One of the primary reasons why appellate lawyering is a specialty is because appellate lawyers must contend with persuading a collective, institutional decision maker. An appellate panel isn’t like a jury. The members of a jury come together for the first time for a particular case, and part forever when it’s over. Members of an appellate panel have generally been on the Court for months if not years, and will be there for years after a particular case is over. Members of a jury don’t share anything akin to the “law of the Circuit” or the “law of this Court” as a collective enterprise built over a span of years. And although historically, there’s been considerable pressure on jurors to find unanimity – although less so in recent years on the civil side – they almost always are trying to reach a binary decision: yes/no, one side wins, one side loses. An appellate panel, on the other hand, is attempting to reach unanimity on a collective reasoned, written argument. Decision making by appellate panel rather than individual judges has all kinds of potential effects on the outcome, and therefore on appellate lawyers’ task of persuasion – from making judges more reluctant to dissent from a decision they disagree with, to causing judges to vote in a more (or less) liberal or conservative direction than they otherwise would because of the panel’s deliberations.
Over the past few generations, political scientists, law professors, economists and statisticians have developed a host of tools for better understanding the dynamics of group decision making. These include game theory, organization theory, behavioral microeconomics, opinion mining and data analytics. Some researchers have used game theory to develop important insights about everything from the inner workings of the U.S. Supreme Court[1] to why Federal Circuits follow Supreme Court precedent.[2] Others have used traditional labor theory in an attempt to develop a unified theory of judicial behavior.[3] With the rise of widely available massive computerized databases of appellate case law, the most fast-growing and widely varied area of research has applied sophisticated statistical and “big data” techniques to understanding the law.
Data analytics is revolutionizing litigation. Several different companies are offering such services at the trial level. Lex Machina (recently acquired by LexisNexis), Ravel Law and Premonition each offer detailed analytics about trial judges, courts and case types based on databases of millions of pages of case information. ALM has also expanded its judicial profiles services to increase their focus on judge analytics.
Early last year, we at Sedgwick Appellate founded the Illinois Supreme Court Review to bring rigorous, law-review style empirical research founded on data analytic techniques to the study of appellate decision making. Today, we expand our focus with the California Supreme Court Review, a new blog devoted to sharing insights culled from tens of thousands of pages of opinions about the Justices and their decision making process, the parties and issues which come before the Court – all based upon a database of dozens of data points taken from every one of the 1,600+ decisions handed down by the Court from 2000 to 2015.
We hope you’ll join us.
Image courtesy of Flickr by OmiB91 (no changes).
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[1] James R. Rogers, Roy B. Flemming, and Jon R. Bond, Institutional Games and the U.S. Supreme Court (2006).
[2] Jonathan P. Kastellec, “Panel Composition and Judicial Compliance on the U.S. Courts of Appeals,” The Journal of Law, Economics & Organization, 23(2): 421-41.
[3] Judge Richard A. Posner and Professors Lee Epstein and William M. Landes, The Behavior of Federal Judges: A Theoretical & Empirical Study of Rational Choice (2013).