The segregation of generations: ancestral groups in Sydney, 2011

Abstract

Most models of immigrant minority enclave formation in cities represent their situation as relatively transient elements in urban residential mosaics. As minority group members become both economically integrated and socially–culturally assimilated into the host society, so they move away from the enclaves where they initially concentrated. Such shifts are especially likely in the second and later generations of group members, who are more likely to overcome the disadvantages experienced by many of the original settlers with regard to human capital. This paper evaluates that model using data on the residential distributions of three generations of those claiming one of 19 different ancestral groups in Sydney in 2011, at four nested spatial scales, deploying a recently developed inferential method for evaluating the intensity of residential segregation. The findings are not consistent with the model: in general, members of the second and third generations in any ancestral group are as segregated as the first generation (that is, those born outside Australia) at both regional and neighbourhood scales.

Ethnic residential segregation and identificational assimilation: An intergenerational analysis of those claiming single (heritage) and dual (with Australian) ancestries

“…In part, this reflects the division of the Lebanese in Sydney into two separate communities, Christian and Muslim; the latter having close attachments to mosques and schools in the inner west, even among the third generation claiming dual identities (cf. Johnston et al., 2017: 256).…”

“…Australian multiculturalism is seen to work because of its encouragement of an open society, with no one ethnic immigrant group dominating (Forrest et al., 2006a, 2006b). Ethnic immigrant enclaves are seen as only a temporary phenomenon (Jones, 1996) associated with intergenerational assimilation (Edgar, 2014; Johnston et al., 2017). Furthermore, Australian cities are characterised by low levels of residential segregation relative to other major immigrant-receiving societies like the United States and Canada (Johnston et al., 2007); ‘Sydney is a leading exemplar of ethnic residential intermixing’ (Poulsen et al., 2004: 375).…”

Placing the second generation: A case study of Toronto

“…The major exception to the overall trend is among African heritage and dark‐skinned Latino households, which frequently remain in housing and neighbourhoods of far lower quality than white households with comparable socio‐economic status (Darden and Kamel 2000; Logan 2013). Australian research also points to divergent degrees of spatial assimilation among second‐generation ethno‐racial groups (Edgar 2014; Johnston et al 2017). Some groups, such as Turks and Vietnamese, are more spatially concentrated than predicted by their socio‐economic status.…”

Ethnic and class residential segregation: exploring their intersection – a multilevel analysis of ancestry and occupational class in Sydney

“…Previous analyses of segregation patterns in Australian and other cities have explored the degree to which ancestral groups are concentrated in particular parts of an urban area at a variety of spatial scales (Manley et al, 2015;Johnston et al, 2016Johnston et al, , 2017. All groups in the places analysed are spatially concentrated at a number of scales: in particular there is segregation at a macro-scale of intra-urban regions and, within those regions, further concentration at both meso-and especially micro-scales.…”

“…) The Australian census TableBuilder facility allows data to be extracted on individuals categorised by both their ancestry -the census does not collect data on ethnicity -and their occupation, that can be aggregated at a variety of spatial scales. 1 These data have been analysed to identify segregation patterns at multiple scales using an innovative multi-level modelling procedure (described below) for a wide range of ancestry groups and also for generations within those groups (Johnston et al, 2016(Johnston et al, , 2017. The analyses reported here use tables from the 2011 census that cross-classify ancestry by occupation for all economically active and employed adults aged 20-64 (i.e.…”