Politics in Peer Groups

Abstract

Social capital researchers have suggested that bridging ties are important for political participation. However, thus far the literature lacks testing on the direction of this relationship: do diverse ties stimulate political participation or does political participation stimulate political diversity among friends and acquaintances? This article examines how ethno-cultural and political diversity within social networks influence political participation among a unique panel of 4,235 young people in Belgium. The results reveal a reciprocal cross-lagged effect. In particular, having politically diverse social networks increases political participation, which in turn promotes meeting politically diverse others.

Keywords

political participation political diversity youth social networks panel data

Introduction

Social capital researchers have suggested that bridging ties, namely, networks of people with different opinions and backgrounds, are important for democratic politics (Cigler and Joslyn 2002; Marschall and Stolle 2004; Putnam 2000). Bridging ties in informal networks of friends and acquaintances have been highlighted as particularly beneficial for the dissemination of information and political mobilization (Granovetter 1973; Mutz and Mondak 2006). Yet, the limited research into the impact of social diversity on political participation has contrasting findings: while some suggest a dampening effect (Alesina and Ferrara 2000; Costa and Kahn 2003; Mutz 2002a, 2006; Putnam 2007), other research has shown a positive effect on political participation, at least for some types of participation and among some populations (Pattie and Johnston 2009; Putnam 2007; Scheufele et al. 2006). Moreover, very little research has questioned and explored the direction of causality from experienced diversity to participation.

Two main questions drive our research. We first attempt to disaggregate network effects: does the relationship between network diversity and political participation function similarly across different dimensions of diversity? In particular, we are interested in both political diversity, which we might expect to have a direct impact on political participation, as well as ethno-cultural diversity. Second, does network diversity cause political participation, or is there evidence that political engagement can fuel diverse encounters? To explore these questions, this study uses a two-wave panel survey collected among Belgian youth in 2006 and 2008. Unlike most research into network effects, this unique longitudinal design allows us to test the direction of causality between social network diversity and political participation.

Our results show that young people who have more diverse social networks are in fact more likely to participate in a variety of social and political activities. Political diversity in one’s social network has the strongest positive effect on political participation, but ethno-cultural diversity also matters. Most importantly though, in terms of causality, we find a reciprocal cross-lagged effect. In other words, political participation strengthens people’s network diversity and diversity spurs political participation (controlling for prior participation and diversity). Our findings thus have significant repercussions for the social network literature that builds its assumptions mostly on the belief that social networks shape political behavior, and not the other way around.

Social Network Diversity and Political Participation

Social networks have often played an important role in explaining political behavior. Early research in the Columbia school of voting studies emphasized the importance of one’s social environment in shaping one’s ideology and vote choice (Berelson, Lazarsfeld, and MacPhee 1963). Sociological research has pointed to the importance of weak social ties in promoting access to new information and occupational opportunities (Burt 1997; Granovetter 1973; Lin, Cook, and Burt 2001). Social capital research has focused on how social interactions in formal and informal networks provide personal benefits as well as the development of civic values and societal engagement (Coleman 1988; Putnam 1993, 2000). The overarching insight of these various research traditions is that social networks have value.

Empirical work has directly linked social interaction to politics. Participation in informal social networks and voluntary associations correlates with political mobilization and participation (Galston 2004; Seligsen 1999; Teorell 2003). Associations, in particular, are believed to foster civic skills (Verba, Schlozman, and Brady 1995) and encourage a civic spirit and volunteerism (Putnam 2000), a sense of political efficacy (Berry, Portney, and Thomson 1993, ch. 8), as well as generalized trust and other civic attitudes (Putnam 1993, 2000; but see Stolle 2001a; Uslaner 2002). Participation in formal associations also expands people’s informal social networks. As a result, they are more likely to be exposed to information about society and politics and to be the target of political recruitment (Putnam 2000, 338; Teorell 2003). Similarly, the more people discuss politics with their acquaintances and friends in informal networks, the more likely they are to participate in politics (Knoke 1990; McLeod et al. 1999; Verba, Schlozman, and Brady 1995).

Social networks, then, serve as an important milieu for mobilizing people into politics. However, several key questions remain unexplored. First of all, little research has focused on the sorts of people with whom one interacts, which is captured, for example, by the distinction between bridging and bonding interactions (Putnam 2000). The second issue relates to causality. While most studies assume that the character of social networks has politically mobilizing (or perhaps dampening) effects, it may also be the case that political participation in itself shapes the types of networks one has. The causal flow can only be examined in a suitable panel study, which has rarely if ever been employed to examine social networks effects on political participation.¹ In the following, we explore these two ideas in more depth.

Diversity of Interaction

First, the composition of social networks may potentially matter for mobilization, yet much remains unclear as to how it matters. Do networks that promote diverse interactions spur political activity, or does surrounding oneself with like-minded individuals facilitate action? And what are the salient cleavages?

Putnam (2000) claims that “bridging” interactions with people from different social backgrounds are more conducive to the acquisition of political information than “bonding” interactions with people from similar backgrounds. Similar to arguments made by sociologists about the power of weak ties to transmit information and social norms (e.g., Coleman 1988; Granovetter 1973), knowing diverse others can promote a better understanding of different political viewpoints and transmit important information about the political world (Barabas 2004; Huckfeldt, Mendez, and Osborn 2004; Jang 2009; McClurg 2003; Price, Cappella, and Nir 2002). Political discussions with people who hold different viewpoints force people to “constantly rethink and refine their issue stances as a result of potentially being challenged in their opinions by non-likeminded others” (Scheufele et al. 2004, 316; see also Huckfeldt, Johnson, and Sprague 2004; Kenny 1992; Klofstad 2005; Leighley 1990; McClurg 2003; McLeod et al. 1999). This process might foster a heightened awareness of one’s political identities and might disseminate mobilizing information that in turn spurs political participation (Delli Carpini and Keeter 1996; Eveland and Scheufele 2000; Teorell 2003).

