2013 Fiscal Year Final Research Report
Quantification Model of Sentencing in Lay Judge (Saiban-in) System
| Project/Area Number |
23730069
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Criminal law
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| Research Institution | Nagasaki Institute of Applied Science (2013)
Tokyo Metropolitan University (2011-2012) |
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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)
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| Project Period (FY) |
2011 – 2013
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| Keywords | 量刑 / 裁判員裁判 / 数量化 / 刑事政策 |
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| 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.
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