Intradistrict equity: A proposed methodology for resource allocation

The purpose of this study was to develop an intradistrict allocation funding model. An extension of research methodology using an index-of-need as a proxy for the magnitude of educational need, this study identified indicators-of-need from the research literature and as present in 31 middle schools in Clark County School District, Las Vegas, Nevada. A neural net analysis categorized schools based on their indicator-of-need variables. Six variables were the basis for the index development: student poverty level, transiency rate, limited English proficiency (LEP) student enrollment, special education student enrollment, percentage of minority enrollment, and percentage of students eligible for Title I services. Schools were clustered in four groups based on the Kohonen neural network analysis. A backpropagation network analysis evaluated the categories to produce a hierarchical index of schools ranked from lowest to highest need. Simulated budget and staffing allocations were based on the derived index and the redistributive effects analyzed. The index-based methodology provided a viable methodology for intradistrict allocation of resources based on a vertical equity standard