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EJSP SPECIAL ISSUE ARTICLE

Perceived social diversity and neighbourhood attachment: The role of intergroup ties and affective appraisals of the environment. Evidence from Poland Sabina Toruńczyk-Ruiz*,† & Maria Lewicka‡ * The Robert B. Zajonc Institute for Social Studies, University of Warsaw, Warsaw, Poland † Centre of Migration Research, University of Warsaw, Warsaw, Poland ‡ Faculty of Psychology, University of Warsaw, Warsaw, Poland

Correspondence Sabina Toruńczyk-Ruiz, The Robert B. Zajonc Institute for Social Studies, University of Warsaw, Stawki 5/7, 00-183 Warsaw, Poland. E-mail: [email protected] Received: 31 July 2015 Accepted: 30 March 2016 http://dx.doi.org/10.1002/ejsp.2209 Keywords: ethnic diversity, age diversity, income diversity, perceived diversity, neighbourhood attachment, Poland

Abstract This paper investigates the relationship between perceived ethnic, age and income diversity and neighbourhood attachment, accounting for measures of objective diversity calculated for small, individualised neighbourhoods. With data from Warsaw in Poland, we examine whether neighbourhood ties with people of different ethnicity, age and income moderate the relationship between perceived diversity and attachment. We also test affective appraisals of the environment (excitement and irritation) as a mediator between perceived diversity and attachment. Perceived ethnic diversity was positively related to neighbourhood attachment, and this link was mediated by the emotion of excitement. Perceived income diversity undermined attachment regardless of the neighbourhood ties, and this link was not mediated by affective appraisals. Perceived age diversity was related to lower neighbourhood attachment only for individuals who had few ties with neighbours of different ages. We argue that the effects of diversity may depend on the socio-cultural context, specifically on the level and meaning of diversity in a given society.

Numerous studies have investigated the consequences of ethnic diversity at the neighbourhood level for social cohesion. This important body of work has predominantly addressed ethnic diversity (Bailey, Kearns, & Livingston, 2012; Greif, 2009; Oliver, 2010), but diversity can be defined more broadly, referring to any social characteristic (e.g., age or social status; Dekker & Bolt, 2005; Lancee & Dronkers, 2011; Tolsma, van der Meer, & Gesthuizen, 2009). The effects of socio-demographic diversity may be particularly salient in societies with relatively low immigration, because socio-demographic diversity may be then more easily disentangled from ethnic diversity. We assume that other dimensions of diversity apart from the ethnic dimension may also have consequences for social cohesion. As such, this paper aims to examine the effect of perceived ethnic, age and income diversity on neighbourhood attachment, accounting for objective diversity. We investigate the impact of diversity on neighbourhood attachment, which is defined as an emotional bond with the neighbourhood of residence (Giuliani, 2003; Lewicka, 2011; Low & Altman, 1992). Although neighbourhood attachment has been so far rarely investigated in research on the ‘diversity effect’, it forms a key dimension of social cohesion, next to social solidarity and social capital (Forrest & Kearns, 2001;

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Greif, 2009), and by some scholars, it is seen as a psychological prerequisite to social capital (Laurence & Bentley, 2015; Perkins, Hughey, & Speer, 2002). Another critical issue of previous work is that it has yielded conflicting results (see for a review, van der Meer & Tolsma, 2014). To address these inconsistencies, we go beyond simply assessing the relationship between diversity and attachment and seek to identify additional conditions and mechanisms influencing this relationship. Specifically, we examine how neighbourhood ties may moderate the effects of perceived diversity on attachment. We also test whether affective appraisals of the environment mediate the effect of perceived diversity on neighbourhood attachment, believing that in order to better understand the link between contextual diversity and neighbourhood attachment, an environmentalpsychological perspective is needed. In the current research, we present an analysis of a survey conducted in Warsaw, Poland. We believe this is the first test of the effect of several dimensions of diversity on neighbourhood cohesion in a Central-Eastern European country. The nature of this survey allowed us, together with assessing perceived diversity, to calculate objective diversity indices for small individualised neighbourhoods and present an analysis accounting for both perceived and objective diversity. This method

European Journal of Social Psychology 46 (2016) 818–832 Copyright © 2017 John Wiley & Sons, Ltd.

S. Toruńczyk-Ruiz & M. Lewicka

goes beyond the standard procedure of focusing only on the effects of objective diversity. Ethnic, Income and Age Diversity Several theories are commonly used to explain effects of social diversity on community cohesion. One such theory is the homophily principle (for a review, see McPherson, Smith-Lovin, & Cook, 2001), which posits that people prefer to interact with similar others. Applying this framework to place attachment, we should expect higher attachment in homogeneous neighbourhoods because they should facilitate interactions between neighbours. The second group of theories refers to conflict and group threat (Blalock, 1967; Blumer, 1954) and argues that competition over resources increases along with the size of the minority group, thus inducing a feeling of threat among majority group members. Third, the effects of diversity may relate to conflicting norms and values (Page, 2008) between different groups. These divergent norms may cause disagreements over how community life should function (see also Nieuwenhuis, Völker, & Flap, 2013). From this perspective, neighbourhood diversity harms social cohesion only if translated into a diversity of norms. While these theories may explain the effects of various types of social diversity, the existing scientific debate focuses mostly on ethnic diversity and points to its negative effect on the within-neighbourhood indicators of cohesion (van der Meer & Tolsma, 2014). The few studies that investigated neighbourhood attachment have also revealed a negative relationship. Ethnic and racial diversity undermined neighbourhood attachment in two studies carried out in large US cities (Greif, 2009; Oliver, 2010) and in a study conducted in six European cities (Górny & Toruńczyk-Ruiz, 2014), but for the UK, evidence was mixed: ethnic diversity reduced affective attachment in a quantitative study carried out by Laurence and Bentley (2015), but not in a qualitative study, in which the residents were asked about their own perceptions of neighbourhood characteristics and experience of place attachment (Livingston, Bailey, & Kearns, 2010). Several researchers have recently argued that it is not cultural differences but instead economic disadvantage that undermines neighbourhood social cohesion (Letki, 2008; Tolsma et al., 2009), including place attachment (Bailey et al., 2012). The explanations for the negative consequences of neighbourhood deprivation focus on the higher level of crime and safety that erodes neighbourhood cohesion (Letki, 2008; Oliver & Mandelberg, 2000; Tolsma et al., 2009). At the same time, both the psychological and sociological literatures highlight negative stereotypes of the poorer, including labels such as dirty, uneducated, criminal, violent (Cozzarelli, Wilkinson, & Tagler, 2001) or low both in warmth and competence (Fiske, Cuddy, Glick, & Xu, 2002). These stereotypes also apply to neighbourhoods —poor neighbourhoods are generally perceived as less attractive and safe (Permentier, van Ham, & Bolt,

