Gender, Race, and Dissensus in State Supreme Courts

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Gender, Race, and Dissensus in State Supreme Courts John Szmer, University of North Carolina, Charlotte Robert K. Christensen, University of Georgia Erin B. Kaheny., University of Wisconsin, Milwaukee Supplemental Descriptive Information & Analysis Due to space limitations in the text, we provide some descriptive information regarding the presence of women and minorities serving on state high courts in this supplemental appendix. First, 91 of the 460 justices (about 20 percent) casting votes in the State Supreme Court Database, 1995-1998, were women. There were very few states with more than three female state supreme court justices serving in this time period. However, five women served on the high courts in Minnesota and Texas, and four women served on the Michigan state supreme court during these four years. Most typically, fewer than three women were present on each court. In fact, the average number of women justices sitting on each state supreme court bench during this period was 1.82, though there were seven states in which no woman sat during the time period under investigation. Further, although there has been significant headway in the appointment of African American justices to these courts, of the 460 justices casting votes in the State Supreme Court Database, 27 (i.e., about six percent) were African American. Though sizeable enough for statistical analysis, it is important to note that this is still a relatively small percentage of justices. Moreover, African American state supreme court justices were not appointed in disproportionate numbers to any single state court. Indeed, the only state in which there was more than one African American high court justice during this time period was Georgia, where there were two. The other states in which an African American high court justice sat included: Arkansas, California, Indiana, Louisiana, Alabama, Colorado, Connecticut, Florida, Illinois, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, New Jersey, New York, North Carolina,

Pennsylvania, South Carolina, Tennessee, Texas, Virginia, Washington, and West Virginia (Texas, however, is removed from the models reported in the text). The Latino justices in the State Supreme Court Dataset served on the high courts in Colorado, Florida, Michigan, New Mexico, New York, and Texas (again, Texas is removed from the models reported in the text). Finally, there were very few African American women justices serving on state high courts during the time period of the study. Specifically, we identified five African American women serving on the high courts in Arkansas, California, Georgia, Indiana, and Louisiana. While we explore the dissenting behavior of these women judges in relation to African American males and white males, like others before us, our ability to generalize is obviously limited by the number of justices experiencing the intersectional influences of race and gender during the four years of data that we have available. Additional descriptive statistics for the models presented in the study are available in Table A-1.

TABLE A1 Descriptive Statistics, US State Courts of Last Resort Cases, 1995-1998 Independent Variable Mean Standard Deviation Judge Dissent 0.056 --- Justice Gender 0.189 --- Panel Gender 1.069 0.79 Women s Issue 0.091 --- African American Justice 0.083 --- Panel Race 0.47 0.56 Minority Issue 0.03 --- Latino Justice 0.004 --- African American Female 0.015 --- White Female 0.173 --- African American Male 0.067 --- Amicus 0.084 --- Amicus Rate 0.076 0.081 Ideological Distance 16.645 19.153 Cross Appeal 0.046 --- Criminal (Other) 0.177 --- Reversal 0.365 --- Assault 0.038 --- Murder 0.132 --- Rape 0.035 --- Death Penalty 0.001 --- Domestic Violence 0 --- Affirmative Action 0 --- Abortion 0.045 --- Sexual Orientation Rights 0.36 --- Right to Die 0.375 --- Constitutional (Other) 0.052 --- Panel Size 6.393 1.357 Partisan Election 0.192 --- Nonpartisan Election 0.33 --- Legislative Appointment 0.083 --- Gubernatorial Appointment 0.148 --- Strategic Assignment 0.017 --- Chief Judge 0.157 --- Tenure 8.768 6.774 Elite Law School 226 --- Intermediate Appellate Court 0.728 --- Clerkships 2.094 0.968 Party Competition Index 0.857 0.085 Proportion of White Residents 0.847 0.106 Court Caseload 155.234 42.659 Justice Caseload 2.292 1.824 Court Professionalism 0.565 0.152

