Decoding the data dichotomy: applying QuantCrit to understand racially conscience intersectional meta-analytic research

Abstract

ABSTRACT Our purpose is to proffer QuantCrit methodological approaches to interrogate notions of statistical practice by convention. We present two approaches to meta-analysis and mean effect size calculations for student achievement. The first approach is the conventional approach which applies between-group differences to calculate effect sizes representing achievement gaps. The second approach is commonly referred to as a single-group summary meta-analysis within the medical literature, which calculates within-group mean differences referred to here as student growth. In the conventional study, 39 independent effect sizes were combined to produce an overall mean difference effect size of −.85, which indicated that the average difference in performance between Black and White girl literacy was almost one standard deviation. The second approach summarized the mean differences from 33 effect sizes using the previous administration year as the comparison group. A statistically significant mean difference of .09 was observed for the QuantCrit approach. Our study contributes to the literature on racially just epistemologies by providing concurrent analyses of meta-analytic data to expose the unique features of QuantCrit that make it distinct from traditional approaches to Quantitative research.