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Deciding to Agree: Explaining Consensual Behavior on the United States Supreme Court
Unformatted Document Text:  21 liberties are least likely to be decided unanimously or consensually, and we use governmental powers cases as our baseline for comparison. Finally, we test for the possibility that cases with a high degree of salience to external political actors and the public will also be salient to the Court itself. As Grossman and Wells argue, “[T]hese are the kinds of cases least likely to be decided unanimously. There is no a priori reason to expect…justices to be united on politically contentious issues that divide the country” (1989: 59). Thus, salient cases – specifically, those covered on the front page of the New York Times (Epstein and Segal 2000) – should be unlikely to result in unanimous decisions or highly consensual decisions. Appendix A provides a full explanation of how each variable was constructed and coded. Table 2 provides summary statistics for each variable as well as the expected direction of each coefficient. The reader should note we coded our variables where possible such that a positive change in the independent variable reflects an increased likelihood of unanimity or an increased likelihood of a high degree of consensus. [Insert Table 2 about here] Achieving Consensus on the Supreme Court Table 3 presents the results of the logit regression and the OLS regression. Table 4 present a series of predicted probabilities associated with each of the statistically significant variables in these two models. The first row of Table 4 shows the baseline predicted probability of achieving a unanimous decision and the baseline predicted percentage of consensus. The baseline probabilities are computed by holding all continuous variables (such as the level of complexity) at their mean values, while holding all discrete values (such as dissent in the court below) at their modal values, with the exception of the dummy Chief variables, which are set at

Authors: Corley, Pamela., Steigerwalt, Amy. and Ward, Artemus.
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liberties are least likely to be decided unanimously or consensually, and we use governmental
powers cases as our baseline for comparison. Finally, we test for the possibility that cases with a
high degree of salience to external political actors and the public will also be salient to the
Court itself. As Grossman and Wells argue, “[T]hese are the kinds of cases least likely to be
decided unanimously. There is no a priori reason to expect…justices to be united on politically
contentious issues that divide the country” (1989: 59). Thus, salient cases – specifically, those
covered on the front page of the New York Times (Epstein and Segal 2000) – should be unlikely
to result in unanimous decisions or highly consensual decisions.
Appendix A provides a full explanation of how each variable was constructed and coded.
Table 2 provides summary statistics for each variable as well as the expected direction of each
coefficient. The reader should note we coded our variables where possible such that a positive
change in the independent variable reflects an increased likelihood of unanimity or an increased
likelihood of a high degree of consensus.
[Insert Table 2 about here]
Achieving Consensus on the Supreme Court
Table 3 presents the results of the logit regression and the OLS regression. Table 4
present a series of predicted probabilities associated with each of the statistically significant
variables in these two models. The first row of Table 4 shows the baseline predicted probability
of achieving a unanimous decision and the baseline predicted percentage of consensus. The
baseline probabilities are computed by holding all continuous variables (such as the level of
complexity) at their mean values, while holding all discrete values (such as dissent in the court
below) at their modal values, with the exception of the dummy Chief variables, which are set at


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