Measuring Diversity

This week I’m going to use the blogger’s best friend and repost the interesting blogs of others with commentary.

The Chronicle of Higher Education hosts a very interesting data points blog that recently ran a three part series on measuring diversity.

The first post began by looking at the impact of of Michigan’s ban on affirmative action on minority enrollment but ended by noting that while enrollment of African-Americans and Hispanics had declined, diversity appeared to be stable.  How can this apparent paradox be resolved?  The answer has to do with measurement and the interaction of measurement with culture.

One part of the answer has to do with the part of the population that does not report race.  The size of this population and its racial composition appear to be related to the existence of race-based affirmative action.  When such affirmative action exists, whites are less likely to report race; when it does not exist, other groups are less likely to report race.  This makes it very difficult to determine how exactly changes like those in Michigan affect enrollments, since the change not only affects enrollments but also whether individuals report their race at all.

It also matters how people report their race and/or how they are allowed/encouraged to report their race.  In particular it matters whether people have the opportunity to report more than one race. The second post discusses how the US Department of Education measures race.  A key point in this discussion is that while the census began allowing respondents to identify with multiple races in 2000, the Department of Education did not do so until 2009.  This makes it hard to evaluate changes in racial composition of students before and after this change.  The apparent decline in African-American and Hispanic students may result from multiracial students now reporting as multiracial rather than selecting a single race category.

As a sociologist, I must point out that race is a social construct and not biologically determinable or verifiable.  If you say you are Asian, I cannot give you any objective psychological, biological or other kind of test to confirm or falsify your statement.  As a sociologist, I would argue that the same is true of the male/female gender binary.  The futility of the biological approach to determining a binary gender scheme is revealed in the very attempts to find a biologically determined gender binary.  This comes up most often in the context of sports, which often seeks to enforce rigid gender segregation.  The difficulty of determining sex for the purposes of classifying competitors demonstrates the point that sex  is no simple biological fact. (In the 48 hours since I drafted this blog another major case of gender testing in sports has been in the news.)

The lack of biological correlates does not mean that race and gender are not “real.”  As the sociologist W.I. Thomas famously said “If men [sic] define situations as real, they are real in their consequences.”  Race and gender–and the assumption that these are biological–matter in our lives because we act as if they are real.

The third post looks at how diversity is measured, comparing a measure called the diversity index to more traditional comparisons to local demographics.  EvCC has typically used comparisons to local demographics although, as the blog post indicates, this can be more complicated than it at first seems.  EvCC also faces the same challenges in categorization described in these articles.  Some students do not report their race.  We have difficulties with data over time because like other institutions we now ask people if they are multiracial when previously we did not.



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