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How the majority populations explain and view ethnic residential segregation
in Helsinki, Oslo and Stockholm
Roger Andersson, Institute for Housing and Urban Research, Uppsala University
Ingar Brattbakk, Department of Sociology and Human Geography, University of Oslo
Mari Vaattovaara, Department of Geography, University of Helsinki
First draft version, not complete.
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1. Introduction
Is ethnic segregation a problem? This is one of the most common questions that ethnic segregation
researchers get from media representatives and it is often difficult to answer. Although a researchbased answer to the question is a legitimate request to put on the research community it might be
equally important to put the question to the ordinary residents, who collectively shapes the future of
segregation by taking decisions regarding where to move to and from. If people judge the quality and
characteristics of residential areas by taking their ethnic composition into account, for instance by
exercising a flight or avoidance behaviour in relation to immigrant concentration areas, segregation
might be difficult to combat even if we the researchers would know how the phenomenon comes
about and what consequences it might bring. This is one reason for our choice to approach nativeborn residents with precisely this question; is ethnic residential segregation a problem and for
whom?
This paper also deals with ordinary peoples’ view on the mechanisms that generate ethnic
segregation. We know that politicians like to emphasize the “natural” and “voluntary” character of
neighbourhood sorting processes, lately expressed by the Swedish prime Minister Fredrik Reinfeldt:
“It is not necessarily problematic that people from another country prefer to live in proximity to
country fellowmen” (Translation from newspaper interview November 29, 2012;
http://www.sydsvenskan.se/bostad/fordubblad-bostadssegregation/ ) This is of course correct but
this commentary in an ongoing debate on increasing concentration of minority residents in already
immigrant dense neighbourhoods tends to favour one particular type of explanation: volunteer
clustering. We think that this not only affects the public’s view regarding why segregation develops
but we believe that it is also of importance to know whether this popular explanation is indeed
widespread among ordinary citizens. If so, the scope for political interventions is probably weak. Why
intervene in processes shaped by something highly natural?
Neither of these two questions, whether segregation is viewed as something problematic by ordinary
citizens and peoples’ way of explaining ethnic segregation, have –as far as we can ascertain– been
researched before and certainly not in northern Europe. Besides surveying new aspects, we intend to
contribute to the ethnic residential segregation research field also by focus our attention not to
ethnic minority residents but to the native-born majority, i.e. to those that in the Nordic context can
be expected to have on average a) more economic resources to make a choice where to reside in the
city, b) better information about the housing market, c) better access to informal networks that can
be an asset in competing over housing, and not least d) face less discrimination when applying for
loans or a rental contract.
2. Explaining ethnic residential segregation –a research perspective
There are many hypotheses regarding causes of ethnic residential segregation. Some refer less to the
ethnic dimension of the housing market sorting processes as such but focus rather on the
compositional differences between different ethnic groups. If a minority category comprises people
having rather different age, family or income characteristics compared with another group, this could
translate into systematic differences in residential and mobility patterns (Andersson 2012, Finney
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and Simpson 2008). Other explanations focus more explicitly on factors more directly related to the
ethnic dimension. Such causes could either be attributed to the minority or to the majority category
and/or to the interplay between members of these categories. Some theorists argue that ethnic
segregation should be understood as produced by minority households’ strive to cluster, i.e. to
congregate for mitigating accommodation to new, relatively unfamiliar or frightening circumstances,
or to congregate in order to sustain certain cultural, including religious, practices (Boal 1976).
A variant of this strand of research sees geographical concentrations of minorities (clustering) as a
more or less temporary stage and argues that as newcomers become socially more integrated they
will also assimilate spatially, i.e. move out of ethnic concentrations to neighbourhoods having a
higher proportion of majority residents. This so called spatial assimilation thesis (Massey 1985,
South, Crowder & Pais, 2008) predicts that ethnic concentrations comprise a higher share of
newcomers and of people not being well integrated in the labour market but it stresses that ethnic
residential segregation should be studied by focusing on decisions taken by minority group members.
