This is one of our all time best efforts from a scientific perspective (and it is now 7 years old). We did a rehash of it in our recent paper in the March 31, 2017 edition of Science magazine.
What are some of the key takeaway points?
(1) The Supreme Court’s increasing reliance upon its own decisions over the 1800-1830 window.
(2) The important role of maritime/admiralty law in the early years of the Supreme Court’s citation network. At least with respect to the Supreme Court’s citation network, these maritime decisions are the root of the Supreme Court’s jurisprudence.
(3) The increasing centrality of decisions such as Marbury v. Madison, Martin v. Hunter’s Lessee to the overall network.
The Development of Structure in the SCOTUS Citation Network
The visualization offered above is the largest weakly connected component of the citation network of the United States Supreme Court (1800-1829). Each time slice visualizes the aggregate network as of the year in question.
In our paper entitled Distance Measures for Dynamic Citation Networks, we offer some thoughts on the early SCOTUS citation network. In reviewing the visual above note ….“[T]he Court’s early citation practices indicate a general absence of references to its own prior decisions. While the court did invoke well-established legal concepts, those concepts were often originally developed in alternative domains or jurisdictions. At some level, the lack of self-reference and corresponding reliance upon external sources is not terribly surprising. Namely, there often did not exist a set of established Supreme Court precedents for the class of disputes which reached the high court. Thus, it was necessary for the jurisprudence of the United States Supreme Court, seen through the prism of its case-to-case citation network, to transition through a loading phase. During this loading phase, the largest weakly connected component of the graph generally lacked any meaningful clustering. However, this sparsely connected graph would soon give way, and by the early 1820’s, the largest weakly connected component displayed detectable structure.”
We also explore this network in our 2010 paper — Michael Bommarito, Daniel Martin Katz, Jonathan Zelner & James Fowler, Distance Measures for Dynamic Citation Networks 389 Physica A 4201 (2010) < SSRN > < arXiv >
I am honored to be Elected as a Fellow of the College of Law Practice Management. The College includes legal technologists, law firm leaders, corporate counsel, etc. I am looking forward to joining many friends and colleagues who are members of the college …
We are excited to be giving a talk at Stanford the day before the Future Law Conference. Our talk will be hosted by Stanford CodeX – The Center for Legal Informatics. If you are in the Bay Area – you can join us by signing up for free here.
The underlying paper is available here. Some starter slides here (start at slide 158) and we will be previewing our second paper in this three part series.
I am very excited to be heading back to UM – Ann Arbor to speak at the Workshop on Law + Complex Systems. I am particularly interested given that my PhD thesis is called “Modeling Law as a Complex Adaptive System.”
“Michael Bommarito II and Daniel Martin Katz, legal scholars at the Illinois Institute of Technology, have tried to measure the growth of regulation by analyzing more than 160,000 corporate annual reports, or 10-K filings, at the US Securities and Exchange Commission. In a pre-print paper released Dec. 29, the authors find that the average number of regulatory references in any one filing increased from fewer than eight in 1995 to almost 32 in 2016. The average number of different laws cited in each filing more than doubled over the same period.”
William Li, Pablo Azar, David Larochelle, Phil Hill & Andrew Lo, Law is Code: A Software Engineering Approach to Analyzing the United States Code
ABSTRACT: “The agglomeration of rules and regulations over time has produced a body of legal code that no single individual can fully comprehend. This complexity produces inefficiencies, makes the processes of understanding and changing the law difficult, and frustrates the fundamental principle that the law should provide fair notice to the governed. In this article, we take a quantitative, unbiased, and software-engineering approach to analyze the evolution of the United States Code from 1926 to today. Software engineers frequently face the challenge of understanding and managing large, structured collections of instructions, directives, and conditional statements, and we adapt and apply their techniques to the U.S. Code over time. Our work produces insights into the structure of the U.S. Code as a whole, its strengths and vulnerabilities, and new ways of thinking about individual laws. For example, we identify the first appearance and spread of important terms in the U.S. Code like “whistleblower” and “privacy.” We also analyze and visualize the network structure of certain substantial reforms, including the Patient Protection and Affordable Care Act (PPACA) and the Dodd-Frank Wall Street Reform and Consumer Protection Act, and show how the interconnections of references can increase complexity and create the potential for unintended consequences. Our work is a timely illustration of computational approaches to law as the legal profession embraces technology for scholarship, to increase efficiency, and to improve access to justice.”
Mike and I are excited to see this paper as it is related to two of our prior papers:
Daniel Martin Katz & Michael J. Bommarito II, Measuring the Complexity of the Law: The United States Code, 22 Journal of Artificial Intelligence & Law 1 (2014)
Michael J. Bommarito II & Daniel Martin Katz , A Mathematical Approach to the Study of the United States Code, 389 Physica A 4195 (2010)
Lets face it – legal systems are complex. They are complex for the sophisticated players and even more complex for the average citizen. Complexity is the problem and the question which has been at the center of some of our recent work (see here) is how best to mediate that complexity.
For long periods of time, clients and legal stakeholders have dealt with complexity by allocating human capital to the problem. However, there are other tools/methods that might be employed to mediate legal complexity.
Reducing legal complexity is a question of information engineering and it is a question of design. Legal systems need a user interface such as the one displayed above. They need UI/UX. This is a major thrust of behind design thinking for lawyers and this is will be a major thrust of work (undertaken by lawyers and non-lawyers) over the coming years. Stay tuned!
(HT: Robert Richards, Ted Sichelman for flagging this project)
From our abstract: “Einstein’s razor, a corollary of Ockham’s razor, is often paraphrased as follows: make everything as simple as possible, but not simpler. This rule of thumb describes the challenge that designers of a legal system face—to craft simple laws that produce desired ends, but not to pursue simplicity so far as to undermine those ends. Complexity, simplicity’s inverse, taxes cognition and increases the likelihood of suboptimal decisions. In addition, unnecessary legal complexity can drive a misallocation of human capital toward comprehending and complying with legal rules and away from other productive ends.
While many scholars have offered descriptive accounts or theoretical models of legal complexity, empirical research to date has been limited to simple measures of size, such as the number of pages in a bill. No extant research rigorously applies a meaningful model to real data. As a consequence, we have no reliable means to determine whether a new bill, regulation, order, or precedent substantially effects legal complexity.
In this paper, we address this need by developing a proposed empirical framework for measuring relative legal complexity. This framework is based on “knowledge acquisition,” an approach at the intersection of psychology and computer science, which can take into account the structure, language, and interdependence of law. We then demonstrate the descriptive value of this framework by applying it to the U.S. Code’s Titles, scoring and ranking them by their relative complexity. Our framework is flexible, intuitive, and transparent, and we offer this approach as a first step in developing a practical methodology for assessing legal complexity.”
This is a draft version so we invite your comments (email@example.com) and (firstname.lastname@example.org). Also, for those who might be interested – we are building out a full replication page for the paper. In the meantime, all of the relevant code and data can be accessed at GitHub and from the Cornell Legal Information Institute.
UPDATE: Paper was named “Download of the Week” by Legal Theory Blog.