Proceedings of the Annual Meeting of the Cognitive Science Society

Languages exhibit a tremendous amount of variation in how they organise and order morphemes within words; however, regularities are also found. For example, gender and number inflectional morphology tend to appear together within a single affix, and when they appear in two separate affixes, gender marking tends to be placed closer to the stem than number. Formal theories of gender and number have been designed (in part) to explain these tendencies. However, determining whether the abstract representations hypothesised by these theories indeed drive the patterns we find cross-linguistically is difficult, if not impossible, based on the natural language data alone. In this study we use an artificial language learning paradigm to test whether the inferences learners make about the order of gender and number affixes—in the absence of any explicit information in the input—accord with formal theories of how they are represented. We test two different populations, English and Italian speakers, with substantially differ- ent gender systems in their first language. Our results suggest a clear preference for placing gender closest to the noun across these populations, across different types of gender systems, and across prefixing and suffixing morphology. These results expand the range of behavioural evidence for the role of cognitive representations in determining morpheme order.