Critical Race Quantitative Intersectionality

How Administrative Data Collection and Analysis Can Better Reflect Racial and Ethnic Identities

“…This directly contradicts the argument that quantitative research is neutral, objective, and generalizable (Carbado & Roithmayr, 2014;Gillborn et al, 2018;Sablan, 2019). Critical race theorists argue that quantitative research cannot be as neutral and objective as is claimed because quantitative researchers make many decisions about measurement and analysis that remain as artifacts in their results (Covarrubias & Vélez, 2013;Zuberi & Bonilla-Silva, 2008). Quantitative research also tends to focus on R/E as an individual experience.…”

“…Galton was the founder of the eugenics movement and justified the movement by utilizing statistics to create the illusion that science backed up its tenets. To Galton, the measurability of race was for nefarious purposes-to prove his hypothesis that some races were superior to others (Covarrubias & Vélez, 2013;Sablan, 2019;Zuberi, 2001). The destruction that was caused by the eugenics movement, including genocide, mass sterilization, and pseudoscientifically based subjugation, and its continued legacy today in the White nationalism movement cannot be denied.…”

“…Scientists have now come to the consensus that race is not biological; it is socially constructed (Covarrubias & Vélez, 2013;Gillborn et al, 2018;Ladson-Billings, 2012). R/E has salience for individuals only to the extent that they can self-identify with a particular R/E identity or that others categorize them with one.…”

“…There has been little engagement between critical race theory and quantitative scholarship (Covarrubias & Vélez, 2013;Sablan, 2019). As Ladson-Billings (2012) wrote, education researchers have typically utilized R/E with a lack of attention or understanding that the categories they utilize are superficial and constructed using naïve understandings of class and race that are then imbued with deficit-oriented markers of inferiority and superiority.…”

“…Administrative data sets-information gathered about an entire population of individuals often collected by the government (Figlio et al, 2017)-tend to include a limited range of categories for R/E, and quantitative researchers often utilize even fewer of these categories in analysis (e.g., combining smaller R/E groups into an "other" category) to create parsimonious models (Denton & Deane, 2010;Ladson-Billings, 2012). At the same time, some critical race theorists, building on a theory that has been discussed for over a hundred years (DuBois, 1899;Jones, 1998), 1 suggest that quantitative analysis is unsuitable for studying inequality and outcomes based on R/E due to the history of the development of statistics in conjunction with racist movements like eugenics (Covarrubias & Vélez, 2013;Gillborn et al, 2018;Zuberi & Bonilla-Silva, 2008).…”