Agenda Setting for the Burger Court Judicial Database, 169-1985 Terms

Michigan State University, East Lansing MI

Investigators

Abstract

The process of setting its agenda has long been recognized as among the Supreme Court's most significant activities. Yet, little systematic work has been done on this critical aspect of the Court's decision making, a fact due in large part to the absence of systematic data on cases denied certiorari. The great majority of these cases deny certiorari requests for Supreme Court review. Without an adequate sample of the denied cases, analysis of agenda setting lacks validity because selection on the dependent variable results. This study will analyze a random set of summary decisions from the "orders" section at the back of each volume of the United States Reports to provide the agenda-setting data on cases not granted by the Court. Although the previous Vinson and Warren Court databases contain the cases denied review, they do not contain the other sets of variables that I have provided for the cases in the main part of each volume ("cases adjudged"): identification, background, chronological, substantive, and outcome. Without these latter five sets - along with case name, docket, date of decision, and the votes of the participating justices - meaningful comparisons cannot be had. In order to enhance comparison between the "cases adjudged" and a sample of "orders," the PI will add a series of relevant variables to the 4370 "cases adjudged" decisions in the Burger Court database, and to the sample of "orders." He will also add to the sampled cases those of the 334 variables that the Burger Court database contains that are also relevant to cert denials. The resulting database will be a highly valuable resource for the large number of social scientists and legal academics concerned with the Court's agenda setting process, whether that concern assesses the predictions of existing theories grounded in a range of socio-legal traditions or with building and testing new theories. Theories and models limited only by users' imaginations will be amenable to systematic and rigorous testing. Finally, these data will be subject to extensive reliability testing, and will be archived at the Michigan State website and, as such, freely available and easily accessible to all interested individuals and organizations.