Predictors of protest, conventional and civic participation: A
representative study of Slovenian youth
Assistant Prof. Dr. Andrej Kirbiš
Department of Sociology,
Faculty of Arts,
University of Maribor, Slovenia
andrej.kirbis@um.si
Assistant Prof. Dr. Marina Tavčar Krajnc
Department of Sociology,
Faculty of Arts,
University of Maribor, Slovenia
marina.tavcar@um.si
Assistant Tina Cupar
Department of Sociology,
Faculty of Arts,
University of Maribor, Slovenia
tina.cupar@um.si
Abstract: Previous studies have indicated that protest participation (i.e. elite-challenging
behaviour) has been increasing in recent decades in industrialized and postcommunist
countries, along with the emergence of a “critical citizen” (Norris, 1999; Inglehart and
Catterberg, 2002; Dalton and van Sickle, 2005; Inglehart and Welzel, 2007; Kirbiš, 2013). In
addition, past research has also indicated that protest engagement is more frequent among
more pro-democratic oriented public (both in established and postcommunist European
democracies; Kirbiš, 2013) and among youth; yet young people are on the other hand also less
frequently active in conventional (i.e. “political party”) politics (Kirbiš and Flere, 2011). Few
studies have compared predictors of different dimensions of citizen participation among
postcommunist youth. The purpose of the present study was to examine Civic Voluntarism
Model (CVM; Verba et al., 1995) by testing three competing models (resources, political
cultural and social network model) and their power in predicting different dimensions of
citizen participation. We analyzed survey data from Youth 2010 study – a representative
sample of Slovenian youth (N = 1257, M age = 22.5 years, SD = 4.25; 48.8 % female).
Principal component analysis of indicators of citizen participation identified three distinct
dimensions of citizen participation: conventional political participation, protest participation
and civic (social) participation. Results of regression analyses indicated that the three models
within CVM explained 17.2 % of variance (Adjusted R2) in protest, 13.0 % in conventional
and 5.8 % of variance in civic participation. Political cultural model explained the largest
amount of variance in all three participation dimensions. Among predictor variables, political
interest, a feeling of duty to vote, more frequent discussion of politics with friends/peers,
female gender and older age were the strongest and most frequently significant predictors of
citizen participation. Implications of the results are discussed in terms of the future of
democratic consolidation processes in postcommunist states.
Keywords: citizen participation, protest participation, conventional political participation,
youth, democratic consolidation, postcommunist democracies, Slvoenia.
1.1 Introduction
Citizen participation – in a broader sense defined as activities of individuals or groups with
the aim to influence the life of the political community (Macedo et al., 2005; Zukin et al.,
2006), and in a narrow sense defined as activities whose purpose or consequence is
influencing decision-making (Kaase and Marsh, 1979; Parry et al., 1992) – is considered one
of the key elements of a functioning democracy (Almond and Verba, 1963; Pateman, 1970;
Dahl, 1972; Barber, 1984; Parry and Moyser, 1994). Verba and Nie (1972: 1), for instance,
argued that “Where few take part in decisions there is little democracy; the more participation
there is in decisions, the more democracy there is”. Within the context of studies on citizen
participation, participation of youth and young adults in old and new (postcommunist)
democracies has received increasing attention during the last decades. One of the important
aspects of citizen participation is also participation inequalities; i.e., what is the extent of
differences in citizen participation among different groups within societies and what accounts
for (explains) these differences.
Our analysis will involve three dimensions of citizen participation since researchers most
commonly differentiate between conventional political participation (e.g., trying to convince
others who to vote for, contacting politicians, contributing money to or working for political
parties/candidates, etc.), protest participation (e.g., demonstrating, boycotting products,
signing petitions, etc.) and civic/social participation (e.g., being a member of a voluntary
organization, doing charitable work, etc.) (Barnes et al., 1979; Mihailović, 1986; Pantić, 1988;
Inglehart and Catterberg, 2002; Torney-Purta and Richardson, 2002; Zukin et al., 2006).