Perceived diversity and neighbourhood attachment

2009). Neighbourhood stigmatisation undermines shared identity and can lead to individual disengagement from the community (Stevenson, McNamara, & Muldoon, 2014), hence damaging neighbourhood attachment. Not only low neighbourhood status—how poor the residents are on average—but also economic diversity may dampen community cohesion, including neighbourhood attachment. The poorer and the richer have different lifestyles, engage in different activities and share fewer norms (Bourdieu, 1984), possibly implying large barriers and tensions between social groups (Tolsma et al., 2009; Piekut, Rees, Valentine, & Kupiszewski, 2012). Class-related cultural differences may be as strong as those emerging from ethnic cleavages because they are related to different ‘class’ identities (Baldwin & Huber, 2010). Several studies have looked at the relationship between economic diversity and neighbourhood cohesion, again yielding inconclusive findings. While socioeconomic diversity reduced place attachment in the Netherlands (Dekker & Bolt, 2005) and in the USA (Taylor, Gottfredson, & Brower, 1985; however, place attachment was operationalised as house ownership and length of residence), a UK study found no relationship between the two (Bailey et al., 2012). Lancee and Dronkers (2011) in turn showed for the Netherlands that trust in neighbours was positively related to income diversity (and unrelated to neighbourhood ethnic diversity). At the same time, several studies revealed lower neighbourhood satisfaction in socioeconomically mixed areas (Baum, Arthurson, & Rickson, 2009) and tensions between occupants of different housing tenures, which can be treated as an indicator of social mix (Wood, 2003). To our knowledge, there have been no studies on the effects of age diversity in the neighbourhood on any indicators of social cohesion. However, age differences are the most natural dimension of neighbourhood diversity, because young residents replace long-established ones in most housing estates. Age is related to generational differences, specific lifestyles and values (Lewicka, 2012) and thus can be a meaningful dimension in social categorisation and a source of potential clashes. Studies show that young residents are viewed as problematic and are a source of annoyance and fear of crime (Brown, 2005; Pain, 2005). On the other hand, older residents may tend to withdraw from social life and thus be poorly engaged in local joint activities, or even block some of them. In a large-scale survey conducted in Germany, Schaeffer (2013) showed that the young and elderly were seen after the drunkards as the most problematic groups in the neighbourhood, and to an extent much higher than any ethnic minority. In an ageing Europe, the question of how age diversity affects community life, including emotional bonds with places, seems crucial. Actual Versus Perceived Diversity To date, most of the literature on diversity has focused on the effects of objective diversity. However, people


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do not perceive the social composition of their neighbourhoods equally. It seems that statistically measured diversity may affect attitudes and behaviour in the neighbourhood only if it is noticed (Alba, Rumbaut, & Marotz, 2005; Hooghe & de Vroome, 2015; Koopmans & Schaeffer, 2015). Recent studies have found that perceptions of diversity had an independent effect on social cohesion indicators, over and above that of objective diversity (Koopmans & Schaeffer, 2015), and that perceived outgroup size, rather than its actual size, led to anti-immigrant attitudes (Hooghe & de Vroome, 2015; Semyonov, Raijman, Yom Tov, & Schmidt, 2004). We believe that especially in societies with low but increasing actual diversity, research on neighbourhood diversity should incorporate measures of perceived diversity (see also Piekut, 2014). While the few studies addressing perceptions of diversity have focused mostly on its effect on anti-immigrant attitudes, perceived diversity may also influence place attachment. Being surrounded by similar others in terms of ethnicity, socioeconomic status or age may be associated with more interactions and local involvement (Taylor et al., 1985) and consequently, stronger attachment. The inclusion of measures of perceived diversity with regard to ethnicity, age and income may help understand which dimensions of diversity contribute to neighbourhood attachment. Intergroup Ties and Affective Appraisals While most previous work has treated contextual diversity as a proxy for actual contact experiences, recent research has stressed the difference between exposure to diversity and direct individual contact with diversity (Dinesen & Sonderskov, 2015; Górny & ToruńczykRuiz, 2014; Hewstone, 2015; Laurence, 2011; Schmid, Al Ramiah, & Hewstone, 2014; Stolle et al., 2013). These studies have been inspired by the contact hypothesis (Allport, 1954; Pettigrew, 1998), which claims that contact between members of different groups will lead to improved mutual attitudes. Combined with the theories predicting a negative effect of contextual diversity, we can assume that simply living among diverse neighbours—without direct intergroup contact—may be threatening for residents, but once contact with outgroup members occurs, the effect of contextual diversity will be neutralised or even positive (Hewstone, 2009). Several empirical studies support this reasoning, finding that interethnic ties neutralise the negative effects of ethnic diversity on outgroup trust (Stolle et al., 2013), trust in neighbours (Laurence, 2011) and neighbourhood attachment (Górny & Toruńczyk-Ruiz, 2014). However, the effect of intergroup contact for other types of objective diversity and for perceived diversity remains unexplored. Neighbourhood attachment is an emotional bond with a place, and thus, it depends on the affective appraisal of the neighbourhood (Lewicka, 2012). According to Russell’s (1988) “circumplex model of affective appraisal”, environments generate various emotional 820

reactions, which can be described by two main dimensions: arousal (arousing vs. non-arousing) and pleasure (pleasant vs. unpleasant). This gives four possible emotions: arousing and pleasant (exciting), non-arousing and pleasant (relaxing), arousing and unpleasant (irritating) and non-arousing and unpleasant (boring). Most environmental research focuses on the relationship between affective appraisals and physical features of the environment (e.g., its familiarity, complexity or sensory characteristics; Russell & Snodgrass, 1991). However, the neighbourhood is above all a social entity, and the perceived social composition of the residence place may be a powerful source of affective reactions. Social diversity means complexity and stimulation; we can therefore expect that it will lead to emotional arousal. This may be exciting (pleasant) or irritating (unpleasant)—depending on additional factors. Most people would prefer their neighbourhood to be relaxing rather than exciting (Lewicka, 2012). If diversity is a source of arousal, we expect this to lead to the appraisal of the neighbourhood as unpleasant (as irritating rather than exciting). This reaction should mediate the relationship between perceived diversity and attachment.

