Background: Quantitative methods used in social science research draw from frameworks that (a) abstract constructs and separate them from relevant knowledges that are not easily quantifiable, and (b) reify deficit orientations in support of racial oppression (Strunk & Hoover, 2019; Zuberi, 2001; Zuberi & Bonilla-Silva, 2008). This paper presents a simple, methodological tool to support researchers in the critical interpretation of quantitative findings associated with racialized identities1. In this proposal, I adapt and extend Gillborn et al.'s (2018) five QuantCrit tenets while also drawing on Critical Race Mixed Methodology (DeCuir-Gunby, 2020) as well as Critical Race Quantitative Intersectionality (Covarrubias & Velez, 2013) to develop the REASN Framework. Purpose: This paper proposes a complementary method to interpret the findings and interrogate the processes and contexts of quantitative work the REASN Framework. The REASN Framework requires researchers to engage in five iterative actions: Reflect on the role of race; Engage measures and methods; Assess findings; Seek insight; and Name the known. These processes are engaged in an iterative process of interrogation and assessment. During the interpretive process, researchers should seek insight by deepen their understanding of contextual factors in their study and theorize possible mechanisms of how White supremacy is operationalized within the data, findings, and research questions with an openness to revision. Researchers need to be open to revisiting the data and research questions, pursuing additional relevant research literature, and reflecting personal experience to frame and interpret findings. The REASN Framework is less of a specific method and more a holistic process to reduce the presence of White supremacy in quantitative research. This process concludes with a focus on communication practices that emphasize asset-based approaches or contextualize findings within systems of harm. Practice: The REASN Framework is an iterative tool to interrogate, assess, and communicate the findings of the quantitative analysis using interpretivist perspectives informed by Critical Race Theory and QuantCrit research. This framework is intended to reduce the potential for harm associated with quantitative research on racialized identities. A sample outline of the process is displayed in Figure 1. Data Collection and Analysis: An example study using public-use data from the High School Longitudinal Study of 2009 will be provided to illuminate the use of the REASN in practice. This study will examine students' racialized identities and academic achievement in STEM as measured by grade point average. ["Figure 1: Example study graphic organizer" omitted.]