Transitioning grad students and young researchers to think like scientists is a daunting task, especially given the typically subsumptive style of undergraduate and high school education. At this upcoming lecture, Nobel prize winner Carl Wieman shares his thoughts on how to better train scientific thinkers based on insight from recent psychological research.
Back in early April, I was invited to present the results from the Data Science for Democracy project at the 2018 International Studies Association conference, a premier conference for international relations academics. Over 7000 attendees filled the halls of the Union Square Hilton in San Francisco for the 4 day event. Topics spanned political science, international relations, military planning, etc, on issues ranging from military privatization,to free trade, conflict deescalation, election monitoring, populism, the role of science and technology in policymaking, as well as many others. The types of research also varied, from highly technical, quantitative studies based on large datasets laden with mathematical models, to more anecdotal, interview-based research, which was often presented as an oration at the podium without any accompanying media. Being a physical scientist with a quantitative background, it was very exciting to see how social and political issues were being tacked in these fields, and to learn about the diversity of problems that were being investigated.
I presented the paper on the noise in the electoral college in an illiberal democracy panel, which was part of a series of panels focused on discussing varying degrees and types of illiberal democracies around the world. It was an honor to be presenting these results alongside researchers who spent time interviewing the electorate in the Phillipenes, Haiti, and eastern europe. A very insightful presentation on this panel was lead by Prof. Henry (Chip) Carey from Georgia State University, who discussed the populist right movement and recent transition of some stable democracies towards ‘sultanism’ and the loss of influence or integrity of important democratic institutions (e.g. CIA, FBI, EPA, courts, etc) which traditionally balance government in these states – essentially a transition from a more complex society of institutions designed to prevent authoritarian rule, to a simpler one with less checks and balances. I received thoughtful comments feedback from Chip as well as many others and overall the paper was very well received for its empirical value and given its quantitative nature, was rather unique for the field. By attending the conference, I’ve been able to put the paper in a larger context than before, as well as incorporate the thoughts and feedback from leaders in the field.
I’ve edited the discussion to include the feedback from the conference, and I will be uploading the latest version of the draft here soon. I want to thank the wet lab for the thoughtful discussion when writing this paper as well as the donors who support the project and provide a means for traveling to conferences and exchange of ideas with leaders in the field.
Thanks so much for the thoughtful discussion about the Data Science for Democracy paper at the journal club last week. I’m incorporating your feedback into the paper and I believe it has improved the quality of the paper and its content. Thanks so much for the thoughtful insights and discussion! Submitting it in a couple weeks to the conference. Looking forward to the next JC!
We are looking for a data science apprentice volunteer for the Data Science for Democracy project. As part of this position you will learn about and help to:
- run ANOVA analysis and update figures with latest result
- run statistical analyses
- edit visualizations in Tableau and post to Tableau public
- discuss and interpret results
- convert document from word to Latex
- There may be additional data analysis opportunities for other components of this project as it grows.
Ideally we are looking for an undergraduate student or more experienced candidate, who is interested in developing analytical skills while working on a pragmatic problem.
If you, or someone you know, are excited to learn more about data science and/or are interested in solving problems in Political Science please contact us.