However, attempts to document a direct empirical link between exposure to differing viewpoints and political participation have provided mixed results. If we consider politically diverse others, some research has documented a positive link (Knoke 1990; Leighley 1990), at least for some forms of political acts (Pattie and Johnston 2009) and among certain populations (Jang 2009). Yet, other research has suggested that political similarity, rather than diversity, promotes political engagement. The sharing of views among like-minded people can reinforce one’s position, promote recognition of common problems, and spur collective action’ (Hooghe 2003; McKenzie 2008; Mutz 2002a; Putnam 2000).² From this perspective, diverse networks seem problematic for political action. Mutz (2002a, 2006), in particular, argues that discussion in strong tie networks with people who hold different political opinions can create political ambivalence (conflicting information makes people less certain of their choices) and situations of social accountability (people don’t like choosing sides when facing opposition), which in turn decreases political participation (see also McClurg 2006b; Scheufele et al. 2004; Ulbig and Funk 1999). Many people prefer social harmony and prefer to avoid arguments with close friends, leading them to arguably stay out of politics and political discussions altogether when their networks contain a diversity of opinions (Eliasoph 1998; Lane 1959; Mutz 2002a, 2006). Clearly, with these contradictory findings there is need for further research into the effects of network diversity on political participation. This requires further tests of the effect of politically diverse networks on participation, but also how other types of cleavages within networks translate into political (dis)engagement.

Many political values are based in social background variables (Berelson, Lazarsfeld, and MacPhee 1963). People who interact with individuals from different social backgrounds are likely to be exposed to a broader range of viewpoints. If so, then the diversity of sociodemographic characteristics in one’s social network should have similar effects on political participation as diverse political networks. However, very little work has examined the link between various types of diversity within social networks and political participation.³

One of the most salient cleavages in contemporary politics is based in racial, ethnic, and religious differences. Increasingly, research has suggested that living in diverse areas affects a person’s politics. Focusing on neighborhood-level indicators, Putnam (2007) finds that ethnic diversity—despite its negative correlations with voting—is conducive to some forms of political participation, especially protest activities and social reform groups, as well as political interest and knowledge. Oliver (1999) has also found that the level of civic participation is highest in diverse, middle-income cities. Furthermore, greater heterogeneity at the country level is related to more political discussion networks and generating citizens’ interest in politics, at least in democratizing countries (Anderson and Paskeviciute 2006). This mobilizing effect of diversity is often explained with the consequences of heightened ethnic conflict. However, contextual ethno-cultural diversity has also been clearly linked to negative effects on civic and political engagement (see e.g., Alesina and Ferrara 2000; Costa and Kahn 2003; Hill and Leighley 1999), suggesting perhaps that people might withdraw from public life and hunker down when facing diverse others (see Putnam 2007 for voter registration). For example, Campbell (2007) shows that classroom racial diversity is linked with less political discussion and thus lowers intentions of adolescents to become informed voters. Most importantly though for the purposes of this analysis, the political consequences of ethno-cultural social networks (as opposed to diverse neighborhoods or schools) have been mostly left unstudied (however, see Stolle 2001b).

In sum, the literature seems to suggest that social network diversity might be related to political participation, although the findings deliver contradictory results as to whether diversity has dampening or mobilizing effects. In addition, the consequences of ethno-cultural network diversity are understudied. One of the contributions of this article is to directly assess the causal relationship between various types of network diversity (political and ethno-cultural) on the one hand and political participation among young people in Belgium on the other.

Causal Flow between Networks and Participation

In addition to a closer look at composition effects of various dimensions of diversity, an equally important task is to establish more definitively the direction of such effects. The causal flow between social networks and political participation is so far only assumed. While social capital and social network theory presupposes that social networks affect political outcomes, it is entirely plausible that the causal logic works the other way around as well. Especially among young people, some forms of participation become social events, which potentially broaden one’s social networks. For some political activities, such as raising money for a cause, young people might get together with various others of diverse backgrounds and political opinions in order to solve a political issue. Thus, it is also plausible that political activities potentially make young people’s networks more diverse.

As far as we are aware, the only study to try to directly disentangle the causal structure between diversity and political participation is Pattie and Johnston (2009). Using the British Elections Survey, they show that diversity breeds certain forms of political participation (volunteering as well as intended party activism and protest participation).⁴ Relying on reported disagreement in party support among those with whom respondents discussed politics, their findings attempt to disentangle the causal direction by assessing the effect of disagreement on changes in two dependent variables: political interest and voting. This is made possible by the panel design of their survey; however, as they note themselves (Pattie and Johnston 2009, 267), the measure of disagreement was only asked in the post-election wave, forcing them to assume “conversation patterns reported after the election were typical of those experienced before the election” and to limit the analysis to the two dependent variables for which they have change scores. Not surprisingly, they fail to find an effect for diversity on the change in political interest and voting (where voting is measured as a gap between intention to vote and actually voting). They unfortunately cannot test the other forms of civic and political engagement, which were only asked at the same time as the discussion questions.

While this analysis provides an important initial attempt to test causation, the placement of the social network variables in the post-election survey limits the analysis substantially. To more fully test causal direction, social network variables should be measured prior to participation, with controls for prior levels of participation. This is precisely what the panel design employed here is able to do.

Hypotheses

While we note that there is countervailing evidence on whether network diversity is a positive or negative force for participation, it has become clear as well that negative effects have mostly been found with regard to voting and other conventional forms of political participation (Campbell 2007; Mutz 2002a; Putnam 2007). This is perhaps because potential cross-pressures and ambivalence about one’s viewpoints are addressed along sharp party lines when voting. Yet young generations today engage more frequently in a variety of so-called extra- parliamentary and unconventional forms of participation, which are not necessarily lining up alongside party attachment (Dalton 2007). For these forms of participation, we thus expect the mobilizing potential of diverse networks that comes with more political discussion, information, and inspiration to overpower the potential negative effects of diversity. Furthermore, we expect the strongest effects to emerge from political diversity, rather than ethno-cultural diversity. First of all, some research suggests that higher levels of ethno-racial diversity in a young person’s surrounding may decrease its salience in friendship choice (Joyner 2000), whereas no such findings have been shown with regard to political diversity. Second, political diversity is more clearly linked to political outcomes such as participation. While ethno-cultural diversity in some societies might stand for or capture value conflict or diverse interests, we believe that political diversity measures more efficiently and directly the difference of opinion and viewpoints of a network. Thus, we expect political diversity to be a more powerful correlate of political mobilization compared with other socioeconomic and cultural aspects of diversity. Thus, the first hypothesis is:

Hypothesis 1: Political diversity will have a stronger, positive effect on young people’s future political participation than ethno-cultural diversity.

Our second hypothesis addresses the causal direction of network effects on participation. Our expectations here are rooted largely in the assumption in the past literature that social networks facilitate participation by increasing discussion and information about politics (Huckfeldt 1979; Rosenstone and Hansen 2003; Verba, Schlozman, and Brady 1995). More specifically, we expect:

Hypothesis 2: Network diversity has a larger effect on future political participation than political participation will have on future network diversity.