We acknowledge the relevance of including the spatial assimilation thesis in studies of ethnic
residential segregation but we also argue that it might direct interest away from another potentially
more important category of people: the majority group (Ellen 2000; Crowder, Hall and Tolnay 2011).
In the context of immigration to the Nordic countries it can be argued that not only are majority
residents on average better informed about the housing markets and variations in institutional and
neighbourhood conditions, they have also on average more options due to their wider social network
and higher income (Figure 1). Key concepts in our strategy to focus more closely on the natives’
behaviour are ‘flight’, ‘avoidance’, and ‘blocking’. These concepts will be applied in other papers
making use of the same survey as this one while this particular paper focuses more on the nativeborn Finns’, Norwegians’, and Swedes’ general attitude towards ethnic segregation and whether they
see this urban phenomenon as problematic or not.
Figure 1 sketches some of the most common propositions regarding ethnic residential segregation,
focusing on two generalised categories of actors (a minority and a majority/charter group) and the
institutional setup affecting relations between them as well as regulating the housing market. Both
categories of residents are hypothesized to have preferences but the constraints facing the two
groups differ. It is more likely that the minority category faces discrimination, either directly by
majority residents or by institutional actors influencing housing allocation in a city. Preferences could
of course vary much within each category but segregation research attaches flight, avoidance and
active blocking behavior (the latter meaning keeping minorities out of native-dense neighbourhoods)
to the majority category while clustering and its counterpart spatial assimilation is seen from the
perspective of the minority category. It is of course the case that the natives’ flight, avoidance and
blocking behavior in reality produce clusters of natives; “isolated host communities” as they are
labeled by Johnston, Forrest and Poulsen (2002).
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Figure 1. Sketching a conceptual frame.
Ethnic residential segregation
Minority category
Majority category
Behaviour/actions
Institutional
regulations and
arrangements
Behaviour/actions
Preferences Constraints
(gatekeepers)
Constraints
Clustering
Housing allocation
in the rental market
Income/wealth (+) Flight
Income/wealth (-)
Spatial
Information (-)
assimilation Awareness space (-) Financing purshase
of a cooperative
Discrimination
dwelling or a house
(Blocking)
Housing market
segmentation
Information (+)
Preferences
Avoidance
Blocking
So, partly in response to the behaviour of the majority, the minority itself may either attempt to
achieve spatial assimilation or to cluster. In the latter case, the literature offers a set of reasons for
why a minority would cluster: for defence, for mutual support, for the opportunity to reproduce
cultural behaviour, and for (offensive) struggle (see Boal 1976 and Know and Pinch 2006). Knox and
Pinch (2006) also discuss three types of ethnic clusters, distinguished on the basis of
longevity/permanence and the degree of free choice: colonies, enclaves, and ghettos. While both the
colony and the enclave is regarded to be a type of congregation (volunteer clustering), the ghetto is
not. The difference between the colony and the enclave is that the former is predominantly a first
generation phenomenon (these clusters therefore decline and dissolve if immigration decreases or
ends), while the latter is maintained and reproduces over generations. Applying this conceptual
scheme on the Nordic countries, we can state that –despite the rhetorics of the former Danish
government– there are no ghettos. Enclave-like residential patterns might be found to some degree
but they are unusual and not at all of the scale and density characterising well-known examples of
ethnic enclaves in for instance the U.S. (China Towns in some cities, “Korea-Town” in Los Angeles,
clusters of Hispanics in Miami etc). What we do find in Nordic cities is moderate levels of
concentration of first generation immigrants, i.e. the colony type. One should however add that even
such colony concentrations are small in numbers and seldom comprise more than 10 percent of the
population of a particular neighbourhood.
Although figure 1 is only a rough account of the state of the art in ethnic segregation research, it
serves as a starting point for our analyses. Segregation research in the Nordic countries has expanded
rapidly over the last decade and our knowledge about how residential patterns have evolved and
changed is relatively good. There is also a growing body of research focusing on the effects of
segregation (in particular neighbourhood effects and in Sweden). However, surprisingly few studies
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have approached the two groups of actors discussed above: minority and majority group residents.