Previous studies have indicated that among these dimensions, protest participation (i.e. “elitechallenging” behaviour) has been increasing in recent decades in industrialized and
postcommunist countries and that a phenomenon of “critical citizen” emerged alongside
(Norris, 1999; Inglehart and Catterberg, 2002; Dalton and van Sickle, 2005; Inglehart and
Welzel, 2007; Kirbiš, 2013). In addition, past research has also indicated that protest
participation is more frequent among more pro-democratic oriented public (both in
established and postcommunist European democracies; Kirbiš, 2013) and among youth; yet
young people are on the other hand also less frequently active in conventional (i.e. party)
politics (Kirbiš and Flere, 2011). Few previous studies have compared predictors of different
dimensions of citizen participation among postcommunist youth.
One of the most prominent explanations of within-country differences in citizen participation
has been the Civic Voluntarism Model (CVM; Verba et al., 1995), which “entails the
accumulation of various factors—resources, location in networks of recruitment, and
psychological involvement in politics—that facilitate participation” (Burns et al., 2001: 198).
In other words, the question on factors of political participation (i.e., the question of “Why
people participate?”) can be inverted and a question may be asked: why people do not
participate (Verba et al., 1995: 269). Verba and colleagues argue that people are politically
inactive because they can’t be, don’t want to be or because nobody asked them to be
politically active (ibid.: 269). In the following paragraphs we turn briefly to each of these
three factors influencing participation: resources, engagement and recruitment/mobilization.
Resource model has been one of the most widely accepted models of citizen participation
(Norris, 2002: 29). The argument goes that personal resources, especially those regarding
one’s socioeconomic status (SES), may increase the likelihood of one’s engagement in
politics and public life. Specifically, “SES increases citizens’ skills with regard to managing
and understanding political content and being active in the public sphere. Individuals with
higher SES therefore have more resources available (higher education and occupational
status, more economic resources, etc.), which allows them to participate in political life more
frequently and with less effort” (Kirbiš, 2013: 182; see Cho et al., 2006; Sandell Pacheco and
Plutzer, 2008). In fact, Verba and colleagues argue that the majority of differences in
participation at the individual level stem from the socioeconomic status of an individual
(Verba et al., 2003: 56). Other resources, which include time, money (e.g., income, as an
important dimension of SES), and civic (verbal and cognitive) skills (Burns et al., 2001: 201;
Badescu and Neller, 2007) may also impact citizen participation.
Political cultural model or psychological involvement/engagement model is the second group
of factors previously found to influence citizen participation within the CVM. The concept of
psychological political engagement refers to the motivational and cognitive elements of
political culture (Norris, 2002; Pantić in Pavlović, 2009), which in past research proved to be
one of the most important factors of citizen participation. In other words, being motivated to
be active in politics, being interested in political life, and not feeling powerless when it comes
to influencing political institutions and political actors, increases the likelihood of citizen
participation. Within political engagement model, political interest (Macaluso and Wanat,
1979; Shin, 1999: 117; Patterson, 2005; Hutcheson and Korosteleva, 2006), political trust
(Thomassen and van Deth, 1998; Letki, 2004; Hadjar and Beck, 2010; cf. Spehr and Dutt,
2004; Besley, 2006; Smith, 2009), internal political efficacy (Solhaug, 2006; McIntosh et al.,
2007; cf. DiFranceisco in Gitelman, 1984; Bäck in Teorell, 2005) and external political
efficacy (Thomassen and van Deth, 1998: 158; Roller and Rudi, 2008; 266; van Deth, 2008:
203; cf. Duch, 1998) were found to impact citizen participation. Within political cultural
model, other concepts such as (dis)satisfaction with democracy (Badescu and Neller, 2007),
having a sense of duty to be active in politics (e.g., to turn out to vote) and others also play a
prominent role (Norris, 2002: 29).
Finally, social networks and recruitment, including within different settings of institutional
affiliation, can also greatly impact one’s citizen participation. As Burns and colleagues show,
institutional involvement (e.g., being employed, being a member of a voluntary association,
being engaged in a religious institution) has been found linked to citizen participation (Burns
et al., 2001: 198; see, among others, Verba et al., 1995; Conway, 2000; Norris, 2002). When
examining the impact of social networks on citizen participation, it is necessary to include not
only nominal institutional affiliation, but also a wider social context, i.e. family and
friends/peer context, (news) media exposure, religious engagement, etc. For this reason our
analysis will include three dimensions of social network: 1) political media use, which was
previously found to be associated with higher levels of citizen participation (Pasek et al.,
2006, Romer et al., 2009); 2) individual’s social networks with regard to political discussions
both with family members and friends/peers (discussing politics with parents and peers) since
discussing politics more frequently has previously also been found to be associated with more
frequent citizen participation (McLeod et al., 1999; Scheufele, 2002; Kang and Kwak, 2003;
also see Bimber et al., 2014); and 3) church attendance as an indicator of not merely
institutional affiliations but also active engagement in religious life, which has previously also
been found to increase the likelihood of citizen participation (Shupe, 1977; Brady et al., 1995;
Leong, 2004; Conklin, 2008; Smith, 2009).