While the direction of this hypothesis is largely driven by the assumption in the literature, the potential for a reverse or reciprocal cross-lagged relationship is compelling. Politics is often a game of opposing viewpoints. Those who engage in it are likely to encounter diverse others, and such exposure may well lead to new relationships.

Data and Method

The data for this study come from the Belgian Political Panel Survey (BPPS). These data constitute a two-wave panel study among sixteen- and eighteen-year-olds. In 2006, a representative survey was conducted among 6,330 sixteen-year-olds in Belgium. Analysis of the survey responses confirms the sample is representative for region, school type, gender, and educational track. Based on written surveys completed by the respondents in 112 schools, the study focused on young people’s social and political attitudes and contained questions about their participation habits. To obtain a national random sample, all schools included in the survey were selected through a stratified sample, based on the location and type of the school. In each school, a minimum of fifty students was selected, representative of the academic tracks in that school. The response rate was 66 percent for the schools and within the schools, 99 percent for the pupils.

In 2008, the respondents were surveyed for a second wave, this time at the age of eighteen. While most of the initial respondents could still be reached in school, for those who had left or changed schools, alternative strategies had to be developed. Of the initial 112 schools, 109 participated again in the survey in 2008. In these schools, the same classes were resurveyed and this allowed reinterviewing almost three thousand students. The other students were contacted through a mail survey. In total, 4,235 pupils (or 67 percent) from the initial panel were resurveyed. The attrition rate is in line with what we can expect for this kind of panel study. The second wave is again representative with regard to region, school type, gender, and educational track. As such, this data set is ideally suited to test our hypotheses. It provides us access to a total sample of 4,235 panel respondents who were interviewed both in 2006 (average age sixteen) and in 2008 (average age eighteen).

The main dependent variable for this analysis results from a series of nine questions asking the respondent how often they have participated in a given political activity in the previous twelve months. The activities were selected to vary in terms of the ways in which young people in contemporary democracies might be involved in politics, from signing a petition, being involved in a political party, to boycotting a product. The Political Participation Scale is constructed as a factor score (for the ordinary least squares [OLS] regression) and a latent variable (for the structural equation model, chi² value: 167.855; 24df; p value < .001; Comparative Fit Index [CFI] = 0.944; root mean square error of approximation [RMSEA] = 0.038). The exact question wording is presented in the online Appendix 1 (available at http://prq.sagepub.com/supplemental/). We must note, however, that this scale does not include voting, as this survey was undertaken among young people (aged sixteen and eighteen year old). In addition, voting is compulsory in Belgium, which would complicate international comparisons.

For the first part of the analysis, the main independent variables are questions about the composition of the respondents’ networks. Three different types of diversity were queried in two different contexts that measure strong and weak ties. Each respondent indicated how many of their close friends (strong ties) and how many of the other people at school they speak with other than their close friends (weak ties): are from a different race (e.g., racial diversity), are from a different religion (or was religious if the respondent was not) (e.g., religious diversity), often disagree about politics or public affairs (e.g., political diversity). Answers varied on a 7-point scale from 0 (none) to 6 (all). Because of the relatively high correlations between racial and religious diversity and between close friends and acquaintances (see online Appendix 2), we combine them into one variable: ethno-cultural diversity. Similarly, we combine the political diversity of weak and strong political ties in one political diversity scale (0-6).

Earlier we discussed how the literature has focused on a variety of causal mechanisms that relate diversity to political participation. Network diversity may foster political discussion and knowledge as well as interest in political issues by making political discussion more likely and providing new information through exposure to dissimilar others; this in turn might spur political action. We have therefore included these three measures of political engagement—political knowledge, political interest, and the frequency of political discussion—in order to be able to test them as potential intermediary variables in the relations between diversity and political participation. Alternatively, people who engage in politics more actively might broaden their network diversity simply through their political engagement.

Several control variables are included in both the OLS regression and structural equation model, including gender (0 = female), citizenship status (0 = not Belgian citizen), socioeconomic status (factor score of educational track,⁵ educational goal,⁶ and number of books at home), and the number of close friends the respondent has (7-point scale from 0 = none to 6 = 15 or more).

In a first step, the independent variables will be regressed on the political participation scale to see which network characteristics relate to political participation. In a second step, the direction of the relationship between diversity and political participation will be determined by structural equation models, more specifically cross-lagged models, that are based on the Markov Simplex models (Schlueter et al. 2007). The autoregressive models allow the prior value to determine the future values. Taking into account that the literature suggests that political behavior is a habit (Gerber, Green, and Shachar 2003; Plutzer 2002), autoregressive models are appropriate. Furthermore, autoregressive models allow for cross-lagged effects: political participation and network diversity can influence each other over time. In Figure 1, the model with its control variables is graphically represented. The cross-lagged model is often used in psychology to explain drug use, behavior, and pupils’ skill development in school (Burkholder and Harlow 2003) and in sociology to test whether anomie caused authoritarianism or vice versa (Schlueter et al. 2007), but not very frequently in political science (Finkel 1985). As we have only two waves of data, we can only model the direction of the effect, yet we believe this provides a better test of causality than prior studies have allowed. Furthermore, our study will only be able to provide evidence for what happens in a two-year time interval. The exact effect of diversity on political participation and vice versa should be analyzed by a longer study with multiple waves (see also “Conclusion”). As the analyses indicate that multilevel analysis, or alternative variance estimators, leads to the same results, and as the intraclass correlation of the dependent variables is low (e.g., 5 percent for political participation), we present here the simpler models.

Figure 1.

Graphical representation of cross-lagged model with control variables.

Findings

To begin, it is important to determine what types of diversity are present in young people’s networks. We find that young people have more diverse political ties than ethno-cultural ties (Table 1). We also find that political diversity in networks increases between the ages of sixteen and eighteen. It is likely that as young people get older, they start to discuss politics more often and perhaps therefore also become more aware of political opinions of their friends and classmates (Dawson and Prewitt 1969). The racial and religious composition of the networks shows a slight but significant decrease in diversity. Young people’s ethno-cultural networks appear to become more homogenous as they grow older.

Table 1.

Means of Diversity Measures

	2006		2008
	M	SD	M	SD
Political diversity	1.335	0.999	1.688	0.991***
Ethno-cultural diversity	1.153	1.052	1.121	1.098***

Entries are means, standard deviations, and significances between the 2006 and 2008 measures. Range = 0 to 6. Panel respondents (n = 4,235).

Source: Belgian Political Panel Survey 2006-2008.

***

p < .001.

