Ethno-racial Diversity and Social Capital in English Schools

Abstract

Since the racial disturbances in the Northern English towns of Bradford, Oldham and

Burnley, the belief has gained strength in educational circles that ethnically mixed

schools contribute to inter-community trust and social cohesion. Several recent studies

from the field of political science, however, have found that trust and participation are

lower in ethnically diverse neighborhoods. This paper explores the relation between

ethno-racial diversity and social capital in English schools using data from the IEA Civic

Education Study. Controlling for various conditions at the individual and school class

level, it finds no effect of diversity on generalized trust and ethnic tolerance. Diversity is

positively related to participation in human rights and environmental organizations and

participation in ethnic and religious associations, however. It further finds social capital,

particularly its bridging form, to be a complex multidimensional phenomenon.

Consequently, it proposes to decompose social capital into its constituent parts – trust,

participation and tolerance.

Key words: social capital, bonding, bridging, ethnic and racial diversity, schools

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Introduction

Desegregation has been a prime educational objective throughout the western world over

the last forty years. Initially, the effort to create ethnically and racially mixed schools was

motivated by indignation about racial inequality and discrimination produced by

segregated school systems. The Civic Rights movement in the US came to epitomize this

effort in its struggle to achieve civic equality, integration and emancipation for African

Americans. The term ‘desegregation’ itself was very much part of and restricted to a

social justice discourse.

From the late 1990s, however, the objective of mixed schools also started to be

embraced by scholars concerned about declining levels of community cohesion and

growing ethnic and religious intolerance. These scholars felt that the prevailing practices

of multiculturalism and recognition of minority cultures had only reinforced the isolation

of ethnic and racial minorities and had led to more divisiveness. Herbert (2001), for

instance, argued that faith schools serving the needs of particular ethnic groups constitute

a kind of ‘educational apartheid’ segregating rather than integrating various ethnic

communities. A string of events in the early 2000s – Nine-Eleven, the racial disturbances

in the Northern English towns of Bradford, Oldham and Burnley, and the London and

Madrid underground bombings – added great weight to the analysis of these scholars and

led to the adoption of their views by various policy makers and government advisers.

Thus, the Cantle Report, commissioned by the British Home Office, suggested that

ethnically segregated schools have contributed to the disorders in Bradford, Oldham and

Burnley and explicitly called for admissions policies maximizing the proportion of pupils

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of the same cultural or ethnic background at 75 per cent in schools in multi-cultural areas

(Cantle 2001).

However, at a time when a consensus in education circles about the benefits of

ethnic mixing seems to be growing, a tradition in the political science field pointing to the

negative effects of diversity on social capital, trust and solidarity is also gaining strength.

A recent important contribution in this tradition is the study on local level community

cohesion in the United States by Putnam (2007). His main finding is that people in

ethnically and racially diverse communities exhibit not only less out-group but also less

in-group trust compared to people in homogenous neighborhoods. In other words,

diversity has a “constricting” effect (p. 144), making people in diverse surroundings

“hunker down – that is, to pull in like turtles” (p. 149).

This raises the obvious question whether Putnam’s findings also apply to schools,

like the neighbourhood a local level phenomenon. In other words, is it possible that

schools with a mixed ethnic intake do not produce cross-cultural integration and bridging

social capital (as hoped for by the Cantle report) but rather its opposite: isolation,

disengagement and distrust? We will explore this question in the present paper by

analyzing survey data collected among 14 year olds in England. We find, firstly, that

social capital, particularly its bridging variety, is a complex phenomenon comprised of

quite unrelated behavioral and attitudinal components. We further find that the effect of

diversity on the attitudinal component (generalized trust and ethnic tolerance) is merely

compositional and therefore spurious. Its effect on the behavioral component

(participation in several organizations) is positive however, which supports the notion

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that ethnic mixing contributes to inter-ethnic harmony (i.e. the key assumption of the

Cantle report).

We start by discussing the much used concept of social capital, the dependent

variable of this paper. We then review the political science literature on relation between

diversity and social capital and examine to what extent educational studies have

addressed this issue. Subsequently, we discuss the data source, research design and

methodology used for the analyses. Finally we present the results of these analyses. The

conclusions rehearse the main findings and offer suggestions for further research.

Social capital

A term widely used in the social sciences to include notions of trust, cooperation and

community cohesion is social capital. In fact, Putnam has been recognized as the key

scholar promoting this concept ever since he published Making Democracies Work: Civic

Traditions in Modern Italy (1993), in which he argued that social capital enhances the

performance of democratic government. In his 2007 study it is therefore the relation

between diversity and social capital that Putnam essentially examines, albeit with a

strong focus on trust as one of its components. Defining the concept as “social networks

and the associated norms of reciprocity and trustworthiness” (Putnam 2007: 137), he

contends that social capital, like monetary and human capital, is a desirable asset in that it

contributes to the health, happiness, civic mindedness and career opportunities of the

individuals who possess it. Social capital is further said to have positive spillover effects

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for outsiders: living in an area rich in social networks contributes to trust in neighbors

and feelings of safety even if one does not join community life oneself. As we seek to

replicate Putnam’s study for schools, we adopt his definition of the term and will

operationalise the concept in accordance with this definition.