This paper aims at contributing to expand our knowledge in this respect. It is based on a survey
conducted during the fall of 2011 in Helsinki, Oslo and Stockholm. 3,000 native-born individuals aged
25 to 50 were targeted in each city by a jointly developed questionnaire sent out by respective
statistical authority. As indicated in the introduction, we have two main objectives with this paper.
First, we will in draw upon a set of questions where we tried to grasp how the majority views and
explains existing patterns. We will analyse whether or not the native-born see ethnic segregation as a
problem, and if yes, for whom? We will then study what people in general think produces ethnic
residential segregation: as something caused by minority residents’ wish to congregate? Do they
maybe see it as caused by the natives’ strive to live among natives? Do they emphasize
discrimination and/or factors related to the structural features of the housing market? Our second
objective is to bring the neighbourhood context into the picture: Is it so that people living in different
ethnic compositional contexts tend to explain the phenomena in different ways and to view
segregation differently? Are natives residing in the most immigrant-dense neighbourhoods
emphasizing other explanations and do they see segregation as less or more problematic compared
to those who reside in other neighbourhood contexts?
3. Deriving hypotheses: attitudes towards immigrants in the Nordic
countries
As will be clearer below, we possess survey data that enables us to make different types of
comparative studies. Not only can we compare data from Helsinki, Oslo and Stockholm, we can also
compare different subgroups defined by their residential characteristics within each of the three
cities. However, before engaging with our own material we will portrait the more general features
concerning attitudes towards immigration and immigrants in respective country. If such attitudes
differ much it can be hypothesized that we will find similar variations in our own survey data. The
bulk of existing research has used survey approaches and relates hypotheses and findings to theories
about trust, tolerance, and discrimination.
Using data from the World Value Survey (WVS 2009) Delhey and Welzel (2012) find –not
surprisingly– that people in fifty researched countries across the world have a high level of trust in
their in-group (measured as trust in family members, neighbours and people one knows personally).
Trust in out-groups (defined as trusting people of other nationality, other religion and people one
meet for the first time) varies substantially across countries. Finland, Norway and Sweden score high
on both dimensions. Norway at the very top in terms of ingroup trust followed by Egypt, Sweden and
Finland while Sweden scores at the top in terms of outgroup trust, followed by Norway, France, UK
and Finland. Delhey and Welzer find that there is a fairly strong correlation between the two forms
of trust (r=.43) and that it is always positive, i.e. when ingroup trust is higher we can expect outgroup
trust also to be higher. However, only about one third of the variance in outgroup trust can be
explained by the level of ingroup trust so Delhey and Welzer aim at understanding what else can
explain these variations. They find that human empowerment (access to media, GNP per capita and
individual income/education) and an index of open-access activities (measured as ‘signing petitions,’
‘joining in boycotts,’ and ‘attending peaceful demonstrations’) explain a substantial part of the
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remaining variation in outgroup trust. As can be expected, in a global perspective the three Nordic
countries do not differ much internally in this respect and being democracies with a high level of
economic standard and low level of inequality they come out as strong “trust societies”.
Weldon (2006) has studied the institutional context of tolerance for ethnic minorities in Western
Europe. The framework is macrotheoretical and he classifies EU member states into “citizen regime
types”, distinguishing between Collectivistic-ethnic, Collectivistic-civic, and Individualistic-civic. He
sets out to measure social and political tolerance where the former refers to tolerating “the content
of that expression and an actual willingness to accept ethnic difference” (p. 336). Political tolerance
concerns to what an extent ethnic minorities are entitled to the same basic political rights as the
native population. Weldon hypothesizes that the collectivistic-ethnic type produces low social
tolerance and low political tolerance, the Collectivistic-civic type is expected to generate low social
tolerance but high political tolerance while the Individualistic-civic type is expected to score high on
both these tolerance dimensions. Among the larger countries, Germany is classified into the first
type, France into the second, and the UK into the third. He groups Denmark into the middle category
while both Finland and Sweden are placed in the last regime type. We guess that had Norway been
included it would also fall into the third type.