Table 2 presents the results of the ordinary least squares regression. Looking at the control variables, we find no effect for gender or citizenship among this age group (Quintelier 2009). Socioeconomic status is, as in most political participation research, positively related to political participation: the higher the social status of the respondent and their family, the more likely they will participate (Verba, Schlozman, and Brady 1995). With respect to the political attitudes and intermediary variables, we find a large and significant effect of political interest and political knowledge on political participation. It should be noted that the effect of political interest on later political participation is largely mediated by the level of political participation in 2006, which is the largest predictor in this model. Political discussion with friends enhances the likelihood of participating in politics in the future. This relationship has been shown extensively with respect to single-wave data (Eveland and Hively 2009; Kwak et al. 2005; Mutz 2002a). This article adds to the existing knowledge by providing evidence that this relationship also holds over time. Finally, although previous research has shown that the size of the network affects (electoral) participation (Mutz 2002b), it does not do so here: young people with more friends are equally likely to participate in politics in the future than those with fewer friends. Others have operationalized the network size in terms of number of discussants and find positive effects on contacting, campaigning, cooperative activities (Leighley 1990), and political participation (Kwak et al. 2005).

Table 2.

Predicting Political Participation (2008)

		2008 Political participation
	Control variables
	Political diversity		0.054***
	Ethno-cultural diversity		0.056***
	Male	0.005, ns	0.013, ns
	Socioeconomic status	0.062***	0.052***
	Belgian citizen	−0.007, ns	0.006, ns
	Political interest	0.046**	0.035*
2006	Political knowledge		0.062***
	Number of close friends	0.014, ns	0.010, ns
	Political discussion	0.109***	0.088***
	Political participation	0.410***	0.402***
	Explained variance	0.263	0.273
	Number of cases	3,744	3,558

Ordinary least squares regression. Entries are standardized coefficients and significances.

Source: Belgian Political Panel Survey 2006-2008.

p < .05. **p < .01. ***p < .001.

Second, we also entered the measures of social network diversity into the regression. We find that both political and ethno-cultural diversity matter for political participation. More specifically, bridging (e.g., more diverse) networks have more effects on future political participation than bonding networks, as both dimensions are here presented as opposites (one has a completely bonding or completely bridging network at the endpoints). Both types of bridging ties relate positively to political participation, and in this base model, the size of these effects are similar. On the other hand, the analyses indicate that political and ethno-cultural diversity both relate to political participation, contrary to our expectation that political diversity would have a more pronounced effect (Hypothesis 1).

Table 3 presents the results of a cross-lagged model with political participation and political diversity among close friends and classmates. We analyze ethno-cultural diversity in a subsequent model. To test whether the cross-lagged effects (between political participation – political diversity) are equal, we tried to constrain the cross-lagged parameters (see Table 3, column 2). Then we compare the chi² values of both models. If this test leads to a significant chi² difference (p < .05), this indicates that there are significant differences in the cross-lagged parameters, so they cannot be set equal, and that we should prefer the constrained model. When these parameters cannot be constrained, either the effect of diversity on political participation or the effect of political participation on diversity is more prominent. An insignificant p value (p > .05), on the other hand, indicates that both models have a similar fit and that the parameters can be constrained to be equal. The best fitting models are shaded in Tables 3 and 4. For political participation and political diversity, the model fit of the constrained model is not significantly different (Δchi² value = 0.006; Δdf = 1, ns), so this model should be preferred and is presented in Table 3, column 2. This model shows that the effect of political participation at the age of sixteen (2006) has an effect on political diversity at age eighteen (2008) equal to the effect that political diversity at the age of sixteen (2006) has on political participation at the age of eighteen (2008) (B = .098; SE = 0.021). In other words, those who participate in earlier years have more politically diverse friends later, and those with politically diverse networks early on are more likely to participate two years later. While most literature assumes that political diversity stimulates political participation, we find that the mechanism also works the other way around. The literature to date thus only presents half of the picture: it does not take into account that prior political participation also stimulates political diversity in social networks. In short, by drawing on panel data, we are better able to explore the direction of these effects, which appear to be a reciprocal cross-lagged relationship between participation and diversity. It appears that many acts of political participation indeed do open up the potential for contact with politically diverse others. The implication is that political diversity and political participation are reinforcing trends, at least in Belgium in a sample of sixteen- to eighteen-year-old adolescents.

Table 3.

Relationship between Political Diversity and Political Participation

	Unconstrained model	Constrained model
Stability effects
Political participation (β2)	0.603 (0.038)	0.602 (0.036)
	0.622***	0.622***
Diversity (β1)	0.429 (0.032)	0.431 (0.028)
	0.427***	0.429***
Cross-lagged effects
Diversity on political participation (β3)	0.096 (0.026)	0.098 (0.021)
	0.121***	0.122***
Political participation on diversity (β4)	0.100 (0.041)	0.098 (0.021)
	0.082*	0.080***
Error covariances
2006 (Φ)	0.092 (0.012)	0.092 (0.012)
	0.276***	0.276***
2008 (ψ)	0.058 (0.012)	0.059 (0.012)
	0.214***	0.215***
Control variables: Political diversity 2006 (γ)
Socioeconomic status	0.113 (0.014)	0.089 (0.015)
	0.127***	0.121***
Political interest	0.126 (0.016)	0.184 (0.021)
	0.133***	0.236***
Political knowledge	0.055 (0.011)	0.063 (0.011)
	0.085***	0.118***
Political discussion	0.466 (0.021)	0.291 (0.029)
	0.388***	0.292***
Control variables: Political participation 2006 (γ)
Socioeconomic status	0.089 (0.015)	0.113 (0.014)
	0.121***	0.127***
Political interest	0.184 (0.021)	0.126 (0.016)
	0.236***	0.134***
Political knowledge	0.063 (0.011)	0.055 (0.011)
	0.118***	0.085***
Political discussion	0.290 (0.030)	0.466 (0.022)
	0.293***	0.388***
Control variables: Political participation 2008 (γ)
Socioeconomic status	0.164 (0.019)	0.164 (0.019)
	0.184***	0.184***
Explained variance
Political diversity 2006	0.280	0.281
Political participation 2006	0.285	0.285
Political diversity 2008	0.303	0.303
Political participation 2008	0.473	0.473
Goodness of fit
Chi² test	822.343	817.989
df (significance)	276***	277***
Comparative Fit Index	0.953	0.953
Root mean square error of approximation	0.018	0.018
Chi² difference, df, significance	0.006, 1df, ns
Number of cases	3,578

Weighted least square (WLSMV) estimation. We opted for a WLSMV estimator for categorical variables using a diagonal weight matrix with standard errors and mean- and variance-adjusted chi-square test statistic that use a full weight matrix, comparable to Satorra-Bentler (Hancock and Mueller, 2006; Muthén and Muthén, 2007). The constrained parameters are italicized. The shaded model is the best fitting model. Entries are unstandardized effects (SE), standardized effects, and significances.

