Political Science Fail

Quoting the research from a new ISQ article on what academic training best informs global policymaking, Henry Farrell quotes the work of Paul Avey and Michael Desch:

Aside from Economics, the scholarly disciplines that policymakers found of greatest use were Area Studies and History. … compared to the other disciplines, Political Science did rather poorly (see figure 10. This lower ranking may reflect the fact that in recent years the discipline has become dominated by more complex methodologies such as formal modeling and statistics. Policymakers tend to eschew, in the words of one respondent, “all formulaic academic, as opposed to historically based temperamental, realist projects,” preferring, in the words of another, “historical analysis, case studies, theoretical writings that illustrate theory with case studies and concrete examples.” … the higher the rank of the government official, the less likely he or she was to think that formal models were useful for policymaking.

Farrell observes: “There are a number of possible responses that international relations scholars could make to this e.g. to argue that political science is in the business of finding out about the world, not helping policy makers, or to argue that it’s not US policy makers who international relations scholars should be trying to help. Or scholars could argue as many have that we should reform political science to move away from quantitative techniques and formal modeling towards more policy relevant work.”

via The Monkey Cage.


One thought on “Political Science Fail”

  1. Being relatively new to the world of Political Science, I have been surprised by the amount of quantitative analysis, rather than qualitative, that is expected of us. I think, though, that this is emblematic of the shift in modern politics. For some reason, it’s not enough that somebody lost an election or that a certain idea is more popular than others. People feel like they must know all of the statistical data regarding these issues. I think that this comes down to over-reliance on dogmatic principles. For example, when the Mitt Romney handily loses the Latino vote in the 2012 election, Republican statisticians scramble to discern what parts of the community support his ideas and which don’t. They look for geographic, economic, and ethnic trends that might explain why he lost their vote. It seems that the last issue they are willing to consider is that maybe he just had a policy that was disagreeable. Rather than using qualitative analysis and considering the impact certain ideas might have on others, today politics is dominated by the idea that statistics will explain it all and, eventually, carry the day–an idea that would likely seem absurd to history’s greatest political and social thinkers.

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