Weldon’s empirical analysis, using a multilevel regression model, makes use of both country
indicators and individual survey data (taken from the 1997 Eurobarometer Survey on prejudice and
intolerance). Weldon’s results confirm a strong relationship between the laws governing the
acquisition and expression of citizenship, that is, citizenship regime type, and individual tolerance
judgments. However, he also stresses the importance of having better contextual information:
“Finally, along with other recent contributions to the tolerance literature (….) the findings indicate a
need to rethink our approaches to understanding tolerance, focusing more on contextual factors.
(….)Thus, in order to understand fully the nature of tolerance, it is necessary to understand the
political and social context in which people are required to make tolerance judgments.” (p. 346)
We have used data from the European Social Survey (Round 5, 2010) for analysing the country-wide
opinions towards immigrants in Europe (Source: ESS Round 5: European Social Survey Round 5 Data
(2010). Data file edition 2.0. Norwegian Social Science Data Services, Norway – Data Archive and
distributor of ESS data). We will partly draw upon these general attitudes when deriving a set of
hypotheses regarding what to expect from analysing our own survey data.
Using the sample weights recommended by ESS for the 26 countries targeted, all four Nordic
countries score high on replying to the question whether immigrants make country a worse or better
place to live (1 to 10 scale where 10 is the most affirmative response). While the average score for
the 26 countries is 4.7, Sweden scores at the top (6.5), Denmark number 3 (5.8), Finland number 6
(5.4) and Norway number 7 (5.3). Responses are however very different if we analyse the proportion
of respondents stating that they would like many immigrants from poorer non-European countries to
come and live here. Swedes are still the most willing (34% state this option), which is almost three
times more than the average European value (12%). Respondents from Finland are among the most
unwilling (5%), but also Denmark is below the average (11%). With 14% Norway ranks number 8,
after countries such as Bulgaria, Croatia, Poland, Ukraine, Spain and Germany.
There is a wide-spread belief across Europe that people with different ethnicity/race are treated
differently by the Police; 44% state that “people from different race treated worse”. If this is taken as
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an indicator of real police praxis or of whether people in general are aware of discriminatory
behavior is difficult to know. However, once again a clear majority of the Swedes report that
discrimination in this sense exists (65%, ranking tied second after Israel (67%)). Norwegians (48%)
and Danes (45%) score slightly above the European average while Finland is below (39%). It seems as
if positive attitudes towards immigrants and refugees go hand in hand with acknowledging that
immigrants are discriminated against; a bigger proportion of those acknowledging police
discrimination on racial grounds in Sweden compared to those who do not thinks that immigrants
make the country a better place to live in (6.9 compared to 6.1).
The role of neighbourhood for affecting attitudes and trust
In American political science research on voting, the term racial threat refers to the association
between white peoples’ propensity to vote for racial conservatives and the proportion of AfricanAmericans living in their local area (Key 1949; Blalock 1967). This idea takes its point of departure in
the fact that white racial attitudes and discriminatory behavior is associated with the relative size of
minority groups in a community. The idea that peoples’ social relations and behaviour are affected
by racial/ethnic compositions has much later taken center stage in much of the ongoing social
science research on social cohesion, trust, and participation (Alisina and Ferrara 2000, 2002, Putnam
2007) and it is stated that ethnic diversity in communities and neighbourhoods undermines trust
between people. In a series of papers by Uslaner (summarized in Uslaner 2012)) he argues that it is
not diversity but social isolation produced by residential segregation that drives such results: "The
problem is not diversity, but residential segregation." Living in segregated neighborhoods reinforces
in-group trust at the expense of out-group (generalized) trust." (p. 36)
Reading the literature on attitudes towards ethnic minorities and some of the other partly related
bodies of literature around issues such and tolerance and trust, it is clear that the actual
neighbourhood context of individuals matters, and so does ethnic residential segregation. Precisely
this idea lies behind the design of our questionnaire (see below).
