 The charge that connectionist nets are disadvantaged in explaining systematicity has generated a lot of interest. Chalmers (1993) points out that Fodor and Pylyshyn’s argument proves too much, for it entails that all neural nets, even those that implement a classical architecture, do not exhibit systematicity. Given the uncontroversial conclusion that the brain is a neural net, it would follow that systematicity is impossible in human thought. Another often mentioned point of rebuttal (Aizawa 1997b; Matthews 1997; Hadley 1997b) is that classical architectures do no better at explaining systematicity. There are also classical models that can be programmed to recognize “John loves Mary” without being able to recognize “Mary loves John,” for this depends on exactly which symbolic rules govern the classical processing. The point is that neither the use of connectionist architecture alone nor the use of classical architecture alone enforces a strong enough constraint to explain pervasive systematicity. In both architectures, further assumptions about the nature of the processing must be made to ensure that “Mary loves John” and “John loves Mary” are treated alike.