1.2 The aim of the study
The aim of the present study was to examine the predictors of three dimensions of citizen
participation; specifically, to test the predictive power of Civic Voluntarism Model, and
within it, to compare the predictive power of each of the three individual predictive models of
citizen participation using data from a representative national study of Slovenian youth from
2010 (young people aged 15–29 years). The main research question was: which of the three
citizen participation dimensions are explained to the largest extent by CVM (RQ1). The
second research question was: is there a model which explains the largest amount of variance
in all three citizen participation dimensions (RQ2)? The third research question was: which
individual variable is the best predictor of citizen participation (RQ3)? Finally, based on
previous studies we predicted that each of the three models would significantly predict each
of the dimensions of citizen participation (Hypothesis 1).
1.3 Methods
1.3.1
Sample
Slovenian Youth 2010 study was based on a representative random sample of Slovenian
youth. The target population were all residents residing in the Republic of Slovenia, who were
on July 26th aged between 15 and 29 years (N = 1257; Mage = 22.90; SD = 4.25; 48.3 %
women). Field survey was conducted between July 27th and September 24th in the form of
face-to-face interviews. The target population of the study was prior stratified into twelve
statistical regions and six types of settlements (for details on sampling, data collection, etc.,
see Lavrič et al., 2011).
The survey questionnaire consisted of two parts: oral and written part. The oral part of the
questionnaire was conducted within face-to-face interviews with interviewers reading the
questions aloud to interviewees and with interviewers filling out survey responses they
received from the respondents. Upon completion of the oral part of the questionnaire the
interviewer handed the respondent the written questionnaire and asked him/her to fill out the
written questionnaire himself. Written part of the questionnaire consisted of questions that
were more personal and intimate in nature.
1.3.2
Measures
1.3.2.1 Predictor variables
Resources model
We measured respondent’s family and personal socioeconomic resources by means of three
commonly used indicators of socioeconomic status (SES): maternal and paternal educational
level and self-perceived family material status of respondents.
Parental education
We measured father’s and mother’s educations with two identical questions on a 9-point
scale: “What is the highest achieved level of [your father’s / your mother’s] education?” (1 =
uncompleted primary school; 2 = completed primary education; 3 = uncompleted vocational
or other secondary education; 4 = completed 2-year, 2.5-year or 3-year vocational secondary
education; 5 = completed 4-year secondary education; 6 = uncompleted higher non-university
education; 7 = completed 2-year higher non-university education; 8 = completed university
education; 9 = completed master or doctorate degree). For the purposes of statistical analyses
the values were recoded into a 3-point scale: 1 = uncompleted secondary education (original
values 1, 2, 3); 2 = completed secondary education (original values 4, 5, 6); 3 = completed
tertiary education (original values 7, 8, 9)).
Self-perceived family material status
Respondents also assessed their family material (economic) status in comparison to perceived
Slovenian average with the following question: “How do you rate the material situation of
your family according to the Slovenian average”? Family material status was coded on a 5point scale (1 = highly below average; 5 = highly above average). We recoded the 5-point
scale into a 3-point scale of family’s relative material status (1 = (highly) below average, 2 =
average; 3 = (highly) above average).
Three demographic variables included in our resources model were age (measured as year of
birth, recoded into age in years and the into age groups: 1 = 15-18 years, 2 = 19-24 years, 3 =
25-29 years), gender (female = 1, male = 2) and size of current residential settlement (1 =
larger city, 2 = small town (between 1,000 and 50,000 inhabitants), 3 = countryside/village).
All three demographic variables were included in resources model since previous studies have
indicated that age (Zukin et al., 2006; Quintelier, 2007; Dalton, 2008; Fahmy, 2006), gender
(Almond and Verba, 1963; Parry et al., 1992; Rosenstone and Hansen, 1993; Schlozman
et al., 1995; Verba et al. 1995; Vassallo, 2006) and living in urban environment (Milbrath,
1965: 114; Mihailović, 1986; Inglehart, 1997; Shin, 1999: 113) were significant predictors of
more frequent citizen participation, although previous studies of Slovenian youth (e.g., Kirbiš
and Flere, 2011; Kirbiš and Zagorc, 2014) have not detected significant differences in citizen
participation between age groups and between genders.
