Yesterday, we began our analysis by addressing the competing theories of judicial behavior. Formalism, the oldest theory, teaches that judicial decision making can be explained and predicted based upon the facts, the applicable law and precedent and judicial deliberations – and nothing more.
But if formalism explains all of judicial decision making, then many of the factors studied by empirical analysts, such as the judges’ individual ideologies and voting records, the lower courts involved and the nature of the parties to the litigation, should have little ability to forecast voting and outcomes. But many studies have shown that such factors do have predictive power.
One of the two primary alternative theories was set forth in The Supreme Court and the Attitudinal Model, by Professors Harold J. Spaeth and Jeffrey A. Segal. Attitudinalism holds that judges vote based upon their individual ideologies set against the facts of a specific case. For example, a judicial conservative will require substantially more extreme facts before being willing to condemn the conduct of a police investigator than a liberal will. Conversely, a judicial liberal will approve of government interference in business based upon a lesser showing of need than a conservative will require.
Attitudinalists have proposed two principal methods for proxying the ideologies of judges. First, a Federal judge is presumed to be of the same party as the President who nominated him or her. Although simple enough to determine, this model has been criticized as a blunt instrument, not allowing for the possibility that a Democratic president might nominate a judge who is equally if not more conservative than a Republican one. Professor Segal and Professor Albert D. Cover have proposed “Segal-Cover scores,” which are based upon analysis of newspaper editorials published prior to a Justice’s confirmation. Segal-Cover scores have proven to be valuable predictors of judicial voting patterns. Other analysts have attempted to deriveex post ideological measures by tracking judges’ actual votes over a substantial period.
A third theory of judicial behavior is represented most prominently by Judge Richard Posner of the Seventh Circuit, and is known as legal pragmatism or realism. Legal realism is based upon the idea that the law evolves over time as society moves forward. Judge Posner has written that the task of the judge “is to decide cases with reasonable dispatch, as best one can, even in what I am calling the interesting cases – the ones in which the conventional materials of judicial decision making just won’t do the trick.” Legal realism attempts to integrate the other theories into a kind of unified theory. To a legal realist, a not insubstantial fraction of every appellate court’s caseload can be explained using traditional formalist techniques. Another portion of the docket can be explained by attitudinalism – more so in appellate courts of last resort than in intermediate appellate courts. But the rest cannot be entirely explained by either theory, since formalist rules do not dictate a determinate answer to the question, and judicial concerns, such as the limitations on what courts can practically do or the value of stability in the law, constrain judges from following their ideological preferences.
In the decades since C. Herman Pritchett’s work on the Roosevelt Court – and especially in the past thirty years – data analytic researchers have provided considerable evidence to suggest that the attitudinal and realism theories have considerable power to illuminate judicial decision making. Next Thursday, we’ll begin applying those techniques to the past sixteen years’ worth of decisions from the California Supreme Court.
Image courtesy of Flickr by Michael Coghlan (no changes).
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