# TaxProf Blog

Paul L. Caron
Dean

Tuesday, August 14, 2018

### The U.S. News Peer Reputation Rankings And The Availability Heuristic

Jeff Lipshaw (Suffolk), Submission Angsting and the Availability Heuristic:

Paul Caron over at Tax Prof Blog does us the community service every year of re-ranking the schools by their "peer assessment" number, which ranges from 1.1 at the low end to 4.8 at the top.  I am assuming for this exercise that the peer assessment is meaningful even though I have my doubts.

My doubts stem largely from the likelihood that so much of this is determined by the availability heuristic, the term coined by Tversky and Kahneman for a mental strategy in which people make judgments about probability, frequency, or extremity based on the ease with which and the amount of information that can be brought to mind.  Hence, we bias our judgments based on available information.

Having said that, here goes.  One of the most available pieces of information is the linear ranking in US News.  It's really available.  It's available to the people who send in their votes for peer ranking and it's available to authors trying to place their articles.  What is not so available (thank you Paul) because you have to pay to get it isn't just the re-ranking by peer assessment but the actual peer score.

The histogram above shows the peer assessment scores from the 2019 US News law school ranking by the number of schools at each peer score from 1.1 to 4.8.  You can draw your own conclusions, but I think trying to thin-slice differences between scores close to each other is kind of silly.

It's pretty clear that whatever peer assessment means, the top 17 are in their own world.  As between 18 and 50, yeah, maybe there's difference between 18 and 50, but I wouldn't get too worked about about the difference between 30 and 40.  That effect is even more dramatic in the 50-100 range.  The point is that the rankings are linear, but the actual data sits on a curve.  So the differences between linear rankings mean different things at different levels.  (I'm pretty sure re-grouping the data in other significant categories like entering LSAT score would yield similar results.)