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Unaffiliated demonstrators: How they are mobilized, with whom they identify, how they are
motivated*
Bert Klandermans, Jacquelien van Stekelenburg, Marie-Louise Damen, Dunya van Troost and
Anouk van Leeuwen
VU-University, Amsterdam
The Netherlands
*This research was supported by the European Science Foundation Grant (ESF-08-ECRP001). Send all correspondence to Bert Klandermans (p.g.klandermans@vu.nl).
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Abstract
Collective action literature tends to focus on how people are affiliated to mobilizing structures
and on how affiliation to these networks facilitates collective action participation. Much less
attention is given to the fact that sometimes large proportions of the participants are not
affiliated to the organizers’ networks. In this paper we compare the social psychological
dynamics of participation in street demonstrations for participants who are not affiliated to the
organizers with those of participants who are. How were they mobilized; what was their
collective identity and what was their motivation? Reporting data from a unique study of 60
street demonstrations in seven European countries we compare the social psychological
dynamics of participation by unaffiliated and affiliated demonstrators (n=12.681). The paper
theorizes about the impact of being unaffiliated on the processes of mobilization,
identification and motivation. Fifty-one percent of the demonstrators appeared to be
unaffiliated to the organizers. The 60 demonstrations span the whole range from hardly
anybody who is unaffiliated to the organizers to almost everybody. Our findings show that
unaffiliated demonstrators are mobilized in different manners than affiliated demonstrators;
patterns of identification with the organizers and the other participants differ, as do the
strength and nature of their motivation.
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In the year 2009 we surveyed a protest demonstration in Rotterdam against a proposal by the
Dutch government to restrict early retirement rights. Over 85% of the participants were
members of the labor unions that staged the demonstration while 15% were not. A few
months later we covered a demonstration against austerity measures in the cultural sector of
the Dutch society. This time, no more than 11.5% of the participants were members of
organizations that staged the event while 88.5% were not. The literature on protest
participation is very clear with regard to the impact of affiliation to organizer networks on
protest participation. Citizens who are affiliated to the networks of the organizers are more
likely to take part in the protest event than citizens who are not. But fifteen of every hundred
participants in the early retirement demonstration and close to ninety in the culture
demonstration were not affiliated to the organizers’ networks . This raises the question how
they got involved?
Collective action literature tends to focus on how people are affiliated to mobilizing
structures and on how affiliation to these networks facilitates collective action participation.
Much less attention is given to the fact that sometimes large proportions of the participants are
not affiliated to the organizers’ networks. In this paper we compare the social psychological
dynamics of participation in street demonstrations for participants who are not affiliated to the
organizers with that of participants who are. How were they mobilized; what was their
collective identity like and what was their motivation? Movement research is not very well
versed to make such comparisons. Most research among participants in protest events
concerns single case studies or general surveys retrospectively inquiring whether people have
taken part in any protest event in the past so many years. Case studies by definition don’t have
comparative designs, while general surveys such as the World Value Survey or the European
Social Survey register reported participation in collective action in general, but do not specify
which action individuals took part in. Yet, such information is needed for a comparison of
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affiliated and unaffiliated participants in various instances of collective action. So far, such
comparative research among participants in protest events was lacking. This article begins to
fill the gap. Reporting data from a study of 60 street demonstrations in seven different
countries we will compare the social psychological dynamics of participation for unaffiliated
demonstrators and affiliated demonstrators. We will begin with an explanation of how social
cleavage structures in a society together with organizers’ efforts to build mobilizing structures
make that some participants in collective action are unaffiliated to the organizers. We will
then theorize about the impact of being unaffiliated on the processes of mobilization,
identification and motivation. Next we will report results from our demonstrations study to
test our hypotheses. In a concluding section we will interpret our findings.
Social cleavages and affiliation to the organizers
Why is it that some participants are affiliated to the organizers while others are not? This
evolves from the fit between the mobilizing structures that the organizers assemble and the
organizational fields potential participants are embedded in. Organizers forge mobilizing
structures from the organizational fields in society. If individuals are embedded in those parts
of the organizational fields organizers built into a mobilizing structure, they end up being
affiliated to the organizers. These mobilizing structures and organizational fields are not
random but shaped by a society’s cleavage structures. The issues movements mobilize people
for reflect the social cleavages in a society (Verhulst 2011; Jansen 2011). The cleavages these
issues are related to determine along which fault lines people tend to mobilize. (Kriesi et al.
1995). According to Lipset and Rokkan (1967) political conflict in societies is related to a
limited number of cleavages of which class, religion, ethnicity, and region are the most
important. Kriesi et al. (2008) proposed a ‘new’ schism between ‘winners’ and ‘losers’ of
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globalization; while Hutter (2011) suggests the ‘integration’ ‘demarcation’ cleavage in
European countries caused by waves of migration. Others have proposed ‘new’ attitudinal
cleavages re issues such as the environmental and animal rights (cf. Jansen, 2011), or see an
unlimited number of cleavages (Knutsen 2007). In a similar vein, resource mobilizationists
have argued that grievances abound.
