Date of Award
Master of Arts
Marcus L. Britton
Kent Redding, William Velez
Milwaukee Metropolitan Statistical Area, Ordered Logistic Regression, Racial/Ethnic Inequality, School Accountability, School Segregation, Socioeconomic Inequality
This thesis examines the extent to which one can predict school accountability ratings based only on the demographic make-up of their student bodies, especially their racial/ethnic composition. Analyses were conducted on all elementary schools in the Milwaukee metropolitan region using data from the National Center for Education Statistics, the Wisconsin Department of Public Instruction, and the U.S. Department of Education. Ordered logistic regression analyses showed that one can largely predict accountability ratings assigned to schools by state report cards without knowing anything about various measures of improvement over time. Using only the racial/ethnic and socioeconomic composition of schools’ students, the model correctly predicted schools’ ranking more than 60 percent of the time. Simulation results indicated that predominately white schools have almost a 95 percent predicted chance of being ranked as meeting or exceeding expectations, while predominately black schools have more than a 95 percent predicted chance of being ranked as meeting few expectations or failing to meet expectations. These findings raise serious questions about the report card system. After decades of educational reform that have promised equal education to all students, accountability systems appear to reify inequality rather than effectively measure how schools’ serve their student populations.
Miner, Michael A., "Separate and Unequal: To What Extent Do Student Demographic Characteristics Predict School Accountability Ratings?" (2017). Theses and Dissertations. 1670.