Diversity in Poland Poland provides an interesting case for diversity research. Before World War II, it was a highly ethnically diverse society—ethnic minorities constituted nearly one-third of the total population (Eberhardt, 2006). Following World War II, owing to the Holocaust and changes in the Polish borders, Poland became ethnically homogeneous and remained so during the communist regime. Since 1989, new immigrants have arrived —especially from the former USSR—and Polish society has become more multicultural (Piekut et al., 2012); this process is expected to increase (Duszczyk, Góra, & Kaczmarczyk, 2013). Within Poland, Warsaw is the most ethnically diverse city, with foreigners in Warsaw comprising around one-fourth of all foreigners in Poland (Piekut, 2012). Nevertheless, the overall share of immigrant residents in Warsaw does not exceed 2% of the whole city population (Piekut, 2012; Winiarska, 2014). The largest immigrant groups in Warsaw are from Ukraine and Vietnam. Warsaw has no immigrant neighbourhoods comparable with those in Western Europe but contains small ethnic enclaves. These mainly include Vietnamese migrants, who are the most established and visible ethnic group in Warsaw. Although they seek to preserve their own national identity, the Vietnamese conform to the norms of Polish society (Winiarska, 2010). Importantly, ethnic diversity in Poland is not accompanied by socioeconomic differences because the majority of foreigners living in Poland are economic migrants, who are on average better educated and work in non-manual occupations more often than the indigenous Warsaw population (Piekut, 2012).



While anti-immigrant sentiments exist in Polish society (Zick, Küpper, & Hövermann, 2011), the European Social Survey has found more positive attitudes towards immigration here than in most of Western Europe (ESS Round 6: European Social Survey Round 6 Data, 2012). This may be due to the low number of foreigners in Poland and the fact that at the time of the study, ethnic cleavages had not been mobilised in Polish political discourse (Tavits & Letki, 2014). At the same time, economic inequalities have become salient since 1989 and are increasing (Keeley, 2015). The major dimensions that differentiate the socio-spatial structure of Warsaw are the family situation and socioeconomic status of residents (Smętkowski, 2011). The city includes a mixture of building types constructed in various periods, which provide high variation in terms of social composition (Górczyńska, 2014). Newly constructed apartment buildings usually have younger residents than the prewar tenements and communist-era apartments. Therefore, both socioeconomic and age diversity are present at a local level. Research Objectives The current study examines the relationship between three types of perceived diversity—ethnic, income and age diversity—and neighbourhood attachment. We integrate the theories explaining macro-level processes— the homophily principle, conflict theories and conflict of norms theory—with the contact hypothesis, which addresses individual experience with diversity. Moreover, we consider perceived diversity as a source of affective appraisals of the residential setting. Based on existing findings showing a negative effect of ethnic diversity on various indicators of neighbourhood cohesion, we expect perceived diversity in all three dimensions to be negatively related to neighbourhood attachment. Our analyses will allow to compare the effects of each of the perceived diversities. Furthermore, generalising the findings on the moderating role of interethnic ties at the neighbourhood level (Górny & Toruńczyk-Ruiz, 2014; Laurence, 2011; Stolle et al., 2013) to other types of diversity, we expect that for all three dimensions of neighbourhood diversity, the relationship between perceived diversity and neighbourhood attachment will be neutralised by having ties with neighbours from diverse backgrounds in terms of ethnicity, income and age. Finally, we expect that this negative relationship will be mediated by the emotion of irritation (negative arousal) rather than excitement (positive arousal) because people tend to prefer a relaxing neighbourhood rather than an exciting one (Lewicka, 2012). Method Research Design

We use data from a survey conducted on a random sample of 300 Polish residents of one city district in Warsaw


—Ochota. The district was chosen for the study because of its high socio-demographic variety resulting from a mix of building type, and a relatively high share of foreigners compared with other Warsaw districts (Winiarska, 2014). The district hosts both visible migrants from Vietnam and China as well as immigrants from the former USSR, and importantly, includes small immigrant enclaves (Piekut, 2012; Winiarska, 2014). We thus assumed that our respondents would have opportunities to encounter various types of diversity, including ethnic diversity. Data were collected in June and July 2014 by a professional research company by means of computer assisted face-to-face interviews. Respondents were selected based on address-based sampling. Individual data derived from the survey were then matched with data on the composition of the population in the postal codes of the Ochota district, obtained from the Social Insurance Institution (Zakład Ubezpieczeń Społecznych, hereafter ZUS) in 2014 for the purpose of this study. Given that the last census data (2011) do not permit analyses on a level lower than cities, the ZUS database is the best available data source for assessing social diversity indices: it contains detailed information about all individuals who have social insurance, including their address, country of origin, age and income. The database includes the working population as well as unemployed and pensioners—because these groups have social insurance—but does not include children, people working illegally or those who are not registered as unemployed. This means that age diversity and income diversity of the population covered by the database may be underestimated, compared with the numbers in the whole population living in certain areas. Conversely, the level of ethnic diversity may be overestimated because the share of working foreigners in Warsaw is higher than that of Poles (although some of the foreigners work illegally). Altogether, while the diversity indices based on this data source may not exactly reflect the diversity in the total population living in the studied areas, we believe that they do capture the variety of socio-demographic structure across the studied neighbourhoods. Inspired by the works of Hipp and Boessen (2013) and Dinesen and Sonderskov (2015), in order to obtain neighbourhood characteristics for the participants, we drew a circle with a given radius around each respondent and calculated neighbourhood measures based on the socio-demographic characteristics of the residents living within that circle. This way we obtained overlapping, individualised measures of actual diversity for each participant, referred to by Hipp and Boessen (2013) as “egohoods”. Such an approach relies on the idea that the neighbourhood does not have strict physical boundaries but is personally defined (e.g., Galster, 2001; Lewicka, 2010) and that people tend to perceive their neighbourhood as a small area around them. Most importantly, creating “egohoods” overcomes the problem of arbitrary borders of administrative units such as census tracts or postal codes, which vary in size and do


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not always reflect the actual immediate environment of the individuals living in them (Hipp & Boessen, 2013). Creating neighbourhoods around each respondent enables focusing on small spatial units of equal size. We believe that if diversity is to impact individuals, it is most likely in the immediate setting (see also Oliver & Wong, 2003; Schmid et al., 2014; Stolle et al., 2013; van der Meer & Tolsma, 2014). Our ‘egohoods’ had a radius of 250 m, which reflects an area reachable within around a 5-minute walk (see also Kearns & Parkinson, 2001). This also suited the definition of the neighbourhood provided in the questionnaire—the respondents were told that whenever asked about their neighbourhood, they should think of the area reachable by foot within a short, few minutes’ walk from their home. To construct our measures for “egohoods”, we geocoded the addresses of the respondents1 and drew a radius of 250 m around each of them using the geographic information system software QGIS. Because the socio-demographic characteristics obtained from ZUS were for postal codes, we first had to determine the postal codes within each egohood and then sum the information for all postal codes included in the circle using weights according to the proportion of the given postal code within the egohood.2 For example, if the circle around respondent 1 contained the whole postal code A, one-half of the postal code B and one-fourth of C, the given population of interest, for example, foreigners in this egohood, would be equal to the number of foreigners living in A + one-half of the foreigners living in B + one-fourth of the foreigners living in C. This way, we calculated percentages of age groups, income groups and foreigners for each ‘egohood’.

