This is part of our ongoing visualizations of the United States Code. For previous posts visualizing other portions of the code see Title 26 Tax and Title 11 BK. So, we wanted to test out the new Sea Dragon Visualizer from Microsoft Labs and thought Title 17 Copyright would be a fun way to give it a go. In this visual, each of the chapters under Title 17 is separately colored.
To use the visual, start in the center with the large label “Title 17 U.S.C.” and traverse the graph all the way out to any section or subsection. Sea Dragon should allow the user to smoothly zoom in and read any node. We love the interface.
Our multipart series on the clerkship tournament continues above with an expanded edition of our underlying dataset. It is important to note that we do not threshold for the number of graduates per school. Specifically, we do not just divide by the number graduates per school because we do not have any particular theoretic reason to believe that placements linearly scale to differences in size of graduating classes. In other words, given we do not know the proper functional form — we just offer the raw data for your consideration. For those interested in other posts, please click here for the law clerks tag.
In the previous circuit/district post, we focused upon the “top” 15 schools as ranked by an older version of US News. When we expand the analysis to consider a wider slice of institutions, two schools standout — Texas and Notre Dame. Basically, the arbitrariness of the prior cut off we imposed did not really do justice to these institutions … this wider view provides a deeper indication of their standing relative to other institutions.
This article offers a very interesting insight into the structure of academic disciplines. Using a variety of sources, the authors collected nearly 1 billion interactions from scholarly web portals including Thomson Scientific, Elsevier, JSTOR, etc.
Residing between Economics, Sociology and International Studies, notice the location for legal studies in the upper center portion of this screen print.
The Full Size visualization as well as relevant analytics are available within the paper. Among other things, the approach undertaken by Johan Bollen, Herbert Van de Sompel, Aric Hagberg, Luis Bettencourt, Ryan Chute, Marko A. Rodriguez & Lyudmila Balakireva provides an alternative view of the current structure of the academic disciplines from that offered in existing bibliometric studies.
So it has and will be light blogging while we finish a number of projects here in Ann Arbor. There are a number interesting papers in the queue including The Development of Community Structure in the Supreme Court’s Network of Citations (with James Fowler, James Spriggs and Jon Zelner) and A Tale of Two Codes: An Empirical Analysis of The Jurisprudence of the United States Tax Court (1990-2008) (with Lilian V. Faulhaber). Both are forthcoming to the SSRN and the CLS BLOG in the coming days. So in the mean time please enjoy the above movie …. and we will do our best to provide content during this busy period….
We enjoyed today’s discussion at the Harambeenet Conference here in the Duke Computer Science Department. The conference is centered upon network science and computer science education. It features lots of interdisciplinary scholarship and applications of computer science techniques in novel domains.
We are looking forward to an interesting final day of discussion and hope to participate in allied future conferences.
The visual above is drawn from the Netlogo Simulation of preferential attachment. “In the model, a given node prefers to connect to other nodes that already display high indegree. As the number of connections a given agent displays is a function of the number the agent possessed in earlier time periods, the distribution of connections is highly susceptible to the initial starting conditions. For instance, consider a network that has four nodes A, B, C and D where A is connected to B and C is connected to D. If node E enters the network, assume the initial probability of attachment to the AB community is equal to that of the CD community. Once E connects to either the AB or CD community, subsequent entrants such as node F, G and beyond are more likely to connect with the community selected by E.” The model offers one of the generative processes responsible for creating a network with a power law distribution.
There are important differences between the abstract model as initially described in Albert-László Barabási & Reka Albert, Emergence of Scaling in Random Networks, 286 Science 509 (1999) and the dynamics of broader social world. While a number of extensions of the model have been authored in the period following the original article, what is striking is how much leverage on basic dynamics can be gleaned from the graph analog of a Yule process.
For purposes of positive legal theory consider the following passage … “In order to contextualize what a particular observed network structure implies, it is critical to remember that the social landscape need not take any particular form. Scaffolding could indeed assume a variety of flavors and there are causal mechanisms that act at the micro-level to produce the observed macro-architecture.” While such distributions have been documented in a variety of context relevant for positive legal theory, it is important to note this distribution of social authority is by no means a given. Specifically, as we described in Social Architecture, Judicial Peer Effects and the ‘Evolution’ of the Law: Toward a Positive Theory of Judicial Social Structure social systems can embrace a wide variety of architectures. Thus, we believe the documented tendency of common law and its constitutive systems to generate such highly skewed distributions is highly relevant.
In Part II of this post, we will highlight the current state of the relevant applied legal literature. This includes not only our work but also important studies by a wide number of other legal scholars. To preview, check out this post from a few days ago…
It has been light blogging while we finish some projects here in Ann Arbor. In the meantime, here is an interesting visual offered by CDC website. Also, check out an important paper in this vein by Nicholas Christakis & James Fowler entitled The Spread of Obesity in a Large Social Network Over 32 Years (Click to the Left to Link to the Original Movie). Anyway, more to come later in the week…
Here at the CSCS Lab, we are working hard to finish up some projects. In the meantime, we wanted to highlight one of our favorite articles, an article we previously highlighted on the blog. Some of you might ask “what does this have to do with law or social science?” (1) We believe the taxonomy outlined in this article could potentially be applied to a wide set of social phenomena (2) As we say around here, if you are not reading outside your discipline, you are far less likely to be able to innovate within your discipline. So we suggest you consider downloading this paper….
This article in a recent issue of Science Magazine — authored by some of the leaders in field including Gary King, James Fowler, David Lazer, Albert-László Barabási, Lada Adamic as well as several others — highlights some of the possibilities of and perils associated with a computational revolution in the social sciences. We believe it is a worthwhile read….