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Changing patterns of residentialand workplace segregation in theStockholm metropolitan areaSzymon Marcińczakab, Tiit Tammaruc, Magnus Strömgrenb & Urban

Lindgrenb

a Faculty of Geography, Institute of Urban Geography and TourismStudies, University of Łódź, Kopcińskiego 31, 90-142 Łódź, Polandb Faculty of Social Sciences, Department of Geography andEconomic History, Umeå University, Umeå, SE-901 87, Swedenc Department of Geography, University of Tartu, Vanemuise 46,Tartu, 51014, EstoniaPublished online: 16 Apr 2015.

To cite this article: Szymon Marcińczak, Tiit Tammaru, Magnus Strömgren & Urban Lindgren (2015):Changing patterns of residential and workplace segregation in the Stockholm metropolitan area,Urban Geography, DOI: 10.1080/02723638.2015.1012364

To link to this article: http://dx.doi.org/10.1080/02723638.2015.1012364

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Changing patterns of residential and workplace segregation in theStockholm metropolitan area

Szymon Marcińczaka,b*, Tiit Tammaruc, Magnus Strömgrenb and Urban Lindgrenb

aFaculty of Geography, Institute of Urban Geography and Tourism Studies, University of Łódź,Kopcińskiego 31, 90-142 Łódź, Poland; bFaculty of Social Sciences, Department of Geography and

Economic History, Umeå University, Umeå, SE-901 87, Sweden; cDepartment of Geography,University of Tartu, Vanemuise 46, Tartu, 51014, Estonia

(Received 24 February 2014; accepted 26 August 2014)

Immigrant–native segregation is present in the spaces in which individuals fromdifferent ethnic/racial groups practice their everyday lives; interact with others anddevelop their ethnic, social and spatial networks. The overwhelming majority ofacademic research on immigrant segregation has focused on the residential domain,thus largely overlooking other arenas of daily interaction. The present study contri-butes to the emerging literature on immigrant residential and workplace segregation byexamining changes in patterns of residential and workplace segregation over time. Wedraw our data from the Stockholm metropolitan region, Sweden’s main port of entryfor immigrants. The results suggest a close association between residential and work-place segregation. Immigrant groups that are more segregated at home are also moresegregated in workplace neighborhoods. More importantly, we found that a changingsegregation level in one domain tends to involve a similar trend in the other domain.

Keywords: segregation; immigrants; home; work; Sweden

Introduction

Immigrant–native segregation is a multidimensional phenomenon. It is present in thespaces in which individuals from different immigrant origin groups practice their every-day lives; interact with others and develop their ethnic, social and spatial networks(Houston, Wright, Ellis, Holloway, & Hudson, 2005; Schnell & Yoav, 2001). Examplesof such spaces or domains of daily interaction include residential estates, the family,workplaces, shopping centers and various leisure time areas (Hägerstrand, 1970; Neutens,Schwanen, & Witlox, 2011). Regardless of the domain, segregation is usually understoodas (1) pattern—the degree to which members of different ethnic/social groups live apartfrom each other and (2) the process by which such spatial disparities are produced(Johnston, Poulsen, & Forrest, 2009; Reardon & O’Sullivan, 2004). In addition to thesetwo common meanings, some scholars also distinguish “effects” of segregation (Kaplan &Woodhouse, 2005). Thus far, the overwhelming majority of academic research on patternsof immigrant segregation has focused on residential separation (for recent reviews, seeAndersson, 2006; Malheiros, 2002; Musterd, 2005; van Kempen & Murie, 2009), largelyignoring the variation in immigrant–native segregation in other domains of daily interac-tion (Schnell & Yoav, 2001). However, knowledge on the extent and nature of workplacesegregation is very important not only for understanding how segregation is produced and

*Corresponding author. Email: szymmar@geo.uni.lodz.pl

Urban Geography, 2015http://dx.doi.org/10.1080/02723638.2015.1012364

© 2015 Taylor & Francis

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reproduced per se over the different domains of daily interaction, but also for betterunderstanding how the labor market functions (Åslund & Skans, 2010). For example,working in less segregated workplaces is associated with higher earnings among immi-grants (Catanzarite & Aguilera, 2002; Kmec & Trimble, 2009; Tammaru, Strömgren,Stjernström, & Lindgren, 2010). The first studies to take an interest in the patterns ofimmigrant–native residential and workplace segregation have emerged only recently(Ellis, Wright, & Parks, 2004, 2007; Strömgren et al., 2014; Wright, Ellis, & Parks,2010). The seminal paper by Ellis et al. (2004), which explicitly compared the level ofsegregation in those two domains using the Dissimilarity Index for census tracts in LosAngeles, revealed that workplace segregation is less prominent than residential segrega-tion. The later study by Wright et al. (2010) additionally revealed that the two domains areclosely related to each other and their geographies deeply interwoven.

In Europe, where the number of immigrants has significantly increased in the last fourdecades, the processes contributory to their segregation from natives have attractedincreasing academic attention as well (for recent reviews, see Andersson, 2006; Arbaci,2007, Semyonov and Glikman, 2011; Musterd & van Kempen, 2009). Lately, also theworks on “effects” of segregation have firmly entered the mainstream of Europeansegregation research (Hedberg & Tammaru, 2013; Musterd, Galster, & Andersson,2012). Unfortunately, even though studies of processes of segregation reveal how differ-ent policies (affirmative actions, etc.) shape ethnic/racial divisions, and even thoughworks on effects of segregation illuminate the impact of individual and neighborhoodcharacteristics on employment outcomes of immigrants, such works also tend to obscurethe evolving patterns and local geographies of immigrants’ spatial divisions. In otherwords, despite the remarkable progress in segregation studies, efforts using traditional andmodern methodologies of segregation measurement to systematically examine patterns ofimmigrant–native spatial divisions in workplaces are rare. Interestingly, there are voicesthat emphasize the continuous merit of the essentially descriptive “ecological” methods ofpattern analysis for monitoring the changing scale and form of social and spatial divisionsin the contemporary city (Simpson & Peach, 2009). Confined to a wider regional ornational spatial context, the few existing papers on patterns of immigrant workplacesegregation in Europe (Åslund & Skans, 2010; Strömgren et al., 2014) generally confirmthe findings from North America (Ellis et al., 2004); on both sides of the Atlantic,workplace segregation is less prominent than residential segregation. However, to thebest of our knowledge, there has been no explicit focus on changing patterns of bothresidential and workplace segregation in the intra-urban/metropolitan spaces of Europe.Systematic knowledge of mutating immigrant–native spatial divisions is necessary tounderstand how geographies of home and work evolve over time—not least because acomprehensive analysis of spatial patterns is essential for a better recognition of segrega-tion processes and effects (cf. Johnston et al., 2009).