Embracing Putnam’s definition of social capital does not mean that we apply the

term without reservations. Two important objections can be raised. First, as the term

incorporates several notions with some referring to attitudes (trust and norms) and others

to behaviors (networks, association, cooperation), it can be criticized for being an

incoherent concept comprising a number of disparate components. This criticism does not

seem to be of great concern to Putnam, though, as he simply assumes social capital to

refer to a coherent syndrome of attitudes and behaviors at the individual level:

Our discussion of trends in social connectedness and civic engagement has tacitly

assumed that all the forms of social capital that we have discussed are themselves

coherently correlated across individuals. This is in fact true. Members of associations are

much more likely than non-members to participate in politics, to spend time with

neighbors, to express social trust and so on (Putnam 1995: 73).

To be sure, there is research supporting this assumption for a number of western

countries including the US and Great Britain (Brehm and Rahn 1997; Hall 1999).

However, studies examining a much larger set of countries have found the components of

social capital to be only weakly correlated across individuals (Newton and Norris 2000;

Janmaat 2006). Janmaat (2006) moreover argues that the external distinctiveness of the

concept can be called into question because the correlations among the social capital

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components are not stronger than the correlations of these components with external

conditions. From a policy perspective working with concepts that are not internally

consistent is troublesome, as it may well mean that interventions aimed at fostering one

particular component do not contribute to other components – or worse affect them

negatively (see also Janmaat 2008; Tolsma et al 2008). In the empirical section we will

therefore explore to what extent our indicators of social capital intercorrelate and form a

distinctive syndrome.

Secondly, it has been pointed out that social capital can take many forms, some of

which are not commendable such as youth gangs, ethnic militias or terrorist

organizations. Putnam (2007: 138) is the first to acknowledge this, calling for instance Al

Qaeda “an excellent example of social capital, enabling its participants to accomplish

goals they could not accomplish without that network”. Yet, he maintains that social

capital by and large is a positive phenomenon leading to happier, healthier and better

educated people and making democracy and the economy work better. Still, in our view

this objection cannot be dismissed this easily, particularly because it relates to that other

important issue in social capital theory: the distinction between bonding and bridging

forms of social capital. The bonding variety refers to small, culturally homogenous

communities characterized by ‘thick’ forms of trust, solidarity and cohesion, and high

levels of exclusion. Bridging forms, by contrast, refer to broad outward-looking networks

uniting people of various backgrounds who interact on the basis of mutual respect

(Putnam 2000). The latter are usually seen in a more positive light as they are considered

to contribute to tolerance, overall integration and societal cohesion (Granovetter 1978).

The former on the other hand are looked upon with much more ambivalence: bonding

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forms may help minority groups in finding their way in the wider society but they may

also enhance ethnocentrism, oppose society and fuel intercommunity distrust and

hostility. Examples of this divisive form of bonding social capital are abundant and not

just restricted to the extreme groups mentioned above. It suffices to refer to the religious

communities in Northern Ireland and in Lebanon and the ethnic communities in Bosnia

and in Sri Lanka to show that even more moderate forms of exclusive bonding can have

disastrous effects for society at large (Green et al 2006).

Clearly, it was fear of the divisive variety of bonding social capital that has

motivated the authors of the aforementioned Cantle report to advocate ethnic mixing.

This makes the distinction between bonding and bridging social capital highly relevant

for the current study. Is there a tension between bonding and bridging social capital as the

Cantle report implicitly implies, and are schools with a mixed ethnic intake therefore

undermining bonding forms but fostering bridging forms? Or is diversity affecting both

forms of social capital, as Putnam’s study shows? Or is diversity connected in completely

unexpected ways to bonding and bridging forms of social capital? These are the key

questions we will address in the empirical section.

The attentive reader might ask why we focus on Putnam’s conception of social

capital when there is literature relating the concept specifically to youngsters, which is

after all the target group of this study. Coleman (1988), for instance, argues that social

capital as manifested in the family and in the immediate environment of children, i.e.

micro forms of social capital, are particularly important for the creation of human capital

and school performance of youngsters. In his view, a crucial property of this environment

is the degree of intergenerational closure of networks of parents and children: the better

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parents know the parents of their children’s friends, the more likely they are to develop

mutually agreed norms and sanctions regulating their children’s behavior and

contributing to their academic achievements. Coleman’s conception of social capital,

however, is incapable of addressing issues of inter-community trust, solidarity and self-

organisation, which is the key concern of the Cantle report. Indeed, it is entirely

imaginable that multi-ethnic communities display both high levels of intergenerational

closure within each group (i.e. high levels of bonding) and high levels of inter-group

hostility (i.e. low levels of bridging) simultaneously. For this reason we focus on

Putnam’s bonding and bridging forms of social capital and disregard scholars who

understand social capital as an individual or micro-level property (e.g. Bourdieu (1986)

who considers social capital to be a resource possessed and exploited by individuals).

Another reason to embrace Putnam’s conception of social capital is the growing

body of research claiming that its key components, trust, tolerance and participation, are

shaped in one’s formative years and will change little thereafter (Stolle and Hooghe

2004; Flanagan and Sherrod 1998). It is thus highly relevant to explore the conditions

affecting the acquisition of these attitudes and behaviors by adolescents since this is

precisely the age group in which these outcomes take definite shape.

