Critical Mass for Affirmative Action: Dispersing the Critical Cloud

By Kalbfeld, Jessica Rose | Law & Society Review, January 1, 2019 | Go to article overview

Critical Mass for Affirmative Action: Dispersing the Critical Cloud


Kalbfeld, Jessica Rose, Law & Society Review


I understand my job [is] to determine if your use of race is narrowly tailored to a compelling interest. The compelling interest you identify is attaining a critical mass of minority students at the University of Texas, but you won't tell me what the critical mass is. How am I supposed to do the job that our precedents say I should do?

Chief Justice John Roberts, Oral Arguments for Fisher v. University of Texas, October 10, 2012

We should probably stop calling it critical mass then, because mass, you know, assumes numbers, either in size or a certain weight ... So we should stop calling it mass ... Call it a cloud or something like that.

Justice Antonin Scalia, Oral Arguments for Fisher v. University of Texas, October 10, 2012

1.Introduction

During oral arguments in Fisher v. University of Texas at Austin in October 2012, Justice Antonin Scalia and Chief Justice John Roberts expressed confusion over the concept of critical mass. Both perceived that it implied numbers and found definitions of critical mass without reference to numbers dissatisfying. Scalia suggested that the description, established in the Grutter v. Bollinger (2003) majority opinion, described an amorphous cloud more than a definable mass. Roberts expressed frustration that he was asked to rule on the merits of an insufficiently explained concept. Their frustration illustrates a problem with the use of critical mass in both legal discourse and in social science. Reaching a critical mass of underrepresented students and employees has been hailed as a cure for problems related to stereotype and social identity threat,1 unconscious bias,2 lack of diversity, and climates of exclusion in universities and organizations. However, what remains unclear is how organizations should determine what number constitutes a critical mass of students or employees, or whether indeed there even is a particular critical mass that will solve institutional issues related to a lack of diversity and inclusion. In this paper, I survey the history and use of the term critical mass in the social sciences and in affirmative action jurisprudence, then, I use Agent-Based Models (ABMs) to instantiate the Supreme Court's assumptions as testable models of the relationships between student body composition and isolation and stereotyping to evaluate whether those relationships really have the properties the Court assumes.

Unfortunately, critical mass is simultaneously underdefined and overdefined within the social sciences. While it is invoked across a broad scholarly literature, there is no consensus on what it is and how it can be accomplished. Its use by scholars and lawyers-simultaneously as a metaphor, mathematical threshold, and social scientific relationship-creates confusion, particularly within the legal discourse around affirmative action (see Garces and Jayakumar 2014; Terrell 2011 for more details). Recent invocations of the concept by the Supreme Court highlight the need for clarification. For example, in Grutter v. Bollinger, decided in 2003, the Court accepted the University of Michigan Law School's use of race as a "plus factor"3 in admissions decisions as a means to create a "critical mass" of minority4 students. In Justice O'Connor's majority opinion, which shaped the terms of the court's future debate about the constitutionality of affirmative action programs used by institutions of higher education, critical mass has less a concrete definition than a list of conditions it is intended to prevent. The Court fought over this nondefinition in both rounds of Fisher v. University of Texas at Austin, which provoked the aforementioned frustration on the part of Justices Scalia and Roberts. Critical mass-as it is used both in the physical and social sciences-implies a specific mathematical form, where, at a specific value of one variable (in this case proportion of minority students in the student body population), there will be a sudden and sustainable change in the state of another variable (in this case the number of students who feel isolated in their universities). …

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