The present study investigates levels and patterns of immigrant–native residential andworkplace segregation. Adhering to the recent development in studies of immigrant–native intra-urban spatial divisions (Holloway, Wright, & Ellis, 2012; Johnston, Poulsen,& Forrest, 2010; Wright et al., 2010), we study both global and local patterns ofresidential and workplace segregation/intermixing. In order to illustrate the multidimen-sional nature of segregation, we draw our empirical evidence from the Stockholmmetropolitan region (SMR), Sweden, during the period 2000–2008. The SMR, a regionthat has developed under high labor- and asylum-seeking immigration in the last 40 years(Murdie & Borgegård, 1998), provides a good case study for analyzing the changingpatterns of residential and workplace segregation. Furthermore, the excellent Swedish

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population register allows us to also provide evidence of the evolution of immigrant–native segregation in these two domains over time. In the empirical part of the article, wewill address the following questions: How do changes in workplace segregation patternscompare to those in residential segregation? Are those immigrant groups (by country oforigin) that are more segregated in terms of residential area also more segregated atworkplaces? If so, is this tendency stable over time? To what degree do local patterns ofresidential and workplace segregation overlay in urban space and how does this spatial(in) congruity change over time? Based on this evidence, we will broaden the ongoingdiscussions of the multidimensional nature of segregation in increasingly ethnicallydiverse cities in the final part of the article.

Theorizing patterns of residential and workplace segregation

The link between the location of home and work is one of the core topics in urbangeography (Glasmeier & Farrigan, 2007; Hanson & Pratt, 1988; Scott, 1988). Inspired bythe land-use model of von Thünen and empirical evidence from Chicago, William Alonso(1964) formulated a model that revolves around the concept of bid-rents in the context ofa mononcentric urban region. The model showed that each land user outbids other landusers in certain parts of the city, resulting in a series of land-use rings around the centralbusiness district (CBD) where most of the jobs could be found. High-density housingareas are located closer to the city center, while low-density housing is located furtheraway in the suburban ring. The lower social status groups are overrepresented in high-density housing areas in the inner city close to the workplaces; higher social status groupsprefer living in low-density housing areas at the edge of the city. However, processes suchas immigration, gentrification, urban sprawl and decentralization of jobs in metropolitanspace have all considerably reshaped the geographies of home and work over the pastdecades. This has reinvigorated scholarly interest in the links between the two domainsand in the changing patterns of segregation across them (Ellis et al., 2004; Strömgrenet al., 2014). Next, we will review literature on changes in the geographies of home andwork among immigrants and natives.

Diverging views on changes in immigrant residential segregation

Upon arrival, immigrants tend to settle in ethnic areas (Alba, Denton, Leung, & Logan,1995). There are diverging views, however, on immigrant residential changes over time.According to the spatial assimilation framework, residential integration starts to increasetogether with the rise of the social status of immigrants, as they convert their socio-economic achievements into residence in better neighborhoods where native populationstend to be overrepresented (Massey & Denton, 1988). Acculturation of immigrants,however, is also needed for improving residential integration. Bolt and van Kempen(2010, p. 335) therefore summarize spatial assimilation research as follows: “While socialmobility provides necessary resources, then acculturation provides the desire for immi-grants to achieve spatial assimilation.” The important outcome of the spatial assimilationprocess is the increasing ethnic/racial mix in residential neighborhoods documented inmany recent studies in North America (Alba et al., 1995; Holloway et al., 2012) andEurope (Lancee & Dronkers, 2011). In other words, the spatial assimilation frameworkargues that—when necessary conditions are at work—residential mobility of immigrantsleads toward the formation of more and more ethnically/racially mixed neighborhoods asvarious immigrant groups achieve a similar residential situation as natives.

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Yet, such a view of residential integration and the formation of increasing ethnically/racially mixed neighborhoods over time is not held universally. Indeed, it has been arguedthat, for various reasons, levels of immigrant–native residential segregation have remainedhigh (Andersson, Bråmå, & Holmqvist, 2010; Lichter, 2013). Furthermore, members ofeach ethno-racial or immigrant group still tend to live in neighborhoods with a greaterrepresentation of ingroup rather than of outgroup members (Pais, South, & Crowder,2009). The three complementary explanations of continued high levels of residentialsegregation are as follows: a lack of economic resources that would allow immigrantsto live in the same neighborhoods as natives—especially when arriving from less affluentcountries, discriminatory practices in the housing market imposed in the host country andresidential preference among immigrants themselves for living together with co-ethnics(McPherson, Smith-Lovin, & Cook, 2001; Semyonov & Glikman, 2009).

With regard to preferences, it has been found that immigrants could prefer to live inethnic residential neighborhoods because social networks and institutional resources aremore likely to flourish in large, viable ethnic communities that allow easier access toemployment and housing information for their members (Bråmå, 2008; Hou, 2009). Forexample, Li (1998) introduced the “ethnoburbs” concept to characterize suburban ethnicneighborhoods with vibrant ethnic economies for mainly white-collar immigrant workersthat emerged in Los Angeles. This means that socioeconomic success of immigrants doesnot necessarily lead to desegregation and increased ethnic diversity in neighborhoods.Furthermore, the residential choice of natives matters as well. The increase in neighbor-hood integration between immigrants and natives could just be a temporary phase inneighborhood change that leads to the out-migration of natives so that, ultimately, ethnicneighborhoods will form again. Such an argument stems from the “white flight” and“white avoidance” literature that first emerged in the United States, which showed thatWhites tend to avoid or even leave neighborhoods with already high presence of ethno-racial minority groups (Galster, 1990). Similar patterns of migration have also been foundamong natives in Sweden (Bråmå, 2006). However, in today’s multiethnic cities withimmigrants originating from very different countries of origin, such intra-urban migrationpatterns have become more and more complex, and many ethnic neighborhoods haveindeed become increasingly multiethnic in character (Pais et al., 2009).

Given these increasingly complex trends of segregation, it is of great interest toestablish how such patterns evolve with time. Yet another strand of newly emergingliterature has taken interest in the degree to which residential and workplace segregationoverlap (Ellis et al., 2007; Wright et al., 2010). This is the issue that we will turn to next.

Overlaps between residential and workplace segregation

Research on workplace segregation often takes residential segregation as its starting point.The motivation for assuming such a causal relationship dates back to the spatial mismatchhypothesis (Ellis et al., 2004; Parks, 2004). According to John F. Kain (1992), theeconomic disadvantage of especially low-skilled African Americans in the United Statesis associated with a massive metropolitan decentralization of employment that discon-nected them spatially from jobs; they also faced discrimination in entering the suburbanhousing market. Hellerstein and Neumark (2008) demonstrate more recently that the lackof local availability of jobs per se is less important for Blacks than a lack of jobs intowhich they are hired. These authors argue that the true essence of spatial mismatch isracial mismatch; other ethnic and racial groups with a more recent immigration back-ground (Hispanics and Asians) in the United States suffer from spatial mismatch to a

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lesser extent than does the Black minority (Gobillon, Selod, & Yves, 2007). Someevidence of spatial mismatch for newly arrived immigrants can be also found inEuropean cities. For example, Åslund, Östh, and Zenou (2010) demonstrate that refugeesto Sweden who were placed in a location surrounded by few jobs suffered from significantemployment disadvantages.

