It is Martin Luther King Day and as I paused to reflect on the meaning of the day, I noticed yet another challenge to admissions policies that factor in race has been launched. Inside Higher Ed reported that Students for Fair Admissions (the same group suing Harvard) is suing University of North Carolina at Chapel Hill over differential admissions standards based on race. In part, they note that the ACT scores required of white and Asian students are higher than those required of African-American and Latino students. Sigh.
This is just one of the many challenges to affirmative action that have taken place over the years. Before we focused on differences in test scores, folks complained about quotas. I recall discussing this in classes 20 years ago. Many of my students were angered by the very notion of a quota. It seemed to fly in the face of their assumptions about merit and equality. At that time, I had a Jamaican-American student who raised her hand and stated simply: “So, you’re upset about 2% of the spots being saved for me. What about the 98% being saved for you?” This simple argument revealed the difference between equity and equality.
Twenty years later and we’re still struggling with those distinctions. Deep in the values of the United States is a notion that upward mobility is within our grasp if we only work for it. But it is hard for us to grasp the difference in levels of work required depending on where we start on that economic ladder.
Add to this the discomfort we feel about racial categories. We have managed to make them complicated and multi-dimensional, which is to the good, and these efforts have left many people feeling that we should be moving away from simplistic categories. Our discomfort may be a sign of progress, but the experiences and opportunities we have are still tied up in the biases we carry toward people who do not look the same as us. And those biases still skew towards those who aren’t white.
Still, sorting admissions by race nags at us. It doesn’t feel quite right. So, how about we shift the conversation. Since K-12 environments have a very strong impact on our likelihood of attending college, why not adjust the admissions process with that in mind? Instead of looking at race, let’s adjust SAT (or ACT) scores based on K-12 context.
Here are three things that are regularly reported on K-12 school districts in CT that could be used to adjust SAT scores: Percent of students who qualify for free lunch, percent of students who are English Language Learners, and the percent of students who attend college after graduation. Districts with higher numbers of students who qualify for free lunch and who are English Language Learners tend to have lower average SAT scores than districts with less need in these areas. These two variables are associated with all sorts of barriers to achieving high SAT scores. ELL students, for example, usually don’t have family members who can help with homework because folks at home don’t speak English. Students who qualify for free lunch rarely have access to summers at academic camps, or tutors, etc. Districts addressing these needs are likely to have fewer resources available for the niceties of field trips, SAT test-prep classes, or robust academic extra-curriculars. These two issues are then likely to impact the percent of graduates in a district that attend college.
Here is my proposed adjustment. Take the difference between a perfect SAT score (1600) and the district average. Multiply that difference first by the percentage of students who receive free lunch and then by the percentage who are English Language Learners. Then determine the percentage of students who don’t attend college from the district and multiply that by the same number as the other two variables. Add these three numbers to the SAT scores for an equity adjustment.
Here’s how it looks.
|District 1||District 2||District 3|
|Base combined SAT Scores||968||1076||1227|
|Difference from 1600||632||524||373|
|District ELL Percentage||14.4||1.5||0|
|District Free Lunch Percentage||44.3||21.2||1.8|
|College Attendance Percentage||69.9||79||90.7|
|Free Lunch Adjustment||280||111||7|
|College attendance adjustment||190||110||37|
|Total Points Added||561||229||44|
|Adjusted Average SAT Score||1529||1305||1271|
Now, I’m sure it won’t surprise you that District 1 is more ethnically diverse than District 3 and obviously the free lunch numbers point to families in need of support. But, the focus here is on a holistic experience that results from being in a less advantaged school district. As a general rule, all students in District 1 will have less opportunity to participate in the enrichment opportunities that lead to high SAT scores, so everyone attending that school should be awarded the additional points.
This takes race out of the admissions questions while at the same time addressing the structural racism that results from economic segregation everywhere.
We could go farther. For example, only 16% of the students in District 1 will have successfully earn AP credit, 70% of the students in District 3 will. Should we make an adjustment? Students from poor families will not be able to go to summer enrichment programs because they will be working. Should we make an adjustment? Students attending schools in neighborhoods with high levels of crime will have difficulty fully focusing on their studies because they are dealing with trauma. Should we make an adjustment? And there are many more variables we might consider.
But if we just start with these three, perhaps we can achieve what we hoped to achieve when we starting asking questions about our admissions policies in the first place. Because equality will never be reached without some level of equity.
2 thoughts on “Adjusting for Equity”
Interesting proposal! Not only it takes the thorny race issue out of the debate, the adjustment is also dynamic.The most disadvantaged variable will be weighted the most. When a district’s performance improves overall or in any factor, the added score will be adjusted lower. No district or factor enjoys a fixed favorable treatment.
Exactly. I am sure there are better ways to calculate things like this, but the central idea is to repair the results of structural issues (funding, poverty, segregation) that get in the way of our standardized measures. Not that I love those measures, but with these adjustments they might be made more fair.