excerpted from: Mario L. Barnes and Erwin Chemerinsky, What Can Brown Do for You?: Addressing Mccleskey V. Kemp as a Flawed Standard for Measuring the Constitutionally Significant Risk of Race Bias, 112 Northwestern University Law Review 1293 (2018) (197 Footnotes) (Full Document)
[I]f you're the intelligent man on the street and the Court issues a decision, and let's say, the Democrats win, and that person will say: Well, why did the Democrats win? And the answer is going to be because EG was greater than 7 percent, where EG is the sigma of party X wasted votes minus the sigma of party Y wasted votes over the sigma of party X votes plus party Y votes. And the intelligent man on the street is going to say that's a bunch of baloney. --Chief Justice John Roberts
As Chief Justice John Roberts's above quotation--which derives from the oral argument for Gill v. Whitford, a political gerrymandering case heard during the Supreme Court's fall 2017 term--suggests, at least some distinguished members of the nation's highest court are deeply skeptical of social science evidence. In fact, later in the argument, the Chief Justice further cautioned against courts attempting to make decisions based on “sociological gobbledygook.” Beyond Roberts's expressed belief in Gill that political science data can be unfathomable to the common person and thus should not be relied on by the Court, there have been numerous instances of the Court more generally applying inconsistent approaches to social science research. This has especially been the case when the Court has considered social science data on racial impact. On this, the thirty-year anniversary of McCleskey v. Kemp, we suggest that the Court's decision in that case stands out for a number of problematic reasons, but namely as a case where social science evidence elucidating the meaning of race in America was woefully ill-considered.
The majority opinion in McCleskey made two very disturbing assertions about social science data. First, the Court claimed the Baldus studies introduced by McCleskey, a black man sentenced to death for the killing of a white police officer, failed to prove a sufficient causal link between race and the imposition of the death penalty in Georgia. Second, the Court maintained the data did not “demonstrate a constitutionally significant risk of racial bias affecting the Georgia capital sentencing process.” The Justice Lewis Powell-led opinion reached these conclusions despite data in the studies confirming that a black person who killed a white person in Georgia was treated very differently, receiving the death penalty 22% of the time, as opposed to the 1% of black defendants who received the death penalty when their victims were black. Powell's claims about the Baldus data reflect an incommensurate approach for courts considering empirical research on race. For example, he seems to suggest that he would have been influenced by empirical data more persuasively evincing causation. Specifically, Powell stated: “Even Professor Baldus does not contend that his statistics prove that race enters into any capital sentencing decisions or that race was a factor in McCleskey's particular case. Statistics at most may show only a likelihood that a particular factor entered into some decisions.” In determining, however, that McCleskey involved no constitutional violation, he ignored the relative strength of the multiple regressions in the Baldus research--which are by definition probabilistic measures the reality that social science studies very rarely expound on causation in a manner that could support absolute certainty.
This Essay claims the McCleskey Court demonstrated a cramped understanding of both equal protection doctrine and the value of social science evidence. First, we propose that the McCleskey majority opinion problematically expanded the antidiscrimination standard articulated in earlier cases by adhering to a rigid “because of” requirement for establishing intent to discriminate in a specific case. The Court's Washington v. Davis opinion in 1976 first explicated that a Fourteenth Amendment Equal Protection Clause claim required both disparate racial impact and a discriminatory purpose. In 1979, Personnel Administrator of Massachusetts v. Feeney clarified that, in order to prove the discriminatory purpose of some state legislation, one would need to prove the state selected the course of action “because of,” not merely “in spite of,” its adverse effects upon a protected group. The McCleskey majority recommitted to these standards but did so despite the Court's willingness to authorize complaints based solely on disparate impact in other areas of the law and the availability of social science data that revealed racial inequality in death sentencing in Georgia. To our minds, the racial impact data in McCleskey demonstrated the fallacy of overly weighing intent in discrimination cases and the limits of the discriminatory purpose requirement more generally.