Measures Neighbourhood attachment. Neighbourhood attachment was measured by a 6-item scale by Lewicka (2010): “I miss this neighbourhood when I am not here for long”, “I am proud of this place”, “This place is part of me”, “I want to be engaged in its affairs”, “I am rooted here” and “I want my family and friends to live here in the future”. All items were rated on a 5-point scale (1 = strongly disagree, 5 = strongly agree). The scale proved to be one-dimensional and had high reliability (α = .84). The measure used in the analysis was the standardised factor score with a mean of zero and a standard deviation of one, with higher values indicating greater neighbourhood attachment. Perceived diversity. We included measures of perceived ethnic, income and age diversity. The respondents were asked: “In some places, people are very 1

Unfortunately, seven respondents had invalid addresses. We assumed that the proportions between specific groups were the same within postal codes.

2

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similar to each other with regard to various characteristics, in others they are very different from each other. What is your neighbourhood like, regarding: (1) level of income? (2) age? (3) ethnicity?”. Answers were given on 11-point scales (0 = very similar; 10 = very diverse). Apart from these measures, we also asked the respondents about the percentages of certain groups in their neighbourhood: “I would now like to ask which groups are in your view present in your neighbourhood. Please try to estimate the percentage of the residents who are… [poor, rich, average, children and teenagers under 18, people aged 18–25, 26–35, 36–59, 60 years and older; immigrants]”. Responses were given on a scale from 0 to 100. Neighbourhood ties with persons of different ethnicity, age and income. The measures of

neighbourhood ties with persons of different ethnicity, age and income were based on Lewicka’s (2010) relations with neighbours scale. The scale consists of six items in which participants are asked to rate the proportion of neighbours with whom they maintain various relations, ranging from relatively distant to close ones, for example, “How many neighbours do you know by name?”, “With how many neighbours do you maintain contacts?”. Responses were given on a 5-point scale (1 = with no one, 5 = with all neighbours). The scale had high reliability (α = .85). The respondents who reported having any contacts with their neighbours were then asked to assess the proportion of the neighbours (among all neighbours with whom they had contacts) who were: much older than them; much younger than them; had much higher income than them; had much lower income than them; and who were foreigners. Responses were again given on a scale 1–5 (1 = no one, 5 = everyone). Based on these responses, we created three dummy variables for each type of intergroup contact: ties with neighbours of different ethnicity; ties with neighbours of different income; and ties with neighbours of different ages. Given that as many as 83% in our sample did not maintain ties with any foreigners within their neighbourhood, we operationalised interethnic relations as having mentioned neighbourhood ties with at least one foreigner. Ties with neighbours of different age and income were more frequent in our sample: only 24% respondents said they had no ties with persons of different ages, and 42% said they had no ties with persons of different income. Therefore, these two types of contacts were operationalised as having at least half of ties with persons of a different age and at least half of ties with persons of different income. Affective appraisals. Affective appraisals were measured with a scale based on Russell’s (1988) model. It included 10 items presented on a 5-point bipolar scale, in which the end points were associated with opposing reactions: boring–interesting; relaxing–irritating; safe– unsafe; quiet–noisy; drowsy–exciting; gloomy–cheerful;



monotonous–diversified; dull–lively; calm–hectic; and ordered–chaotic. As expected, a principal component analysis (PCA) with orthogonal rotation yielded two components, which explained 67.8% of the total variance: one related to evaluating the place as boring versus exciting (α = .88) and the second related to evaluating the place as relaxing versus irritating (α = .86). In the analyses, we used standardised factor scores, with higher values indicating excitement and irritation and lower values indicating boredom and relaxation, respectively. Control variables. To minimise confounding of the relationship between perceived diversity and neighbourhood attachment, we controlled for measures of actual diversity and other neighbourhood characteristics, as well as individual-level variables. Actual diversity. Based on the ZUS data, we included three actual diversity measures: ethnic, income and age diversity, each calculated separately for the egohood of each respondent as described earlier. Ethnic diversity was measured by a dichotomous variable, based on the range of the percentage of immigrants in the egohood. Immigrants were defined as persons with a non-Polish citizenship. While ethnic diversity is commonly measured by fractionalisation indices such as the Simpson diversity index or Herfindahl index,3 in Europe, the percentage of immigrants and ethnic diversity indices are statistically indistinguishable because ethnic diversity is strongly related to immigration (Schaeffer, 2014). Moreover, fractionalisation diversity indices are not sensitive enough when minority groups are not numerous, and this was the case in our study. We created a categorical variable instead of a numeric one, assuming that the relationship between ethnic diversity and social cohesion is not necessarily linear. Especially in the Polish context, in which the general level of ethnic diversity is low, small linear changes in the percentage of foreigners are unlikely to affect neighbourhood cohesion (for a similar argument, see Piekut & Valentine, 2015). We assumed that rather than this, there might be a qualitative difference between neighbourhoods with no or very low ethnic diversity and these with an above average level of diversity. The percentage of immigrants in the “egohoods” ranged from 1.55% to 16.12%, with a median of 3.74. We created a dummy variable based on the median split, with 1 indicating values equal or larger than the median and 0 indicating below the median. Income diversity was measured by the Theil index, which is an entropy index that accounts for the discrepancies between the distribution of income and the distribution of population between groups and has the advantage over the commonly used Gini index that it is more sensitive to the ends of the distribution, which 3 Both these indices capture the probability that two randomly selected individuals in a given population belong to two different groups.


is important given the data we have. The index is calculated by the following formula: m

∑ w i *ln i¼1

wi ni

where group’s i income share is wi and population share is ni. T can range from 0 to 1, with 0 reflecting perfect equality and 1 occurring when all the income belongs to one group. Given that the ZUS data contained incomes in intervals, income groups were created based on midpoints of a given interval. Age diversity was measured by the standard deviation of age in each of the egohoods. Because the data from ZUS on the distribution of age were only available in 5-year age intervals, we calculated the standard deviation again using midpoints for each interval. Other control variables. Other neighbourhood level variables included the unemployment rate in the neighbourhood (as a measure of socioeconomic deprivation in the neighbourhood), population density in the neighbourhood and type of building in which the respondent lives, because the type of building has been repeatedly shown to predict place attachment (Lewicka, 2011). Individual-level variables included gender, age, education (number of years of education), employment, self-reported financial situation, number of books owned (as a measure of cultural capital), length of residence in the neighbourhood, homeownership, having children under 16 years of age and the strength of neighbourhood ties, measured by a standardised factor score based on the scale described earlier. Descriptive statistics of all used measures are presented in Table 1.

