The final chapter will commence with an explication of a 1963 Theodore Becker lamentation that ―judicial behavioralism generally has not begun to consider the Court as a court.‖ Few scholars, he said, ―have viewed the judicial decision-making process in its uniqueness,‖ adding that ―most have treated it no differently from any other decision-making process, e.g., from the street corner gang to the Congress‖ (Becker, 1963, 264). Today, we are certainly closer to having a more comprehensive portrait of judicial decision-making than we were at the time of
11 Future research might wish to add an ancillary component to this analysis by recognizing whether certain combinations of characteristics could help to explain the voting behavior of those justices who significantly deviate from the expectations of appointing presidents (e.g., justices appointed by Republicans that ultimately exhibit liberal voting patterns).
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Becker‘s declaration. The biggest reason for this is that more of the variables associated with the process of Supreme Court decision-making have been identified and empirically studied. Of course, as Segal and Spaeth note, ―A model is a simplified representation of reality‖ (Segal and Spaeth, 2002, 44) designed to ―explain and predict behavior‖ (Segal and Spaeth, 2002, 46, emphasis added). And, by adding the disclaimer that when a model ―explains everything‖ it actually ―explains nothing‖ (Segal and Spaeth, 2002, 86), they seem to indicate that one should not strive for a single model that incorporates all of the information that could be brought to bear on the matter of judicial behavior. What one should aspire to create, though, is a model that contains ―variables [that] explain a high percentage of the behavior in question‖ (Segal and Spaeth, 2002, 46). To this end, the final chapter will offer a technique for combining the information analyzed in previous chapters into a comprehensive, yet parsimonious, model.
Specifically, I will suggest using the individual, year-by-year, conservative/liberal voting records of a sample of Supreme Court justices as a dependent variable. This would be easy to quantify for a wide cross-section of justices, and analyzing liberal and conservative voting patterns can have valuable explanatory and predictive power, for voting patterns represent the most visible outcome of the judicial decision-making process and offer an indication of the direction in which justices are shaping policy. Further, I will suggest studying variation in this dependent variable through the use of a GLS, random-effects time series model. Independent variables will involve a combination of the different variables offered at various points in this dissertation. This will make it possible to track whether voting behavior can be explained by pre-confirmation factors, such as the party of the appointing president, the composition of the confirming Senate, and the presence or absence of divided government—and by
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confirmation factors, such as the length of a justice‘s ―allegiance period‖ and the percentage of a justice‘s tenure that is served with an ideologically-compatible Congress or White House. The comprehensive model will also control for other variables that literature has described as influences on liberal and conservative voting behavior, such as age at time of appointment, prior judicial experience, political experience, and total terms served (Ulmer, 1973, 623; Aliotta, 1988, 278; Hagle, 1993, 1144).12 Collectively, this will allow for the incorporation of attitudinal,
―acclimation,‖ and New Institutionalist concerns into one model.
Ultimately, the overall importance of generating such a model, and for explaining and predicting judicial behavior, is implicit in James Spriggs and Thomas Hansford‘s assertion that Supreme Court decisions ―fundamentally affect the allocation of resources in society‖ (Spriggs and Hansford, 2006, 133), and in the Michael Heise passage invoked earlier (see page 3). The final chapter will attempt to consolidate efforts to explain and predict the behavior of Supreme Court justices, perhaps the most relevant judicial actors referenced in Heise‘s statement (at least in terms of having an impact on national policy making). In addition, the final chapter will distill pertinent findings from various statistical models presented herein and will expound upon the relevance of both significant and insignificant findings. Finally, it will delineate the theoretical and methodological limitations of this work (including the small sample size relative to other work in the discipline of political science), and will offer suggestions for future research in the sub-field of judicial politics (including expansion of the Spaeth databases and the search for more independent and dependent variables related to the process of judicial decision-making).
12 Lee Epstein et al. have compiled a dataset that tracks these variables. See U.S. Supreme Court Justices Database in ―References‖ section.
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More specifically, the final chapter will demonstrate that the theory underlying this research can ultimately be used to assess the extent (however large or small) to which democratically-elected actors in the executive and legislative branches can shape judicial outputs via the confirmation process—as well as how individual citizens can influence this process through their voting choices. Further, this research can also be used to illustrate the degree to which justices are loyal to the mores of an appointing president or a partisan Congress, and might help to appraise whether the notion of an ―independent judiciary,‖ a sacred idea rooted in our nation‘s founding (see Alexander Hamilton‘s Federalist #78), is in fact apparent in our society today.
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