Over the last decade or so, much has been made about the role of race-based admissions policies. In 2003, the United States Supreme Court handed down a pair of cases involving race-based admissions schemes at the University of Michigan. Grutter v. Bollinger, 539 U.S. 306 (2003); Gratz v. Bollinger, 539 U.S. 244 (2003). In this pair of decisions, the High Court came down generally against racial preferences, but maintained that race may be considered, so long as it is done on an individualized basis that allows for some discretion, such as the one that the Law School employed.
So what of minorities in law school? I'm sorry, "underrepresented minorities", since the supposed white racism doesn't oppress Asian-Americans as much as it does blacks or Latinos.
One would have to be very prejudiced, indeed, to believe that blacks and Latinos do not deserve a shot at a good legal education. And, undoubtedly, diversity may be a reasonable or legitimate interest for a law school. But what if the pursuit of "diversity" damages individuals by forcing perfectly bright young men and women in direct competition with veritable geniuses? In an industry which so highly prizes intellectual acumen, does the color of a student's skin matter more than his ability to keep up?
Vikram Amar and Richard H. Sander's attempts to answer this question of "mismatch", by studying data from the State Bar of California, were recently halted by interested parties. Amar and Sander explain what they're trying to study in Los Angeles Times article:
IMAGINE, FOR A MOMENT, that a program designed to aid disadvantaged students might, instead, be seriously undermining their performance. Imagine that the schools administering the programs were told that the programs might be having this boomerang effect -- but that no one investigated further because the programs were so popular and the prospect of change was so politically controversial.
Now imagine that an agency had collected enough information on student performance that it might, by carefully studying or releasing the data, illuminate both the problem and the possible solutions. What should the agency do?
Given the richness of the data and the intensity of interest in the mismatch issue, it was not surprising that a blue-ribbon panel of diverse scholars (including both of us) approached the bar with a detailed proposal to study its data, backed by full funding and letters of support from dozens of scholars, law school deans and public officials.
But although the California bar was initially enthusiastic, one of its committees recently rejected the study proposal. Its stated reasons are implausible; it expressed concern, for example, about disclosing confidential information; but the proposed study includes the bar's own in-house expert, thus mooting the need for any data release.
It seems more probable that the bar, like many law schools, is simply queasy about touching a delicate area. The Society of American Law Teachers captured this sentiment in a letter it sent the California bar, cautioning it against releasing the information because, it said, "SALT is concerned about the potential negative impacts upon minority bar applicants and attorneys" who "already face a variety of misperceptions about their qualifications." By this reasoning, no one should seriously attempt to get to the bottom of racial disparities in bar performance because the attempt itself would make more people aware of the disparities!
A generation ago, the late U.S. Supreme Court Justice Harry Blackmun wrote in Regents of UC vs. Bakke, the famous UC Davis affirmative action case, that for society to get beyond race, the government must first take account of race. Last summer, Chief Justice John G. Roberts Jr. countered that the way to get beyond racial discrimination was for government to stop using race as a consideration. We suspect both justices would agree that however one feels about race-conscious school admissions policies, it is vital that we do our best to understand the effects of those policies, and doing that requires more, not less, analysis of real-world data.
Indeed! Let us understand how things play out in the real world so that we can find the best (and least discriminating) solutions to these questions.
(Hat-tip: Mad Minerva)