For the last two years, Christy Boyd and I, along with some friends, have been working on a paper on how attorneys construct complaints. The project began when we were working to code some other detritus of federal litigation and decided to collect the causes of action in complaints to understand the legal issues in our cases in a better manner than NOS codes alone permitted. Soon enough, we got to thinking that our causes of action were pled in distinctively patterned ways. Obviously, this isn’t an earth-shaking insight, as most first year students have thought, at one time or another, that each of their classes’ exam fact patterns could easily substitute for any other. That is: causes of action are alternative, mutually complementary, theories that channel a limited number of fact patterns into claims to legal relief. Everyone knows that contract and tort claims are pled together, and that constitutional claims come accompanied by state law torts. But we thought it’d be worthwhile to nail down this insight using a very similar analysis to the one that enables Amazon to tell you which books you might like — i.e., if you plead a particular cause of action, what other causes of action are you likely to bring in a particular case?
We gathered a set of 2,500 complaints (from a much larger sample of federal complaints derived through RECAP). The complaints were sampled to be fairly representative of all federal litigation, excluding pro se, social security, and prisoner petition cases. The sample contained 11,500 individual causes of action – around 4.6 causes of action per case. Guided by co-authors at Temple’s Center for Data Analytics, we used spectral clustering to examine the relationship between causes of action. Two years later and presto, we’ve a (draft) paper is up on SSRN! The ungainly title is Building a Taxonomy of Litigation: Clusters of Causes of Action in Federal Complaints. I welcome your comments, and your suggestions for a better title. Follow me after the jump for an exploration of our findings.