State-by-State Rates of Dissensus As can be seen in Table A-2, most state supreme court decisions are rendered without any dissents. For interested readers, however, we report the percentage of dissents cast (out of all votes) for each state for the time period of the analysis in Table A-2. TABLE A2 Percentage Votes Cast as Dissents, State Supreme Court Dataset, 1995-1998 Alabama 8.38 Nebraska 3.18 Alaska 3.64 Nevada 8.69 Arizona 4.13 New Hampshire 2.54 Arkansas 5.12 New Jersey 5.03 California 9.23 New Mexico 2.06 Colorado 4.87 New York 4.02 Connecticut 6.22 North Carolina 2.88 Delaware 1.09 North Dakota 2.67 Florida 4.69 Ohio 11.19 Georgia 4.11 Oklahoma 8.97 Hawaii 1.31 Oregon 3.97 Idaho 3.28 Pennsylvania 9.18 Illinois 9.19 Rhode Island 0.76 Indiana 3.08 South Carolina 2.44 Iowa 1.89 South Dakota 6.40 Kansas 1.99 Tennessee 2.37 Kentucky 9.85 Texas 9.95 Louisiana 7.57 Utah 6.85 Maine 2.53 Vermont 3.41 Maryland 4.49 Virginia 3.60 Massachusetts 1.94 Washington 9.05 Michigan 16.48 West Virginia 2.52 Minnesota 3.99 Wisconsin 4.77 Mississippi 9.52 Wyoming 2.29 Missouri 3.56 Montana 6.31 Alternative Approaches toward Modeling Dissensus Of course, an alternative approach to assessing race and gender-based influences of dissensus than that provided in our manuscript would be to model the justices career dissenting behavior as a function of race and gender. Unfortunately, the State Supreme Court Dataset, which includes four years of data,

provides a limited window with which to assess a justice s career behavior. More importantly, however, such an approach would not allow us to simultaneously consider other relevant case, court, and judge characteristics. However, in a limited regression analysis of career dissent scores using the State Supreme Court dataset, a justice s gender (coded 1 if the justice was female; 0 otherwise) or minority status (coded 1 if the justice was an African American or Latino; 0 otherwise) was not statistically related to the judge s career dissent score. The results of these analyses are provided in the Tables A-3 and A-4. TABLE A3 OLS Model of State Supreme Court Justice Career Dissenting Scores (Gender) Independent Variable Coefficient Std. Error Justice Gender Constant N F (1, 458) Prob >F R 2-0.005 0.057 460 0.68 0.4092 0.0015 0.007 0.000 TABLE A4 OLS Model of State Supreme Court Justice Career Dissenting Scores (Race) Independent Variable Coefficient Std. Error African American/Latino Justice Constant N F (1, 442) Prob >F R 2 0.007 0.057 444 0.48 0.4882 0.0011 0.010 0.000 PAJID as a Function of Race or Gender? All of the models reported in the text include an important control for judge ideology (specifically, the ideological distance between the justice and the majority opinion author). This control is introduced to be consistent with other literature in the field, as we should expect any justice (race or gender issues aside) to be more likely to dissent if they disagree with the policy preferences of the majority opinion author. It is

also important to include this control since one might assume the ideological preferences of women and minority justices differ systematically from male and non-minority justices. Interestingly, a difference of means test revealed no statistically significant differences in the ideology scores of men and women state supreme court justices (measured by way of the judges PAJID scores). However, there was a statistically significant difference in the ideology scores between minority (African American and Latino) justices and white state supreme court justices, with the former group of justices exhibiting more liberal values on the PAJID measure. The results of these analyses can be seen in Tables A-5 and A-6. TABLE A5 Difference of Means Test, PAJID by Gender Gender Mean Std. Error Male Female H a : diff <0 Pr (T<t) = 0.1798 38.894 41.373 H a : diff=0 Pr ( T > t )=0.3596 1.197 2.449 H a : diff>0 Pr (T>t)=0.8202 TABLE A6 Difference of Means Test, PAJID by Race Gender Mean Std. Error White Justice African American/Latino Justice H a : diff <0 Pr (T<t) = 0.0132 38.721 47.959 H a : diff=0 Pr ( T > t )=0.0265 1.128 3.085 H a : diff>0 Pr (T>t)=0.9868 Amicus, Amicus Rate, and Amicus x Amicus Rate Finally, our models include a measure of the presence of an amicus in a case (Amicus), the rate of amicus filings before the state supreme court (Amicus Rate), and a multiplicative term, Amicus x Amicus Rate. As these are control variables, significant attention is not paid toward analyzing the nature of this conditional relationship in the text. However, this relationship is quite interesting. In Figure A-1, we provide a

graphical display of the statistical significance of Amicus across various levels of Amicus Rate. As clearly seen in the figure, as the rate of amicus filings before a state supreme court increases, the effect of a given amicus brief on the likelihood of a justice dissenting in a case decreases. FIGURE A1 Conditional Effects -.03 -.02 -.01 0.01.02.03 Conditional Effects of Amicus by State Amicus Rate 0.1.2.3.4.5 State Amicus Rate