Political cultural model
The predictors included in this model were political interest, ideological (left-right)
orientation, internal and external political efficacy, satisfaction with the state of democracy in
Slovenia, and attitude that turning out to vote is a citizen’s duty.
Interest in politics was measured with the following item: “People have different interest in
politics. How interested would you say you are in politics? (1 = not interested at all; 4 = very
interested).
Ideological (left-right) orientation was tapped with the following item: “In politics people talk
about “left” and “right”. Where would you place yourself on a scale from 0 to 10, where “0”
indicates “left”, “10” indicates “right” and where “5” indicates “the middle”? Please assess
using the scale below”.
Internal political efficacy was a tapped with the flowing item: “I have a good understanding
of politics”. The indicator was rated on a 5-point Liker scale (1 = does not apply to me at all;
5 = applies completely to me).
External political efficacy was a summation scale which consisted of three indicators:
“Politicians are generally interested only in getting elected and not in what voters really
want”; “People like me don’t have any influence anyway on what the authorities do” and “I
don't believe politicians spend a lot of time on what people like me think”. The indicators
were rated on a 5-point Liker scale (1 = does not apply to me at all; 5 = applies completely to
me). Reliability of the scale was found to be sufficiently high (Cronbach’s alpha = 0.76).
Satisfaction with the state of democracy in Slovenia was measured with the following item:
”In general, how satisfied are you with the state of democracy in Slovenia? Please indicate it
on a scale from 1 (not satisfied at all) to 5 (very satisfied), and where “3” indicates the middle
point. Please assess using the scale below”.
Finally, we measured the extent of (dis)agreement that turning out to vote is citizens’ duty
with the following item: “It is every citizen’s duty to take part in elections” (1 = totally
disagree; 5 = totally agree).
Social network model
Predictors included in this model were the use of different forms of media with political
contents, discussing politics with parents and with friends/peers, and the frequency of church
attendance.
Political media use was measured with the following questions: How often do you follow
politics/news in the following mass media: A) TV; B) newspapers; C) radio; D) the Internet
(1 = never, 2 = less than once a month, 3 = 1-3 times a month, 4 = 1-3 times a week, 5 = 4-6
times a week, 6 = daily). Summation scale was formed from these five items and the
reliability of the scale was found to be sufficiently high (Cronbach’s alpha = 0.81).
Political discussion was measured with the following two items: How often do you discuss
politics with: A) parents; B) friends/peers (1 = never, 2 = less than once a month, 3 = 1-3
times a month, 4 = 1-3 times a week, 5 = 4-6 times a week, 6 = daily).
Church attendance was measured with the following question: “How often do you attend
church/religious services?” (1 = regularly, several times a week; 2 = regularly, every week; 3
= at least one or twice a month; 4 = several times a years; 5 = one of twice a year for religious
holidays; 6 = never). The original values were then recoded into five values (1 = never; 2 =
one of twice a year for religious holidays; 3 = several times a years; 4 = at least one or twice a
month; 5 = regularly, at least weekly).
1.3.2.2 Outcome variables
Youth 2010 survey questionnaire contained numerous indicators of citizen participation.
Principal component analysis (PCA) carried out on thirteen indicators of citizen participation
identified three distinct dimensions of citizen participation: non-electoral conventional
political participation, protest participation and civic (social) participation (PCA results not
shown; analyses can be obtained from the authors). In the next paragraphs, we describe the
indicators and summations scales of participation dimensions.
Non-electoral conventional political participation
Non-electoral conventional political participation was measured with five items. The
following question was asked for all participation items: “People are active in politics in
different ways. Have you ever been engaged in the following activities or would you be
engaged in them if you had the possibility?”. The items were: “Try to convince others to vote
for the same candidate or party as me”, “Contact politicians”, “Contribute money to a political
party”, “Work for political party or candidate”, and “Hand out leaflets with political content”.
All items were rated on a scale from 1 to 3 (1 = would definitely not do; 2 = would probably
do, 3 = have already done). Summation scale was formed and the reliability of the scale was
found to be sufficiently high (Cronbach’s alpha = 0.70).