The diversity perspective

At its core the diversity perspective argues that cultural similarity enhances trust,

solidarity and cooperation. While some scholars seem to accept this claim as a given fact

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(e.g. Alesina and La Ferrara (2002: 208), who argue that people have “a natural aversion

to heterogeneity”), others have sought to explain the relation theoretically. Conflict

theorists for instance assert that it is the competition over scarce resources that fuels intra-

group solidarity and inter-group hostility. The more often people encounter members of

ethnic out-groups in their daily lives and the larger the size of these out-groups, the

tighter their in-group bonding and stronger their fear of ethnic others (Bobo 1999;

Quinlan 1995). From a slightly different viewpoint, evolutionary theorists have also

pointed to the mechanism of group competition. Thus Salter (2004) contends that the

current propensity of people to bond with ethnic kin and be distrustful of ethnic others is

the result of a long historical process in which clans and tribes with internal mutual

support schemes have outperformed groups lacking these support systems in the group

struggle for survival. In this perspective, multiethnic societies will continue to be troubled

by ethnic conflict, ethnic nepotism and faulty welfare systems.

However the diversity argument is elaborated theoretically, its advocates have

marshaled an impressive amount of research evidence in support of their claims. Most of

this research relates to the United States and Canada, where a series of studies have found

a negative relation between ethnic or racial heterogeneity on the one hand and trust,

cooperation and solidarity on the other at the city or state level (e.g. Alesina, Baqir and

Easterly 1997; Hero and Tolbert 1996; Luttmer 2001; Soroka, Johnston and Banting

2004). Combining tract level data from the census and public opinion data from the

General Social Survey, Luttmer, for instance, discovered that white support for welfare

spending diminishes as the proportion of black recipients of welfare in the tract

population increases. This result indicates that racial heterogeneity seems to be

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particularly harmful for social solidarity if racial cleavages coincide with social

inequalities. Focusing on Canada, Soroka, Johnston and Banting (2004) established that

interpersonal trust diminishes as the proportion of visible minorities in census tracts

increases, and that trust in turn is positively linked to pro-welfare attitudes.

The aforementioned study by Putnam (2007) is the latest in this string of studies.

Controlling for a number of individual and contextual conditions, he found that diversity

does not only reduce both in- and out-group trust, but is also showing a negative link with

other civic attitudes such as cooperation, altruism, political efficacy and confidence in

local institutions. Putnam believes though that this negative impact of diversity is likely

to be only temporary. In the long run, “successful immigrant societies create new forms

of social solidarity and dampen the negative effects of diversity by constructing new,

more encompassing identities” (ibid. pp. 138,139) He explicitly notes that ethnic and

racial identities are dynamic, socially constructed phenomena and that therefore the

substance of diversity can change with some cleavages becoming less and others more

salient over time.

Research highlighting a negative link between diversity and trust is

counterbalanced however by studies finding no effect for diversity. In her study of formal

and informal social capital in 839 British neighbourhoods, Letki (2008), for instance,

found that the socio-economic status of a neighbourhood was the most important driver

of social capital, while its ethno-racial composition hardly mattered. Oliver and Wong

(2003) even found a positive relation between community heterogeneity and favorable

attitudes towards out-groups. People living in homogenous areas turned out to have

stronger ethnic stereotypes and to be more suspicious of ethnic others. Tolsma et al

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(2008) observe that ethnic diversity can be related in completely different ways to various

components of social cohesion. In their study of 503 neighbourhoods and 245

municipalities in the Netherlands, they found that ethnic diversity is not conducive to

volunteering and the frequency of contacts with neighbours, but contributes positively to

ethnic tolerance and shows no relation with generalized trust. Summarizing this

contradictory evidence, we can conclude that the nature of the link between diversity and

social capital seems to vary across different components of social capital and different

countries and to depend on the number and kind of control variables included in the

analysis. The review thus only adds weight to the concern raised above that social capital

encompasses a collection of highly disparate notions.

Remarkably, the education literature seems not to have picked up on the explosion

of political science studies suggesting a negative link between diversity and social

capital. Traditionally, educationalists have been more concerned with the effects of ethnic

and racial segregation on student performance (e.g. Orfield 1978; Rumberger and Willms

1992). Yet, there is a distinct tradition within the field of education examining the

consequences of (de)segregation for inter-racial friendships, inter-cultural understanding

and comfort in dealing with multi-cultural settings. Recent studies in the US by

Frankenberg et al (2003) and Holme et al (2005), for instance, found that the experience

of racially mixed schools left graduates with a better understanding of different cultures

and an “increased sense of comfort in interracial settings” (ibid p. 14). Research by

Ellison and Powers (1994) and Sigelman et al (1996), moreover, shows that the tolerant

attitudes and interracial friendships developed in racially integrated schools persist into

adulthood. Holme et al (2005) further claim that the daily experience of interracial

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schooling is much more effective in this regard than multicultural curricula or student

exchange programs. Bruegel (2006), investigating inter-ethnic frienships among pupils of

12 primary schools in London and Birmingham, reaches similar conclusions. In her view,

“the day-to-day contact between children [of different ethnic background, XX] has far

more chance of breaking down barriers between communities, than school twinning and

sporting encounters” (ibid. p. 2). Given her positive appraisal of racially mixed schools,

she is skeptical of policies promoting school choice as these might have the unintended

effect of promoting segregation. Other research in the UK focusing on community

relations in Northern Ireland has argued that integrated (i.e. mixed faith) schools “impact

positively on identity, outgroup attitudes, forgiveness and reconciliation” (McGlynn et al,

2004: 1). All these studies can thus be said to strongly refute the aforementioned conflict

perspective: daily contact between people of different ethnic or racial background does

not contribute to interethnic hostility but to its opposite: inter-ethnic understanding and

trust, in short to bridging social capital

Yet, not all educational research points in this direction. In fact, a thorough review

of the literature on the effects of school desegregation observed that the extant research

was strikingly inconsistent in its findings (Schofield 2001). While many studies indeed

point to the positive effects of ethnic mixing for out-group attitudes, others suggest the

opposite or claim there is no effect, and again others argue that the effects are different

for majority and minority groups. Our analyses will allow us to explore all these

possibilities for both bonding and bridging social capital.

