Skip to main content

Using an Ecologists' Measure of Diversity in Higher Education

Diversity is a topic a lot of us in higher education think about and write about and work towards, and yet, we don't really have a common definition of what it means. At its most basic level, we simply talk about the percentage of our students who are non-white. And, of course, if you compare colleges today to those in the 1950's, this makes perfect sense, and allows us to give ourselves all a pat on the back.

But the success of Asian students over the past few decades has complicated this: While they are not white, their large numbers at the nation's most selective institutions, and performance on college admissions examinations, makes us occasionally shift the discussion to under-represented students of color, which today might include Native American and Alaska Natives, Latino or Hispanic students, African-American students, Asians who are Hawaiian or Pacific Islander, and students of two or more races or ethnicity. This of course causes us to wonder whether a student of mixed Asian/Caucasian ethnicity should count, and to remember that technically, Hispanic is not a race. It's all very confusing.

On top of that, there are institutions who serve large numbers of under-represented students (HBCUs, for instance) that are not very diverse in the clinical sense: Almost everyone enrolled in those institutions are African-American. How do we think about decribing diversity that makes sense to everyone?

One way to do it is to use a measure called Simpson's Diversity Index. You can read about it here if you'd like, but it essentially says that once you come up with a category and count the population, you can calculate the likelihood that choosing any two members at random presents a mismatch of type. For instance, at a college in Puerto Rico, if you randomly select two students, the chances they are of different ethnicities is probably very small: You'll usually get two Hispanic students. Go to Howard University, and odds are you'll select two African-American students on your trials. This translates into a lower Simpson's number. If you have a university that is truly more diverse in the ecological sense, you'll see that number go up.  All the numbers in the index are between zero and one.

Of course, it's short-sighted to measure diversity just on race or ethnicity, but it's the thing we have the best data on. We can add other elements into the mix, but since the data are pre-aggregated, we cannot break the groups into subgroups (for instance, wealthy White students vs. poor White students.) This would yield better insight.

Look below. The first view shows all four-year, public and private not-for-profit colleges and universities in the US, and their Simpson's Diversity Index as calculated from total undergradute enrollment in 2013 Fall. On the first view, the bars are colored by freshman admissions rate, with an interesting theory suggesting that if your admit rate is low, you could be more diverse if you really wanted to be. In the tool tip that pops up when you hover over a bar (like in the screenshot right below), you'll see the breakdown of enrollment by ethnicity.


And if you hover over several bars in the same range, you'll see you can get to similar numbers in very different ways. So, even among diverse institutions, there are very different student body mixes in play.

On the second tab, you'll see some element of economic diversity added in: Pell Grant eligibility as a color. The chart is a scatter of Simpson's and Admission rates.

One note: I calculated the index two ways, using as the base number only those with known ethnicity, and then those whose ethnicity was not listed.  I think the first number is probably a better tool, but I did include it the second in the tool if you're interested.

Do you see anything interesting here? I'd love to hear it.



Comments

Popular posts from this blog

Educational Attainment and the Presidential Elections

I've been fascinated for a while by the connection between political leanings and education: The correlation is so strong that I once suggested that perhaps Republicans were so anti-education because, in general, places with a higher percentage of bachelor's degree recipients were more likely to vote for Democrats. The 2024 presidential election puzzled a lot of us in higher education, and perhaps these charts will show you why: We work and probably hang around mostly people with college degrees (or higher).  Our perception is limited. With the 2024 election data just out , I thought I'd take a look at the last three elections and see if the pattern I noticed in 2016 and 2020 held.  Spoiler: It did, mostly. Before you dive into this, a couple of tips: Alaska's data is always reported in a funky way, so just ignore it here.  It's a small state (in population, that is) and it's very red.  It doesn't change the overall trends even if I could figure out how to c...

First-year student (freshman) migration, 2022

A new approach to freshman migration, which is always a popular post on Higher Ed Data Stories. If you're a regular reader, you can go right to the visualization and start interacting with it.  And I can't stress enough: You need to use the controls and click away to get the most from these visualizations. If you're new, this post focuses on one of the most interesting data elements in IPEDS: The geographic origins of first-year (freshman) students over time.  My data set includes institutions in the 50 states and DC.  It includes four-year public and four-year, private not-for-profits that participate in Title IV programs; and it includes traditional institutions using the Carnegie classification (Doctoral, Masters, Baccalaureate, and Special Focus Schools in business, engineering, and art/design. Data from other institutions is noisy and often unreliable, or (in the case of colleges in Puerto Rico, American Samoa, and other territories, often shows close to 100% of enro...

Education Levels in the US, by State and Attainment

Attainment has always been an interesting topic for me, every since I first got stunned into disbelief when I looked at the data over time.  Even looking at shorter periods can lead to some revelations that many don't make sense at first. Here is the latest data from NCES, published in the Digest of Education Statistics . Please note that this is for informational purposes only, and I've not even attempted to visualize the standard errors in this data, which vary from state-to-state.  There are four views year, all looking at educational attainment by state in 2012 and 2022.   The first shows data on a map: Choose the year, and choose the level of attainment.  Note that the top three categories can be confusing: BA means a Bachelor's degree only; Grad degree means at least a Master's (or higher, of course); and BA or more presumably combines those two.  Again, standard errors might mean the numbers don't always add up perfectly. The second shows the data o...