Results Analytical Approach

Given that we had a random, geographically scattered sample and we used individualised neighbourhood data, we performed ordinary least squares regression. We conducted our analysis in several steps. In the first model, we included only control variables on both the individual and contextual level, including measures of actual diversity. Next, we added the three measures of perceived diversity, each separately. We also included measures of the perceived percentages of specific groups in the neighbourhood—the immigrants, the elderly, the young and the poor—in order to test whether they are driving the effects of perceived diversity. We then investigated the moderating role of neighbourhood ties for each type of diversity separately by adding measures of ties with neighbours of different ethnicity, age and income, respectively, and an interaction between the given type of neighbourhood ties and its corresponding dimension of perceived diversity. In order to test the


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Table 1. Descriptive statistics

Variable Neighbourhood attachment Age Woman Length of residence in neighbourhood (in years) Has child under 16 years Employed (yes) Years of education More than 200 books owned Self-reported financial situation (good) Home ownership (yes) Type of building—block of flats Type of building – tenement house Type of building – new apartment building Type of building – family house (detached or row) Neighbourhood ties Ties with neighbours of different ethnicity Ties with neighbours of different age Ties with neighbours of different income Unemployment rate Population density (in thousands per square kilometre) Ethnic diversity (yes) Age diversity Income diversity Perceived ethnic diversity Perceived age diversity Perceived income diversity Neighbourhood exciting Neighbourhood irritating

reflected the actual levels of ethnic diversity, but this was not the case for income and age diversity.4

N

M (SD) or Percent

Range

300 300 300 300

3.62 (0.65) 46.5 (18.98) 62% 20.48 (20.39)

1.33–5 18–94 0/1 0–89

300 300 300 300 300

22% 60% 14.89 (2.96) 18% 30%

0/1 0/1 7–24 0/1 0/1

300 300

65% 49.3%

0/1 0/1

300

33.7%

0/1

300

12.3%

0/1

300

4.7%

0/1

300 300

2.06 (0.71) 17%

1–4.83 0/1

300

44%

0/1

300

32%

0/1

293 293

12.83 (3.97) 9.74 (4.94)

5–18.50 0.98–19.64

293 293 293 281 283 295 300 300

50% 11.17 (0.92) 0.45 (0.03) 3.28 (2.09) 5.29 (2.18) 4.63 (2.17) 3.56 (0.68) 2.60 (0.76)

0/1 8.76–12.28 0.37–0.53 0–10 1–10 0–10 1.20–5 1–5

indirect effects of affective appraisals, we performed mediation analyses.

Correlations Between the Study’s Key Variables

Correlations between neighbourhood attachment and the main predictors are included in Table 2. Neighbourhood attachment was negatively correlated with perceived income and to age diversity, but interestingly, it was positively related with perceived ethnic diversity. Moreover, there was a positive correlation between perceived ethnic diversity and evaluating the neighbourhood as exciting, while irritation was not correlated with any of the perceived diversity measures. Although not reported in Table 2, there was a positive and significant correlation between perceived and actual ethnic diversity but of modest size (r = .21, p < .001). For income and age diversity, the relationships were not significant (r = .02, p = .752 and r = .00, p = .949, respectively). Therefore, the subjective perceptions partly 824

The Effects of Perceived Diversity on Neighbourhood Attachment

Table 3 presents the results of the regression models predicting neighbourhood attachment. The first model included only control variables at both the individual and contextual level. Neither of the actual diversity measures was significant,5 which contradicts the studies suggesting a negative link between ethnic diversity and neighbourhood attachment. Apparently then, in our study, people living in more diverse neighbourhoods were not less attached to their neighbourhoods, although the homophily principle, group threat theory and conflict of norms theory would predict otherwise. However, most of the variables that were significant confirm the well-known patterns from previous work on neighbourhood attachment. Being older, having lived in the neighbourhood for longer, having children under 16 years of age, a good financial situation and living in an area with higher population density were all related to higher neighbourhood attachment, whereas cultural capital (measured by the number of books owned) and living in a new apartment building were related to lower attachment. The remaining control variables were non-significant. In model 2, we included perceived ethnic diversity, which explained an additional 0.03 of the variance in neighbourhood attachment. Interestingly, it was positively related to neighbourhood attachment: individuals who perceived more ethnic diversity were more attached to their neighbourhood. When the perceived percentage of immigrants was added to the model6 along with perceived ethnic diversity, perceived ethnic diversity remained significant (B = 0.09, SE = 0.03, p = .002), while the perceived percentage of immigrants was not (B = 0.01, SE = 0.01, p = .155), which implies that perceived ethnic diversity captures something more than just the perceived number of immigrants. The positive effect of perceived ethnic diversity is a surprising finding, given that both actual and perceived ethnic diversity have been shown to reduce social cohesion and that we controlled for a number of both individual and contextual variables. 4

This may be because ethnicity is more visible than age or income. In ethnically homogenous societies like Poland, foreigners, particularly of a different race, stand out from the native population and are easily noticed, whereas socioeconomic status is less evident. The fact that age diversity was not reflected in perceptions comes as a surprise, because age differences seem easier to assess. However, this may relate to the reference group: whereas people in Poland are generally not familiar with ethnic diversity, they are familiar with age and income diversity, and therefore, a neighbourhood that is mixed in terms of income or age may not stand out because these dimensions of diversity are more common. 5 These variables were also non-significant when added separately to the model. 6 Perceived percentages of the immigrants, the elderly and income groups were not included in Table 3 for the sake of clarity.




Table 2. Pearson correlations between neighbourhood attachment and its main predictors included in the regression models

Neighbourhood attachment Perceived ethnic diversity Perceived age diversity Perceived income diversity Neighbourhood exciting Neighbourhood irritating Interethnic ties with neighbours Ties with neighbours of different age Ties with neighbours of different income

Perceived ethnic diversity

Perceived age diversity

Perceived income diversity

Neighbourhood exciting

Neighbourhood irritating

Ties with neighbours of different age

Interethnic ties with neighbours

0.13* 0.15*

0.11

0.21*

0.28**

0.51**

0.22**

0.05

0.01

0.03

0.03

0.00

0.08

0.08

0.08

0.06

0.17**

0.03

0.09

0.13*

0.30**

0.16**

0.06

0.04

0.11

0.37**

0.33** 0.21*

0.10

0.06 0.02

0.23** 0.00

0.05

0.14*

0.59**

*p < .05. **p < .01 (two-tailed).