Source: Belgian Political Panel Survey 2006-2008.

p < .05. **p < .01. ***p < .001.

Table 4.

Relationship between Ethno-Cultural Diversity and Political Participation

	Unconstrained model	Constrained model
Stability effects
Political participation (β2)	0.771 (0.041)	0.778 (0.04)
	0.747***	0.751***
Diversity (β1)	1.146 (0.034)	1.099 (0.033)
	0.947***	0.916***
Cross-lagged effects
Diversity on political participation (β3)	0.029 (0.020)	0.031 (0.020)
	0.045, ns	0.051, ns
Political participation on diversity (β4)	−0.090 (0.058)	0.031 (0.020)
	−0.046, ns	0.016, ns
Error covariances
2006 (Φ)	0.052 (0.013)	0.045 (0.011)
	0.211***	0.186***
2008 (ψ)	0.021 (0.009)	0.014 (0.008)
	0.242*	0.143, ns
Control variables: Ethno-cultural diversity 2006 (γ)
Socioeconomic status	0.101 (0.021)	0.099 (0.022)
	0.116***	0.113***
Political interest	0.034 (0.023)	0.027 (0.023)
	0.038, ns	0.029, ns
Political knowledge	−0.030 (0.015)	−0.033 (0.015)
	−0.05*	−0.055*
Political discussion	0.179 (0.029)	0.170 (0.030)
	0.153***	0.144***
Control variables: Political participation 2006 (γ)
Socioeconomic status	0.065 (0.018)	0.064 (0.018)
	0.12***	0.122***
Political interest	0.137 (0.030)	0.133 (0.029)
	0.24***	0.242***
Political knowledge	0.042 (0.012)	0.041 (0.012)
	0.113***	0.114***
Political discussion	0.238 (0.047)	0.229 (0.046)
	0.327***	0.326***
Explained variance
Ethno-cultural diversity 2006	0.048	0.042
Political participation 2006	0.327	0.328
Ethno-cultural diversity 2008	0.875	0.846
Political participation 2008	0.579	0.585
Goodness of fit
Chi² test	1007.841	1011.126
df (significance)	377***	378***
Comparative Fit Index	0.951	0.951
Root mean square error of approximation	0.026	0.026
Chi² difference, df, significance		4.075, 1, *
Number of cases		2,569

Weighted least square (WLSMV) estimation. The constrained parameters are italicized. The shaded model is the best fitting model. Entries are unstandardized effects (SE), standardized effects, and significances.

Source: Belgian Political Panel Survey 2006-2008.

p < .05. **p < .01. ***p < .001.

Looking at the other estimates in the table, we find that the stability coefficients indicate that political participation is quite stable, already at a young age, with a standardized coefficient of 0.622(***). Political diversity, on the other hand, is less stable, with a standardized coefficient of 0.429(***). Furthermore, the covariances indicate that the correlation between political participation and political diversity is quite weak, once controlled for prior participation and diversity (0.276***, 0.215***). The regression coefficients show the same effects as in Table 2. Thus, political participation is influenced by socioeconomic status, political discussion, political knowledge, and political interest, similarly to political diversity. With these models, we can explain about 30 percent to 50 percent of the respondents’ political diversity and political participation. With respect to the goodness-of-fit indices, we find the RMSEA and CFI indicate that the model has a good fit, while the chi² test indicates a worse fit. This is mostly because the chi² test is largely affected by the sample size (n = 3,578).⁷

Table 4 presents the same analyses as in Table 3, but for ethno-cultural diversity. The chi² difference test indicated that the cross-lagged effects could not be constrained (Δchi² value = 4.075; Δdf = 1*), although the effects are both insignificant (Table 4, column 1). We find no significant cross-lagged effects: political participation does not reinforce ethno-cultural diversity, nor does ethno-cultural diversity reinforce political participation. On the other hand, ethno-cultural diversity is much more stable than political diversity (with a stability coefficient of 0.947 compared to 0.429), but ethno-cultural diversity has four observed indicators, while political diversity has only two indicators. Political participation has a stability of 0.747. Second, while the same predictors hold for political participation as in the previous models, ethno-cultural diversity is only influenced by socioeconomic status and political discussion, and slightly negatively affected by political knowledge. Third, the covariances with ethno-cultural diversity are at the same level as those for political diversity (i.e., 0.211***). Still, one reason that we do not find cross-lagged effects in this model is that the level of ethno-cultural diversity in 2006 is highly correlated with ethno-cultural diversity in 2008 and political participation 2006. By controlling for ethno-cultural diversity at 2008 in the final column, the direct effect of the 2006 levels fails to reach significance. Again, this seems largely due to the inclusion of the 2008 ethno-cultural diversity variable. Moreover, ethno-cultural diversity is positively correlated with political participation within each year of the study (2006 and 2008). Finally, the model fit is comparable to the previous model, which had a good fit. However, in contrast with Table 3, this model indicates that political participation and ethno-cultural diversity are quite stable and correlated, but they do not reinforce one another.

Clearly, then, we find evidence of a positive effect for both political and ethno-cultural diversity on political participation, as well as a cross-lagged effect for political participation on political network diversity. While the causal logic of the latter may be quite direct (political participation brings you directly into contact with diverse others), past research has pointed to the importance of discussion, knowledge, and interest as the mechanism through which network diversity translates into political participation. In a final step, we provide further evidence that prior network diversity promotes political knowledge, interest, and discussion within a two-year time span. In Table 5, we rerun the analysis using these three measures (collected in 2008) as dependent variables, controlling for 2006 levels. As is assumed by researchers who demonstrate a positive network effect, we find that young people with more political and ethno-cultural diversity are more likely to discuss politics later. We find no such relationship for political knowledge (p = .060). However, political interest in 2008 is predicted by prior political network diversity (although no corresponding effect is evident for ethno-cultural diversity). This analysis benefits from the panel design of this study. While discussion is often intertwined with measures of political diversity, we are able to tease out the independent effects here. In doing so, we provide further support for the theoretical benefits of political diversity on political participation.

Table 5.