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Data, indicators and method

We explore the relationships between diversity and social capital by analyzing data of the

IEA Civic Education Study (Cived) (Torney-Purta et al 2001). This study consisted of a

large scale survey conducted in April 1999 among a sample of 90,000 14-year-olds in 28

countries worldwide. To this day, the Cived study has not enjoyed the same level of

popularity as other large international surveys addressing civic values, such as the World

Values Survey, the ISSP and the Eurobarometer. This is somewhat surprising given the

quality of the data. Not only are the national samples much larger in the Cived study

(around 3000 respondents in each country), the non-response is also significantly lower

than in the other surveys. One of the advantages is that respondents of immigrant origin

are represented to a sufficient degree (the share of these minorities ranges between seven

to twenty per cent of the national samples of a number of West-European states). Given

the nested character of the national samples, with one class being selected in 120-200

sampled schools in each participating country, the Cived study further allows researchers

to explore both contextual effects (such as diversity) and individual-level factors. We

selected the national sample of England, which is composed of 3043 students selected in

128 schools (i.e. classes).

Social capital

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Ideally, the bonding and bridging forms of social capital are explored with measures

reflecting in- and out-group trust, solidarity and cooperation. Unfortunately, apart from

two items on participation in an ethnicity or religion-based organizations, the Cived

questionnaire does not have questions capturing the ethnic in/out-group notion. It does

however include items covering the different scales at which the bonding and bridging

forms can be said to operate. While bonding social capital is clearly a micro-level

phenomenon reflecting close contacts with family, friends, classmates and ethnic kin,

bridging social capital refers to the often infrequent ties that bind people of different

backgrounds together at various levels, micro, meso and macro. The latter moreover can

be said to include notions of tolerance and respect for people who are culturally or

ideologically different. In line with these definitions, we devised one measure reflecting

the bonding form and three measures reflecting the bridging form of social capital:

Bonding Bridging

- Participation in ethnic and religious - Participation in human rights and

organizations environmental organizations

- Generalized trust

- Ethnic tolerance

The measure for bonding social capital was tapped with the item “have you participated

in the following organizations? (1) a cultural association based on ethnicity; (2) an

organization sponsored by a religious group”. Based on the answers to this item, we

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created a binary variable with values 0 [no participation] and 1 [participated in one or

more organizations].

We did likewise for participation in human rights and environmental

organizations, which we considered to reflect bridging social capital. Although this

measure does not capture the in/out-group dimension, it does nicely represent the broad,

outward-looking forms of association said to be typical of the bridging variety. Moreover,

according to Hooghe (2003) an organization’s ideology is more important than the ethnic

or social make up of its member base for the promulgation of values like tolerance and

intercultural understanding. Analyzing survey data of the adult population in Flanders,

Belgium, he found that membership of environmental and human rights organizations

was particularly negatively related with ethnocentrism (i.e. the counterpart of tolerance),

controlling for many background variables including education.

Generalized trust was tapped with an item asking respondents how much of the

time they trusted the people “who live in this country” <categories: never – only some of

the time – most of the time – always>. Because of the explicit reference to the national

scale in this item we considered it to reflect bridging social capital. The bridging nature

of this item is moreover supported by Uslaner (2000: 575), who found generalized trust

to be closely linked to trust in strangers.

We further used a ready-made scale in the Cived database as a measure of ethnic

tolerance, our third indicator of bridging social capital. The scale clusters the following

five items on immigrants and is internally consistent with an alpha reliability of .82

(Torney-Purta et al 2001, 208):

(1) Immigrants should have the opportunity to keep their own language;

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(2) Immigrants’ children should have the same opportunities for education that other

children in the country have;

(3) Immigrants who live in a country for several years should have the opportunity to

vote in elections;

(4) Immigrants should have the opportunity to keep their own customs and lifestyle;

(5) Immigrants should have all the same rights that everyone else in a country has.

Categories: <strongly disagree – disagree – agree – strongly agree>

These items, it must be noted, seem to reflect primarily accommodating views on

immigrants rather than ethnic tolerance. However, Ford (2008) showed that such views

are strongly linked to ethnic tolerance (as measured, in his research, by attitudes on social

contact with ethnic minorities at work or in the family). Pettigrew (1997) moreover found

these views to correspond in the same way as ethnic tolerance to a number of explanatory

conditions including intergroup contact. Theoretically it is also highly plausible that the

two are intimately related. Expressing disagreement with the five statements implies

privileging the native majority over immigrants, a mindset which intuitively goes

together with ethnocentrism and prejudice – the very antonyms of ethnic tolerance. For

these reasons we assumed the five-item scale to be a good proxy of ethnic tolerance. The

higher the values on this scale, the more the respondent agrees with the five statements

and the more tolerant we consider him/her to be.

