By Dan Markel, Ethan Leib, Rick Garnett, Matt Bodie, Paul Horwitz , Steve Vladeck, and Orly Lobel
First, thanks to Dan and everyone else at Prawsblog for inviting me to post here this month. I'm really looking forward to it.
I found Jonathan Simon's recent posts about the future of empirical legal scholarship quite interesting. On the one hand, as someone in the ELS field, I found his general optimism about its future uplifting. But I'm not sure I share it, although my concern is more internal to the field itself than external. I'm going to be writing about this a lot this month, so I thought I'd use my first post to just lay out my basic concerns.
Jonathan focuses on trends outside of ELS: cultural and attitudinal shifts within the law as a whole, and more global changes in, say, economic conditions. And at one level I think he is right--the decreased cost of empirical work, the PhD-ification of the law, the general quantitative/actuarial turn we have witnessed over the past few decades all suggest ELS is here to stay. But there are deep internal problems not just with ELS, but with the empirical social sciences more generally, that threaten their future. I will just touch on the major points here, and I will return to all of these issues in the days ahead.
To appreciate the problem, it is first necessary to note a major technological revolution that has taken place during the past three decades. The rise of the computer cannot be overstated. Empirical work that I can do in ten minutes sitting at my desk would have been breathtakingly hard to do twenty-five years ago and literally impossible fifty years ago. The advances have been both in terms of hardware (computing power and storage) and software (user-friendly statistics packages). The result is that anyone can do empirical work today. This is not necessarily a good thing.
So what are the problems we face?
1. An explosion in empirical work. More empirical work is, at some level, a good thing: how can we decide what the best policy is without data? But the explosion in output has been matched by an explosion in the variation in quality (partly because user-friendly software allows people with little training to design empirical projects). The good work has never been better, and the bad work has never been worse. It could very well be that average quality has declined. Some of the bad work comes from honest errors, but some of it comes from cynical manipulation.
2. A bad philosophy of science. Social scientists cling to the idea that we are following in the footsteps of Sir Karl Popper, proposing hypotheses and then rejecting them. We are not. We never have. This is clear in any empirical paper: once the analyst calculates the point estimate, he draws implications from it ("My coefficient of 0.4 implies that a 1% increase in rainfall in Mongolia leads to a 0.4% increase in drug arrests in Brooklyn"). This is not falsification, which only allows him to say "I have rejected 0%." Social science theory cannot produce the type of precise numerical hypothesis that falsification demands. We are trying to estimate an effect, which is inductive.
3. Limited tools for dealing with induction. Induction requires an overview of an entire empirical literature. Fields like medicine and epidemiology have started to develop rigorous methods for drawing these types of inferences. As far as I can tell, there has been no work in this direction in the social sciences, including ELS, of any sort. This is partly the result of Problem 2: such overviews would be unnecessary were we actually in a falsificationist world, since all it takes is one black swan to refute the hypothesis that all swans are white.
As a result of these three problems, we produce empirical knowledge quite poorly. To reuse a joke I've made before and will likely make again at least a dozen times this month, Newton's Third Law roughly holds: for every empirical finding there is an opposite (though not necessarily equal) finding.
With more and more studies coming down the pike, and with little to no work being done to figure out how to separate the wheat from the chaff, ELS could defeat itself. If it is possible to find any result in the literature and no way to separate out what is credible and what is not, empirical research becomes effectively useless. (This only exacerbates the problem identified by Don Braman, Dan Kahan and others that people choose the results that align with their prior beliefs rather than adjusting these beliefs in light of new data.)
So what is the solution? Empirical research in the social sciences needs to adopt a more evidence-based approach. We need to develop a clear definition of what constitutes "good" and "bad" methodological design, and we have to create objective guidelines to make these assessments. We have to abolish string cites, especially of the "on the one hand, on the other hand" type, and replace them with rigorous systematic reviews of the literature.
Of course, these guidelines and reviews are challenging to develop for the methodologically straight-forward randomized clinical trial that medicine relies on. In the social sciences, which are often forced to use observational data, the challenge will be all the greater. But, as I'll argue later this month, the rewards will be all the greater as well.
The use of systematic reviews is particularly important in the law, for at least reasons:
1. Inadequate screening. Peer review is no panacea by any means, but it provides a good front line of defense against bad empirical work. We lack that protection in the law. There are some peer reviewed journals, but not many. And the form of peer review that Matt Bodie
talked about for law reviews recently isn't enough. The risk of bad work slipping through is great.
The diversity of law school faculties, usually a strength, is here a potential problem. Even theoretical economists have several years of statistics, so everyone who reads an economics journal has the tools to identify a wide range of errors. But many members of law school faculties have little to no statistical training, making it harder for them to know which studies to dismiss as flawed.
2. Growing importance of empirical evidence. Courts rely on empirical evidence more and more. And while disgust with how complex scientific evidence is used in the courtroom has been with us since the 1700s if not earlier, the problem is only going to grow substantially worse in the years ahead. Neither Daubert nor Frye are capable of handling the evidentiary demands that courts increasingly face.
Given that my goal here was just to touch on what I want to talk about in the weeks to come, I think I'll stop here. This is an issue I've been thinking about for a while now, and I am looking forward to seeing people's thoughts this.