The spatial mismatch hypothesis highlighted the spatial dimension in the functioningof housing and labor markets and emphasized the key role of complex links connectinghome and work in shaping both the residential and work careers of different ethnic/nativegroups. Essentially, being constrained to housing that is available and affordable andbeing disconnected from certain jobs (spatial accessibility to jobs) and information flows(social accessibility to jobs) in residential enclaves results in a strong overlap betweensegregation at home and work (Ellis et al., 2004; Parks, 2004). This is especially true forthe more low-skilled immigrants. Furthermore, since both low-skilled immigrants andtheir employers seek low-rent districts, low-skill workers and low-wage jobs tend toconcentrate near one another in the city (Parks, 2004). As a consequence, the viciouscircle of disadvantage emerges (Hanson & Pratt, 1988; Wilson, 1987): living in an ethnicenclave disconnects immigrants from social networks with natives and many better-paying jobs on the one hand, while the modest earnings of immigrants is an importantobstacle for them in achieving spatial assimilation with natives on the other hand (Bolt &van Kempen, 2010; Massey & Denton, 1988).

Both the spatial mismatch and the dual labor market, with immigrants being con-strained to its peripheral part characterized by labor-intensive production, changingdemand for labor, temporary work contracts and relatively poor working conditions arethus at the core of the vicious circle of disadvantage (Wilson, 1987), working againstresidential spatial assimilation. Thus, studies of immigrant employment niching alsodemonstrate that this phenomenon is spatial—immigrant workers tend to concentratenot only into certain jobs and industries because of their skills and other productivecharacteristics, but also into workplaces located in certain often immigrant-dense areaswithin the city (Wright et al., 2010). In other words, employment networks are inherentlyspatial, not least since information about enclave employment circulates in enclaveneighborhoods since people tend to know each other locally. Enclave workplace neigh-borhoods could then be conterminous with enclave residential neighborhoods (Parks,2004; Sanders & Nee, 1987).

However, residential and workplace patterns may not necessarily overlap to a strongdegree. Due to the decentralization of jobs where immigrants are also potentiallyemployed, employment opportunities for immigrants are more dispersed in metropolitanspace compared to their places of residence (Åslund et al., 2010; Ellis et al., 2004).Furthermore, immigrant social and employment networks are not confined to residentialneighborhoods alone (Ioannides and Loury, 2004). If ethnic networks crossing neighbor-hood borders are still more important, it would facilitate workplace segregation. Ifimmigrants start to establish social networks also with natives, lower levels of workplacesegregation will result. Indeed, studies both in the United States (Ellis et al., 2004) and inSweden (Åslund et al., 2010) indicate lower levels of workplace segregation compared toresidential segregation. Workplace integration is also supported by increasing efforts tocounteract discrimination against immigrants and ethnic minorities in the labor market(Rydgren, 2004). In short, living in an enclave neighborhood does not necessarily lead toworking in segregated workplaces (Portes & Jensen, 1989). Especially for high-skilledworkers, higher salaries and more permanent work contracts allow them to undertake

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longer commutes (Östh & Lindgren, 2012; Scott, 1988) and to work at more integratedworkplaces (Strömgren et al., 2014).

Finally, previous research on the geographies of ethnic divisions in the labormarket also suggests that the link between home and work is not only skill-based, butalso highly gendered. To start with, in Sweden, the labor market participation rates arelower for immigrant women, especially for those originating from the Global South (GS)(Hedberg & Tammaru, 2013). Results from the United States further show that immigrantwomen tend to work closer to home than men (Ellis et al., 2007; Parks, 2004). Twomechanisms are proposed to explain this gender difference. First, the social networks ofimmigrant women tend to be smaller and more residential neighborhood-based than thoseof men (Moore, 1990; Wang, 2010). Second, immigrant women usually have morehousehold-related responsibilities than immigrant men, which limit their job search areacompared to men (Hanson & Pratt, 1992). If women do work closer to home, residentialsegregation might be a more important determinant of labor market segregation forwomen than for men. So far, we have only indirect evidence on this matter. The studyby Virginia Parks (2004) in Los Angeles found that women across most studied immigrantgroups are much more overrepresented in niched sectors than men, with the rates of nicheemployment also being higher for women who live in enclave neighborhoods than formen. The results from commuting studies are not as straightforward. For example,Preston, McLafferty, and Liu (1998) did not find any gender difference in commutingtimes for African Americans and Latinos in New York. To summarize, patterns ofsegregation have become increasingly complex in today’s multiethnic cities and bothscenarios—that ethnic geographies of home and work are either conterminous or not—arepossible (Ellis et al., 2007; Wright et al., 2010). Moreover, the degree of overlap is likelyto vary by immigrant origin groups and by gender (Hanson & Pratt, 1992; Parks, 2004).

Setting the scene

Patterns of residential segregation in Sweden

Sweden is probably one of the most extensively studied countries in Europe with respect tothe evolution of ethnic segregation and its effects (for the most recent reviews, see Anderssonet al., 2010; Åslund & Skans, 2010; Hedberg, 2009). There is a general consensus thatresidential segregation between natives and non-White or “visible” immigrants from thedeveloping countries of the GS has been increasing in Sweden over the past three decades(Andersson, 1998; Bråmå, 2008; Hårsman, 2006; Murdie & Borgegård, 1998). These chan-ging patterns have been attributed to changes in housing policy (Andersen & Clark, 2003;Andersson et al., 2010; Murdie & Borgegård, 1998), selective migration of immigrants andnatives in and out of ethnically dense neighborhoods (Andersson & Bråmå, 2004; Bråmå,2008; Hårsman, 2006) and different housing careers of different ethnic groups stemming fromvarying housing affordability and preferences (Abramsson, Borgegård, & Fransson, 2002).

The number of ethnic and racial minorities—immigrants from the GS in particular—has significantly increased in major Swedish cities during the past four decades (Bråmå,2008; Hedberg & Tammaru, 2013). The unfolding patterns of residential segregationappear to be following a specific origin-related trend: one in which different immigrantgroups are increasingly separated along with the increasing sociocultural distance fromnatives (Murdie & Borgegård, 1998). Such divisions have also been claimed to character-ize the labor market (Andersson & Molina, 2003; Åslund & Skans, 2010). Specifically,above-average unemployment and delayed entry into the labor market are indeed common

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features of the GS immigrants (Hedberg & Tammaru, 2013), and living in an immigrant-dense neighborhood is also associated with their lower incomes (Musterd, Andersson,Galster, & Kauppinen, 2008; Tammaru et al., 2010). However, systematic studies illus-trating the levels and local patterns of intra-metropolitan workplace segregation inEuropean cities are still virtually absent.

