17  Open and Reproducible Spatial Analyses of Educational Opportunity

In this analysis we provide a detailed walkthrough of powerful functionality provided by the geosnap and PySAL software packages, a brief introduction to exploratory spatial data analysis, and an analysis of the geography of educational opportunity in California. Although the “geography of opportunity” is a familiar and oft-used phrase in both scientific and policy arenas, the formal analysis of spatially explicit relationships in inequality remains unfortunately scarce.

The reason for this dearth of research is twofold; first, many social scientists are unfamiliar with spatial analysis and the critical importance of considering geographic relationships when conducting analyses like regression modeling. Second, the tools necessary for conducting spatial analyses have traditionally been expensive to obtain and labor-intensive to learn. This document serves as a proof-of-concept that further work in educational inequality can and should adopt a more rigorous treatment of spatial relationships. By providing all the code necessary to replicate this analysis, we hope to encourage other researchers to adopt a perspective rooted in open geographical science.