We summarize our reading of some of the relevant existing survey-based research to generate a set
of hypotheses concerning what to expect from our own study.
(1) Given the prominent position but negative connotations that ethnic residential segregation has in
each Nordic country’s political and cultural debate, we expect that most our respondents in all three
capital cities will regard ethnic segregation as a problem. We think it is natural to expect that people
living in the most immigrant-dense neighbourhoods will regard the problem to be bigger, not least
because they will potentially face territorial stigmatization, i.e. that their neighbourhoods have a bad
reputation and is regarded to be unattractive. Such a stigma would not only affect immigrants
residing there but native-born residents as well.
(2) We expect attitudes reported in our Nordic survey to confirm the overall pattern found in the ESS
data. This means that we expect native Swedes in Stockholm a) to a higher extent point at structural
and institutional factors as contributing to ethnic segregation, and b) to a lesser extent put blame on
immigrants for the situation. Following this reasoning, we expect respondents in Oslo to be in a
middle position concerning these two aspects while Helsinki respondents will place more emphasis
on immigrants’ self-segregation. However, as indicated by Weldon’s study, differences cannot be
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expected to be big –despite the fact that an immigrant dense neighbourhood normally and in both
absolute and relative terms means something different in Helsinki compared to Oslo and Stockholm.
(3) It is likely so that a person’s own exposure to immigrants affects the view on ethnic residential
segregation. However, precisely how is difficult to know. If the Swedes overall more positive
attitudes towards immigration and immigrants are due to higher exposure to immigrants, we would
expect those individuals residing in high immigrant densities in all three cities to be less inclined to
“blame the victims”, i.e. to declare that ethnic segregation is driven by minorities’ wish to congregate
among co-ethnics. It is however also possible that if volunteer clustering is an important factor, those
witnessing this locally would be in a better position to judge. The outcome would thus be the
opposite.
4. Data collection and sample design
The surveys targeted native-born residents in the Helsinki, Oslo, and Stockholm region. They were
carried out as postal surveys with an optional possibility for Helsinki respondents to respond on-line
(web-based questionnaire). The questionnaires used in the three cities were more or less identical
but each team could also add questions that seemed to be important in one context but maybe not
in the other two. Questions were developed in English in the spring and summer of 2011 and they
were later translated into respective language (Norwegian for Oslo, Swedish for Stockholm, and
Finnish and Swedish for Helsinki (officially a bilingual city)). The design of the questionnaires was
carried out in a dialogue with respective statistical authority, which was also commissioned to carry
out the following tasks.
1. Identify the population and draw the sample.
2. Sending out the questionnaires and three reminders (Helsinki and Stockholm); two
reminders for Oslo. At least one reminder contained a new questionnaire.
3. Collecting questionnaires and transforming data into electronic form.
4. Add register data onto each individual respondent.
5. Merge survey and register data into one single data file.
6. Carry out the non-response analysis and producing sample weights to be used in the
analyses.
7. Producing the technical report and deliver the completed data file.
Questionnaires were sent out in September 2011 (Helsinki and Stockholm) and October 2011 (Oslo).
The collection of questionnaires went on until around Christmas (January for Oslo) and the final
datasets were delivered in January to March 2012.
Four strata
The samples were drawn from four sub-populations residing in each capital region January 1st 2008
and still living there at the time the sample was drawn (summer 2011). In all three cities, 750 nativeborn aged 25 to 50 in 2008 in each of the following four strata received the questionnaire.
Stratum 1: ‘Stayers’ in the most immigrant-dense neighbourhoods. This sub-population lived in any
of the neighbourhoods belonging to the upper decile in terms of percentage Non-Nordic born in
neighbourhoods. We label these neighbourhoods ‘Decile 10 neighbourhoods’ and stratum 1 is
labeled Decile 10 stayers. The requirement for qualifying was that people should have lived in the
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same Decile 10 neighbourhood 2008 and 2009 (two years) and that they still lived there at the time
of the survey.