Main characteristics of the Stockholm metropolitan region

In 2008, the SMR, which comprises 23 of Sweden’s 290 municipalities (SwedishAssociation of Local Authorities and Regions, 2013), had a population of 1.8 millioninhabitants—one fifth of the total Swedish population. Almost half of the SMR populationlive in the actual municipality of Stockholm; the remainder are distributed across 22suburban municipalities. During the period 2000–2008, the population of the SMRincreased by about 150,000 inhabitants. The bulk of the population increase can beattributed to net immigration from abroad and a positive natural increase. Net domesticmigration was also positive, albeit much less so; such population inflows are primarilytaking place in the suburban municipalities of the SMR (Statistics Sweden, 2013). All in all,the SMR has seen a considerable increase in the share of foreign-born individuals between2000 and 2008. In 2008, 19% of the SMR population was foreign born—an increase ofthree percentage points since the beginning of the decade. This population growth hasprimarily taken place among immigrants from Central and Eastern European (CEE) and—inparticular—GS countries. In 2008, 34% of the immigrants in the SMR originated from theGlobal North (GN), 19% from CEE and 47% from the GS.

The SMR is the largest and most dynamic labor market in Sweden (Eriksson &Lindgren, 2009). In 2008, almost one million people were employed in workplaceslocated in the SMR; 60% worked within the Stockholm municipality (StatisticsSweden, 2013). The service industry provides many jobs, ranging from simple servicescarried out by unskilled labor to highly specialized expert functions within the private aswell as the public sector. Employment within manufacturing has decreased rapidly inrecent years. This negative employment trend has to some extent been counterbalanced bythe relocation of many corporate headquarters and other related activities to the SMR, aswell as the expansion of industries such as finance, insurance, and information andcommunication technology (Lundmark & Power, 2008). Although Stockholm is adynamic and expanding region, people born in other countries face much greater problemsentering the labor market; immigrants suffer from lower employment and higher unem-ployment rates compared to native Swedes (SWE) (Rydgren, 2004; Statistics Sweden,2013). These systematic differences in labor market participation are partly responsible forconsiderable variations in income; the earnings of immigrants amounted to 75% of thenatives’ earnings in 2008, according to Statistics Sweden.

In light of the nature of immigrant–native divisions in Sweden and the composition ofthe immigration influx during the study period, we propose a set of working hypotheses.First, assuming that the levels of residential and workplace segregation are closelyinterlinked (Ellis et al., 2004), we expect that immigrants who are more segregated athome are also more segregated at work. Second, as the numbers of the GS and CEEimmigrants increased between 2000 and 2008, and bearing in mind that newly arrivedimmigrants are more likely to find residence and employment in areas overrepresented bytheir co-ethnics (Wright et al., 2010), we expect the levels of residential and workplacesegregation to increase, and that the changes in one domain will be reflected in the other.

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Finally, for the same reason, we expect increasing spatial overlap between the localpatterns of residential and workplace immigrant concentrations.

Research materials and methods

Research materials

Data for the current study stem from the Swedish population register. We retrieved datafor all individuals residing or working in the SMR in 2000 and 2008. The variable“country of birth”, central to this study, is grouped into four distinct categories:

(1) Swedish-born individuals;(2) Immigrants originating from the GN: the Nordic countries, Western Europe, the

United States, Canada, Australia, New Zealand and Japan;(3) Immigrants originating from CEE: the former socialist countries of CEE, as well

as Russia and some more-developed former Soviet Union republics; and(4) Immigrants originating from the GS: Middle East (including North Africa), Asia,

Africa and South America.

These subdivisions largely correspond to the already identified ethnic/racial divisions inSweden (Andersson & Molina, 2003; Murdie & Borgegård, 1998).

The residential and workplace immigrant composition in the SMR is then analyzed atthe level of small areas for market statistics (SAMS) areas. SAMS is a spatial subdivisionof Sweden that aims to define homogenous residential areas for statistical and planningpurposes. The SAMS subdivision is largely comparable to the United States census tractdelimitation. Similar to census tracts in North America, SAMS areas have been commonlyused as a useful representation of residential neighborhoods in previous studies onsegregation in the Swedish context (e.g., Bråmå, 2008; Murdie & Borgegård, 1998;Musterd et al., 2008; Tammaru et al., 2010). Even if the spatial scale of census tracts isgenerally effective to approximate a residential neighborhood in different contexts(Johnston, Poulsen, & Forrest, 2007), its applicability in workplace segregation researchhas limitations. People first and foremost work not in a neighborhood, but in factories,offices, shops, hospitals, etc. Census tracts may then conceal considerable ethnic/racialdivisions at the finer spatial scale of work establishments. However, bearing in mind thatmeasures of segregation are sensitive to the scale and zoning of areal units, and thatcensus tracts are conventionally used in studies of intra-urban residential segregation,there is at least one advantage to use such units as a proxy for the workplace: the use ofmatching areal units makes it possible to directly compare the levels of segregation athome and work (Ellis et al., 2004). In total, there are 896 SAMS neighborhoods locatedwithin the SMR; 128 of these make up the municipality of Stockholm. In our analysis, weexcluded residential and workplace neighborhoods where the total number of residents orworkers amounted to fewer than 50 persons.

Methods

Major advancements in the analysis of ethnic/racial segregation patterns have been madeduring the past three decades. The hegemony of single number indices has recently beenquestioned and new methods exposing the global and local facets of neighborhoodintermixing have thus become more prominent in segregation studies. Indices of segrega-tion—measures that have dominated the field for the past 60 years—summarize general

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patterns only and are not sensitive to the actual spatial distribution of population groups.However, one should not overlook the fact that these simple methods allow for straight-forward comparisons across time and space (Simpson, 2007).

Studies of immigrant–native neighborhood intermixing have generally been (and arestill largely being) developed using a “raw” data approach (Johnston et al., 2010).Although certain works revolving around typologies that include different types ofethnically/racially mixed areas were present in the field already in the 1990s (Albaet al., 1995), this strand of segregation research has become more prominent in the lastdecade (Bråmå, 2008; Holloway et al., 2012; Johnston et al., 2007, 2010). Explicitlyputting more geography into segregation studies, different typologies of immigrant–nativeneighborhood mix have often been merged with the variety of measures of local spatialconcentration. This advancement offers new possibilities to more comprehensively gaugethe complexity of immigrant–native disparities in intra-metropolitan space (Johnstonet al., 2009). Despite the recent progress in segregation analysis and the criticism oftraditional methods, an inclusive approach to measurement—one that considers bothglobal and local patterns of segregation—seems to constitute the most promising approach(Alba et al., 1995; Johnston et al., 2010; Simpson & Peach, 2009; Wright et al., 2010).