Second, we suggest that, at times, the Court's approach to considering racial impact data has been quite uneven. In other cases, the Court has been much more open to social scientific considerations of race, even with data that were less robust than the findings of the Baldus studies. As an example of the unevenness of the Court's approach to racial data, we look to the Court's consideration of social science evidence in Brown v. Board of Education. In Brown, in perhaps one of the most famous (or infamous footnotes in Fourteenth Amendment jurisprudence, the Court referenced social science data attesting to the negative psychological effects of segregation on African-American children. The Court, however, cited to studies without presenting the findings or interrogating the strength of the methodologies employed. This fact takes on greater relevance when one considers that numerous critics have challenged the findings of those studies over the years. Ironically, then, what some consider to be weaker data on the impact of race was welcomed by the Court in Brown, while significantly more robust studies evaluating race in capital sentencing (alongside numerous other factors) were rejected in McCleskey. Brown, however, was not an ideal example of how the Court should consider social science data. Dr. Kenneth Clark, a researcher who testified in the trial court in Brown and conducted doll studies that were cited in footnote 11, for example, claimed the Court ignored two of his important findings that racism was uniquely an American institution and that Whites were also negatively affected by segregation. Nevertheless, we argue that despite the imperfect manner in which the social science evidence was treated in Brown, the outcome of the decision appropriately addressed the harm--namely, racial segregation--and its societal consequences. This was not the case in McCleskey.
The disparate approaches to social science data across cases such as Brown, McCleskey, and Gill, reflect that the Court is in need of guidance on both evaluating social science data more generally and on the special considerations that may be necessary when assessing race data. This Essay proceeds in four parts.
In Part I, we consider the shortcomings of the Court's approach to intent in McCleskey and its implications for equal protection doctrine. In particular, we argue that the Court's dismissal of data finding an association between juror decision-making and disparate racial impact in criminal sentences paved the way for the rise of the Court's current post-racial reality contemporary moment where a majority of the Justices rarely assume that racial outcomes are tied to racial animus.
In Part II, we specifically point out how the McCleskey Court underestimates the robustness of the social science data presented in the case.
In Part III, we highlight the Court's history of inconsistently considering social scientific studies of race, in part by looking to the Court's analysis in the Brown v. Board of Education case.
In Part IV, we suggest that in light of the Court's peculiar dismissal of social science data in cases like McCleskey, it would be advisable for appellate courts to apply more regularized standards when considering social science data. These standards, however, would need to be mindful of the knotty history surrounding how scientific studies have considered race and best contemporary practices for capturing the complicated nature of race as a research study variable. As part of this assessment, we consider work by a number of sociolegal scholars who have recently advocated for a subfield that merges conceptualizations of race from critical studies with social science methods. Given the possibilities presented across various disciplines and involving myriad types of methods, it would make little sense to argue for an adoption of a one-size-fits-all approach to considering social science research data. Rather, our goal is to begin a discussion about how appellate courts should interpret the standard from Daubert v. Merrell Dow Pharmaceuticals, Inc. Presently, that case is seen as requiring trial judges to perform a gatekeeping function by ensuring that expert witness testimony rests on a reliable foundation and is relevant to the scientific issue at hand. There needs to be, however, a greater emphasis placed on formulating evidentiary standards for appellate courts to consistently apply when reviewing cases with social science data, especially where that research bears on disparate racial impact.
. . .
Three years after he retired from the U.S. Supreme Court, Justice Powell identified McCleskey as the case he should have decided differently while he was on the Court. His change of heart, however, had nothing to do with revisiting the strength of the data contained in the Baldus studies. Rather, he simply decided that the death penalty should be eradicated altogether. McCleskey, we have argued, was wrongly decided, but for reasons beyond those affecting Justice Powell's change of heart. The Baldus studies confirmed for the death penalty in Georgia something many scholars (and Justice Powell) believe about the U.S. criminal justice system overall: At every critical juncture within that system, race matters in determining outcomes. Had the McCleskey Court been predisposed to an understanding of the operation of racial disadvantage that was adopted by the Court in Brown, it is almost certain that the Baldus data would have been sufficient to support the finding of a violation of the Equal Protection Clause. It is also true that had Justice Powell privileged justice over preserving discretion within a biased but presumptively necessary criminal justice system, the last thirty years could have been spent addressing rather than lamenting the seamless overlaps between race, crime, and punishment that remain in this country. Here, however, we have attempted to lay the groundwork for options to improve current judicial assessments of social science research in general, and racial impact data more specifically. The Court's post-race societal sentiments being what they are today, it would be folly to expect courts to embrace a different understanding of the connection between race and societal disadvantage in the near term. Still, we should continue to create tools that will assist courts in thinking about social science data and the meaning of race in new and more sophisticated ways, understanding that this task may seem Sisyphean until the day comes when more Justices see statistically significant evidence of racial impact data as sufficient to sustain a constitutional equal protection claim.
Mario L. Barnes, Professor of Law & Criminology, Law and Society (by courtesy); Senior Associate Dean for Academic Affairs; Co-Director, Center on Law, Equality and Race (CLEaR), University of California, Irvine.
Erwin Chemerinsky, Dean and Jesse H. Choper Distinguished Professor of Law, University of California at Berkeley, School of Law. T