60. URL: https://doi.org/10.1111/1468-2230.12571
  10. Davis D., Leo R. A. Interrogations and Confessions. Wiley Online Library. URL: https://doi.org/ 10.1002/9781118517383.wbeccj271 (accessed: 13.11.2022).
  11. David G. C., Rawls A. W., Trainum J. Playing the Interrogation Game: Rapport, Coercion, and Confessions in Police Interrogations. Symbolic Interaction. 2018. Vol. 41. No. 1. P. 3–24. URL: https://doi.org/ 10.1002/symb.317.
  12. Morehouse L. Render Confessions Involuntary. American Law Review. 2019. Vol. 56. P. 531–545.
  13. Kassin S., Redlich A., Alceste F., Luke, T. On the general acceptance of confessions research: Opinions of the scientific community. American Psychologist. 2018. Vol. 73. No. 1. P. 63–80. Doi: 10.1037/ amp0000141.
  14. Kleinbaum D., Klein M. Survival Analysis: A Self-Learning Text (3rd ed.). Springer: 2012, 715 p.
  15. Unified register of pre-trial investigations. URL: https://erdr.gp.gov.ua. (accessed: 23.06.2013) [In Ukrainian].
References:
  1. Involuntary Confessions by Criminal Suspects. JUSTIA. American website specializing in legal information retrieval. 2022. URL: https://www.justia.com/criminal/procedure/miranda-rights/involuntary-confessions/ (accessed: 11.11.2022).
  2. Berezka K. M., Kovalchuk O. Ya., Banakh S. V., Zlyvko S. V., Hrechaniuk R. A Binary Logistic Regression Model for Support Decision Making in Criminal Justice. Folia Oeconomica Stetinensia. 2022. Vol. 22. No. 1. P. 1–17. Doi: https://doi.org/10.2478/foli-2022-0001.
  3. Kovalchuk O., Banakh S., Masonkova M., Burdin V., Zaverukha O., Ivanytskyy R. A Scoring Model for Support Decision Making in Criminal Justice, 12th International Conference “Advanced Computer Information Technologies”. Spišská Kapitula. Slovakia. 2022. P. 116–120. Doi: 10.1109/ACIT54803. 2022.9913182.
  4. Kovalchuk O., Banakh S., Masonkova M., Berezka K., Mokhun S., Fedchyshyn O. Text Mining for the Analysis of Legal Texts, 12th International Conference “Advanced Computer Information Technologies”. Spišská Kapitula. Slovakia. 2022. P. 502–505. Doi: 10.1109/ACIT54803.2022.9913169.
  5. Babii A. Important aspects of the experimental research methodology. Scientific Journal of TNTU. 2020. Vol. 97. No. 1. P. 77–87. URL: https://doi.org/10.33108/visnyk_tntu2020.01.
  6. Lupenko S., Lytvynenko Ia., Stadnyk N. Method for reducing the computational complexity of processing discrete cyclic random processes in digital data analysis systems. Scientific Journal of TNTU. 2020.
    Vol. 97. No. 1. P. 110–121. URL: https://doi.org/10.33108/visnyk_tntu2020.01.
  7. Aliluiko A., Ruska R. Robust stability and evaluation of the quality functional for linear control systems with matrix uncertainty. Scientific Journal of TNTU. 2020. Vol. 99. No. 3. P. 55–65. URL: https://doi.org/ 10.33108/visnyk_tntu2020.03.
  8. Krishnamurthi G. The Case for the Abolition of Criminal Confessions. SMU Law Review. 2022. Vol. 75. No. 1. P. 15–71. Doi: 10.2139/ssrn.3730499.
  9. Ho H. L. Confessions in the Criminal Process. Modern Law Review. 2020. Vol. 84. No. 1. P. 3–60. URL: https://doi.org/10.1111/1468-2230.12571
  10. Davis D., Leo R. A. Interrogations and Confessions. Wiley Online Library. URL: https://doi.org/ 10.1002/9781118517383.wbeccj271 (accessed: 13.11.2022).
  11. David G. C., Rawls A. W., Trainum J. Playing the Interrogation Game: Rapport, Coercion, and Confessions in Police Interrogations. Symbolic Interaction. 2018. Vol. 41. No. 1. P. 3–24. URL: https://doi.org/ 10.1002/symb.317.
  12. Morehouse L. Render Confessions Involuntary. American Law Review. 2019. Vol. 56. P. 531–545.
  13. Kassin S., Redlich A., Alceste F., Luke, T. On the general acceptance of confessions research: Opinions of the scientific community. American Psychologist. 2018. Vol. 73. No. 1. P. 63–80. Doi: 10.1037/ amp0000141.
  14. Kleinbaum D., Klein M. Survival Analysis: A Self-Learning Text (3rd ed.). Springer: 2012, 715 p.
  15. Unified register of pre-trial investigations. URL: https://erdr.gp.gov.ua. (accessed: 23.06.2013) [In Ukrainian].
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