For decades, education reform has focused on removing barriers that keep low-income students from reaching their potential. Among the notable efforts include expanding educational options for disadvantaged families, holding schools accountable for academic outcomes, and providing extra resources to educate children growing up in poverty.
Of these policy strands, school funding has received the most attention lately in Ohio, with the Cupp-Patterson plan driving much of the discussion. One of its provisions—a praiseworthy one at that—is to increase the amount of additional money allocated to districts and charter schools based on their enrollment of economically disadvantaged students. The effectiveness of the program hinges in part on the accurate identification of low-income students to ensure that the extra resources are allocated appropriately based on need.
But what if identifying economically disadvantaged students isn’t as easy as it sounds? A new report from the Ohio Department of Education (ODE) discusses current problems in spotting economically disadvantaged children. Importantly, it also outlines options that could yield more precise headcounts moving forward. Though it may sound wonky, identification issues are clearly of interest to lawmakers, as the report was issued in response to legislation that asked the agency to review its current method of identification and to investigate other states’ procedures and funding models.
First, let’s review the challenge. As many in education know, states, including Ohio, have traditionally flagged children as economically disadvantaged based on their eligibility for the free and reduced price lunch program (FRL). Students whose families earn at or below 130 percent of the federal poverty guidelines are allowed free meals, while those between 130 and 185 percent can receive reduced-priced ones (the income thresholds by household size are here). As the ODE report discusses, incomes are generally verified through the completion of an FRL application form or through “direct certification.” The latter method refers to an electronic process that matches students to their families’ participation in SNAP or TANF—federal programs that are open to those with incomes at or below 130 percent of the poverty guidelines.
For many years, tying economically disadvantaged status to FRL eligibility made sense. But in more recent times, the rise of the federal Community Eligibility Provision (CEP) has made this linkage problematic. Under CEP, qualifying districts or schools may provide all students free meals, regardless of whether they come from a low-income family. While this supports nutritional goals, avoids stigmatizing children, and reduces administrative burdens, hundreds of schools—and a number of entire school districts—now report 100 percent of their students as economically disadvantaged. In many of these schools, the universal classification now significantly overstates the actual number of low-income students.
Inflated counts have a deleterious impact on policy and public perceptions. In school finance, it means that CEP districts and charter schools are being somewhat “overfunded” relative to their actual needs based on economically disadvantaged enrollments. In a 2019 analysis, I estimated that roughly $50 to $65 million per year in state funding was being misallocated due to identification issues. Those funds might be better spent on other pressing educational needs, such as special-education or supporting other at-risk students (e.g., those who are homeless or in foster care). They also create problems in school accountability and reporting systems. When a district or school reports its students as 100 percent economically disadvantaged, it’s impossible to tell from state assessment data how well it’s serving the children who actually are low-income. Lastly, universal identification may lead to somewhat exaggerated conceptions of poverty in Ohio schools.
Considering these issues, the ODE report concludes: “Continuing to count all students in CEP schools and districts as economically disadvantaged is not a viable path forward; most states have or are planning to move away from this approach.” But how should Ohio address these problems?
While various options exist, the most promising avenue is to rely on direct certification—not FRL eligibility—to identify economically disadvantaged children. Such a move should come with one addition. Because direct certification identifies only students at or below 130 percent poverty (the SNAP and TANF cutoff), it wouldn’t reflect students with incomes between 130 and 185 percent poverty. One way to capture pupils in the higher income range (apart from paper forms) is to include Medicaid participation in the direct certification process, something that nineteen states have already done. In addition to capturing children in the higher income range—the threshold for Medicaid is 185 percent of poverty—it could also help identify poor students whose families don’t participate in SNAP or TANF. ODE does mention some legal and logistical hurdles in incorporating Medicaid into direct certification; if necessary, the governor or legislature should act quickly to clear any roadblocks.
ODE has statutory authority to define which students are economically disadvantaged, so it could make changes unilaterally. However, it would likely be prudent to gain more widespread support before making a shift. To that end, state lawmakers and local leaders need a clear understanding of the current problems and they need to recognize the consequences of misclassifying students.
At the same time, policymakers should also appreciate the benefits of more accurate headcounts. As Ohio debates school finance policy, for instance, lawmakers might consider leveraging direct certification information to drive even more dollars to the lowest income students by including a higher funding multiplier for children at or below the 130 percent income threshold (as suggested here and something that Minnesota does). But all this starts with reliable data. If Ohio can improve its identification methods, state and local policymakers will be able to more effectively target funding and interventions to the children who need the extra help.