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Independent variables

We collected the answers to the question “which best describes you”1 to calculate the

proportion of pupils not identifying as white, and used this proportion as a class-level

measure of ethnoracial diversity, our main variable of interest (henceforth simply called

‘diversity’). Properly speaking this measure refers to density, which does not necessarily

correspond to diversity. Density, for instance, is high and diversity low in situations

where a single ethnic minority group makes up the majority of the class population.

However, having carefully examined the data, we found that classes with high ethnic

densities were also relatively diverse in terms of the number of children of different

ethnic groups. For this reason we considered this measure of density to be a good proxy

of diversity. Moreover, density measures have the distinct advantage of not being colour

blind like the more traditional measure of diversity, the Herfindahl Index of

Fractionalization (Tolsma et al 2008). Unlike the latter, density measures are able to

distinguish a situation of an 80% native majority and a 20% ethnic minority from its

mirror image (80 % ethnic minority and 20 % native majority). Being able to distinguish

between the two situations obviously matters for West-European countries because

differences between the ethnic majority and ethnic minorities are accentuated by gaps in

socio-economic status.

In subsequent analyses we will explore the effect of diversity controlling for a

number of individual and class-level conditions. The individual level conditions are: (1)

1 The answer categories of this question are: (1) White; (2) Black Caribbean; (3) Black African,; (4) Black other; (5) Indian; (6) Pakistani; (7) Chinese; (8) Bangladeshi, (9) Other

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gender [0 – girl; 1 – boy]; (2) Social status [scale with six values] (based on the item

‘number of books at home’; this item is strongly correlated with ‘education mother’ and

‘education father’; unlike Hooghe et al (2007) we chose not to create a composite index

combining all three items because of high numbers of missing values on the education

items); (3) civic competence (a ready-made composite measure based on the results of a

civic knowledge and skills test); (4) ethnoracial identity [0 – white; 1 – non-white] (based

on the “which best describes you” item). The importance of each of these conditions in

shaping different components of social capital has been amply demonstrated in the

literature: on the effect of gender, see Verba, Brady and Schlozman (1995) and Hooghe

and Stolle (2004); on that of social status and educational attainment in particular, see

Dalton (2004), Nie, Junn and Stehlik-Barry (2004) and Hagendoorn (1999); on that of

civic knowledge and skills, see Galston (2001) and Delli, Carpini and Keeter (1996); on

that of ethnic background, particularly of a non-western kind, see Rice and Feldman

(1997).

The inclusion of ethnoracial identity enables us to assess whether diversity

represents a true contextual effect exerting an independent influence on the dependent

variables or whether it is merely a compositional effect reflecting no more than the sum

of individual differences. A class-level condition is a true contextual effect if the social

capital levels of all students in that class are affected by this condition. The condition is

only a compositional effect if it no longer exerts an independent effect on social capital

once it is controlled for its individual level equivalent. For example, if differences in

social capital are solely a function of individual ethnoracial identity, then the diversity of

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a class is nothing more than a compositional effect. If diversity affects all students in that

class, in addition to the effect of ethnoracial identity, then it is a contextual effect.

We used two class-level conditions as control variables. The first of these –

classroom climate – is the class average of a ready-made scale in the database labeled as

‘an open climate for classroom discussion’. Previous research by Torney-Purta (2002,

2004) on the same dataset has shown that this variable is strongly correlated to various

components of social capital. The second is class status, which is the class average of the

aforementioned individual-level social status. Many studies have pointed to the

importance of this contextual condition for a range of social outcomes. As noted before,

Letki (2008) found low neighbourhood status to be particularly harmful for both formal

and informal forms of social capital. In similar vein, Oliver and Mandelberg (2000) note

that residents in low status neighbourhoods are often exposed to crime, decay and

disorder, leading them to develop feelings of anxiety, alienation, and suspicion towards

strangers.

Table 1 provides the descriptives of all variables. The distribution of scores on the

trust variable (‘never’ – 5.1%; ‘only some of the time’ - 29.5%; ‘most of the time’ –

36.5%; ‘always’ – 12.6%) appears to approximate a normal distribution, which means

that it can be analyzed as a continuous variable in a linear regression model. The ethnic

tolerance scale can likewise be treated as a continuous variable. The scores on the other

two dependent variables (the two participation measures) very much lean towards non-

participation (85.1% and 85.3% not participating in religious/ethnic and

environmental/human rights organizations, respectively). We treat these measures as

binary variables and will consequently analyze them in logistic regression models.

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Among the independent variables we find that ethnoracial diversity is highly skewed

towards the homogenous end, the average share of non-white students being only 12.7%.

Unsurprisingly, the variable on which diversity is based, ethnoracial identity, is tilted in a

similar manner with a mere 12.6% not identifying as white.

Table 1 about here

We further note that the strength of the correlations among the contextual variables is not

such that there is a risk of multicollinearity in subsequent analyses (these correlations are:

-.03 between diversity and class status; .14** between diversity and classroom

climate; .36** between class status and classroom climate). Remarkably, ethnoracial

diversity and class status are only weakly correlated, which runs counter to the common

perception that diversity is closely linked to deprivation.