Predicting Political Interest, Discussion, Knowledge 2008

	Political interest	Political discussion	Political knowledge
Control variables (2006)
Political diversity	0.039*	0.044**	0.034, ns
Ethno-cultural diversity	−0.008, ns	0.047**	0.011, ns
Male	0.028, ns	0.053***	0.069***
Socioeconomic status	0.153***	0.103***	0.275***
Belgian citizen	−0.017, ns	0.002, ns	0.005, ns
Political interest	0.285***	0.126***	0.122***
Political knowledge	0.193***	0.048**	0.384***
Number of close friends	0.000, ns	0.003, ns	−0.033*
Political discussion	0.099***	0.223***	0.041*
Political participation	0.081***	0.101***	−0.010, ns
Explained variance	0.318	0.198	0.380
Number of cases	3,620	3,625	2,486

Entries are standardized coefficients and significances. Note that the respondents who filled in a mail survey did not receive the political knowledge questions in 2008.

Source: Belgian Political Panel Survey 2006-2008.

p < .05. **p < .01. ***p < .001.

Conclusion

In this article, we went beyond the current literature and examined the relationship between two dimensions of social network diversity and political participation among young people in Belgium. Most importantly, the data allowed for a crucial test of the direction of causality in that it relies on panel analysis of the same respondents while testing multiple measures of social network composition and participation at two points in time. While the literature contains contradictory findings as to the mobilizing or dampening effects of network diversity on political participation, the research needed a fresh look at a wider variety of forms of political participation. More specifically, given some previous findings, we expected that diversity of social networks would have more mobilizing effects on non–voting related forms of participation in which young people engage more frequently. The nature of contact in diverse networks, we argued, might be converted into heightened political engagement, especially political discussion, without the “uncomfortableness” that such discussion may create among closer friends. Such discussion is arguably the means by which network diversity translates into more political involvement. We also expected political diversity to matter more than ethno-cultural diversity. While we find positive relations between both, only political diversity showed a reciprocal cross-lagged effect with political participation. We therefore provide important confirmation of the effect of networks on political action while establishing new evidence that political participation can also create more politically diverse networks. However, the effect of ethno-cultural diversity on political participation is reduced if one controls for prior diversity, but still remains correlated at Time 1 (2006) and Time 2 (2008), see Table 4 (column 1).

Our research in Belgium has confirmed the expectations that diverse ties seem to be positively related to political outcomes in young people. Experiencing political diversity makes young people more likely to participate in politics within a two-year span. In other words, when we broaden the political participation repertoire and study network effects on young people, we see a clear tendency that diversity stimulates political participation. This finding is quite important in light of the contradictory findings in the literature. Since young people tend to be more disengaged in the political process, our findings at least suggest that encouraging young people to interact with peers of different political convictions might stimulate rather than dampen their political participation and engagement. We believe that this relationship is spurred on by political discussions, which are fostered in politically diverse networks (Lake and Huckfeldt 1998; McClurg 2006a).

Most importantly though, we have identified an additional causal flow than the one assumed in the literature: political participation and political diversity reinforce each other. While most research on the role of social networks for political participation assumes the dominance of networks for political outcomes, our research here on young people in Belgium has shown that political participation also strengthens the network diversity of close friends and classmates. So, those who are politically active report more politically diverse friendship networks. Many of the political activities are social in character and our research suggests that such activities might bring one into contact with people of different beliefs.

While these findings go beyond past research, several caveats to our analyses have to be discussed. Although we find political diversity and political participation to mutually reinforce each other, future research needs to more fully flesh out the underlying process. Our analysis can only take into account a relatively short time frame. Yet, it might be that in the short run political participation leads to more politically diverse networks while it may take a substantially longer period of time (and influence) for individuals in politically diverse networks to become engaged. While we found that within the relatively short time frame of two years, diversity affects participation as well as the other way around, longitudinal repeated measures are required to more fully understand the strength and longer term consequences of these two variables.

This study draws on data from Belgian young people, and it is important to consider how these insights travel to adults and other contexts. Clearly, politics is not salient to everyone, and this seems to be particularly true among young people today. Given the importance of early experiences in the political socialization process, we expect network effects to be particularly strong for youth. Adults’ political attitudes and behavior tend to be more crystallized, and so we assume they are less susceptible to influence. Political activities at a young age may also sharpen young people’s awareness of political differences around them over time while providing the tools to deal with such differences. The extent to which we would find similar reciprocal cross-lagged relationships among adults requires further research.

Belgian youth, like young people in other industrialized democracies, are in the process of developing their political identities. While we expect political socialization to work similarly in other contexts, the political context may also matter to the potential for network effects. Belgian pupils tend to score lower on political interest, future political engagement, and social and political trust than youth in other countries, according to the International Civic and Citizenship Education Study (Schulz et al. 2010). Furthermore, despite Belgium’s overall linguistic diversity, social networks tend to be fairly homogenous.⁸ In such a context, with high political apathy and low social diversity, we expect that exposure to social diversity in networks may be limited but that its potential impact on political participation may be especially pronounced. While we are limited in the extent to which we can make comparative conclusions with our single-country youth data, the strength of our analysis lies in its innovative panel design. Such a design allows us to make an important contribution to the literature that assumes one-way mobilization from social ties and networks to participation.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research authorship, and/or publication of this article:

The Research Council of the K.U.Leuven, the Research Foundation-Flanders, and the Canadian Social Science and Humanities Research Council.

Notes

Bios

Ellen Quintelier, is a postdoctoral researcher of the Research Foundation - Flanders, and an Invited Scholar at the University of Mannheim (Germany). Her research interest lies in political behavior, political sociology and comparative politics. More specifically, she focuses on patterns of inequality in political participation and the effect of political socialization agents on political participation.

Allison Harell, is an assistant professor in the Department of Political Science at the Université du Québec à Montréal. She is a member of the 2011 Canadian Election Study. Her research focuses on ethno-racial diversity, gender and political behavior.

Dietlind Stolle, is Associate Professor in Political Science at McGill University, Montréal, Canada. She conducts research and has published on voluntary associations, trust, institutional foundations of social capital, political mobilization, and new forms of political participation, particularly political consumerism. She is co-principal investigator of both the Comparative Youth Survey (CYS) as well as the Canadian Election Study (CES).

References

Alesina

Alberto

Ferrara

Eliana La

. “Participation in Heterogeneous Communities.” Quarterly Journal of Economics 115 (2000): 847-904.

Anderson

Christopher J.

Paskeviciute

Aida

. “How Ethnic and Linguistic Heterogeneity Influence the Prospects for Civil Society: A Comparative Study of Citizenship Behavior.” Journal of Politics 68 (2006): 783-802.

Barabas

Jason

. “How Deliberation Affects Policy Opinions.” American Political Science Review 98 (2004): 687-701.

