The nascent field of Quantitative Critical Race Theory, or QuantCrit, applies the insights of Critical Race Theory to improve the use of statistical data in social research. And it is ripe for "innovation, experimentation, and exploration," according to a new paper by Wendy Castillo, a lecturer of public and international affairs. 

The paper, "Transforming the future of quantitative educational research: a systematic review of enacting QuantCrit," was published in the journal Race Ethnicity and Education in August and was co-authored by Nathan Babb, who received his Master in Public Affairs from the School of Public and International Affairs in 2021.

The paper explores the early scholarship within the field of QuantCrit, which was developed by David Gillborn, the editor-in-chief of Race Ethnicity and Education and a professor emeritus at the University of Birmingham. CRT, which was developed by the civil rights advocate and law professor Derrick Bell, has captured the attention of the political right in recent years and ignited so-called "culture wars" over what children should be taught in schools.

"CRT – the word and the theory – has become co-opted to mean a lot of different things, and it's been misused and misinterpreted," says Castillo. "My definition of it is that it is a lens to examine how institutions, policies, and systems have produced inequitable outcomes by race."

The five tenets of QuantCrit include recognizing the centrality of racism and how it is "intertwined in the fabric of society"; acknowledging that numbers are not neutral since there can be a lack of objectivity in how data is collected; understanding that categories of race are not natural or given and that race can be socially constructed; conceding that data cannot speak for itself because biased people need to analyze it; and orienting the focus of research around social justice and equity.

Though CRT was labeled in the 1980s and QuantCrit was coined in the 2010s, neither theory is particularly new: Castillo says the study and use of data for social justice can be traced back to W.E.B. Du Bois in the early 1900s. The idea to use “numbers for justice” has mostly flown under the radar, but QuantCrit’s purpose is not to be under-appreciated.

"What QuantCrit has done," says Castillo, "is to give people verbiage to be able to say that data is biased and data is not objective, and figure out how to move forward to use it for justice."

After Castillo first came across Gillborn's work, she says, she sent him an email, declaring his theory "the greatest thing since sliced bread." They then paired up to write a paper together, entitled "How to 'QuantCrit:' Practices and Questions for Education Data Researchers and Users," which was published by EdWorkingPaper in September.

Castillo's two recent papers are similar in their purpose: "How to 'QuantCrit'" lays out the tenets of the theory and how it should be put to work, while "Transforming the future of quantitative educational research" analyzes how QuantCrit has actually been used in practice.

Castillo says she was inspired to write her paper with Babb "because people say, 'Well, I don't know what that looks like.'" So they analyzed all of the empirical education studies published from 2010 through 2022 that explicitly applied QuantCrit – 27 papers – and highlighted the best practices and common pitfalls within the field of study.

"It's such a new field, and so many new articles are coming out in the last couple of years, so I felt like it would be just a good contribution to the field to put these examples forward," Castillo says. "I wanted other scholars to be able to draw from everybody, and I like to uplift good, equitable work."

What followed in the paper were examples of how authors went about conducting their research and presenting their findings in line with the basic principles of QuantCrit.

The first example was including a "positionality statement" in which the authors of a given paper highlight their identities and reflect on their biases. In Castillo's own positionality statement, she listed her identities as a Latina and first-generation college student who grew up as the daughter of undocumented immigrants in a working-class household, before reflecting on the impact of those identifying features.

"She understands that she cannot separate her life experiences because they have influenced her outlook on the topics she researches," Castillo wrote. "She is proud of her bias to use data to help Black and Brown communities. As an early adopter and scholar of QuantCrit, she also acknowledges that she has a bias of holding others to a high bar when it comes to doing research related to quantitative data and race. Additionally, as a lecturer in econometrics and statistics at a prestigious institution, she understands the privileges and assumptions that are associated with these affiliations."

Castillo says that calling attention to biases can help illuminate how the data is being read and interpreted.

The second example Castillo and Babb highlighted in the paper focused on community input, and the importance of conducting research within a community rather than as an outsider looking in. "Giving communities a voice in creating and shaping that data is essential for using data with a social justice orientation," they wrote.

The third example centered on collecting racial and ethnic data that is accurate, intersectional, and consistent over time, and the final example explored rhetoric about centering whiteness in research. The paper concluded by examining some of the innovative approaches Castillo and Babb encountered when it came to how researchers identified variables in their research, conducted measurements, and interpreted their findings.

Castillo says she sees this paper as a "starting point to get the conversation going," and she notes there is already a need to write another similar paper since many new and applicable papers have been published between the time when she finished writing the paper and submitted it for publication in January to when it was actually published in August.

As the scholarship in the field continues to grow and develop, Castillo says she's curious to see what processes are "triangulated and validated," and how this kind of research will evolve to produce better, more equitable results while also eliminating harm.

"This lens is critical to public policy," Castillo says. "What I want people to take from this [paper] is: you can start doing these things [in your research], like, tomorrow.

"I hope that it's inspiring in some way," she adds.