The present study proceeds in two stages. First, the global patterns of immigrant segrega-tion at home and at work will be examined by means of single number indices, as they delivereasy-to-interpret descriptive statistics on immigrant–native segregation in the SMR.Consequently, the following indices are employed: the index of dissimilarity (ID) 1 and theindex of segregation (IS).2 In the second stage, the typology of residential areas introduced byBråmå (2008) will be adopted (in a slightly modified form) to reflect the level of immigrant–native intermixing at home and work. This classification has already been tested in theSwedish context and its design explicitly refers to the typologies used in internationalcomparative studies (cf. Johnston et al., 2007). Essentially, residential and workplace neigh-borhoods, in our case SAMS areas, will be divided into three mutually exclusive neighbor-hood types (cf. Bråmå, 2008):

(1) Native neighborhoods—segregated native neighborhoods, where immigrants arelargely absent; native SWE constitute 80% or more of the population;

(2) Mixed neighborhoods—neighborhoods with substantial presence of immigrants;natives constitute 50%–79% of the population; and

(3) Minority neighborhoods—immigrant-dense neighborhoods where immigrants con-stitute more than 50% of the population.

In addition to statistical analysis of the changing immigrant–native composition of resi-dential and workplace neighborhoods, the evolving spatial patterns of immigrant–nativeintermixing in the two domains are illustrated in maps. Finally, we also employ simplecross-tabulations to evaluate the degree of spatial matching and stability over time ofresidential and workplace neighborhood types in and between 2000 and 2008, respectively.

Results

Patterns of segregation in residential and workplace neighborhoods

We start by examining global patterns of residential and workplace segregation among ourresearch groups: native SWE, as well as immigrants originating from the GN, CEE andthe GS. The IS shows that, in both 2000 and 2008, GS immigrants were by far the group

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most separated from the rest of the population (Table 1). The IS values pertaining to theresidential segregation of GS immigrants could be interpreted as moderate (IS indices inthe low 40s), whereas all other values should be interpreted as low (IS indices in the 30sor lower). In line with Ellis et al. (2004), we also find that the level of residentialsegregation is significantly higher than the level of workplace segregation.

The change in residential segregation differs between the concerned groups: whilenative SWE and CEE immigrants exhibit increased separation over time, the opposite istrue for GN and GS immigrants. Overall, the changing levels of residential separation in2000 and 2008 follow the trend characterizing both the SMR and Sweden as a whole inprevious decades, except for the reduced segregation of GS immigrants (Andersson, 1998;Hårsman, 2006; Murdie & Borgegård, 1998). The relative change in the levels of workplacesegregation over time is somewhat less marked than the relative change in residentialsegregation (Table 1). The case of GS immigrants reveals another intriguing relationshipbetween residential and workplace segregation. Although the other research groups exhibitincreases or decreases in segregation that vary in magnitude between the two domains, thedirection of change remains the same. GS immigrants, however, have become moreintegrated in the residential domain, but slightly less so concerning workplace neighbor-hoods (Table 1).

The patterns of residential and workplace segregation are further illuminated by theID. This measure was calculated to evaluate the level of gendered separation betweenpairings of the research groups by domain and year. The analysis that follows thusseparately compares men/women of one group to men/women of another group.Figure 1 illustrates the outcomes; the bars are ordered from left to right by increasinglevel of workplace segregation. The results of the ID analysis show that men and womenfrom each immigrant group were more segregated by residence than by workplace, butalso shed new light on the issue of immigrant–native divisions in Sweden (Figure 1).Irrespective of gender, the levels of spatial separation in both domains are rather lowcompared to the results obtained in North America (Ellis et al., 2004). Accordingly,almost all ID values should be interpreted as low (IDs in the 30s or lower). Still, somenotable differences can be discerned between the pairings. Overall, male and female GSimmigrants are clearly most segregated from native SWE (with residential ID values in the40s, which could be interpreted as moderate), followed by CEE immigrants, while theseparation of native SWE from the GN immigrants is smallest. Male and female GSimmigrants tend to be clearly segregated from GN immigrants, too, especially concerningresidential areas. Finally, our results clearly illustrate that the level of workplace segrega-tion is generally higher between the pairings of men than between the pairings of women.

Table 1. Indices of segregation (IS) for residential and workplace neighborhood by populationgroup in the Stockholm metropolitan region in 2000 and 2008.

Population group

Index of segregation

Residential Workplace

2000 2008 Change (%) 2000 2008 Change (%)

SWE 0.288 0.312 8.33 0.151 0.163 7.95GN 0.146 0.134 −8.22 0.116 0.114 −1.72CEE 0.239 0.272 18.78 0.149 0.170 14.09GS 0.433 0.414 −4.39 0.197 0.201 2.03

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A similar trend—albeit stronger—characterizes segregation by residence. It thus appearsthat the gendered patterns of workplace and residential segregation in the SMR do notmatch those known from the United States context; the results of the study by Ellis et al.(2004, p. 631) evidently show that workplace segregation is always higher betweenpairings of women than between pairings of men of the same groups.

Geographies of neighborhood segregation at home and work

Global indices of segregation are usually incapable of distinguishing the variety of localspatial patterns of residential and workplace intermixing. The changing ethnic composition ofthe different types of residential and workplace neighborhoods offers a number of telling

0.00

0.10

0.20

0.30

0.40

0.50

SWE

–GN

GN

–CE

E

GN

–GS

CE

E–G

S

SWE

–CE

E

SWE

–GS

GN

–CE

E

SWE

–GN

GN

–GS

CE

E–G

S

SWE

–CE

E

SWE

–GS

Males Females

Residential neighborhoods

Workplace neighborhoods

2000

0.00

0.10

0.20

0.30

0.40

0.50

SWE

–GN

GN

–GS

CE

E–G

S

GN

–CE

E

SWE

–GS

SWE

–CE

E

GN

–CE

E

SWE

–GN

CE

E–G

S

GN

–GS

SWE

–CE

E

SWE

–GS

Males Females

Residential neighborhoods

Workplace neighborhoods

2008

Figure 1. Indices of dissimilarity for residential and workplace neighborhoods by population groupand gender in the Stockholm metropolitan region in 2000 and 2008.

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insights regarding local patterns of immigrant concentrations in the two domains. Leavingaside all the institutional factors and individual characteristics of immigrants and natives that(co)produce clusters of residences and jobs, we can—obviously, then, with a significantdegree of oversimplification—assume that the evolving immigrant–native makeup of resi-dential and, to some degree, workplace neighborhoods reflects the changes induced bypopulation dynamics (cf. Finney & Simpson, 2009). Even in this relatively short period(2000–2008), such forces noticeably shaped the overall ethnic residential and workplacecomposition of the SMR. A simple simulation exercise was done to illustrate the selectivity ofthese processes. We assume that all SAMS units between 2000 and 2008 followed the region-wide changes in the relative sizes of groups in the two domains. For instance, the predictednumber of GS immigrants in each residential SAMS unit in 2008 has been set at 1.168 of its2000 value (i.e., in each SAMS area the number of GS immigrants was increased by 16.8%),as the total SMR GS population increased by 16.8% during the study period. Based on thesefigures, each residential and workplace neighborhood was then assigned their predicted 2008neighborhood type (i.e., native, mixed or minority neighborhoods).