A society’s cleavage structure reflects in the mobilization potentials of the social
movement sector. A social movement’s mobilization potential consists of the people who
sympathize with the movement’s cause. Movements with large mobilization potentials are
more likely to successfully mobilize people to take part in their activities. In his discussion of
the dynamics of demand Klandermans (2013) argues that the characteristics of a social
movement’s mobilization potential construe the demand side of protest. A movement’s
mobilization potential can be characterized in terms of its demographic composition; in terms
of collective identities, shared grievances and emotions; and in terms of its organizational
infrastructure. It is the latter—the networks and organizations that interconnect individual
sympathizers—that interest us here.
Part of a movement’s mobilization potential is formally organized. Workers are
members of labour unions; women are members of women’s organizations, farmers of
farmer’s organizations, environmentalists are members of environmental organizations, and
war opponents are members of peace organizations. Mobilization potentials differ in that
respect; they can be more or less organized. Such structures serve as the connecting tissue
between organizers and participants in collective action. Passy (2003) denotes this structuralconnection function as one of the three functions social networks in her view perform in the
context of collective action mobilization. The other two being the socialization function that is
the role social networks play in the formation of identity, political consciousness, grievances,
etc.; and decision-shaping, that is the role others in someone’s network play in the decision to
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participate. Boekkooi (2012) emphasizes that mobilizing structures are not given, but must be
assembled over and again, be it not from scratch as abeyance structures and existing
organizations function as starting nodes. She demonstrates that the composition of the
mobilizing structure reproduces itself in the composition of the crowd.
Hence, social cleavages shape the mobilizing structure and the mobilization potential
for a protest event in a society. Organizers are more or less successful in including networks
and organizations in their mobilizing structure. As a consequence, smaller or larger
proportions of the participants in collective action are unaffiliated to the organizers. The
demonstrations we covered in our study vary widely in terms of the proportion of the
participants who are or are not members of any of the organizations staging the event. We will
show that being a member or not has important consequences for how a participant is
mobilized and that affiliated and unaffiliated participants differ significantly in terms of
identification and motivation to participate.
Affiliation and mobilization
Affiliation impacts on the effectiveness of the communication channels that are employed
during mobilization campaigns. Weak ties, strong ties, interpersonal communication, mass
media such as television or newspapers, and recently social media are all employed in
campaigns to mobilize participants in collective action. Indeed, much attention in the social
movement literature is given to organizations, networks and communication channels as
conduits for the spreading of information and campaigns of mobilization (McCarthy 1996;
Diani 1997; Kitts 2000; Diani and McAdam 2003; Corrigall-Brown 2012; Walgrave and
Klandermans 2010). For an individual, being affiliated or not to the networks organizers
assemble makes a real difference in terms of processes of mobilization and recruitment
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(Boekkooi, Klandermans, and Van Stekelenburg 2011; Boekkooi 2012). Being affiliated to
the networks of the organizers makes it more likely for people to be targeted by mobilization
attempts via these networks. The question that interests us here, however, is how unaffiliated
demonstrators are mobilized? Walgrave and Manssens (2000) suggest that under certain
circumstances mass media can take over in the absence of any organization that assembles a
mobilizing structure. They underpin their argument with results from a study of the so called
White March. An event that took place in Brussels out of indignation about the kidnapping,
abuse and murder of teenage girls by a man named Dutroux and more specifically about the
way authorities had dealt with it. The authors argue that in case of widespread, strong
grievances such mobilization without organization might occur. Corroborating this reasoning
Walgrave and Klandermans (2010) show that in countries where the public opinion strongly
opposed the imminent invasion in Iraq mass media were more effective as mobilization
channels than in countries with lower levels of opposition. Verhulst (2011) coins the term
consensual issues to refer to such issues that are highly supported in a society and shows that
consensual issues are more likely to mobilize people without organization.
Klandermans and Oegema (1987) discern in addition to ties with the organization
three routes to target individuals for mobilization: mass media, direct mail, and friendship
ties. They distinguish further between formal and informal mobilization attempts, the first
being deliberate mobilization efforts of the movement (via flyers, posters, stands,
advertisements, and so on), and the second being personal links with someone who planned to
participate in the upcoming demonstration. Snow and colleagues distinguish face-to-face
dissemination from mediated dissemination (Snow, Zurcher and Ekland-Olson, 1980). Faceto-face dissemination requires the physical presence of a source of information while
mediated dissemination implies the use of media--like newspapers, television, mail, the
Internet, and telephone. Furthermore, Snow and colleagues discern ‘private’ channels from
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‘public’ channels. Snow et al.’s taxonomy of recruitment channels suggests that some
channels can reach the public at large, while other channels only reach certain segments of the
population. Finally, Walgrave and Klandermans (2010) propose a distinction between open
and closed channels. Open mobilization channels have no restriction regarding whom they
target, while closed mobilization channels only target people with certain characteristics, for
instance members of an organization. The broader the target groups, the less specific personal
characteristics, the more open the mobilization channel.