Finally, we examine the internal consistency of social capital and its bonding and

bridging varieties. Table 2 presents the bivariate correlations among and between the

three measures of bridging and the one measure of bonding social capital. It turns out that

our aforementioned skepticism towards the concept is more than warranted: we see that

the three indicators of bridging social capital are strikingly uncorrelated. In other words,

generalized trust, participation in inclusive organizations and ethnic tolerance do not

necessarily go together. By contrast, the two participation measures, although tapping

different varieties of social capital, are strongly correlated, blurring the difference

between bonding and bridging. The only relation supporting the notion that there is

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tension between the two forms of social capital is the negative correlation between

generalized trust and participation in ethnic/religious organizations.

Table 2 about here

What the pattern of correlations above all shows is the autonomous nature of the two

attitudinal measures vis-à-vis each other and vis-à-vis the two participation measures.

This does not only undermine the distinction between bonding and bridging forms of

social capital but also the validity of the concept of social capital itself. Our findings thus

strongly contrast with those of Brehm and Rahn, who, as noted before, did find a

cohesive social capital syndrome of attitudes and behaviors at the individual level.

Because our indicators neither cluster neatly in a bridging dimension of social capital nor

in an overall syndrome of social capital, we will explore them individually in the ensuing

analyses. We would like to emphasize that our continued use of the terms bonding and

bridging does not suggest that we hold these theoretical concepts to refer to well-

demarcated empirical phenomena.

Method of analysis

Since our independent variables are pitched at two levels (class and individual) and our

dependent variables are at the individual level, the appropriate method to explore the

relationships between diversity and social capital is a multi-level analysis. This is all the

more required given the nested structure of the data. A structure of this kind, with

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students being nested in classes, classes in schools, and schools in countries, precludes

the use of more conventional multiple regression techniques since these require that

observations are independent. Using such techniques to analyze nested data would result

in an underestimation of the standard errors of the contextual variables (and therefore an

overestimation of the effects of these variables). Aggregating the dependent variables to

the level of the independent contextual variables and performing a conventional

regression analysis at that level is not a solution either as this makes it impossible among

the independent variables to distinguish contextual effects from effects resulting from the

aggregation of individual characteristics (i.e. composition effects) (Hooghe et al 2007;

Snijders and Bosker 1999).

We used Mlwin software to analyze a two level model consisting of classes (level

2) and students (level 1) with ethnoracial diversity, class status and classroom climate

entered as class-level variables and gender, social status, civic competence and

ethnoracial identity entered as individual-level variables. We first explored whether the

effects of the individual-level variables interacted with the contextual variables. This

possibility should certainly not be ruled out since there are studies demonstrating that the

effect of ethnoracial identity on tolerance changes along with the ethnic composition of

the school or neighbourhood. Researching racial prejudice in the American South, Glaser

(1994) for instance shows that racial hostility among respondents identifying as white

increases the more racially diverse the area they live in is. By contrast, and more relevant

for the current paper, Billings and Holden (2007) found ideas of racial superiority among

white 15-year olds in Burnley to be particularly strong in homogenously white schools.

22

However, entering interaction terms of diversity x identity and diversity x social

status in the models, we found no evidence of interaction effects (results can be obtained

from the author). . In other words, ethnoracial identity and social status were correlated

in more or less the same way to the four social capital outcomes across different levels of

diversity. We therefore decided to employ relatively straightforward random intercept

models consisting only of main effects to examine the relations of interest. These models

assume individual-level effects to be constant across classes.

Results

We report on the results in a stepwise fashion. First we present the results of the zero

model, which provides an estimate of the variance in our outcome measures at the class

(L2) and individual (L1) levels (see the columns marked with 0 in Table 3). We then

report on models including only diversity as explanatory variable (Columns I).

Subsequently we present the results of models including the three contextual variables

(Columns II). Finally, we report on models containing all explanatory variables (Columns

III). This procedure allows us to assess (1) whether the variance at the class level is large

enough to warrant multilevel analysis, (2) whether ethnic diversity constitutes a true

contextual or merely a compositional effect, and (3) how much the variance is reduced

after the inclusion of more variables in the models.

Table 3 about here

23

The zero models show that the class level captures 1.7% and 11.2% of the total variance

in generalized trust and ethnic tolerance, respectively (as indicated by the Intraclass

Correlation Coefficients (ICC), which represent the proportion of the total variance in the

outcome measures accounted for by all observed and unobserved factors operating at a

distinct level). According to Duncan and Raudenbusch’s (1999) rule of thumb, these

percentages represent small/medium and very large effect sizes respectively.

Consequently, while the application of multilevel analysis is of marginal utility for trust,

it is a must for ethnic tolerance. ICCs could not be computed for the other participation

outcomes since these are explored using logistic regression. Subsequent analyses will

show, however, that the contextual variables have quite a substantial effect on these

outcomes, thus justifying the use of multilevel analysis.

Examining the effect of diversity without any of the control variables (Model I),

we see that diversity is related in quite different ways to the four social capital indicators.

While diversity is negatively linked with generalized trust, it shows a positive correlation

with ethnic tolerance (though not significant) and the two participation measures. This

pattern of links, moreover, holds when we control for class status and classroom climate,

the other two contextual variables (Model II; note that the link with ethnic tolerance

becomes significant). Thus, unlike Letki (2008) we do not find social status to be the

most important factor at the group level overwhelming the impact of ethnic diversity.

More generally, it can be seen that the effect of diversity is not consistent across the three

indicators of bridging social capital, adding further weight to our observation in the

previous section that there is little empirical support for distinguishing between bonding

24

and bridging forms of social capital. We further note that these results so far are

consistent with other studies finding a negative relation between diversity and trust at the

aggregate level (e.g Pennant 2005; Soroka et al 2004; Delhey and Newton 2005).