Table 2 shows that the predicted classifications of residential and workplace neighbor-hoods largely overlap with the actual situation in 2008. There are, however, somemarkedly incorrect predictions, which differ in character between the two domains ofhome and work. Despite the substantial similarity in the segregation trends illustrated byglobal indices, our simulation exercise overestimates residential intermixing and—inparticular—underestimates workplace intermixing. Moreover, the increase in the numberof minority neighborhoods was higher than expected. Large-scale immigration thus seemsto contribute to a decline of predominantly native neighborhoods and a concurrentincrease of mixed neighborhoods. This process is more evident for workplace neighbor-hoods than for residential neighborhoods. In addition, the continuous influx of immigrantsis associated with the emergence of new immigrant-dense neighborhoods in both theresidential and the workplace domains. It is worth mentioning that, under these circum-stances, the rising number of minority neighborhoods is a logically expected outcome—newly arrived immigrants have a much higher propensity to live and work in ethnicenclaves (Alba et al., 1995; Parks, 2004; Wright et al., 2010).

Tables 3 and 4 illustrate—for residential and workplace neighborhoods, respectively—the number of, and population in, the different neighborhood types in 2000 and 2008.The first thing to notice is that the native-dominated neighborhoods constitute thepredominant type in the two domains, although the changing immigrant–native composi-tion between 2000 and 2008 somewhat challenged this domination. A further inspectionof the tables reveals that the growing residential and workplace intermixing in allneighborhood categories has its roots in the same population trend—irrespective of the

Table 2. Distribution of residential and workplace neighborhoods by neighborhood type in theStockholm metropolitan region: actual values in 2000; predicted and actual values in 2008.

Neighborhoodtype

Distribution of units (%)

Residential Workplace

20002008,

predicted2008,actual 2000

2008,predicted

2008,actual

Native 81.79 76.80 77.07 75.87 67.14 60.65Mixed 16.89 22.47 20.80 23.55 29.34 37.94Minority 1.32 1.47 2.14 0.58 0.56 1.41

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Table

3.Pop

ulationby

residentialneighb

orho

odtype

intheStockho

lmmetropo

litan

region

in20

00and20

08.

2000

2008

Neigh

borhoo

dtype

Native

Mixed

Minority

Total

Native

Mixed

Minority

Total

Num

berof

units

557(81.8%

)115(16.9%

)9(1.3%)

681

541(77.1%

)14

6(20.8%

)15

(2.1%)

702

Pop

ulation

SWE

1,07

8,37

426

4,13

829

,793

1,37

2,30

51,09

0,16

5311,49

243

,788

1,44

5,44

5GN

81,027

36,312

10,638

127,97

775

,423

36,810

13,133

125,36

6CEE

25,601

18,798

4,23

148

,630

30,339

27,914

10,315

68,568

GS

65,773

49,937

25,924

141,63

453

,180

74,714

37,511

165,40

5Total

1,22

5,17

436

9,18

570

,586

1,69

0,54

61,24

9,10

745

0,93

010

4,74

71,80

4,78

4

Row

%SWE

78.58

19.25

2.17

100

75.42

21.55

3.03

100

GN

63.31

28.37

8.31

100

60.16

29.36

10.48

100

CEE

52.64

38.66

8.70

100

44.25

40.71

15.04

100

GS

46.44

35.26

18.30

100

32.15

45.17

22.68

100

Total

73.59

22.17

4.24

100

69.21

24.99

5.80

100

Colum

n%

SWE

88.20

71.55

42.03

81.18

87.28

69.08

41.80

80.09

GN

6.61

9.84

15.11

7.57

6.04

8.16

12.54

6.95

CEE

2.09

5.09

6.01

2.88

2.43

6.19

9.85

3.80

GS

3.28

13.53

36.85

8.38

4.26

16.57

35.81

9.16

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Table

4.Pop

ulationby

workp

lace

neighb

orho

odtype

intheStockho

lmmetropo

litan

region

in20

00and20

08.

2000

2008

Neigh

borhoo

dtype

Native

Mixed

Minority

Total

Native

Mixed

Minority

Total

Num

berof

units

522(75.9%

)16

2(23.5%

)4(0.6%)

688

430(60.7%

)26

9(37.9%

)10

(1.4%)

709

Pop

ulation

SWE

651,56

7119,62

42,55

877

3,74

952

4,09

421

5,61

42,63

074

2,33

8GN

52,565

16,615

1,00

770

,187

36,272

23,794

997

61,063

CEE

17,207

6,12

526

823

,600

17,241

13,700

468

31,409

GS

40,436

17,477

1,36

359

,276

39,383

36,303

2,10

677

,792

Total

761,77

515

9,84

15,19

692

6,81

261

6,99

028

9,411

6,20

191

2,60

2

Row

%SWE

84.21

15.46

0.33

100

70.60

29.05

0.35

100

GN

74.89

23.67

1.43

100

59.40

38.97

1.63

100

CEE

72.91

25.95

1.14

100

54.89

43.62

1.49

100

GS

68.22

29.48

2.30

100

50.63

46.67

2.71

100

Total

82.19

17.25

0.56

100

67.61

31.71

0.68

100

Colum

n%

SWE

85.53

74.84

49.23

83.49

84.94

74.50

42.41

81.34

GN

6.90

10.39

19.38

7.57

5.88

8.22

16.18

6.69

CEE

2.26

3.83

5.16

2.55

2.79

4.73

7.55

3.44

GS

5.31

10.93

26.23

6.40

6.38

12.54

33.96

8.52

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neighborhood group and domain, the proportion of native SWE and GN immigrantsdwindled down.

Whereas the growing neighborhood mix—in particular, the decrease of native neigh-borhoods and the concurrent increase of mixed neighborhoods—is in line with the growingevenness in the spatial distribution of the immigrant population, the rise of minorityneighborhoods appears to be rather counterintuitive. In other words, the almost unchangedor slowly decreasing immigrant separation at home and work, except for CEE immigrants,shown by global indices of segregation seems to mask growing local immigrant concentra-tions. In the residential and—in particular—the workplace domains, the minority neighbor-hoods increasingly turned into a stronghold of CEE and GS immigrants.