Protest participation
Protest participation was tapped with following four items: [Have you ever] “Sign a petition
(printed or electronic)”, “Attend lawful demonstrations”, “Boycott buying certain products for
political, ethical or environmental reasons”, “Buy certain products for political, ethical or
environmental reasons”. All items were rated on a scale from 1 to 3 (1 = would definitely not
do; 2 = would probably do, 3 = have already done). Summation scale was formed and the
reliability of the scale was found to be sufficiently high (Cronbach’s alpha = 0.65).
Civic participation
Civic participation was measured with four items on the frequency of: “Helping peers with
learning”, “Counseling peers on their problems”, “Helping the elderly”, “Helping
physically/mentally challenged”. All items were rated on a scale from 1 to 3 (1 = would
definitely not do; 2 = would probably do, 3 = have already done). Summation scale was
formed and the reliability of the scale was found to be sufficiently high (Cronbach’s alpha =
0.73).
All three outcome summation scales were split into quartiles, which means that each
respondent received a value from 1 (lowest quartile on a particular summation scale) to 4
(highest quartile on a particular summation scale).
1.4 Results
In accordance with our main study aim we were first interested in how much of the variance
in three dimensions of citizen participation could be explained by three competing
explanatory models. Multiple regression analysis was employed; Table 1 presents the results.
Table 1: Hierarchical regression analyses estimating the effects of resources model, political
cultural model and social network model on three dimensions of citizen participation:
conventional political participation (CPP), protest participation (PP) and civic participation
(CP) among Slovenian youth in 2010.
Convention. P.
B
Constant
1.51
.35
Gender
(male)
.04
.05
Age group
.14
.04
Size of
settlement
Father’s
education
Mother’s
education
Subjective
SES
Political
interest
Ideological
(L-R)
placement
Internal
inefficacy
External
inefficacy
Satisfaction
with
democracy
Voting is
duty
Political
media use
Political
discussions
with parents
Political
discussions
with peers
Church
attendance
SE B
β
B
Constant
1.21
.31
.02
Gender
(male)
-.11
.05
-.07
.13
Age group
.10
.03
.10
-.04
.04
-.04
-.01
.02
-.01
.01
.02
.01
.03
.06
.02
.09
.04
.10
-.01
.01
-.01
-.07
.04
-.08
-.01
.03
-.01
.00
.03
.00
-.03
.02
-.03
.04
.02
.06
.07
.03
.10
.07
.03
.09
-.01
.02
-.01
Size of
settlement
Father’s
education
Mother’s
education
Subjective
SES
Political
interest
Ideological
(L-R)
placement
Internal
inefficacy
External
inefficacy
Satisfaction
with
democracy
Voting is
duty
Political
media use
Political
discussions
with parents
Political
discussions
with peers
Church
attendance
SE B
β
Protest P.
-.09
.03
-.09
.02
.02
.05
.01
.02
.02
.07
.05
.04
.08
.04
.10
-.01
.01
-.03
-.02
.03
-.02
.03
.03
.03
.02
.03
.03
.05
.02
.08
.01
.02
.02
.07
.03
.10
.11
.03
.17
-.01
.02
-.02
B
Constant
1.91
.35
Gender
(male)
-.21
.05
-.13
.02
.04
.02
.01
.04
.01
.01
.02
.02
.02
.02
.05
-.08
.06
-.05
-.10
.04
-.11
-.01
.01
-.02
-.06
.04
-.08
.09
.03
.10
.01
.03
.01
.09
.02
.13
.03
.02
.04
.01
.03
.01
.00
.03
.00
.07
.02
.10
Age group
Size of
settlement
Father’s
education
Mother’s
education
Subjective
SES
Political
interest
Ideological
(L-R)
placement
Internal
inefficacy
External
inefficacy
Satisfaction
with
democracy
Voting is
duty
Political
media use
Political
discussions
with parents
Political
discussions
with peers
Church
attendance
R2 = .13
R2 = .172
R2 = .058
F = 10.09
F = 13.69
F = 4.75
SE B
β
Civic P.
Source: Slovenian Youth 2010 Study (2011).
Note: Beta values that are underlined indicate p < .05; beta values that are in bold indicate p <. 01; and beta
values that are both underlined and in bold indicate p < .001.
Table contains only values from model 3, where all three predictor models were entered into regression analysis.