Beck

Paul Allen

Jennings

M. Kent

. “Pathways to Participation.” American Political Science Review 76 (1984): 94-108.

Berelson

Bernard N.

Lazarsfeld

Paul F.

MacPhee

William N.

Voting: A Study of Opinion Formation in a Presidential Campaign. Chicago: University of Chicago Press, 1963.

Berry

Jeffrey

Portney

Kent

Thomson

Ken

. The Rebirth of Urban Democracy. Washington, DC: Brookings Institution, 1993.

Burkholder

Gary J.

Harlow

Lisa L.

“An Illustration of a Longitudinal Cross-Lagged Design for Larger Structural Equation Models.” Structural Equation Modeling 10 (2003): 465-86.

Burt

Ronald S

. “The Contingent Value of Social Capital.” Administrative Quarterly 42 (1997): 339-65.

Campbell

David E

. “Sticking Together: Classroom Diversity and Civic Education.” American Politics Research 35 (2007): 57-78.

10.

Cigler

Allan

Joslyn

Mark R.

“The Extensiveness of Group Membership and Social Capital: The Impact on Political Tolerance Attitudes.” Political Research Quarterly 55 (2002): 7-25.

11.

Coleman

James. S

. “Social Capital in the Creation of Human Capital.” American Journal of Sociology 94 (1988): 95-120.

12.

Costa

Dora L.

Kahn

Matthew E.

“Civic Engagement and Community Heterogeneity: An Economist’s Perspective.” Perspectives on Politics 1 (2003): 103-11.

13.

Dalton

Russell J.

The Good Citizen. How a Younger Generation Is Reshaping American Politics. Washington, DC: CQ Press, 2007.

14.

Dawson

Robert E.

Prewitt

Karen S.

Political Socialization: An Analytic Study. Boston, MA: Little Brown, 1969.

15.

Delli Carpini

Michael

Keeter

Scott

. What Americans Know about Politics and Why It Matters. New Haven, CT: Yale University Press, 1996.

16.

Eliasoph

Nina.

Avoiding Politics: How Americans Produce Apathy in Everyday Life. New York: Cambridge University Press, 1998.

17.

Eveland

William P.

Jr. Hively

Myiah Hutchens

. “Political Discussion Frequency, Network Size, and Heterogeneity of Discussion as Predictors of Political Knowledge and Participation.” Journal of Communication 59 (2009): 205-24.

18.

Eveland

W. P.

Scheufele

D. A.

“Connecting News Media Use with Gaps in Knowledge and Participation.” Political Communication 17 (2000): 215-37.

19.

Finkel

Steven E

. “Reciprocal Effects of Participation and Political Efficacy: A Panel Analysis.” American Journal of Political Science 29 (1985): 891-913.

20.

Galston

William A

. “Civic Education and Political Participation.” PSOnline 37 (2004): 263-66.

21.

Gerber

Alan S.

Green

Donald P.

Shachar

Ron

. “Voting May Be Habit Forming: Evidence from a Randomized Field Experiment.” American Journal of Political Science 47 (2003): 540-50.

22.

Granovetter

Mark

. “The Strength of Weak Ties.” American Journal of Sociology 78 (1973): 1360-380.

23.

Hancock

Gregory R.

Mueller

Ralph O.

Structural Equation Modeling. A Second Course. Greenwich, UK: Information Age Publishing, 2006.

24.

Harell

Allison

Stolle

Dietlind

Quintelier

Ellen

. 2011. “Experiencing Political Diversity: The Mobilizing Effect of Disagreement among Youth.” Unpublished manuscript.

25.

Hill

Kim Quail

Leighley

Jan E.

“Racial Diversity, Voter Turnout, and Mobilizing Institutions in the United States.” American Politics Research 27 (1999): 275-95.

26.

Hooghe

Marc

. “Value Congruence and Convergence within Voluntary Associations: Ethnocentrism in Belgian Organizations.” Political Behavior 25 (2003): 151-75.

27.

Huckfeldt

Robert

. “Political Participation and the Neighborhood Social Context.” American Journal of Political Science 23 (1979): 579-92.

28.

Huckfeldt

Robert

Johnson

P. E.

Sprague

John D.

Political Disagreement: The Survival of Diverse Opinions within Communication Networks, Cambridge Studies in Public Opinion and Political Psychology. Cambridge, UK: Cambridge University Press, 2004.

29.

Huckfeldt

Robert

Mendez

J. M.

Osborn

Tracy

. “Disagreement, Ambivalence, and Engagement: The Political Consequences of Heterogeneous Networks.” Political Psychology 25 (2004): 65-95.

30.

Jang

Seung-Jin

. “Are Diverse Political Networks Always Bad for Participatory Democracy? Indifference, Alienation, and Political Disagreement.” American Politics Research 37 (2009): 879-98.

31.

Jennings

M. Kent

Niemi

Richard G.

“Continuity and Change in Political Orientations: A Longitudinal Study of Two Generations.” American Political Science Review 69 (1975): 1316-335.

32.

Joyner

Kara

. “School Racial Composition and Adolescent Racial Homophily.” Social Science Quarterly 81 (2000): 810-25.

33.

Kenny

Christopher

. “Political Participation and Effects from the Social Environment.” American Journal of Political Science 36 (1992): 259-67.

34.

Klofstad

Casey.

The Art of Associating: The Central Role of Peers in Civic Life. Cambridge, MA: Harvard University, 2005.

35.

Knoke

David

. “Networks of Political Action: Toward Theory Construction.” Social Forces 68 (1990): 1041-063.

36.

Kwak

Nojin

Williams

Ann E.

Wang

Xiaoru

Lee

Hoon

. “Talking Politics and Engaging Politics: An Examination of the Interactive Relationships between Structural Features of Political Talk and Discussion Engagement.” Communication Research 32 (2005): 87-111.

37.

Lake

Ronald La Due

Huckfeldt

Robert

. “Social Networks, Social Capital, and Political Participation.” Political Psychology 19 (1998): 567-84.

38.

Lane

Robert E.

Political Life: Why and How People Get Involved in Politics. Glencoe, IL: Free Press, 1959.

39.

Langton

K. P.

Political Socialization. New York: Oxford University Press, 1969.

40.

Leighley

Jan

. “Social Interaction and Contextual Influences on Political Participation.” American Politics Research 18 (1990): 459-75.

41.

Lin

Nan

Cook

Karen S.

Burt

Ronald S.

Social Capital: Theory and Research. New York: Aldine de Gruyter, 2001.

42.

Marschall

Melissa

Stolle

Dietlind

. “Race and the City: Context and the Development of Generalized Trust.” Political Behavior 26 (2004): 125-53.

