The High Price of Objectivity

(cc photo by kevin dooley)
Dana Goldstein attempts to defend “last in, first out” layoff policies for public school teachers:
In education, reasonable people have been disagreeing, for decades and decades, about how to define and measure good teaching. LIFO has become standard practice because in the absence of such agreement, it has one great advantage: LIFO can be applied completely objectively.
Life is full of situations that demand you to make decisions under conditions of uncertainty. In almost all cases, the right thing to do is to try your best not to simply give up. Note that since teacher compensation costs increase as a function of experience, LIFO is actually worse than the equally objective practice of firing teachers at random. LIFO maximizes layoffs relative to financial targets. Doing layoffs by lottery would allow districts to fire fewer teachers.
But of course doing layoffs by lottery would be a pretty silly way to run an organization. Adopting any criteria, no matter how imperfect or contestable, that had any correlation to performance whatsoever would be an improvement over random firing. Measuring job performance is hard in any field, and it’s hard in teaching. But is it so hard that we really couldn’t do better than firing people at random? Note that if it really is completely impossible to obtain actionable information about teacher quality, then suddenly the case for forcing teachers to swallow dramatic pay cuts looks pretty strong. I don’t buy it. I think hiring good teachers is important, and part of that is thinking that it’s possible to obtain information about which teachers are the good ones. But if you seriously think we can’t, then we should at least shift to random firing.