Social makeup and public school funding effort and distribution in the United States

Abstract It is well documented that states differ in their funding for public schools, both in terms of the fiscal effort that is undertaken and the progressivity with which funds are distributed (e.g., the extent to which more funds are allocated to school districts whose demographic profiles suggest greater need). Yet, much less is known about why different states have enacted such vastly different policies and financing systems. Likewise, the relationship between school funding effort and distribution to students’ achievement outcomes remains contested. In this study, states’ social makeups are examined as predictors of school funding effort and distribution. Measures of ethnic/racial and religious fractionalization (diversity) are included among these measures, thereby extending fractionalization theory into the realm of United States PK-12 education. In this study, the relationship between states’ funding effort and distribution is also evaluated, in combination with student demographic and teacher/systemic factors, upon state-level student achievement outcomes. A number of findings are reported and discussed. States’ public school funding effort was significantly predicted by certain state-level measures of social makeup. Positive predictors included the proportion of Catholics and the extent of voter liberalism in a state. Negative predictors included: the proportion of Evangelical Protestants; the extent of strong religiosity; and the extent of child poverty in a state. School funding distribution proved to be less predictable on the basis of the variables studied, although religious fractionalization served as a significant negative predictor, such that more religiously diverse states tended to be less progressive in their public funding distribution. State-level student achievement (eighth grade, in reading and math) was also evaluated as predicted by a small set state-level student, teacher/systemic, and school funding indicators. In reading, school funding distribution emerged as a significant predictor while controlling for all other factors, such that more progressive funding was predictive of higher student achievement. Also, a student demographic indicator (the proportion of students eligible for free/reduced price lunch) emerged as a strong and negative predictor (as the proportion of eligible students increased, state-level achievement decreased). In math, school funding distribution served as a marginal positive predictor of achievement, while the free/reduced price lunch measure was a highly significant negative predictor. In the final chapter, implications were considered and a number of recommendations—from the perspective of numerous stakeholders—were provided. As well, potential directions for future research were suggested. The findings of this study, it is hoped, will contribute to the scholarly school funding and social diversity/fractionalization literature while providing additional impetus to constituents and policymakers to pursue socially just funding policies