I’m a PhD student at the Brown University Department of Sociology. My research investigates long-term processes of social and environmental change in cities, with a focus on computational methods and longitudinal spatial analysis. I also have an enduring interest and strong publication record in political ecology and science and technology studies. Check out my work using the links below. Thanks for visiting!
The main thrust of my research focuses on integrating novel spatial data alongside historical and contemporary census records to investigate urban and environmental change over the long term. This research is enabled by historical social-environmental data extraction techniques using a variety of computational methods (see this article on machine learning approaches to data extraction, as well as the Socio-ecological City Project). Most recently, these approaches have allowed me to consider the role of industrial risk in the initial formation of racial segregation in US cities going back to the late 19th century (see this article). As part of this work, I have also collaborated with state agencies to identify risks posed by legacy industrial contamination (see this article).
I also have experience in field interviews and mixed qualitative analysis. I conducted semi-structured interviews in Anchorage, Fairbanks, and rural villages in Alaska, and integrated these interview data with planning reports, court cases, and gray literature as part of two articles (1, 2) on contested environmental knowledge production and anti-extraction movements. As part of a separate project, I drew on qualitative coding techniques to understand US media coverage of the sociotechnical controversies surrounding the 2011 Fukushima nuclear disaster in Japan (see this article).
I use a variety of tools and methods, including:
+ Machine learning approaches to data extraction
+ Data scraping and automation in Python
+ Computational text analysis in Python and R
+ Spatial analysis in R, ArcGIS, and QGIS
+ Qualitative analysis in NVivo and HyperResearch