Remaining data can be obtained by interested reader by contacting the authors.
R2 = Adjusted variance.
In all three models, resources variables together with three demographic variables (gender,
age group and size of residential settlement) were entered at Step 1. These variables explained
combined 4.0 % of the adjusted variance in conventional political participation. After the
entry of six variables of political cultural (psychological political involvement/engagement)
model at Step 2, the total variance explained by the model as a whole was 10.8 %, F (12, 963)
= 10.81, p < .001. Six political cultural variables explained an additional 7.3 % of the
variance in conventional political participation, after controlling for resources variables (F
change p < .001). Finally, three social network variables were entered into the model
explaining an additional 2.5 % of the variance in conventional political participation,
after controlling for resources and political cultural variables. Final model explained 13 %
of variance (adjusted) in conventional political participation. In the final model, only four
variables were statistically significant predictors of more frequent conventional participation:
higher age (beta = .13, p < .001), more frequent discussions of politics with parents (beta =
.10, p < .05), higher political interest (beta = .10, p < .05) and more frequent discussions of
politics with friends/peers (beta = .09, p < .05).
With regard to protest participation, resources variables together with three demographic
variables were again entered at Step 1. These variables explained combined 6.4 % of the
adjusted variance in protest participation. After the entry of six variables of political cultural
model at Step 2, the total variance explained by the model as a whole was 13.4 %, F (12, 963)
= 13.58, p < .001. Six political cultural variables explained an additional 7.5 % of the
variance in protest participation, after controlling for resources variables (F change p <
.001). Finally, three social network variables were entered into the model explaining an
additional 4.1 % of the variance in protest participation, after controlling for resources
and political cultural variables. Final model explained 17.2 % of variance (adjusted) in protest
participation. In the final model, six variables were statistically significant predictors of more
frequent protest participation: those discussing politics more frequently with their
friends/peers (beta = .17, p < .001), older youth (beta = .10, p < .001), those more interested in
politics (beta = .10, p < .05), those living in urban environment (beta = .09, p < .01), those
saying that voting is a duty (beta = .08, p < .05) and women (beta = .07, p < .05) were
significantly more frequently engaged in protest activities.
With regard to civic participation, resources variables together with three demographic
variables were again entered at Step 1. These variables explained combined 2.4 % of the
adjusted variance in civic participation. After the entry of six variables of political cultural
model at Step 2, the total variance explained by the model as a whole was 5.2 %, F (12, 961)
= 5.42, p < .001. Six political cultural variables explained an additional 3.4 % of the
variance in civic participation, after controlling for resources variables (F change p <
.001). Finally, three social network variables were entered into the model explaining an
additional 1.0 % of the variance in civic participation, after controlling for resources
and political cultural variables. Final model explained 5.8 % of variance (adjusted) in civic
participation. In the final model, five variables were statistically significant predictors of more
frequent civic participation: those saying that voting is a duty (beta = .13, p < .001), women
(beta = .13, p < .001), those less interested in politics (beta = -.11, p < .05), those with more
frequent church attendance (beta = .10, p < .01) and those reporting lower levels of external
political efficacy (beta = .10, p < .01) were significantly more frequently engaged in civic
activities.
With regard to our main research question RQ1 (Which of the three citizen participation
dimensions is explained to the largest extent by CVM?) the results indicated that CVM is the
best explanatory model for protest participation (Adj. R2 = 17.2 %), followed by conventional
political participation (Adj. R2 = 13 %) and civic participation (Adj. R2 = 5.8 %).
With regard to the second research question (Is there a model which explains the largest
amount of variance in all three citizen participation dimensions?) we found that political
cultural (psychological engagement) model contributed to the largest R2 change in all three
dimension of citizen participation: 7.3 % in conventional political participation, 7.5 % in
protest participation and 3.4 % in civic participation. Other two models predicted substantially
smaller amounts of variance.
With regard to the third research question (Which individual variable is the best predictor of
citizen participation?) the results indicated that the only predictor variable that was significant
in all three citizen participation dimensions was political interest. Interestingly, higher levels
of political interest were (consistent with results of previous studies; e.g., Verba et al., 1995:
352; Burns et al., 2001: 267; Martin and van Deth, 2007; Bimber et al., 2014; also see
Conway, 2000) found to predict more frequent conventional and protest participation, yet
inconsistent with previous studies (Badescu and Neller, 2007; Martin and van Deth, 2007)
less frequent civic participation. The second best predictor within political cultural model of
citizen participation was the sense of duty to vote, which significantly and positively impacted
both conventional and protest participation.
