A Response to Reynolds, Zetlin, and Wang's “20/20 Analysis: Taking a Close Look at the Margins”:

Reynolds, Zetlin, and Wang (1993) have proposed an innovative and thought-provoking approach to allocating special services, which they call "20/20 Analysis." We commend the authors for their attempt to redesign the existing system; clearly, the system's inherent problems necessitate radical reform (Gartner & Lipsky, 1987). Perhaps the most important contribution of Reynolds et al. is that they have appropriately refocused the discussion from classification of students to eligibility for service. By rejecting labels and classification systems, the authors have simplified a complex and seriously flawed system. Although the simplicity of their proposal is initially appealing, careful analysis of the 20/20 model reveals that it may inadvertently systematize many of the inequities plaguing the current system. INEQUITIES IN ELIGIBILITY One such inequity concerns labeling and eligibility. In the absence of widely agreed-on definitions, educators do not base labeling and eligibility decisions solely on objective criteria, but depend on local norms. In other words, students found eligible in one geographic area may not be found eligible in another region (Ysseldyke, Algozzine, & Thurlow, 1992). In the 20/20 method, a school's cutoff score (i.e., the score below or above which 20% of the children will fall) is intentionally determined by that school's norms. As the following example shows, basing cutoffs on local norms, as proposed by Reynolds et al., will serve to perpetuate current inequities. Urban/Suburban Differences In their description of 20/20 Analysis, Reynolds et al. applied the method to two highly similar inner-city schools, thereby masking an inequity that would occur if the 20/20 method were applied in schools serving different populations. Their data indicate that students in the lower 20% groups in the two inner-city schools scored below the 6th and 10th percentiles, respectively, on national norms. Students in the higher 20% groups scored above the 58th percentlie in one school and above the 62nd percentlie in the other. By contrast, we examined reading scores in two dissimilar schools: a suburban school and an innercity school in the New York area. In the suburban school, students in the bottom 20% scored below the 49th percentile, whereas students in the innercity school scored below the 16th percentile. Students in the top 20% in the suburban school scored above the 88th percentile and, in the innercity school, above the 57th percentile. Thus, using the 20/20 method, educators in the suburban school might find a student at the 25th percentile eligible for remedial services; but educators at the inner-city school might find the same student ineligible. Our data indicate that implementation of the proposed 20/20 method would deny children in inner-city schools access to services that their suburban counterparts would receive. Further, because of differences in the racial distribution and economic conditions of large cities and suburban towns, implementation of the 20/20 method would exacerbate existing inequities. Intraindividual Differences We are also concerned about the exclusive use of a single dimension of learning to determine eligibility in the proposed plan. Different children would be deemed eligible, depending on the dimension selected. For example, in the inner-city school we studied, one third of the students who were in the bottom 20% in reading were not in the bottom 20% in mathematics. Conversely, an equal number of students were in the bottom 20% in mathematics, but not in reading. The unidimensionality of the 20/20 model ignores intraindividual differences among learners and overlooks students with great needs---or superior abilities--in nonassessed areas. Persisting Inequities A major argument presented by Reynolds et al. …