43.

McClurg

Scott

. “Social Networks and Political Participation: The Role of Social Interaction in Explaining Political Participation.” Political Research Quarterly 56 (2003): 449-64.

44.

McClurg

Scott

. “The Electoral Relevance of Political Talk: Examining Disagreement and Expertise Effects in Social Networks on Political Participation.” American Journal of Political Science 50 (2006a): 737-54.

45.

McClurg

Scott

. “Political Disagreement in Context: The Conditional Effect of Neighborhood Context, Disagreement and Political Talk on Electoral Participation.” Political Behavior 28 (2006b): 349-66.

46.

McKenzie

Brian

. “Reconsidering the Effects of Bonding Social Capital: A Closer Look at Black Civil Society Institutions in America.” Political Behavior 30 (2008): 25-45.

47.

McLeod

Jack M.

Scheufele

Dietram A.

Moy

Patricia

Horowitz

Edward M.

Holbert

R. Lance

Zhang

Weiwu

Zubric

Stephen

Zubric

Jessica

. “Understanding Deliberation: The Effects of Discussion Networks on Participation in a Public Forum.” Communication Research 26 (1999): 743-74.

48.

Muthén

Linda K.

Muthén

Bengt O.

Mplus User’s Guide. 5th ed. Los Angeles, CA: Muthén & Muthén, 2007.

49.

Mutz

Diana

. “The Consequences of Cross-Cutting Networks for Political Participation.” American Journal of Political Science 46 (2002a): 838-55.

50.

Mutz

Diana

. “Cross-Cutting Social Networks: Testing Democratic Theory in Practice.” American Political Science Review 96 (2002b): 111-26.

51.

Mutz

Diana.

Hearing the Other Side: Deliberative versus Participatory Democracy. New York: Cambridge University Press, 2006.

52.

Mutz

Diana

Mondak

Jeffrey

. “The Workplace as a Context for Cross-Cutting Political Discourse.” Journal of Politics 68 (2006): 140-55.

53.

Oliver

J. Eric

. “The Effects of Metropolitan Economic Segregation on Local Civic Participation.” American Journal of Political Science 43 (1999): 186-212.

54.

Pattie

Charles J.

Johnston

Ron J.

“Conversation, Disagreement and Political Participation.” Political Behavior 31 (2009): 261-85.

55.

Plutzer

Eric

. “Becoming a Habitual Voter: Inertia, Resources, and Growth in Young Adulthood.” American Political Science Review 96 (2002): 41-56.

56.

Price

Vincent

Cappella

Joseph

Nir

LIlach

. “Does Disagreement Contribute to More Deliberative Opinion.” Political Communication 19 (2002): 95-112.

57.

Putnam

Robert D.

Making Democracy Work: Civic Traditions in Modern Italy. Princeton, NJ: Princeton University Press, 1993.

58.

Putnam

Robert D.

Bowling Alone: The Collapse and Revival of American Community. New York: Simon and Schuster, 2000.

59.

Putnam

Robert D

. “E Pluribus Unum: Diversity and Community in the Twenty-First Century. The 2006 Johan Skytte Prize Lecture.” Scandinavian Political Studies 30 (2007): 137-74.

60.

Quintelier

Ellen

. “The Political Participation of Immigrant Youth in Belgium.” Journal of Ethnic and Migration Studies 35 (2009): 919-37.

61.

Rosenstone

Steven J.

Hansen

John Mark

. Mobilization, Participation, and Democracy in America. New York: Longman, 2003.

62.

Scheufele

Dietram A.

Hardy

Bruce W.

Brossard

Dominique

Waismel-Manor

Israel S.

Nisbet

Erik

. “Democracy Based on Difference: Examining the Links between Structural Heterogeneity of Discussion Networks, and Democratic Citizenship.” Journal of Communication 56 (2006): 728-53.

63.

Scheufele

Dietram

Nisbet

Matthew

Brossard

Dominique

Nisbet

Erik

. “Social Structure and Citizenship: Examining the Impact of Social Setting, Network Heterogeneity, and Informational Variables on Political Participation.” Scandinavian Political Studies 26 (2004): 49-66.

64.

Schlueter

Elmar

Davidov

Eldad

Schmidt

Peter

. “Applying Autoregressive Cross-Lagged and Latent Growth Curve Models to a Three-Wave Panel Study.” In Longitudinal Models in the Behavioral and Related Sciences, edited by van Montfort

Kees

Oud

Johan

Satorra

Albert

, 315-37. Mahwah, NJ: Lawrence Erlbaum, 2007.

65.

Schulz

Wolfram

Ainley

John

Fraillon

Jullian

Kerr

David

Losito

Bruno

. 2010. Initial Findings from the IEA International Civic and Citizenship Education Study. Amsterdam, The Netherlands: International Association for the Evaluation of Educational Achievement.

66.

Seligsen

Amber

. “Civic Association and Democratic Participation in Central America.” Comparative Political Studies 32 (1999): 342-62.

67.

Stoker

Laura

Jennings

M. Kent

. “Life-Cycle Transitions and Political Participation: The Case of Marriage.” American Political Science Review 89 (1995): 421-33.

68.

Stolle

Dietlind

. “Clubs and Congregations: The Benefits of Joining and Association.” In Trust in Society, edited by Cook

K. S.

, 202-24. New York: Russell Sage Foundation Series on Trust, 2001a.

69.

Stolle

Dietlind.

“Getting to Trust: An Analysis of the Importance of Institutions, Families. Personal Experiences and Group Membership.” In Politics in Everyday Life: Social Capital and Participation, edited by Dekker

Uslaner

E. M.

, 105-19. London: Routledge, 2001b.

70.

Stolle

Dietlind

Harell

Allison

Mahéo

Valérie-Anne

. Dataset of the McGill Youth Survey 2006. Montreal: McGill University, 2006.

71.

Teorell

Jan

. “Linking Social Capital to Political Participation: Voluntary Associations and Networks of Recruitment in Sweden.” Scandinavian Political Studies 26 (2003): 49-66.

72.

Ulbig

Stacy

Funk

Carolyn

. “Conflict Avoidance and Political Participation.” Political Behavior 21 (1999): 265-82.

73.

Uslaner

Eric.

The Moral Foundations of Trust. Cambridge, UK: Cambridge University Press, 2002.

74.

Verba

Sidney

Schlozman

Kay L.

Brady

Henry E.

Voice and Equality: Civic Voluntarism in American Politics. Cambridge, MA: Harvard University Press, 1995.