My undergraduate degree was in Natural Sciences. Everybody studying with me—botanists to astrophysicists—had to do statistics, whether they liked it, or not. In that environment, letting your research interests be guided by an aversion to a particular set of methods would have seemed as weird as becoming an art critic who refuses to look at the colour red. I worked as a journalist when I graduated, and started hanging out with people who’d at some point gained a degree in politics and often didn’t much like numbers. A disturbing proportion of them sought to be swayed purely by the eloquence of an argument when a little bit of data analysis would have gone a long way. Frustration with this kind of silliness led me to comparative government studies at Oxford. My DPhil here uses quantitative methods to look at the impacts of corruption.
When I began my MPhil studies in International Relations, in order to create the data I needed for my research on free trade agreements (FTAs), I wound up reading and hand-coding hundreds of treaties. The endeavour took me an entire summer to complete. And it wasn’t easy reading—some of the FTAs were over a thousand pages long and went into great detail on the tariff levels of everything from socks to solar panels. By the end of August that year, I needed my first pair of glasses. Had I created the same data today, I would have assigned my computer the task of trudging through the FTAs (presumably resulting in more detailed data, and saving my eyes many hours of strain). As the world of “big data” emerges, it’s unlikely we will want to (or even be able to) sort through and analyze our data by hand. That’s where R comes in. In my current DPhil research, I use R to analyze and map the evolution and diffusion of human and labour rights regulation (and more) in the global network of FTAs.
For a high school project, I wanted to know whether local policies increased the emancipation of female immigrants in my hometown. Since I could not find any data on their experiences, I designed a (very simple) survey and fielded it among a (completely unrepresentative) sample of women I knew. Ever since, I have been interested in the relationship between immigration and the welfare state in advanced democracies, and I have used comparative and quantitative methods to analyse it. For my DPhil project, I examine the effects of immigration on support for the welfare state. Before that, I studied Comparative Social Policy at Oxford and Political Science at the Radboud University in Nijmegen, the Netherlands.
My interest in politics emerged as a pimply and curious high school student in rural Montello, Wisconsin (United States) -- population 1397! -- where I became enamoured with my home state's progressive political history and leaders. Did you know that social policy reforms such as workers’ compensation and unemployment insurance (first enacted in Wisconsin in 1911 and 1932) served as a model for the rest of the country? Or that the "Badger State" became the first in the nation to allow collective bargaining for public employees in 1959? Things have changed since then (read: Scott Walker) but my passion for the political process has not! After graduating from the University of Wisconsin-Madison with the top prize in political science, I went to work in Washington, DC, as a policy analyst for the U.S. Department of Health and Human Services and later as a research associate for the Council on Foreign Relations. I started the DPhil in International Relations at Oxford (Nuffield) in 2013 and have loved every minute since. My research applies mixed methods (statistical techniques and case study analysis) to understand the factors shaping representation in global governance institutions. In my spare time I love to run, practice yoga, and cheer on the Green Bay Packers!
I became interested in statistics and methodology when studying for my MPhil in Politics at Oxford. And, the “stats bug” never left me.
My first degree was a BA (with distinction) in International Relations and International Organisation at the University of Groningen, the Netherlands, for which I spent a semester at the Institut d’études politiques de Paris. In 2014, I completed the M.Phil. (with distinction) in European Politics at Oxford. And, somehow I ended up applying for a DPhil and three more years of graduate study here.
My research focuses on British political development, computational text analysis, big data, and includes the occasional flirtation with bayesian statistics and machine learning here and there. When I’m not programming in R or Python, I enjoy playing the saxophone, listening to jazz, running, and reading.