City Services for a Smarter Boston: Constituent Driven Intelligence through BOS:311

Abstract

This thesis is an interdisciplinary study of BOS:311, the non-emergency city services program for the City of Boston. The study situates BOS:311 within the context of the Smart City, a budding object of scholarly inquiry across academic fields including science and technology studies (STS), urban studies, spatial econometrics, and the quantitative social sciences. Chapters 0 and 1 take a dive into the Smart City landscape, past and present, and review its salient terms, histories, principles and cases. Chapter 2 looks closely at BOS:311 itself, its promises and its challenges. As the empirical ba- sis for this chapter, the research methodology involved semi-structured interviews with Boston City officials and academic scholars. This approach uncovered, with first person authenticity, the inner workings of the 311 program and its focal points. Chapters 3 and 4 take a quantitative leap into the open dataset of 311 service requests. Using geospatial analysis methods, regression techniques and simple machine learning models, I aim to show whether community level characteristics (such as demographics, income and education) can be predictive of 311 request activity at the Census tract level. The study also investigates whether there are disparities in 311 request activity across demo- graphics. The final chapter reviews the insights and results from the interdisciplinary study and ties together our understanding of the Boston 311 program.