teach- ers could argue that the students did worse merely because they were told that the scores wouldnt count in their official record-which, in fact, all retested students would be told. To make the retest results convincing, some non-cheaters were needed as a control group. The best control group? The classrooms shown by the algorithm to have the best teachers, in which big gains were thought to have been legiti- mately attained. If those classrooms held their gains while the class- rooms with a suspected cheater lost ground, the cheating teachers could hardly argue that their students did worse only because the scores wouldnt count. So a blend was settled upon. More than half of the 120 retested classrooms were those suspected of having a cheating teacher. The re- mainder were divided between the supposedly excellent teachers (high scores but no suspicious answer patterns) and, as a further con- trol, classrooms with mediocre scores and no suspicious answers. The retest was given a few weeks after the original exam. The chil-     dren were not told the reason for the retest. Neither were the teachers. But they may have gotten the idea when it was announced that CPS officials, not the teachers, would administer the test. The teachers were asked to stay in the classroom with their students, but they would not be allowed to even touch the answer sheets. The results were as compelling as the cheating algorithm had pre- dicted. In the classrooms chosen as controls, where no cheating was suspected, scores stayed about the same or even rose. In contrast, the students with the teachers identified as cheaters scored far worse, by an average of more than a full grade level. As a result, the Chicago Public School system began to fire its cheating teachers. The evidence was only strong enough to get rid of a dozen of them, but the many other cheaters had been duly warned. The final outcome of the Chicago study is further testament to the power of incentives: the following year, cheating by teachers fell more