Testing a QuantCrit-Informed Approach to the Empirical Study of Race/Ethnicity and Child Maltreatment.

The past several years have seen calls from QuantCrit scholars to "disaggregate" samples into same-race groups. To date, however, there has been no attempt to empirically evaluate the benefits of disaggregation within a child welfare sample. Using a child maltreatment dataset derived from the National Child Abuse and Neglect Data System and Census data, we empirically evaluate the utility of employing sample disaggregation (in which separate records are created for White, Black and Latino populations in each county) as well as variable creation disaggregation (in which we avoid using "full county" economic measures, but instead employ "same race/ethnicity" measures). Using model fit and convergence with findings from individual-level studies as evaluation metrics, we find that both kinds of disaggregation are demonstrably beneficial. We recommend that sample and variable disaggregation be considered by any future researchers using national geographically structured child maltreatment data.