Steve and I had a good Twitter exchange with Tom Ricks about whether or not political science is useless to policymakers, particularly quantitative work and modeling. I thought this exchange was funny because today I saw that Colin Kahl, friend and more importantly, a damn good political scientist, was just appointed as Vice President Biden’s National Security Advisor.

Ricks’ broadside has provoked a few choice blog posts from Steve, Paul Staniland, Tom Pepinsky, and Henry Farrell. (Dan Drezner also had a good one on the topic from 2012). I also thought Ezra Klein’s column from a week or so ago on why he finds academic political science so useful for understanding American politics to be in the same vein. In different forms, they all chide Ricks for ignoring a host of new books and articles that speak to important real world issues.

Ricks references a good forthcoming ISQ article by Mike Desch and Paul Avey that includes elite survey data where policymakers express rather dismissive attitudes towards political scientists, particularly of the quantitative and game theoretic variety.

Having attended the Minerva Initiative conference last week where all of the newly funded projects were given a few minutes to talk about our research, I know that the Pentagon is interested in sophisticated modeling efforts, including game theoretic work, geospatial mapping, MRI analysis, large N work, and other methods. So, what gives?

A number of people in the academy are worried about the disjuncture between academia and political science. Having participated in several Bridging the Gap conferences, I know how hard political scientists are working to try to be relevant and thoughtful. This is also something that Carnegie and other foundations are supporting to get right. They just announced a $1 million award to former colleagues Frank Gavin and Jim Steinberg on this effort to improve the relevance of academic work. In the same announcement, Carnegie also awarded a big award to the University of Denver on non-violent protest movements as well as other grantees.

Some people conflate qualitative and historical analysis with policy relevance and large N work and modeling as theoretical and un-related to real world problems. While I’m largely qualitative, I recognize that there is quite a lot of good quantitative work to be done, and that even if the Big Data revolution is overblown, it has enormous implications for both scholarship and practice. We need to move beyond just the simple critique of the irrelevance of political science based on methods. Instead, we should look at whether the questions people ask are important ones, and if political scientists are able to communicate their findings in a way that is accessible and relevant to policymakers. With efforts like The Monkey Cage, Political Violence at a Glance, The Duck, and others, you can’t say we aren’t trying!