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Thursday, August 27, 2009
Statistics Problems
During my recent years back at Berkeley and especially the last five as Associate Dean for the Jurisprudence and Social Policy program, I have been struck by the surging interest in quantitative methods among the rising generation of sociolegal students. The contrast could not have been greater with my own generation of graduate students in the 1980s. I can remember few in my cohort who were excited about developing a strong quantitative tool kit. It was not because the JSP faculty lacked scholars with quantitative interests. Indeed, JSP had recently hired Dan Rubinfeld away from Michigan. Dan, a superb empirical economist and coauthor of the leading econometrics textbook in the country, understood that few of us in his required quantitative methods class would have volunteered to be there. Thanks to Dan my dissertation included logistic regressions of parole revocation decision making (and to this day I can still explain multicolinearity to the amusement of my friends) but I was busy turning myself into a post-structuralist analyst of the contemporary social control institutions and couldn't be bothered with an advanced class. In the last three years we have added two new superb quantitative scholars to the JSP faculty, Justin McCrary (another loss to Michigan) and Kevin Quinn (taken from Harvard, who is so new we haven't put him on the website yet) so we offer both a basic quantitative methods course dedicated to legal studies and an emerging series of advanced seminars. But becoming really good in quantitative methods means taking not one or two classes, but sequences of courses through multiple years. How do you make that work while you are developing a deep substantive knowledge about law and working knowledge of at least three disciplinary literatures (one well enough to pass a qualifying exam)? Can our best quantitative students hope to compete with those graduating in Economics, Political Science and Sociology who can silo themselves off?
Time will tell. The first goal in any research career should be becoming really excellent at the research tools which you will use, whatever those tools are. So our quantitative students should push me as far as they need to make sure they can get access to those courses and summer programs they need to get the best tools. But the intellectual quality of their research, and especially their dissertation, is going to depend a lot on the the interpretive traditions they have been exposed to and their own ability to be reflexive about them. So I will push back to make sure they work through the breadth demands of our program. Ironically it would have been easier in my day when it was no shame to take a decade (or so) to get through graduate school,but students today for a variety of reasons are driven to move through much faster. How can it work? What has to give to compete against siloed PhDs? Part of the difference can be made up cutting back on the intellectual filler that all traditional disciplines put in their curriculum to make sure your thought remains within the channels that define that discipline, and to cause you to react allergically when you confront antibodies generated by alien disciplines.
Posted by Jonathan Simon on August 27, 2009 at 12:04 PM | Permalink
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