Project Details

Abstract

Several mechanisms exist for identifying sites for upgrading transportation infrastructure for non-emergency maintenance. One key element is the complaints that citizens make about broken or missing features using the 311-service call system. Researchers argue, however, that some locations with less influence, either due to depressed incomes/economy or higher percentages of racial/ethnic minority households, may have fewer complaints, resulting in less actions for maintenance. Over time such locations may end up having worse infrastructure, simply because not enough complaints are being generated in disenfranchised places.

This project will rely on 311 data (2019-2023) available from open data catalogs across case cities in the U.S. We will focus on transportation-sector grievances and generate a new understanding of how citizen complaints cluster across census block group typologies. We will assemble 311 data, where available, for case cities roughly the size of Denver, CO. We will use U.S. Census data to identify types of block groups through cluster analysis and use causal spatial statistical models. The key output from this work is to generate an equity-focused gaps framework by relying on 311 calls, and share this learning with public-sector stakeholders.

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