Within social networks model discussing politics with friend/peers was significantly and
positively associated with two participation dimensions: conventional and protest
participation, followed by discussing politics with parents (associated with more frequent
conventional participation), and church attendance (associated with more frequent civic
participation).
Finally, based on previous studies we predicted that each of the three models would
significantly predict each of the dimensions of citizen participation (Hypothesis 1). Our H1
was confirmed since each three models contributed to significant (.05< p <.001) R2 change in
all three dimensions of citizen participation.
1.5 Discussion and conclusion
The present study examined the predictors of three dimensions of citizen participation by
testing the predictive power of Civic Voluntarism Model and by comparing the predictive
power of each of the three individual predictive models of citizen participation within CVM.
Nationally representative data from the study of Slovenian youth from 2010 (young people
aged 15–29 years) was employed.
Although Civic Voluntarism Model was found to significantly predict all three dimensions of
citizen participation, it was also found that it was not a substantial predictor, since it predicted
only from 17.2 % of adjusted variance in protest participation to 5.8 % of adjusted variance in
civic participation. It seems that among Slovenian youth CVM is able to predict almost a fifth
of protest participation but less than 6 % of civic participation. Within CVM, political
cultural model was the best predictor explaining the largest amount of variance in all three
dimensions of citizen participation. Specifically, political interest was the only significant
predictor in all three dimensions of participation, with those being more interested in politics
also being more conventionally politically active (consistent with other studies; e.g., Verba et
al., 1995: 352) and more protest engaged, while, at the same time, being less civically
engaged. This latter finding is in contrast with other studies on the link between political
interest and civic participation (e.g., associational involvement; see Badescu and Neller,
2007). Future studies should take a deeper look at the reasons for such a link among
Slovenian youth. As already mentioned, the second best predictor of citizen participation
within political cultural model was the sense of duty to vote, which significantly and
positively impacted conventional and protest participation, but not civic participation. It is
especially interesting that a sense of duty to vote predicts protest participation, after
controlling for all other variables, which is a finding in need of deeper inspection in the
future.
Within social networks model discussing politics with friend/peers was found to be
significantly and positively associated with conventional and protest participation, discussing
politics was found to be significantly and positively associated with more frequent
conventional participation, and church attendance was found to be significantly and positively
associated civic participation. All other social networks predictors proved not to be
significant. It seems that discussing politics with friends/peers is the most important factor
influencing citizen participation of Slovenian youth, even when controlling for all other
variables in the model. Our study results thus indicate that future studies should more closely
examine political socialization processes, especially those taking place in school, peer group
and family. Interestingly, in our study political media use was found insignificant predictor of
all three participation dimensions.
Finally, within resources model none of the indicators of socioeconomic status proved a
significant predictor in either dimension of citizen participation. In other words, we detected
no socioeconomic inequalities in citizen participation among Slovenian youth using our three
indicators of SES. Although this seems encouraging for the process of democratic
consolidation, two points should be emphasized. First, an important limitation of our study
was the limited number of SES variables. Future studies should examine the impact of
additional SES indicators, including those indicating objective and subjective material
deprivation. Secondly, we have measured resources in terms of family SES (parental
education and subjective material status of the family), but not personal SES. Interestingly,
within resources model, there were nevertheless significant demographic predictors: women
were found more frequently active on protest and civic participation dimensions, while older
youth were found more frequently active on conventional and protest participation
dimensions.
Despite several limitations of the present study, it was nevertheless one of the few to test the
Civic Voluntarism Model on a representative sample of youth from a postcommunist country.
One of the prerequisites of democracy is not only democratic political culture, such as
democratic values and attitudes (Inglehart in Welzel, 2007), but also pro-democratic
behaviour. In this sense citizen participation is regarded as one of the most important elements
of a functioning democracy (Almond and Verba, 1963; Pateman, 1970; Dahl, 1972; Barber,
1984). Democratic orientation and behaviour of public in postcommunist countries thus plays
an important role for the democratic functioning and consolidation of younger democratic
states. Understanding the predictors of citizen participation in new democracies, especially
among youth, can thus shed light and contribute to continued and effective consolidation of
postcommunist democracies.
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