One of the big education stories of the year was the Supreme Court case of Fisher v.
University of Texas at Austin, in which a young woman named Abigail Fisher sued the school claiming she was denied admission in 2008 because of her skin color. Here’s a look at the case from Michael J. Feuer, dean and professor at the Graduate School of Education and Human Development at The George Washington University. President-elect of the National Academy of Education, he is the author of “Moderating the Debate: Rationality and the Promise of American Education.” This appeared on the Harvard Education Publishing website.
By Michael J. Feuer
One of the rhetorical puzzles that arose during Supreme Court arguments in the Fisher case, in which a white student challenges the race-conscious admissions system at the University of Texas, poses a “catch-22” that could spell the end of affirmative action. The problem, simplified, is that using numerical targets is illegal, but not using them might make the admissions process appear unacceptably vague or unfair.
This is not the first time the Court has struggled with fairness and legality of college admissions. In the landmark Grutter case of 2003, the Court affirmed that diversity is a compelling educational value and that race is allowable as one of many criteria used to assemble a “critical mass” of minority students. The problem, as Justice Scalia somewhat cheerfully observed, is that “critical mass,” a term borrowed from physics, usually connotes something numerical. But if the university sets a quantitative target it violates the Court’s longstanding opposition to goals and quotas; and without numerical targets, as Chief Justice Roberts stressed, it is hard to know if the admissions policy is working and if the law is being obeyed.
The lawyer for Ms. Fisher exploited this logic, while his opponent, who had anticipated the trap, argued valiantly that “critical mass” does not necessarily require a precise numerical definition. Scalia’s wry suggestion that we should therefore substitute the word “cloud” for “critical mass” brought loud laughter in the courtroom but raises a serious question: Can public policy ever be oriented to goals that sound numerical but that elude quantitative precision?
Perhaps the justices who are bothered by this puzzle will consider precedent. Take, for example, the proposition that “all men [sic] are created equal,” a cornerstone of our democracy codified in the constitution. Even if “all” implies a clear numerical target, i.e., 100% of the population, there is still the thorny question of how to measure “equality” (and inequality). It is not a new problem in the history of constitutional jurisprudence, and is one that has for many decades been a focus among empirical economists and sociologists. The “Gini coefficient,” for example, is widely used to measure and compare inequality within and across nations, but it is neither perfect nor universally accepted. Still, the concept is central in debates over significant social and economic policies – everything from taxation to health care to education – that pursue the goal of equal opportunity, even in the absence of airtight definitions of “equality” and “opportunity.” Would we scrap the 14th amendment’s guarantee of “equal protection” and give up on policies that strive toward that goal only because of ambiguity over the numerical definition of equality?
A related example is the measurement of poverty. Although political differences prevent consensus about whether government involvement is necessary to reduce poverty, there is widespread agreement that society would be better off with less of it. In the US today roughly 22% of children live below the poverty line, a depressing statistic that almost everyone would like to see changed even if there is disagreement over exactly where and how that line should be drawn. To insist on acceptance of a specific target, say 18% or 5%, as the prerequisite to action, would be absurd; and it would raise suspicions that those insisting on a numerical target are perhaps opposed to the underlying principle of antipoverty policy as a legitimate role of government. Fortunately, our society seems to understand intuitively the need to reduce poverty, whether through government or other means, and we rely on the best available measures – imperfect as they may be – to monitor progress.
A third example is unemployment. Economists have long debated whether there is a “natural rate,” a level below which it is neither likely nor necessary for a modern economy to aspire. But this arcane argument is immaterial in policy debates that rely on labor market trends. Would a state’s efforts to reduce unemployment be challenged because the state is unable to articulate a precise numerical target? Measurement of employment and unemployment is a complicated matter – despite considerable progress in economic methodology we still don’t have anything like a dipstick to check the level of oil in a car – and setting a specific target would be costly, controversial, and ultimately unsatisfying. Still, those realities do not undermine the moral or legal or economic basis for finding ways to reduce unemployment – and for using the best available measures as benchmarks of success.
Judging from their repeated hammering on how the term “critical mass” is defined, the more conservative justices may have signaled their readiness to overturn key parts of Grutter. It is important to note, though, that even the justices inclined to reject Ms. Fisher’s claim are unlikely to tolerate a completely arbitrary or capricious approach. It is true that educational judgments require attention to complex aspects of learning that are not easily quantified; but that doesn’t mean the only choice is to leave standards of diversity up to the complete discretion of admissions officers.
On this point Justice Breyer argued that countless universities are developing innovative approaches to the “critical mass” problem that are neither arbitrary nor excessively numerical. Maybe they haven’t been sufficiently transparent in how their diversity programs work (and strangely, almost no evidence about exactly how the program works at the University of Texas was considered by the trial court, which left the Supreme Court with little to go on aside from data included in numerous amicus briefs). In any case, though, it would be sad if the Court undermined universities’ efforts only because the “Catch-22” exposed by the Fisher case doesn’t have a perfectly satisfying solution. The simple truth is that most questions in education don’t necessarily have optimal answers, which is why I have argued elsewhere for a greater appreciation of the necessity for compromise and the acceptance of reasonably good rather than perfect solutions. Justice Sandra Day O’Connor, whose presence in the Court during oral arguments served as a poignant reminder, had shaped the wise and reasonable – albeit imperfect – compromise in Grutter. That ruling should now be reaffirmed.