Q&A With Kyler Sherman-Wilkins

PRB spoke with him about his new curriculum that aims to bring a deeper understanding of the roles of race and ethnicity in demographic research and methods.

In commemoration of Black History Month, PRB is exploring changing racial demographics in the United States, their impact on society, and the structural barriers hindering racial equity.

This fall, PRB board member Kyler Sherman-Wilkins, assistant professor of sociology at Missouri State University, will introduce new curriculum that aims to bring a deeper understanding of the roles of race and ethnicity in demographic research and methods. PRB spoke with him about his goals for the program and future implications for the study of demography.

Q: How have definitions of race and ethnicity changed over time in the United States?
A: I’ll start with the quotation by James Baldwin that I use when I teach race to my undergrads at Missouri State: “No one was white before he/she came to America.” I think this quote completely captures the reality of race, which is: it is a social construct. What are key features of socially constructed ideas? They are given meaning by society, in some cases completely created by society; said meanings change over time; these meanings may change across place. And yet, these social constructions are quite real in their consequence.

When we consider race, we have the one-drop rule, which was codified into law among several states, though not everywhere. So you could literally be Black in one state, cross state lines, and then be considered white! Shifts in labeling Mexican migrants (white vs. non-white) were linked to quotas on the number of immigrants. In fact, German, Italian, and Irish immigrants were considered non-white when they arrived in this country. The changing definitions can make it difficult to study race effectively. As demographers who use race and who, arguably, are quite focused on measurement, these changes should give us pause.


Q: How have these changing definitions been reflected in the ways we’ve taught and used statistics, and even in the language we use to describe racial/ethnic disparities?
A: This is a good question. I don’t want to assume that people were taught statistics in a particular way. I was trained at Cornell University (class of 2011) and Pennsylvania State University (Ph.D. class of 2017). At both institutions, but particularly at Penn State where I took comprehensive exams in quantitative methods, I was trained extensively in statistics. There was never any real, critical discussion of measurement of race and ethnicity or the very nature of the methods being used (aside from the usual “are the statistical assumptions for this particular model met?). It wasn’t until last year that I became aware of the book White Methods, White Logic by Tukufu Zuberi and Eduardo Bonilla-Silva. I would wager to say that by and large, researchers are not well trained in this area, but that’s changing. In conversations I have with colleagues and peers it is becoming apparent that there’s an increased appetite to do this kind of work.

As it pertains to the language we use to describe these disparities, that’s an interesting question. We are starting to see studies that attempt to measure systemic racism, which I think is a very positive development.


Q: What was the impetus for developing your new curriculum at Missouri State University (MSU)?
A: The new curriculum largely stemmed from my own commitment to do more to dismantle systemic racism. As a demographer who identifies first and foremost as a teacher, I found that through my work as an undergraduate instructor, I could inspire the next generation of policymakers, researchers, and executives by focusing on anti-racism. I’ve been doing this type of work for a while now. In my substantive courses in social demography, aging, introductory sociology, and health disparities, I feel that students get a great sense that systemic racism is real and that there is real urgency in working to end it. And while I incorporate ideas like intersectionality and critical race theory into methods and statistics, it’s not nearly enough for my liking.

I proposed to develop this curriculum because of recent conversations I’d had with Missouri State’s sociology program coordinator. We had been discussing ways to revamp our curriculum to better meet the needs of our students and make them better prepared for an increasingly competitive job market. These discussions, combined with the university’s renewed interest to engage in real anti-racism work in light of the nation’s ongoing racial tensions, provided the perfect opportunity to receive institutional support for this grant. The added bonus? Perhaps I can get students to really enjoy methods and statistics if I can clearly and consistently link them to the important work of identifying and dismantling systemic racism.


Q: Can you share some of the core concepts underpinning the new curriculum? In other words, what are you trying to solve for?
A: I am quite realistic in my goal regarding this new curriculum. I do not expect it to fix the problem of racism. Nor do I expect that all students will suddenly come to love research methodology and statistics. Instead, I really want to expose students to ongoing debates that are happening now among social scientists regarding data and methods. How do we measure race? Ethnicity? How do we measure racism? Systemic racism? Can we truly model intersectionality quantitatively? Can we understand disparities in outcomes without constantly referring to a white reference group? I want to convey that the methods and statistics books teach the subjects in such a way that suggests this is how we do it and that’s that.

In reality, research is messy! Statistics are messy! The way we design studies and the way we analyze data are shaped by our paradigms. I am hoping that students begin operating through the lens provided by critical race theory.


Q:  What do you hope will be the impact of this initiative?
A: Ultimately, I’d like students to have a solid appreciation for the ways in which methods and statistics can be used to overturn racist systems. I want them to critique the very methods and statistics we use—again, through this critical race lens. The ultimate goal for this curriculum would be to serve as a model for methods and statistics classes in the social sciences.


Q: How will the new curriculum change the way you teach?
A: I don’t think this new curriculum will alter the way I teach, per se. When I teach methods and statistics, I focus on teaching students how to address issues of inequality by asking good research questions, crafting well-designed studies, and understanding basic statistical operations. Instead, I think this new curriculum will allow me to really go all in. By centering on anti-racism specifically, critical race theory and critical approaches to conventional methods will become the entrée as opposed to the side dish of the course.


Q: Do you see the new approach you’re implementing at MSU as a potential model for other universities?
A: Yes, though I will be the first to say that I am very much still a student and welcome the opportunity to collaborate with others in refining the curriculum. I’ve talked with Dr. Amy Thierry of Xavier University of Louisiana and Dr. Lauren Brown of San Diego State University on ways to incorporate anti-racism into methods and statistics classes. Not to mention my work with my colleague, Dr. Katie Hoegeman of Missouri State. In sum, this is a pilot program. We will roll out the class in Fall 2021. Once the kinks are worked out, it’s my hope that this course could serve as a model.


Q: How might using this approach to viewing statistics inform or shape public policy?
A: I think this approach will ultimately allow researchers to make a more compelling case for the existence of systemic racism, or at the very least, compel those decisionmakers to allow us to collect data in a more intentional way. When Ibrahim X. Kendi talks about anti-racism, he always begins with this idea of identifying racist policies and racist structures.


Q: What would success look like for this new program at MSU, and for this approach in general? What do you personally hope to learn?

A: Well, I hope to learn if we can ever truly make statistics and methods fun for undergrads! In all seriousness, I really just want to provide yet another opportunity to center the anti-racism perspective and anti-racism work into our curriculum. Hearing the urgency of anti-racism early and often is key, I think.


Q: What recommendations would you give to researchers for their own research, publications, and communications?
A: Read White Methods, White Logic! Think very carefully about your measures. When it comes to publications, we will often see in the limitations section that certain ideas or hypotheses could not be tested due to data availability. Well, collect the data! Or at least urge agencies to collect those data. Ultimately, question your assumptions. Convention is decided by those in power. We would do well to interrogate those conventions.