What Is a Society Legal
In the legislative process, the structure of legislation is controlled by the administrative officials who make the regulations. Therefore, the hierarchy, reference and order within a corpus of legislative documents contain information about the content of the corpus that is less noisy and easier to analyze than its language. To unlock this information for large-scale comparative and dynamic analysis, we model a set of legislation at a given point in time as a collection of documents according to the Document Object Model (DOM)32 standard (for our domain-specific XML schema definition [XSD], see Section 2.4 of the SI). For each document collection, we link four graphs, as shown in Figure 1a, whose formal definitions are contained in “Modelling Legislative Document Collections”. Our simplest graph is the hierarchical graph, which models the relationships of inclusion between the structural elements of legal texts. It is a subgraph of the reference graph that models inclusion and cross-reference relationships. From a network science perspective, the reference graph is perhaps the most intuitive representation of a collection of legislative documents, and all of our other charts can be derived from it. The sequential chart contains only the following elements of the reference chart connected by cross-reference edges and bidirectional sequence edges (“Modeling Legislative Document Collections” introduces a parameterized definition of this chart for greater analytical flexibility). Cross-reference edges are not weighted, whereas sequence edges have weights proportional to the distance between their endpoints in the undirected version of the hierarchical graph (for example, a sequence edge between section (i-1) and section i of chapter A weighs more than a sequence edge between section i of chapter A and section (i+1) of chapter B). The sequence diagram expresses how lawyers work with a legal text (i.e.
they approach a topic through a certain rule, scan its environment as long as it is also hierarchically close, possibly follow a cross-reference, and then scan the environment hierarchically close to a referenced rule). Finally, we define quotient graphs based on attributes associated with the elements of our reference graphs. In these diagrams, all elements with the same attribute values (for example, all seqitems elements belonging to the same chapter) are combined into a single node and the edges are redirected accordingly. To enable our comparative and dynamic analysis in “Consolidation for Comparative and Dynamic Analysis”, we group each annual snapshot of the legislative network separately for the two countries. As mentioned in “Clustering for comparative and dynamic analysis”, among the abundance of graph clustering methods, we choose the Infomap algorithm as our legal (re)research process because of its informational theoretical foundations, scalability and interpretability. Details of this algorithm can be found in the original papers.33,34 Cabrelli, D. & Siems, M. M. Convergence, legal origins, and transplants in comparative corporate law: a case-based and quantitative analysis. Law 63, 109-153 (2015). Whalen, R.
Legal networks: The promises and challenges of analyzing legal networks. 539-565 (2016). Each year, the annual Journal of Law and Social Sciences publishes a volume of review articles on specific topics in law and the social sciences written by recognized authorities in the field. Essays provide an overview of publications on each topic, usually focusing on specific aspects and indicating prospects for future research. Most people obey the law because they believe it leads to a peaceful society. The law is enforced by the POLICE. The risk of being caught and punished by the police reminds most people to obey the law. But some political activists deliberately break laws they disagree with – an act called “civil disobedience.” Methodologically, our approach focuses on the structural characteristics of legal texts.
In particular for the results we report in this work, the content of legal texts had only an indirect interest, for example in the raw numbers of tokens or in the reference structures that characterize legal subjects. However, as the section “Clustering for comparative and dynamic analysis” shows, qualitative analyses of legal norms contained in our documentary networks can provide additional information, thus opening up possibilities for normative legal research in areas such as comparative law and legal theory.39,40,41 Within these legal disciplines, the United States and Germany are generally associated with different legal traditions, also known as legal families, and categorization, although generally accepted, has not been confirmed by empirical studies.42,43,44,45 A first simple way to reorganize the U.S. code is to aggregate it at the chapter level rather than at the title level. This is particularly convenient because the number of chapters in the US Code is comparable to the number of individual laws in Germany, which we only divide into smaller units if they contain several books (a feature common to major German codifications such as the German Civil Code (BGB) and the German Commercial Code [HGB]). The node-link diagrams of the quotient graphs corresponding to this reorganization for the United States and Germany in 1994 and 2018 are presented in Fig. 4. In these charts, the nodes have the same color if they belong to the same cluster family. Overall, cluster families are clusters (a cluster is a set of nodes), primarily from different snapshots containing many identical, similar, or related rules (see definition 8 in “Comparing Document Networks in Space and Time”) and, as such, they address legal issues. We identify cluster families based on node and cluster alignments (see “Comparing Document Networks in Space and Time”). Cluster families will help us assess the legal issues driving growth, which we report in “Substantial Growth in Volume, Connectivity and Hierarchical Structure.” The cluster family color scheme is used in all other charts; see section 5.1 of the SI for a complete legend representing colours on legal topics. In Fig.4, nodes of the same color can generally be considered related (i.e. the same color (Leftrightarrow) (approximately) the same legal topic), and the colors of the nodes can be compared over the years but not between countries (for example, the legal theme of the red nodes in the charts for the United States may differ from the legal theme of the red nodes in the charts for Germany).
Boulet, R., Mazzega, P. & Bourcier, D. A network approach to the French system of legal systems Part I: Analysis of a dense network. Artif. Intell. Law 19, 333-355 (2011). Post, D. G. & Eisen, M. B.
How long is the coastline of the law? Reflections on the fractal nature of legal systems. J. Legal standard. 29, 545-584 (2000). Armour, J., Deakin, S., Lele, P. & Siems, M. M. How are legal regulations evolving? Evidence from a cross-border comparison of the protection of shareholders, creditors and employees. On the. J. Comp. Law 57, 579-629 (2009).
In Canada, there is a law society (French: barreau) in each province and territory, which is legally responsible for regulating the legal profession in the public interest. These law societies are members of the Federation of Law Societies of Canada, which strives to improve coordination among its members and promote standardization of member rules and procedures.  Our work is one step closer to this goal.