Table 3. Ordinary least squares regression models predicting neighbourhood attachment Model 1

(Constant) Age (in 10 years) Woman Length of residence (in 10 years) Has child under 16 years Is employed Years of education (in 10 years) More than 200 books owned (yes) Self-reported financial situation (good) Home ownership (yes) Type of building (tenement house) Type of building (new apartment building) Type of building (family house) Neighbourhood relations Unemployment rate Population density Ethnic diversity (yes) Age diversity Income diversity Perceived ethnic diversity Perceived age diversity Perceived income diversity 2 Adj. R N

Model 2

Model 3

Model 4

B

SE

B

SE

B

SE

B

SE

0.12 0.16*** 0.01 0.12*** 0.40** 0.11 0.27 0.31* 0.36** 0.07 0.07 0.63** 0.07 0.04 0.02 0.04** 0.12 0.02 3.30

1.35 0.04 0.10 0.03 0.13 0.12 0.18 0.14 0.12 0.13 0.13 0.20 0.26 0.05 0.04 0.02 0.13 0.12 3.44

0.58 0.15*** 0.01 0.13*** 0.42** 0.16 0.26 0.25 0.33* 0.08 0.02 0.75*** 0.18 0.02 0.01 0.03 0.05 0.06 3.50 0.10***

1.38 0.04 0.11 0.03 0.13 0.12 0.19 0.14 0.13 0.13 0.13 0.20 0.26 0.05 0.04 0.02 0.14 0.12 3.48 0.03

0.01 0.16*** 0.01 0.12*** 0.41** 0.12 0.26 0.33* 0.35** 0.06 0.05 0.60** 0.11 0.05 0.02 0.04* 0.11 0.04 2.40

1.40 0.04 0.11 0.04 0.14 0.12 0.20 0.14 0.13 0.13 0.13 0.21 0.27 0.06 0.04 0.02 0.14 0.13 3.59

0.24 0.15*** 0.03 0.12*** 0.42** 0.10 0.29 0.35* 0.31** 0.04 0.04 0.57** 0.07 0.05 0.02 0.05** 0.13 0.06 2.71

1.35 0.04 0.10 0.03 0.13 0.12 0.18 0.14 0.13 0.13 0.13 0.20 0.26 0.05 0.04 0.02 0.13 0.12 3.44

0.04

0.02 0.06** 0.29 288

0.02

0.27 293

0.31 274

0.27 276

Note: Unstandardised coefficients. *p < .05. **p < .01. ***p < .001.

Perceived age diversity, added in model 3, had a negative coefficient, but it was non-significant. Additional analyses showed that when the perceived percentage of older adults (60 years and above) was included in the model, its coefficient was positive (B = 0.01,

SE = 0.00, p = .017), while the coefficient of perceived age diversity remained almost the same (it was negative but non-significant, B = 0.04, SE = 0.02, p = .143). The same pattern occurred when the perceived percentage of younger adults (18–25 years) was included instead


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Table 4. Effect of three types of perceived diversity (ethnic, age and income) on neighbourhood attachment—moderation by neighbourhood ties Model 2

Ethnic diversity B Perceived diversity Interethnic ties with neighbours Perceived diversity * interethnic ties with neighbours 2 Adj. R N

0.10***

Age diversity

Income diversity

SE

0.03

0.11*** 0.20

0.03 0.15

Model 3

Model 3a SE 0.02

B 0.04 0.00

0.02 0.11 0.27 276

Model 4

Model 4a SE

0.06**

0.28 288

0.02

B

0.28 288

SE

0.12*** 0.16 0.06 0.31 274

0.03 0.15 0.06

B

SE

0.10** 0.02 0.13* 0.28 276

0.04 0.11 0.05

Model 4b SE

0.06** 0.02

B

Model 3b SE

0.27 276

B Perceived diversity Ties with neighbours of different income Perceived diversity * ties with neighbours of different income 2 Adj. R N

B

0.31 274

0.04

Model 2b

SE

0.31 274

B Perceived diversity Ties with neighbours of different age Perceived diversity * ties with neighbours of different ages 2 Adj. R N

Model 2a

0.02 0.12

B 0.09** 0.03 0.07 0.28 288

SE 0.03 0.12 0.05

Note: Unstandardised coefficients. Perceived ethnic diversity, perceived age diversity, and perceived income diversity were centred. Control variables included gender, age, education, employment, self-reported financial situation, number of books owned, length of residence in the neighbourhood, homeownership, having children under 16 years, neighbourhood relations, unemployment rate in the neighbourhood, population density, type of building, ethnic diversity, age diversity and income diversity. *p < .05. **p < .01. ***p < .001.

(its coefficient was B = 0.02, SE = 0.01, p = .002; and for perceived age diversity: B = 0.05, SE = 0.02, p = .065).7 In model 4, we added perceived income diversity, which significantly improved the model fit. The variable was negatively related to neighbourhood attachment, meaning that people living in areas perceived as economically diverse were less attached to their neighbourhood. We also added the perceived percentage of poorer people to the model (not shown in Table 3) in order to test if the negative effect of perceived income diversity was actually driven by a percentage of the poorer effect. The effect of perceived income diversity became no longer significant (B = 0.04, SE = 0.03, p = .089), while the perceived percentage of poorer people was, with a negative coefficient (B = 0.02, SE = 0.01, p < .001).8 It therefore appears that the perceived presence of poorer

people, and not income diversity as such, is likely to reduce neighbourhood attachment.9

The Moderating Role of Neighbourhood Ties

We tested the hypothesis about the moderating role of neighbourhood ties, focusing on each of the dimensions of diversity separately. We first analysed ethnic diversity. In model 2a, we added neighbourhood interethnic ties, and in model 2b, we included an interaction between this variable and perceived ethnic diversity. As Table 4 indicates, neither interethnic ties (introduced in model 2a) nor the interaction between this variable and perceived ethnic diversity (model 2b) was significant, which means that the positive relationship between perceived ethnic diversity and 9

7

We also included an interaction between perceived age diversity and the participant’s age in order to test whether age moderated the effect of perceived age diversity (we thank the anonymous reviewer for this suggestion). This interaction was marginally significant (B = 0.02, SE = 0.01, p = .064). A simple slopes analysis indicated that the negative relation between perceived age diversity and neighbourhood attachment was stronger for the younger (B = 0.09, SE = 0.04, p = .018) than for the older adults (B = 0.00, SE = 0.03, p = .926). 8 The perceived percentage of the rich, on the other hand, when added separately to the model, was not related to neighbourhood attachment (B = 0.01, SE = 0.00, p = .137).

