Quantification Model of Sentencing in Lay Judge (Saiban-in) System

• Project/Area Number: 23730069
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Criminal law
• Research Institution: Nagasaki Institute of Applied Science (2013); Tokyo Metropolitan University (2011-2012)
• Principal Investigator: SHIBATA Mamoru 長崎総合科学大学, 公私立大学の部局等, 准教授 (90551987)
• Project Period (FY): 2011 – 2013
• Project Status: Completed (Fiscal Year 2013)
• Budget Amount: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000); Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000); Fiscal Year 2011: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
• Keywords: 量刑 / 裁判員裁判 / 数量化 / 刑事政策

Research Abstract

In this study, I tried to apply the hierarchical neural network (multilayered perceptron), developing basic analytical model (quantification model) of sentencing to apply new statistics technique. As a result, at first it was inspected by a hierarchical neural network (multilayered perceptron) that it was most suitable to distinguish "3 years or less of imprisonment with hard labor" and "more than 3 years of imprisonment with hard labor" to analyze the period of the penalty.