Bivalent grade matrices {#bivalent-grade-matrices-1 .unnumbered}
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Suppose that agents partition into two types: good and bad. The good agents give a grade of 1 to the good agents, and 0 to the bad agents. The bad agents gives a grade of 1 to every agent. Now the generalised PeerRank method give the good agents a grade less than or equal to 1, and the bad agents a grade more than or equal to 0. The bad agents get some credit for grading the good agents (semi-)accurately. This means that the grade of the bad agents by the good agents was a little too harsh, and their own grade suffers.

EXPERIMENTAL EVALUATION
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We tested the performance of the generalised PeerRank rule on some synthetic data. In all experiments, we set $\alpha=\beta=0.1$. Results are, however, relatively insensitive to the actual choice of $\alpha$ or $\beta$. Based on the promise shown in these experiments, we are currently preparing a real world test with undergraduate students. Our typical experimental setup is 10 agents who give an integer mark to each other of between 0 and 10, and an actual mark of between 0 and 100. Therefore a simple baseline against which we compare 