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Additional analyses revealed that there was no significant interaction between own socioeconomic status (measured by self-reported financial situation) and perceived income diversity (B = 0.04, SE = 0.05, p = .408). However, there was a significant interaction between own socioeconomic status and the perceived percentage of poorer people (with perceived income diversity also included in the model) (B = 0.03, SE = 0.01, p = .037). A simple slopes analysis indicated that for participants with higher socioeconomic status, the negative relation between perceived percentage of poorer people and attachment was not significant (B = 0.01, SE = 0.01, p = .535), while for the remaining participants, it was (B = 0.03, SE = 0.01, p < .001). Apparently then, it were not the richer but instead the poorer residents who reacted more negatively to the presence of the poorer.



neighbourhood attachment held regardless of the neighbourhood interethnic ties. For perceived age diversity, we proceeded similarly, but this time, we added ties with neighbours of different ages (model 3a in Table 4) and an interaction between this variable and perceived age diversity (model 3b). The interaction was significant: the negative relationship between perceived age diversity and neighbourhood attachment was present among residents who had few contacts with individuals of different ages but not among residents who maintained numerous such contacts. An analysis of simple slopes indicated that the negative relationship between perceived age diversity and neighbourhood attachment was present among residents who had few contacts with individuals of different ages (B = 0.10, SE = 0.04, p = .004) but not among residents who maintained numerous such contacts (B = 0.02, SE = 0.04, p = .518). This interaction is presented in Figure 1. Finally, we investigated whether neighbourhood ties with people of different income levels moderated the relationship between perceived income diversity and neighbourhood attachment. As model 4b indicates, the interaction between perceived diversity and ties with neighbours of different income was non-significant, indicating that having ties with poorer or richer neighbours does not make people immune to the negative effect of perceived income diversity. Interestingly, an


interaction between perceived income diversity and ties with poorer neighbours was also non-significant (B = 0.04, SE = 0.06, p = .457).

The Mediating Effect of Affective Appraisals

To establish whether the relationships between perceived diversity in the three dimensions and neighbourhood attachment can be explained by affective appraisals of the neighbourhood—that is, as exciting or irritating—we added measures of excitement and irritation to each of the models 2, 3 and 4 separately. Mediation analyses indicate that there was a weak, although significant indirect effect of perceived ethnic diversity on neighbourhood attachment by evaluating the area as exciting (Sobel z-score = 2.45, p = .014). The results are displayed in Figure 2. This means that, contrary to our hypothesis, excitement and not irritation mediated the relationship between ethnic diversity and attachment. As expected, irritation was a negative predictor of attachment, but it was unrelated to perceived ethnic diversity. Interestingly, when measures of excitement and irritation were added to model 3, the direct effect of perceived age diversity on place attachment became more negative and became significant, indicating a

Fig. 1: Effect of perceived age diversity on neighbourhood attachment for persons with low and high share of ties with neighbours of different ages

Fig. 2: Effect of perceived ethnic diversity on neighbourhood attachment through excitement and irritation. Note: * p < .05, ** p < .01, *** p < .001. Unstandardised regression coefficients for the relationship between perceived ethnic diversity and neighbourhood attachment as mediated by evaluating the environment as irritating and exciting. The unstandardised regression coefficient controlling for the two mediators is in parentheses European Journal of Social Psychology 46 (2016) 818–832 Copyright © 2017 John Wiley & Sons, Ltd.

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Fig. 3: Effect of perceived age diversity on neighbourhood attachment through excitement and irritation. Note: * p < .05, ** p < .01, *** p < .001. Unstandardised regression coefficients for the relationship between perceived age diversity and neighbourhood attachment as mediated by evaluating the environment as irritating and exciting. The unstandardised regression coefficient controlling for the two mediators is in parentheses

suppression effect (for an elaboration on suppression effects, see MacKinnon, Krull, & Lockwood, 2000). Further analyses indicated that the indirect effect through excitement was positive and significant (Sobel z-score = 2.22, p = .026), but the indirect effect through irritation was non-significant (Figure 3). It thus appears that in analogy to perceived ethnic diversity, perceived age diversity was positively (although weakly) related to excitement, and this led to higher attachment, but for a fixed level of excitement, perceived age diversity led to decreased attachment.10 After adding excitement and irritation to model 4, the coefficient of perceived income diversity was still statistically significant, and both the indirect effect through excitement (Sobel z-score = 1.37, p = .169) and through irritation (Sobel z-score = 0.58, p = .563) were nonsignificant.

Discussion In this paper, we investigated the relationship between subjective perceptions of three types of diversity—ethnic, age, and income diversity—and neighbourhood attachment while accounting for measures of actual diversity. This study is to our knowledge the first to have analysed the effect of several types of perceived diversity on neighbourhood attachment. Unlike most previous work, which has relied on data from Western Europe and the USA, we focused on a Central-Eastern European country. First, we found that in the studied context, perceived ethnic and income diversity were significantly related to neighbourhood attachment. While this result is consistent with studies establishing a link between perceived ethnic diversity and outgroup attitudes (Hooghe & de Vroome, 2015; Semyonov et al., 2004), our paper contributes to this literature by analysing a different outcome variable—neighbourhood attachment—and other dimensions of diversity. Second, different patterns emerged for each of the three types of perceived diversity. The effect of 10 Additional analyses revealed that the indirect effect of perceived age diversity on attachment through excitement was not significantly moderated by ties with neighbours of different ages.