This implies two plausible interpretations. The first, stemming from works on resi-dential segregation, indicates that this might be evidence for a native/White flight oravoidance type of behavior—a phenomenon that is also present—and at times stronger—in workplace neighborhoods. The second one, originating from studies on immigrantemployment careers, might actually illustrate a development of an ethnic economy (Portes& Jensen, 1989). The changing ethnic/racial composition of immigrant-dense workplaceneighborhoods may thus indicate that more immigrants find jobs in enclaves whereemployees and employers recruit from the same ethnic/racial group.

The geographical pattern of residential and workplace neighborhood segregation inthe SMR is presented in Figures 2 and 3, displaying the situation for the years 2000 and2008, respectively. While native neighborhoods were predominant in both years, we can

Figure 2. Residential and workplace neighborhood types in the Stockholm metropolitan region in2000.

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also observe prevailing concentrations of mixed and—to a much lesser extent—minorityneighborhoods, as well as tangible changes over time. Generally, the number of mixedneighborhoods has increased substantially between 2000 and 2008; this is especially thecase for workplace neighborhoods. The mixed workplace neighborhoods also exhibit ageographically more dispersed pattern compared to their residential counterparts.

Although mixed and minority neighborhoods are represented both north and south ofthe Stockholm CBD,3 there are some notable differences in spatial patterns and theirtemporal change (Figures 2 and 3). In the northern part of the SMR, there is a stable,contiguous cluster of minority neighborhoods located within the municipality ofStockholm, consisting of Rinkeby, Tensta and Husby. In the vicinity of this cluster,several mixed residential and workplace neighborhoods can be found, especially at theend of the study period. The area-based urban policy program Metropolitan DevelopmentInitiative (MDI)—which ran between 1999 and 2001—aimed to counteract residentialsegregation by investment in targeted neighborhoods, mainly identified through incomestatistics. In total, 12 of the MDI areas were situated within the SMR (Macpherson &Strömgren, 2013). Interestingly, there were only three MDI neighborhoods located in thenorthern part of the study area, exactly corresponding to this minority neighborhoodcluster of persistent residential and workplace segregation comprising Rinkeby, Tenstaand Husby. Moreover, Husby constituted ground zero for the 2013 Stockholm riots thatgenerated headlines around the world; the riots subsequently spread to nearby Tensta andRinkeby, as well as certain other areas within and outside of the SMR.

Figure 3. Residential and workplace neighborhood types in the Stockholm metropolitan region in2008.

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The southern part of the SMR exhibits a large, mostly stable cluster of mainly mixedneighborhoods, stretching from the southwestern part of Stockholm municipality to partsof the adjacent municipalities of Huddinge (south of Stockholm) and Botkyrka (southwestof Stockholm). However, there are also an increasing number of—mostly residential—minority neighborhoods in this part of the SMR. Five of the 12 MDI neighborhoods in thestudy area were located within this cluster. In the southern part of the SMR, the above-mentioned increase in the number of mixed neighborhoods primarily pertains to work-place neighborhoods (Figures 2 and 3).

By means of transition matrices, the degree of spatial overlap between residential andworkplace neighborhood segregation patterns can be calculated. The results are displayed inTable 5, in which workplace and residential neighborhood types are cross-classified for 2000and 2008, respectively. The table also shows the temporal stability of the neighborhood typesin 2000 and 2008 for residential and workplace areas, respectively. We employ the Kappa4

measure (Cohen, 1968) to assess the matching and stability of local segregation patterns athome and work. Due to space constraints, only the overall degree of overlap is presented. Thisanalysis reveals that the local patterns of residential neighborhood intermixing are more stablethan local patterns of workplace neighborhood segregation. Still, in both domains, more thantwo thirds of the SAMS units had the same classification in 2000 and 2008. Moreover, itseems that the rather slow change in immigrant separation as measured by global indices,along with the more blatant shifts in the tapestry of local level intermixing, did not substan-tially alter the generally moderate degree of overlap between the different categories ofresidential and workplace neighborhoods. In both 2000 and 2008, slightly less than 50% ofresidential and workplace SAMS units belonged to the same neighborhood category.

Summary and discussion

The aim of this article was to shed new light on how residential patterns of segregationcompare to patterns of segregation at work. This was carried out in order to increase ourunderstanding of the multidimensional nature of segregation processes. Patterns of seg-regation in these two domains were defined as separation of three broad immigrant groupsand native SWE at the level of residential and workplace neighborhoods and weremeasured by single number indices. Leaving aside all the problems related to internationalcomparative studies on segregation (cf. Musterd, 2005), our results based on Swedish datasupport the notion that residential segregation is higher than workplace segregation, thusconfirming the findings by Ellis et al. (2004) in the United States context. This is animportant result since Sweden and the United States represent very different welfare

Table 5. Spatial matching and temporal stability of residential and workplace diversity in theStockholm metropolitan region in and between 2000 and 2008, respectively.

Spatial matching* Temporal stability**

2000 2008 Residential Workplace

Matching/stability (%) 46.30 42.35 87.82 71.55Kappa*** 0.285 0.269 0.767 0.497

Notes: *Spatial matching refers to the percentage of SAMS units having a similar residential and workplaceneighborhood type.**Temporal stability indicates the percentage of SAMS units whose neighborhood type is unchanged.***All values, p < 0.001.

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regimes. Essentially, Sweden is well known for a strong welfare state and egalitarianpolicies that contribute to significant wage compression and, thus, to a level of incomeinequality that is significantly lower than in the rest of Europe and the United States(Musterd & Ostendorf, 1998). The housing market in Sweden is strongly regulated, it ischaracterized by a significant share of public housing, and housing policies are activelydeployed to combat segregation and promote social mix (Andersson et al., 2010).Regarding the labor market, Sweden maintains an array of government policies intendedto sustain full employment, which, in turn, contributed to a steady growth of jobs in thepublic sector. Yet, more studies are needed to determine whether the relationship betweendifferent forms of welfare models and levels of workplace segregation follows the trendstypical in the residential domain (Musterd & Ostendorf, 1998).

It is shown that there is a strong positive correlation between residential and work-place segregation; GS immigrants are the most segregated immigrant group in bothdomains. These results suggest that the immigrant origin-based segregation stretchesfrom the residential domain to other domains of everyday life. Regarding the localpatterns of segregation/intermixing by immigrant origin, we find that more immigrantsand natives dwell than work in neighborhoods where immigrants form more than half ofthe population. Still, one should not overlook the fact that immigrants and natives arestrongly separated along socio-professional status.5

Another important contribution of the present article concerns the analysis of theevolving local patterns of residential and workplace intermixing over time. Our resultsshow that increasing/decreasing segregation in one domain tends to involve a similar trendin the other domain. The increase in neighborhoods dominated by natives but withsubstantial presence of immigrants (mixed neighborhoods in our analysis) is the mostnoticeable tendency in both the residential and workplace domains, a development thatmay indicate growing spatial assimilation of immigrants. However, the patterns ofseparation are complex, as evidenced by the case of GS immigrants. For this group,lowering city-wide residential separation coincided with rising local-level immigrantconcentrations. Our simple simulation exercise indicated that such changes in neighbor-hood intermixing are at least partly related to selectivity in population dynamics.Referring to the recent work on Gothenburg in Sweden (Bråmå, 2008), it appears thatthis selectivity stems from divergent mobility behaviors and natural growth characteristicsof particular immigrant groups and natives. Our study also provides evidence for prevail-ing immigrant group differences already identified in the 1980s and 1990s, with GSimmigrants being the most segregated from SWE (Murdie & Borgegård, 1998).

