一个动态系统分析的犯罪行为使用全国纵向调查的青年数据的动态系统分析
David McMillon1,2,3, Jeffrey Morenoff4,5,6, Carl Simon4,7,8,9
1Department of Economics, Emory University, Atlanta, Georgia, United States of America.
PloS one
|August 8, 2025
概括
首次逮捕的边际增加提高了所有群体的长期犯罪. 黑人男性的犯罪率对最初的犯罪参与和康复很敏感,而没有先前逮捕的黑人女性更有可能放弃.
科学领域:
- 犯罪学 犯罪学
- 社会学 社会学 社会学
- 动态系统建模 动态系统建模
背景情况:
- 之前的研究探讨了犯罪的传播和维持.
- 了解犯罪参与,逮捕,拒绝和康复的动态至关重要.
研究的目的:
- 构建和分析犯罪参与的动态系统模型.
- 通过使用来自全国青年纵向调查的数据来经验地估计模型.
- 检查不同途径如何影响长期犯罪水平和种族差异.
主要方法:
- 开发一个动态系统模型.
- 经验估计使用国家长度青年调查数据.
- 分析犯罪途径中的子组变化和种族差异.
主要成果:
- 在所有子组中,第一次逮捕率的边际增加提高了长期犯罪率.
- 对重复犯罪者的逮捕率并没有显著影响长期犯罪.
- 黑人男性的长期犯罪水平对最初的犯罪参与,逮捕和康复非常敏感.
- 没有先前被捕历史的黑人女性显示出明显更高的抗拒可能性.
结论:
- 该模型为犯罪控制政策提供了洞察力,并解释了黑人和白人参与犯罪的差距.
- 针对首次犯罪者的干预措施在减少长期犯罪方面可能更有效.
- 康复计划显示了减少黑人男性犯罪的潜力.
- 了解特定小组的途径对于有效的犯罪减少策略至关重要.
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