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perceived age diversity was dependent on the composition of neighbourhood ties: it was related to lower neighbourhood attachment for individuals who had few ties with neighbours of different ages but not for those who had numerous such ties. This indicates that contact with individuals of a different age can neutralise the negative effect of perceived diversity, which is in line with the contact hypothesis (Allport, 1954; Pettigrew, 1998) and corresponds with studies that revealed the role of social ties in moderating the negative effects of ethnic diversity (Górny & Toruńczyk-Ruiz, 2014; Laurence, 2011; Stolle et al., 2013). Importantly, we add to this research by showing that intergenerational ties also matter with regard to perceived age diversity. On the other hand, perceived income diversity was negatively related to neighbourhood attachment, regardless of the income diversity of individual neighbourhood ties. This finding points to the limitations of the role played by intergroup contact for groups based on socioeconomic status. There are several plausible explanations for why perceived income diversity had an overall negative effect on neighbourhood attachment, while age diversity did not. First of all, age diversity is more natural than income diversity because it is more familiar to the residents, at least in the settings we studied. The poor and the rich can relate to each other less than representatives of different generations. Second, an important component of perceived income diversity is the perceived presence of poor residents, which might undermine neighbourhood attachment through the stigmatisation of poor neighbourhoods (Permentier et al., 2009; Stevenson et al., 2014). The latter reasoning is supported by the result that the perceived share of poor residents was a more important predictor of neighbourhood attachment than perceived income diversity. It thus seems that it is the perceived presence of poorer people rather than perceived inequalities in the neighbourhood that undermines place attachment. As our data show, these effects of perceived stigmatisation appear stronger among the poorer than richer residents of the studied neighbourhoods, which may point to the higher vulnerability of this group. An unexpected result, given previous studies reporting that ethnic diversity erodes neighbourhood



attachment, is that perceived ethnic diversity was positively related to neighbourhood attachment. Because the study controlled for the actual proportion of migrants, this finding means that it was not the actual level of diversity that matters but how people perceive it. While this result is probably context-dependent, it highlights that in some settings, ethnic diversity does not have to be related to negative social outcomes but may even yield positive ones. Of course, when interpreting the results of perceived ethnic diversity, it is important to remember that the share of immigrants in Poland is generally low, and although it has been increasing in certain neighbourhoods, this increase is gradual. Meanwhile, it has been suggested that in areas with rather stable ethnic-minority levels over time, ethnic diversity is more likely to be viewed positively (Livingston et al., 2010). The characteristics of the migrant groups might also matter. The Vietnamese migrants, who were the most visible ethnic minority in the studied neighbourhoods, are not problematised in the media and are often portrayed as an ‘invisible’ group. They are also perceived as high in the warmth dimension among the Polish society (Winiewski, 2009). Therefore, in this case, cultural differences between this group and the Poles do not imply clashing norms of neighbourhood life. The positive effect of perceived ethnic diversity may also reflect the multicultural history of Warsaw, which is appreciated by the Warsaw residents (Buchowski & Chlewińska, 2012). It may be that viewing the neighbourhood as ethnically diverse upgrades the neighbourhood, bringing back the pre-war diverse Warsaw. To assess how strongly this result is contextspecific, it would be useful to examine the effect of perceived ethnic diversity on neighbourhood attachment or other community cohesion measures in other locations, both in Poland and other countries. Another unexpected result was that both excitement (positively) and irritation (negatively) were related to place attachment. Apparently then, for some residents, it was relaxation, and for others, it was excitement that contributed to stronger neighbourhood attachment. This may be specific to the studied context: the Ochota district is an urban neighbourhood, close to the city centre. As such, it may be a source of positive excitement, which translates into a stronger emotional bond with the neighbourhood. This may also be a unique feature of the Polish capital city. Findings from a large survey recently carried out on a representative sample of Warsaw inhabitants revealed that, unlike other Polish cities (Lewicka, 2012), in Warsaw, the emotion of excitement was a significant positive predictor of attachment to both the city as a whole and to the residence district (Lewicka, 2015). Contrary to what was expected then, there was a positive relationship between perceived ethnic diversity and place attachment, and it was mediated by the emotion of excitement. Perceived age diversity was also (although weakly) related to excitement; however, for a fixed level of excitement, perceived age diversity had a negative direct effect on place attachment. This suggests that age diversity has both a positive and negative component,


which may have opposing effects on place attachment. However, irritation was not a mediator of the relationship between perceived age diversity and attachment, and neither was it for perceived income diversity. The finding that perceived ethnic and age diversity were related to the emotion of excitement and not irritation suggests that in some circumstances, neighbourhood diversity may trigger positive emotions. These circumstances should be explored further in future studies. One explanation that seems likely is that they involve groups who do not interfere with accepted norms and values of the majority population. In other words, social diversity of a neighbourhood may trigger positive emotions among community members under the condition that it does not interfere with their pragmatic interests (i.e., neighbours do not violate social norms of coexistence). Research in environmental aesthetics has shown that complex and mysterious environments tend to be preferred to environments that are monotonous and homogeneous (Kaplan, 1992; Porteous, 1996). It may be that the presence of the non-interfering and thus harmless ethnically or agediversified neighbours will contribute to the generally positive “aesthetic” judgments of the residence area, manifested in the positive emotion of excitement. Limitations and Future Directions

This study has some limitations that could be addressed in future work. The most important one is that the correlational nature of the data does not allow to establish causality. In fact, establishing causality is generally difficult in studies on place attachment (Lewicka, 2011). While the logic underlying this paper was that the perception of the social composition could impact neighbourhood attachment, an opposite causal path might also be true. For example, residents with weak emotional bonds to their neighbourhood may perceive it as socioeconomically diverse, overestimating the number of poorer residents. Conversely, individuals strongly attached to their neighbourhood may see it as more diverse in ethnic terms, because ethnic diversity makes it more international and thus exciting. To unravel causality in this relationship, longitudinal designs are needed, which could identify changes in neighbourhood attachment over time. Future studies could also examine predictors of perceptions of diversity and factors that contribute to “misperceptions” (see also Piekut & Valentine, 2015). The extent to which perceived diversity reflects actual diversity is also likely to be context-dependent and therefore should be studied in different contexts. Another limitation is the measures of objective diversity we use. Because census data covering the whole population living in units as small as neighbourhoods were not available, we used data from the Social Insurance Institution, which provided information on the social composition of the working population. This could have led to an underestimation of measures of actual income and age diversity and an overestimation of ethnic


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diversity. While we are not aware of other contextual data that could be used for the Polish context, it would be worthwhile to test the studied relationship between different types of perceived diversity and community cohesion indicators with better measures of objective diversity.

Conclusion Despite these limitations, we believe that this study contributes to the literature on the effects of diversity at least in two ways. First, it highlights the meaning of perceived diversity and demonstrates that different dimensions of diversity may have different consequences for neighbourhood attachment and social cohesion in general. Second, it points to the importance of going beyond Western European countries. Our study shows that it is not only the level of diversity that matters but also its type and content, which varies across countries. We therefore argue that the effects of different types of diversity and whether they contribute to a harmonious coexistence in the neighbourhood may depend on the socio-cultural context, specifically on the level and meaning of diversity in a given society.

Acknowledgements This research was financed by grant 2012/05/N/HS6/ 03939, and preparation of the manuscript was supported by grant 2014/12/T/HS6/00487, both from the National Science Centre in Poland, awarded to the first author. We thank Agata Górny and Aneta Piekut, as well as Miguel Ramos—the editor of this special issue —and three anonymous reviewers for their helfpul comments and suggestions.

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