Illinois Tech - Chicago Kent College of Law, Chicago, USA.
CodeX - The Stanford Center for Legal Informatics, Stanford, USA.
Sci Rep. 2020 Oct 30;10(1):18737. doi: 10.1038/s41598-020-73623-x.
While many informal factors influence how people interact, modern societies rely upon law as a primary mechanism to formally control human behaviour. How legal rules impact societal development depends on the interplay between two types of actors: the people who create the rules and the people to which the rules potentially apply. We hypothesise that an increasingly diverse and interconnected society might create increasingly diverse and interconnected rules, and assert that legal networks provide a useful lens through which to observe the interaction between law and society. To evaluate these propositions, we present a novel and generalizable model of statutory materials as multidimensional, time-evolving document networks. Applying this model to the federal legislation of the United States and Germany, we find impressive expansion in the size and complexity of laws over the past two and a half decades. We investigate the sources of this development using methods from network science and natural language processing. To allow for cross-country comparisons over time, based on the explicit cross-references between legal rules, we algorithmically reorganise the legislative materials of the United States and Germany into cluster families that reflect legal topics. This reorganisation reveals that the main driver behind the growth of the law in both jurisdictions is the expansion of the welfare state, backed by an expansion of the tax state. Hence, our findings highlight the power of document network analysis for understanding the evolution of law and its relationship with society.
虽然许多非正式因素会影响人们的互动方式,但现代社会还是依赖法律作为正式控制人类行为的主要机制。法律规则如何影响社会发展取决于两种类型的参与者之间的相互作用:制定规则的人和规则可能适用的人。我们假设,一个日益多样化和相互关联的社会可能会产生更加多样化和相互关联的规则,并断言法律网络提供了一个有用的视角,可以观察法律与社会之间的相互作用。为了评估这些命题,我们提出了一个新颖且可推广的法定材料模型,将其视为多维、随时间演变的文档网络。我们将该模型应用于美国和德国的联邦立法,发现过去二十五年间法律的规模和复杂性显著扩大。我们使用网络科学和自然语言处理方法来研究这种发展的根源。为了能够根据法律规则之间的明确交叉引用进行跨时间的跨国比较,我们以算法方式将美国和德国的立法材料重新组织成反映法律主题的集群家族。这种重新组织揭示了这两个司法管辖区法律增长的主要驱动因素是福利国家的扩张,其背后是税收国家的扩张。因此,我们的研究结果强调了文档网络分析在理解法律演变及其与社会关系方面的强大功能。