Moreover, Putnam (2007) also found ethnic diversity to be negatively related to trust and

positively related to alternative forms of political participation across neighborhoods in

the US.

Will these relations hold, however, once we start controlling for individual level

variables? (Model III). We see a marked difference arising between the attitudinal and

behavioral outcomes. While ethnic diversity no longer shows a significant relation with

trust and tolerance, it retains its positive link with each of the two participation measures.

The effect of ethnic diversity is thus spurious with regard to the two attitudinal outcomes,

reflecting merely the sum of the individual-level effects. In other words, it represents a

compositional and not a true contextual effect for these outcomes.

Among the individual-level controls, ethno-racial identity emerges as a

particularly strong condition affecting trust and tolerance in contrasting ways: non-whites

are significantly less trusting and significantly more tolerant than whites. As the ethnic

tolerance measure reflects attitudes on immigrants it is not surprising to find non-whites

showing higher levels of tolerance. These higher levels are likely to reflect an awareness

among minority students that they are themselves (descendents of) migrants and are seen

as such by the dominant group. The non-white students may in other words have

identified with immigrants. Having restrictive opinions on immigrants as a non-white

would thus entail agreeing to be placed in a subordinate position with respect to the

ethnic majority, which, understandably, few minority students would find appealing. In

25

this sense, our ethnic tolerance measure is likely to have only tapped tolerance levels

among whites.

The negative link between minority identity and trust is more puzzling, all the

more so since it has been controlled for gender, social status and civic competence.

Possibly, it can be explained by the specific wording of the item on trust. Students may

have understood the words “the people who live in this country” as referring to the native

majority. If so, the trust item has actually functioned as a measure of in-group trust for

white students and of out-group trust for non-white students. However, if it has been

interpreted this way, then this interpretation must have been unique to Britain because

Janmaat (2008), using the same data set, has not found a similar negative relation

between minority identity and generalized trust in several other West-European states

with large immigrant populations.

Why are the attitudinal outcomes so unrelated to ethnic diversity once we control

for individual-level conditions? We can only speculate about the reasons. Possibly,

youngsters have become so much used to the presence of ethnic minorities in the media

or to direct contact with cultural others in their neighbourhood that the ethnic

composition of the class or school matters less than it used to. Indeed, in Ford’s (2008)

view, the daily exposure to black and Asian Britons on the television and in other

environments is one of the principle factors explaining the steady decline in racial

prejudice among the native majority in Britain. Alternatively, schools’ attempts to

encourage independent thinking or the process of individualization more generally may

have caused the opinions of individual students to be less guided by those of their

26

classmates than before, thus undermining the impact of contextual conditions such as

ethnic diversity.

The positive link of ethnic diversity with the two participation outcomes is no less

difficult to interpret. After all, with participation in ethnic and religious organizations

reflecting bonding social capital and participation in environmental and human rights

organizations representing bridging social capital, these findings are neither in line with

the contact nor with the conflict perspective. Both perspectives assume the two forms of

social capital to be mutually exclusive, but the former expects ethnic diversity to be

positively linked to bridging and negatively linked to bonding social capital while the

latter expects the very opposite pattern of relationships. Moreover, the findings contrast

totally with Putnam’s constrict perspective which anticipates a negative effect of

diversity on both forms of social capital.

What could explain the positive relation of diversity with participation in

environmental and human rights organizations? Again we cannot do more than suggest

possible causal mechanisms. Perhaps the experience of being in a diverse class and

learning about other cultures triggers an individual pupil’s interest in and sense of

involvement with broader issues, which then results in membership of the named

organizations. This mechanism, obviously, would be in line with contact theory. Perhaps

the initiative comes from the school and it is the relatively diverse schools which invest

more time and effort in establishing links with the named organizations than the

homogenous schools. Finally, the positive relation could be the result of selection.

Students participating in these organizations may have parents who value diversity (or do

not object to it) and send their children to ethnically mixed schools (or keep them in these

27

schools), accordingly. We could likewise propose mechanisms linking ethnic diversity to

participation in ethnic and religious organizations However, because of the cross-

sectional nature of the Cived data, we cannot explore all these possibilities.

Whatever the precise mechanisms linking diversity to the two participation

outcomes, our main finding is that diversity relates differently to the attitudinal and

behavioral components of social capital. This is another sign that not only the bonding

and bridging varieties but also the concept of social capital itself need to be reevaluated.

After all, the core assumption of social capital theory, that participation automatically

generates a specific set of attitudes, trust and tolerance including, is not supported by our

findings, neither those pertaining to the interrelations among the social capital indicators

nor those relating to the drivers of social capital outcomes. Thus, while our findings may

be welcome news for those convinced that ethnic mixing is conducive for participation

and engagement, they simultaneously question the assumption that participation has

wider benefits for social cohesion.

Concluding remarks

Does ethno-cultural diversity in the classroom help in creating bridging social capital?

