底龄未成年人重罪问题的规范分析与价值判断
Normative Analysis and Value Judgment on the Issue of Juvenile Offenders Committing Serious Crimes
卫磊1
作者信息
摘要
对于已满12 周岁不满14 周岁的底龄未成年人涉嫌法定重罪的,应当激活《刑法》第17 条第3 款之规定,区分底龄未成年人重罪问题的个案处理与类型事实处理两个方面,并分别从规范分析和价值判断着手.对《刑法》第17 条第3 款规定的两种犯罪应当采取行为说,对其规定的"情节恶劣"应当采取"整体的评价要素"说,对"经最高人民检察院核准追诉"应当理解为程序性核准为主、兼顾实体性核准的法定程序环节.未来应当完善重罪底龄未成年人的量刑规则,应在条件成熟时删除对其减轻处罚的规定,减少基准刑下降幅度;强化监护义务刑事责任化的规制完善,条件成熟时可增加拒不履行监护有关罪名;同时建立健全不良行为未成年人早期预警与分级干预机制,形成底龄未成年人重罪预防与治理协同体系.
Abstract
For juvenile offenders aged twelve to less than fourteen suspected of committing statutory serious crimes,Article 17,Paragraph 3 of the Criminal Law should be activated.Differentiating between individual case handling and typological fact processing is essential in addressing the issue of juvenile offenders committing serious crimes,starting with normative analysis and value judgments.Regarding the two types of crimes stipula-ted in Article 17,Paragraph 3 of the Criminal Law,an act-based interpretation should be adopted,while the notion of "serious circumstances" should be understood through a comprehensive evaluation framework.The phrase "approved for prosecution by the Supreme People's Procuratorate" should be understood primarily as a procedural approval,with substantive approval considered supplementary.Improving sentencing guidelines for juvenile offenders committing serious crimes involves removing provisions for mitigating punishment when condi-tions are ripe and reducing the extent of reduction in the baseline sentence.Strengthening the regulation of guardianship obligations and criminal responsibility,including the possibility of adding charges for failure to fulfill guardianship duties,should be considered when conditions permit.Establishing a sound early warning and graded intervention mechanism for juvenile offenders,forming a collaborative system for the prevention and management of serious crimes committed by juvenile offenders,is imperative.
关键词
底龄/未成年人/低龄/重罪/规范Key words
minority/juveniles/young age/serious crime/norm引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据