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March 09, 2007

Comments

Tracy Lightcap

The experiments that could have the most impact on studies of, at least, appellate courts are the classic ones by Tversky and Kanneman on how people actually make decisions. I've always thought that the revelation that real human beings are, you know, much more risk adverse then the usual rational actor models we use to analyze judicial behavior would predict is of supreme importance in trying to decide why judges make decisions the way they do. Combine that with the inherent uncertainty of the environments they make decisions in and you get a VERY different picture of how judicial decision-making works.

Anyone interested in this, give me an e-mail. I've already done work on the uncertainty part. Put in the experimental results and we might have something worth looking at.

Eileen Braman

In my opinion one can never "oversell" the value of experiments in this endeavor.

I would argue in addition to all the excellent uses Professor Blumenthal mentions experiments are invaluable for understanding how legal decision makers reason about cases. Of course it's up to those of us that use such methods to demonstrate their value in a world of multiple empirical methods. But that's as it should be.

As Professor Blumenthal and Bill mention experiments can help us answer questions that other approaches to legal decision making have not addressed. There is no reason we should be afraid to use them to better understand cognitive mechanisms that drive findings from other empirical approaches.

William Henderson

Jeremy,

Nice post. It was me who wrote about Martin and Epstein "supplying 95% ..." etc. That comment assumes staying in the world of observational data, which reveals narrow blinders I admit.

It is noteworthy that controlled experiment is always touted as the gold standard for causal inference. I realize that laboratory psychological studies are not the same as medical clinical trials, but I agree that they provide our best window on processes that are otherwise impossible to observe and measure.

Thanks for correcting my bias. bh.

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