It should also be noticed that the level of spatial matching of the residential andworkplace neighborhood categories is relatively modest. Yet, there are a few “super-concentrated” (cf. Wright et al., 2010) tracts in the SMR, i.e., SAMS units whereimmigrant groups concentrate simultaneously in the two domains. The recent study byÅslund et al. (2010) on labor market performance of immigrants in Sweden provides apossible explanation of “super-concentrated” tracts identified in our study. Their workclearly illustrates a strong positive effect of job access (proximity to jobs) on immigrants’employment possibilities. Nonetheless, it still remains an open question whether theobserved overlap of immigrant residential and workplace clusters is due to (1) residentialdecisions of individuals who follow new job opportunities, (2) industrial relocations thatfollow labor pools or (3) development of different forms of ethnic economies (cf. Logan,Alba, & Stults, 2003). For example, previous studies suggest that recent, female and less-skilled immigrants live closer to their jobs than others (Ellis et al., 2004, 2007; Sandow,2008; Scott, 1988; Wright et al., 2010). However, it should be kept in mind that—in the

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1990s, at least—socioeconomic inequalities were only moderately related to immigrant–native residential segregation in the SMR (Hårsman, 2006; Hårsman & Quigley, 1995). Inlight of this, there is a need for investigation on how residential and workplace mobilityare related with regard to mechanisms triggering residential and workplace segregationbetween natives and various immigrant groups.

The spatial stability of residential and workplace neighborhood types differs as well.The results suggest that the pattern of immigrant–native intermixing at work is less stablethan that of residential segregation. Furthermore, in residential neighborhoods whereimmigrants account for more than half of the population, we find a growing absolutenumber but decreasing share of native SWE between 2000 and 2008. In workplaceneighborhoods where immigrants constitute more than 50% of the population, we findthat the absolute number and share of native SWE decreased at the same time. Althoughworkplace segregation is less than residential segregation, this result suggests that anative-flight and native-avoidance type of behavior may be stronger for workplacescompared to places of residence. One plausible explanation for this result may be that itis easier to change workplace than to change place of residence. Consequently, changes inworkplace segregation may reveal a more immediate native response to increased immi-grant concentrations compared to corresponding developments in residential neighbor-hoods. However, more studies on workplace mobility capitalizing on theories ofresidential mobility are needed for understanding to what extent immigrant-dense work-places lead to increasing levels of workplace segregation.

Concerning the gender aspect of workplace segregation, our study shows that womenappear to be less segregated from one another, and men to be more segregated from oneanother. The reason for higher workplace segregation of male immigrants might be thatthe labor market is more segregated by gender—gender segregation being greater thansegregation by nativity and immigrant origin. However, future studies should address thequestion to what extent such gender differences are due to institutional arrangements andthe economic and employment structure of the SMR. Another question requiring moredetailed studies is whether the lower level of workplace segregation of immigrant womencould be partially explained by a lower and more selective labor market participation; itmight be that only the few well-integrated immigrant women work (cf. Hedberg &Tammaru, 2013). It should be noted that female labor market participation rates arevery low compared to men in many countries of the GS from which immigrants tend tooriginate (World Bank, 2012). Furthermore, it might be the case that a higher prevalenceof marriages with native SWE among immigrant women compared to immigrant menfacilitates their higher levels of workplace integration (Niedomysl, Östh, & Van Ham,2010).

The lower level of workplace segregation among women may also be related todifferences in occupations. Low-skilled service jobs (e.g., cleaners) usually carried outby women are more likely to be found in workplaces populated by natives as compared totraditional low-skilled jobs generally carried out by men. Working together in such casesdoes not necessarily bring along social interaction between immigrants and natives. Lowerlevels of segregation for women could also be related to the specific character of theSwedish labor market. Sweden is a country with a high share of public sector employ-ment, where women comprise a large share of employees (De La Rica & Dollar, 2011;Rosen, 1996). Public sector workplaces are on the whole significantly less segregatedcompared to private sector establishments (Strömgren et al., 2014). This calls for futurestudies that take the niching of the labor market into account for understanding the

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evolution of residential and workplace careers and how these translate into patterns ofresidential and workplace segregation.

AcknowledgmentWe thank three anonymous referees for their excellent comments on the manuscript.

Disclosure statementNo potential conflict of interest was reported by the authors.

FundingSzymon Marcińczak and Tiit Tammary are very grateful for the financial support provided by theEstonian Ministry of Education and Science [Institutional research grant number IUT2-17].

Notes1. ID ¼ 1

2

P

n

xiX

� �� yiY

� ��� j, where xi is the number of people in the first category in spatial unit i; X

is the number of people in the first category; yi is the number of people in the second categoryin spatial unit i; Y is the number of people in the second category. This index varies from 0 to 1,indicating the degree of (un)evenness in the spatial distributions of different population groups.Values of ID less than 0.30 are interpreted as low; values greater than 0.60 as high (Massey &Denton, 1993). When multiplied by 100, ID constitutes the share of the population of aparticular group that would have to relocate, in order to resemble the spatial dispersion of theother group.

2. The index of segregation is a variant of ID. It compares the distribution of one group with theremainder of the population. In fact, the formula is almost identical to that of the ID. The onlydifferences are that yi is substituted by (ti − xi), and Y is substituted by (T − X), where ti is thetotal number of people in spatial unit i, and T is the total number of people in a city. IS variesfrom 0 to 1, thereby illustrating how (un)evenly an ethnic/social group is distributed in relationto the rest of the population.

3. The Stockholm CBD is approximately located in the eastern end of the vertical center ofStockholm municipality.

4. The Kappa coefficient expresses the concordance between two categorical datasets, correctedfor the concordance that may appear randomly, which depends on the distribution of class sizesin both datasets (Cohen, 1968). Kappa values range from 1 (perfect concordance) to −1 (noconcordance). In other words, higher Kappa values indicate a higher degree of matching orstability in terms of neighborhood diversity patterns.

5. To take into account this form of labor market segmentation, we calculated indices of dissim-ilarity for all pairings of immigrant groups and natives by gender, based on their distribution in112 categories of socio-professional positions in 2008. It appears that GS male immigrants areactually strongly separated from male native workers regarding their socio-professional posi-tions (ID value higher than 80). For the pairing of female workers, the value is higher than 70.

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