From the Editorial Board:Using Quantitative Methods to Answer Critical Questions Caitlin E. Kearney On September 12, 2019, during a debate among Democratic presidential hopefuls, Kamala Harris cited a study on teacher-student race matching. If a Black child has one Black teacher by the end of third grade, the study found, they are 13% more likely to go to college; if that child has two Black teachers before the end of third grade, they are 32% more likely to attend college (Gershenson et al, 2018). Harris cited these statistics to highlight the need for investment in Historically Black Colleges and Universities (HBCUs) and their teacher training programs. In an instant, an academic study of Black teachers reached an audience of millions and, in doing so, Harris proved the power of quantitative methods in shaping a policy debate. One measure of the impact of academic research, although imperfect, is the salience of findings in policy debates. In riding the wave of the evidence-based policy movement, rigorous quantitative studies are often prioritized over qualitative studies. In practice, qualitative and quantitative methodologies often work together in a given subfield. Decades of qualitative literature on the impacts of Black teachers—and damages of an overwhelmingly white teaching force on student-level outcomes, particularly for Black children—provided the theoretical framework for Gershenson and colleagues (e.g., Foster, 1990; Irvine, 1989; Kelly, 2010; Ladson-Billings, 2016; Steele, 1997; Tyson, 2003). Yet the conciseness and seeming finality of statistical findings present in quantitative studies often make the findings stick; policymakers are more convinced by compelling numbers than narrative explanations (Branscomb, 2004). Leveraging data from the Tennessee Student/Teacher Achievement Ratio (STAR) class size experiment and state administrative data from North Carolina, Gershenson and colleagues (2018) employed quasi-experimental economic methods to suggest a causal link between exposure to Black teachers and educational attainment for Black students. Their conclusion was striking. The vestiges of the methodological paradigm wars are still very much with us. The goal of this piece is not to resurrect the tiresome battle between quantitative and qualitative methods, but rather to examine the use of quantitative methods to answer critical policy relevant questions. Quantitative Methods and Education Policy Education research investigates a variety of overlapping issues such as teaching and learning, and the political, economic, organizational, and social contexts in which they occur. Coleman (1976) posits that all education research is inherently policy relevant. Others define education policy research more narrowly, arguing that it must analyze policies by defining specific problems, interrogating alternatives, confronting tradeoffs, and utilizing evidence to make a recommendation (e.g., Bardach, 2012). Over the last several decades, there have been growing calls for education research [End Page 195] to be both policy relevant and empirically rigorous (Institute of Education Sciences (IES), 2013; Shavelson & Towne, 2002). Most policy briefs from federal agencies cite quantitative research, and many name particular quantitative methods as the "gold standard" (IES, 2003). Quantitative education researchers have heavily borrowed from economics over the last several decades. Economic analytical frameworks such as the education production function, which draws on human capital theory, predominate in education policy debates. Similarly, numerous quantitative methodologies within education policy research derive from quasi-experimental designs developed by econometricians. Mounting pressure for organizations to be held accountable for their role in societal inequities undergirds much of the aggressive promotion for rigorous research. Landmark legislation, such as the No Child Left Behind Act (2002) and the Education Sciences Reform Act (2002), explicitly endorse scientific research as paths to address intractable social problems. The full history of quantitative methods, however, must be told. There is more to the story than more rigorous methodology; the history of quantitative methods is inextricably intertwined with our nation's past and present culture of white supremacy and cisheteropatriarchy. Early usage of quantitative methods, such as intelligence quotient (IQ) tests and The Bell Curve (Herrnstein & Murray, 1994), constructed and reinforced systems of oppression. The rise of quantitative methods in education is often characterized as a shift toward objectivity and the onset of trustworthy research; however, embracing such methodologies comes with a host of hidden ideological assumptions rendered invisible by claims of neutrality (Davidson, 2018). Others have gone even further...