Stratum 2: ‘Movers’ out of a Decile 10 neighbourhood. The definition of a mover is that (s)he should
have lived in the same Decile 10 neighbourhood 2008 and 2009 but have moved to another
neighbourhood within the region in 2010 (and not having moved again after that). We label this subpopulation Decile 10 movers.
Stratum 3: ‘Stayers’ in other types of neighbourhoods within the region (i.e. Decile 1 to 9
neighbourhoods). The basic definition of a stayer is the same as for Stratum 1. This category is
labeled ‘Other stayers’.
Stratum 4: ‘Movers’ out of other neighbourhoods (i.e. Decile 1 to 9 neighbourhoods). We apply the
same basic definition of a mover as for (2) and we label this category ‘Other movers’.
In all cities we excluded neighbourhoods having few residents (less than 500 in Oslo, 300 in Helsinki,
and 100 in Stockholm). The difference here has primarily to do with the size of the statistical areas,
these being bigger in Oslo (average size 5,400) and Helsinki (3,900) compared to Stockholm (2,100).
Movers in Stockholm were allowed to move into such a population wise small neighbourhood but no
one resided there in 2008-09. When the questionnaires were sent out it transpired that a few
individuals in all three cities were not actually meeting the basic criteria of being part of a subpopulation; they could have died, left the region or left the country. This ‘over-coverage’ reduces
some of the samples somewhat, see table 1.
As can be seen in Table 1, response rates are higher in Oslo than in Stockholm and Helsinki. One
could speculate concerning the reasons for this outcome (more concern, more public debate about
ethnic residential segregation in Oslo?) but we find response rates across the three cities and the
four strata in each city to be acceptable. We have also a very good picture of the non-responses. To
summarize: in all surveys some categories are less inclined to respond. Broadly speaking, males,
young people, low income people, and those having a low level of education have lower response
rates than have their demographic and socioeconomic opposites. This is the case also in this survey
and such differences also explain most of the differences in response rates across the four strata in
each city. The typical order is that ‘Other stayers’ have the highest response rate, followed by ‘Other
movers’, ‘Decile 10 movers’ and finally ‘Decile 10 stayers’.
We mention above that the statistical authorities carrying out the data collection also added register
data to the respondent files. We did therefore not have to ask about the respondents’ age, gender,
income and education (not included for Stockholm). For Oslo and Helsinki also information
concerning family type was added (civil status for Stockholm). In the Stockholm and Oslo cases we
also have the specific neighbourhood codes for 2008 to 2011, which make it possible to generate and
add other neighbourhood characteristics if needed. When responding to the questionnaire the
person agrees that register information is being used in the analyses. However, only register
variables explicitly mentioned in the introductory letter can be added and only after consent given by
the respondent.
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Table 1. Sub-populations, sample size and response rates for the survey.
City
Oslo
Population
Original sample
Over-coverage
Net sample
Responses
Response rate
Stratum 1
Stratum 2
Stratum 3
Stratum 4
Decile 10 n'hood
Decile 10
Other
Other
stayers
movers
stayers
movers
Total
14728
750
0
750
409
54.4
2931
750
2
748
362
48.4
203199
750
0
750
410
54.7
33954
750
0
750
385
51.3
254812
3000
2
2998
1566
52.2
Helsinki
Population
Original sample
Over-coverage
Net sample
Responses
Response rate
29102
750
1
749
309
41.2
2909
750
3
747
335
44.7
195195
750
0
750
350
46.7
20490
750
1
749
345
46.0
247696
3000
5
2995
1339
44.6
Stockholm
Population
Original sample
Over-coverage
Net sample
Responses
Response rate
24826
750
2
748
298
39.8
3460
750
5
745
321
43.1
351158
750
1
749
396
52.9
37794
750
4
746
356
47.7
417238
3000
12
2988
1371
45.9
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5. Results
The results section is not yet complete.
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