This paper revealed that the answer to this question very much depends on the component

of bridging social capital under investigation. Controlling for various conditions at the

individual and class level, ethno-racial diversity showed no relation to attitudes like

generalized trust and ethnic tolerance while it is positively related to participation in

28

environmental and human rights organizations. Thus, at least for the behavioral

component of bridging social capital this study supports the contact perspective: ethnic

diversity makes people open up rather than hunker down as Putnam claims. Trust and

tolerance, as the attitudinal component, were mainly shaped by individual-level

conditions, with ethno-racial identity being the most prominent among them. In other

words, the effect of ethno-racial diversity on these attitudes was found to be spurious,

reflecting a mere compositional (i.e. sum of individual-level properties) and not a true

contextual effect. This study has thus demonstrated that it is vital to include individual-

level variables in the analysis when assessing the impact of contextual properties on some

social capital related outcome of interest.

However, a more important finding in our view is the lack of coherence among

the social capital indicators. Participation in environmental and human rights

organizations was found to be uncorrelated with trust and tolerance, the other two

indicators of bridging social capital, while it did show a strong positive link with

participation in ethnic and religious organizations, our indicator of bonding social capital.

Trust and tolerance moreover proved to be unrelated. These results raise serious doubts

about the empirical utility of the concept of social capital and its bonding and bridging

forms, and the study thus adds to a growing body of research critical of these concepts.

The effort to develop inclusive concepts reducing the complexity of social reality is

understandable from the point of view of parsimony but this should not result in concepts

that are as multidimensional and complex as the reality they seek to simplify. If reality

resists parsimonious descriptions it is better to acknowledge its complexity and act

accordingly. In the case of social capital this would mean focusing on its individual

29

components: trust, tolerance and participation. The continued use of multidimensional

terms like social capital is even harmful, we would argue, because it might give policy

makers the false impression that measures can be devised that foster a range of social

capital qualities all at once.

Our study is limited in three important ways however. First, although our

indicators of bonding and bridging have nicely tapped the scope of both kinds of social

capital, they could only partially address the crucial issue of within (i.e. bonding) and

between (i.e. bridging) group cohesion. It is clearly the in/out group dimension which is

of most concern to policy makers. It is vital that future survey studies such as the

International Civic and Citizenship Education Study (ICCS – the successor of the IEA

Cived study) include items on in- and out-group trust, solidarity and cooperation. Second,

due to the single point in time character of the data source, it was impossible to determine

the direction of causation or to explore the causal mechanisms linking (or not linking)

ethnic diversity to the four social capital outcomes. Finally, the Cived study’s restriction

to a single age group invalidated an assessment of age, cohort and period effects,

meaning that we could not explore the stability of behaviors and attitudes acquired during

adolescence. Although, as noted previously, there are several studies suggesting that civic

attitudes and behaviors obtained in one’s formative years are relatively enduring, there is

no consensus on this issue. A longitudinal research design involving parallel panels or

repeated cross-sections of multiple age groups would be able to address these limitations.

30

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Table 1. Descriptive statistics of dependent and independent variables.

Values of categorical variables

Minimum Maximum

Mean Standard deviation

N

Dependent Generalized rust 1 4 2.68 .80 2547Ethnic Tolerance 4.04 14.17 9.73 2.24 2737Part in eth&reli org No 85.1% 2985

Yes 14.9%

38

Part in env&hr org No 85.3% 2985Yes 14.7%

IndependentEthnoracial diversity 0 94.4 12.68 18.1 3043Class status 3.12 5.87 4.40 .55 3043Classroom climate 7.85 13.56 9.98 .84 3014Social status 1 6 4.40 1.32 2982Civic competence 40.62 165.04 99.40 18.86 3013Ethnoracial identity white 87.4% 2972

non-white 12.6%Gender girl 50% 2957

boy 50%

Table 2. Relations between social capital components (bivariate correlations)

Bonding social capital

Bridging social capital

Participation in ethnic and religious

organizations

Participation in environmental and human

rights organizations

Generalized trust

Ethnic tolerance

39

BondingPart in eth and rel org - .34** -.05* .02

BridgingPart in env & hr org - .01 -.01Generalized trust - .00

40

Table 3. The determinants of social capital (coefficients of multilevel linear and logistic regressions)

Bonding social capital Bridging social capitalParticipation in ethnic and

religious organizationsParticipation in env and

human rights organizationsGeneralized trust Ethnic tolerance

Class level (L2) I II III I II III 0 I II III 0 I II IIIEthnoracial diversity .020*** .021*** .008* .013*** .013*** .010* -.004** -.004** .001 .007 .009* -.008Class status .605*** .453** .016 -.096 -.096** -.064 -.160 -.312Climate .142 .136 .025 .019 .001 .007 -.209 -.287**

Individual level (L1)Ethnoracial identitya 1.23*** .224 -.255*** 1.53***Social status .195*** .165** -.013 .081*Genderb -.167 -.181 .012 -.60***Civic competence -.001 -.003 -.002* .011***

ICC L2 (%) 1.7 11.2ICC L1 (%) 98.3 88.8(residual) variance L2 .011 .007 .004 .004 .574 .560 .522 .558(residual) variance L1 .631 .631 .631 .625 4.451 4.449 4.448 4.140Explained var L2 (%) 36.4 63.7 63.7 2.4 9.1 2.4Explained var L1 (%) 0 0 1 0 0 7N L2 128 128 128 128 128 128 128 128 128 128 128 128 128 128N L1 2933 2933 2933 2933 2933 2933 2498 2498 2498 2498 2688 2688 2688 2688

Note: * P < .05; ** P < .01; *** P < .001; the data were weighted by houseweight to make the results nationally representativea Reference category: whiteb Reference category: girl

41