Today I am in Oslo giving the Keynote Address at the University of Oslo – Network Analysis and Machine Learning in Law Conference. Some very cool papers have been will be presented –https://www.jus.uio.no/
Call For Papers: “The empirical turn in legal scholarship has intensified with the integration of a new quantitative and computational methods. In our second annual workshop on law and social science methods, we call for papers on two increasingly popular approaches: network science and machine learning. We are especially interested in papers that seek to deepen the understanding of these methods or apply them to doctrinal or interdisciplinary questions in areas such as criminology, international law, corporate Law and sustainable development.
The Keynote Speaker for the workshop is Dan Katz, Illinois Tech – Chicago Kent College of Law, who has been a pioneer in the use of both methods in understanding and predicting the behavior of the US Supreme Court and advancing the field of legal technology”
Acceptance of papers will be notified by 1 September 2018.
Papers should be submitted by 24 September 2018.
Workshop 10-11 October 2018 at the University of Olso
This is a very interesting Net Sci + Law Paper !
I was revisiting some of our old stuff for this Oslo event -early on for us on our #LegalPhysics #LegalAnalytics path – published in Physica A – “By applying our sink clustering method, we obtain a dendrogram of the network’s largest weakly connected component shown in Fig. 4. However, despite their general topical relatedness, these two clusters of cases engage substantively different sub-questions, and are thus appropriately divided into separate clusters. While not a major focus of the docket of the modern court, the early court elaborated a number of important legal concepts through the lens of these admiralty decisions. For example, the red group of cases engages questions of presidential power and the laws of war, as well as general interpretations of the Prize Acts of 1812. Meanwhile, the blue cluster engages questions surrounding tort liability, jurisdiction, and the burden of proof.”
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 >
Above is a tutorial that Mike and I developed for the Jurix Conference in Vienna in December of 2011. Feel free to message if I can answer any questions.