Multidimensional homophily exposes difficulties with thinking about migrant networks in terms of single aspects of migration-driven differentiations. How can we account for the multidimensionality that superdiversity demands and move beyond concluding that things are more complex? In this chapter a fuzzy cluster analysis of homophily patterns is presented as facilitating a data-driven delineation of different types of migrant networks—where the focus is not on one aspect of superdiversity but on multiple. Thus four types of networks are identified: city-cohort, long-term resident, superdiverse, and migrant-peer networks. Each is discussed in light of the networks that are sorted into the cluster. The fuzziness of clusters is considered as well as the relevance of London and Toronto as the two contexts where networks were forged.
|Name||Global Diversities book series (GLODIV)|