Transparency in post-law school graduation employment: Yes, no, maybe?

Law school “transparency” over student employment rates after graduation–and some other factors which, coincidentally, happen to figure into their US News rankings–have been much in the news lately.  The New York Times has been on what may be becoming a mission to explore the ROI on going to law school (see “Is Law School a Losing Game” from January 28, 2011 and “At Well-Paying Law Firms, a Low-Paid Corner” from May 23, 2011).

For that matter, we’ve written about it ourselves, over a year ago (May 6, 2010) in “Rule 10b-5 and Law Schools .”  (OK, yes, I can confirm what you probably already suspected; I am a securities lawyer by training.)

Here’s what I then proposed:

Law schools should be required to disclose:

• Employment by sector (with thanks to Prof. Bill Henderson for the categories):
  • BigLaw (NLJ 250, for clarity)
  • Other law firm
  • Government
  • Public interest
  • Judicial clerkship
  • Business
  • Graduate school (pursuing another degree)
  • Academia (working in academe, that is)
  • Unemployed
  • Unknown/can’t be found, and
  • 1L attrition
• For all its alumni
  • As of graduation, and
  • On the first, third, and fifth anniversaries of their graduation
• Along with average student debt load at graduation.

So now, law school deans, what sayeth thou?  Don’t tell me that you’re opposed to full and fair disclosure; there can’t possibly be anything to hide, can there?

But yesterday we had a new development which may hold some promise:  As reported on Above the Law and covered in far more detail on Law School Transparency, the ABA is going to be working with NALP to try to gather and publish accurate post-graduation law school employment rates.

Schools will now be required to report:

• Employment status, including what credentials (JD or otherwise) are required for the job
• Employer type (law firm or otherwise), and
• Employment location.

Many questions remain about issues such as enforceability, auditing, and representativeness of data.  (Some of these samples will be so small as to be meaningless on a statistical basis, but our view is that that can’t be helped:  The data is what it is.)

What do you think of this?

Step in the right direction?

A sop to a rising tide of protest?  (“When it’s in The New  York Times, it has to be true,” goes the saying.)

The final answer?

Please let us know in comments.