A comparative approach towards ethnic segregation patterns in Belgian cities using multiscalar individualized neighborhoods

Abstract

Levels of spatial segregation in Western European cities are persistent over space and time. To demonstrate the degree or appearance of spatial segregation, most studies on urban residential patterns still rely on fixed spatial units, aspatial measures and single scales. However, a spatial or temporal comparison of patterns and levels of segregation based on such units or metrics is not without problems. To that end, this paper takes an explicit geographic approach and considers individualized neighborhoods using EquiPop-software, allowing various scales. Using the k-nearest neighbors for all individuals increases international comparability and facilitates interpretation, so far often hampered in segregation research. This multiscalar, multigroup comparative approach on ethnic urban geographies-using Belgium as a case study-provides an empirical illustration of a valuable method and tool applicable in segregation research, thereby furthering the comprehension of the increasingly diverse urban geographies and building on emerging work in the US, Europe and beyond.

Demographic dynamics across urban settings and implications for ethnic geographies

“…The relatively high shares of owner occupation in these ethnic communities make Turkish and Moroccan concentration neighbourhoods quite durable (Galster, 2001). Such traditional divisive clustering of subpopulations has been shown to operate at various spatial scales (Imeraj, Willaert, & de Valk, 2018) and therefore feasibly has a differential long‐term demographic impact upon the ethnic composition and geography. For example, because Turks and Moroccans are heavily concentrated into poor concentration areas, the continuing importance of chain migration, the increasing importance of natural growth, and the limited local out‐mobility are likely to consolidate residential fragmentation (segregation), more than we would expect in the case of either less segregated, more locally mobile, or more recent migrant populations.…”

“…As a consequence, the residential attainment of migrants differs considerably across ethnic and cultural lines (Boschman & van Ham, 2015). For example, highest levels of segregation are generally found among non‐Western migrants that occupy the least prosperous socio‐economic position (Imeraj, Willaert, & de Valk, 2018).…”

“…The diversification of urban populations over recent decades has spurred public policy debates around the level of integration of ethnic group populations and related ethnic clustering and spatial fragmentation in urban locations. Extant studies have explored and described how ethnic geographies in urban areas and beyond have changed over time (Catney, 2016a, 2016b); developed and applied innovative methods to better measure the levels and spatiality of segregation (Catney, 2018; Imeraj, Willaert, & de Valk, 2018; Jones, Johnston, Manley, Owen, & Charlton, 2015; Östh, Malmberg, & Andersson, 2014); and elaborated on the underlying processes by which urban populations and geographies are moulded (Bailey, 2012; Bailey, van Gent, & Musterd, 2017; Finney & Simpson, 2009). The latter strand of research covers several perspectives.…”

Uptake of formal childcare among second generation and native mothers in Belgium: can increasing local childcare availability narrow migrant-native gaps?

“…Turkish and Moroccan labour migrants were recruited from 1964 onwards to address labour shortages in sectors such as industry, mining and construction (Reniers, 1999;Van Mol & De Valk, 2016). Consequently, these origin groups were characterised by specific settlement patterns and are still concentrated in the more disadvantaged neighbourhoods where they originally settled (Kesteloot, 1985), which is partly due to the housing market and the generally lower socio-economic status of migrants and their descendants (Imeraj et al, 2018). Turkish origin groups settled in the former industrial areas in Limburg and Wallonia, but also in and around large cities in Flanders (e.g., Antwerp, Ghent) and Brussels, characterised by large secondary labour markets.…”

Neighbourhood migrant composition and tobacco-related cancer mortality: A census-linked study among five origin groups in urban Belgium

“…Other spatial approaches and longitudinal data structures would be an asset to expand and complement our work (Kwan, 2012;Macintyre et al, 2002). An interesting line of research for the future would be to use individualised neighbourhoods in this type of study (Imeraj et al, 2018), although its success will depend on the availability of detailed data and time series. Finally, our measures of same-origin presence were used as proxies for local migrant network capital and were hypothesised to influence health behaviour.…”