In this study we employ a distinction proposed by Boekkooi (2012) between ‘closed’,
‘semi-open’, and ‘open’ communication channels. An organization that targets its own
members when it comes to mobilization is an example of the employment of closed channels.
Labour union demonstrations are instances of recruitment via closed channels. Closed
channels are typically employed in so-called “bloc recruitment” (McAdam, 1986), where
members of a group or organization are recruited as a whole. The mass media (radio,
newspapers, television) are examples of open mobilization channels, but also interpersonal
networks. Mobilization via interpersonal networks including social media is in principle open
as well as it can go on from the one person to the next as long as the chain is not broken.
Semi-open channels are channels such as websites, the Internet, flyers, or posters, which in
principle can reach everyone, but in practice reach limited numbers of people (Earl and
Kimport 2011). Boekkooi (2012) showed how mobilization attempts snowball through an
organizer’s organizational field. The first to be reached are the members of the organizer’s
organization. The next in line are the people tied to organization members (through family,
friendship, or work and study relations) whether or not via social media. Finally, people who
are not reached via any of these interpersonal strong or weak ties can only be reached via
impersonal media such as online media, radio, television and newspapers. Boekkooi shows
that the more distanced from the initial organizer a person is located, the longer it takes for
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mobilization attempts to arrive and, therefore, the longer it takes for a person to decide to
participate.
Organizers employ all three types of communication channels to target ‘their’
mobilization potential. Affiliated people can be reached by all three, but unaffiliated people
can only be reached via open and semi-open channels. As semi-open and open channels reach
people later than closed channels, we expect that it will take longer for unaffiliated
participants to decide to participate in the demonstration than affiliated participants.
Affiliation and identification
It is generally assumed that participants in collective action share a politicized collective
identity (Stryker et al. 2000; Simon and Klandermans 2001; Tindall 2004; Azzi et al. 2011;
Corrigall-Bown 2012). Indeed, identity formation was one of the functions of social networks
in the context of movement participation Passy (2003) listed. Simon (1998, 1999) described
identity as a place in society. There are many different places in a society. People are student,
unemployed, housewife, politician, farmer, and so on. A collective identity is a place shared
with other people. Most collective identities remain latent, but contextual factors may bring a
collective identity to the fore. This is often no matter of free choice. Circumstances may force
a collective identity into awareness whether people like it or not, as for instance the
Yugoslavian and South African histories have illustrated dramatically. However, also in less
extreme circumstances collective identities are made salient. Imagine the announcement that a
waste incinerator is planned next to a particular neighborhood. Chances are that within very
little time the collective identity of the people living in that neighborhood becomes salient
(Aarts 1994). Awareness of a collective identity does not necessarily make that identity
politically relevant. We hold that for people to become involved in political protest on behalf
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of a group, the collective identity of that group must politicize. Simon and Klandermans
(2001) have attempted to develop a theoretical model for the politicization of collective
identity. According to these authors, "..people evince politicised collective identity to the
extent that they engage as self-conscious group members in a power struggle on behalf of
their group knowing that it is the wider, more inclusive societal context in which this struggle
has to be fought out." (p.2). The basic hypothesis regarding politicized collective identity and
protest is fairly straightforward: a strong and politicized collective identity makes
participation in political protest on behalf of the collective more likely.
Several empirical studies report consistently that the more people identify with a group
the more they are inclined to protest on behalf of that group (Kelly & Breinlinger, 1995;
Klandermans, Sabucedo, Rodriguez, & Weerd, 2002; Mummendey et al. 1999; Reicher, 1984;
Simon & Klandermans, 2001; Simon et al., 1998; Stryker, Owens, & White, 2000). Also
meta-analytically this relation is confirmed (Van Zomeren et al., 2008). We hypothesize
therefore that demonstrators who are affiliated to any of the organizations that are staging the
demonstration identify with that organization. But what about those who are not affiliated,
who are they identifying with? Swaab, Postmes, and Spears (2008) suggest that there are two
theoretically distinct pathways to the formation of a sense of shared identity. The classic
perspective on shared identities is that they are inferred deductively from the broader social
context within which the group members act. A shared identity can thus be deduced through
recognition of superordinate similarities such as membership of the same organization or
occupying the same societal position. However, a sense of shared identity can also be induced
by intragroup processes in which individuals get acquainted with one another on an
interpersonal basis and form inductively a sense of shared identity. The authors present
research results showing that both top-down and bottom-up processes lead to the formation of
a sense of shared identity. The authors test their assumptions in the context of interaction
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within and between small groups, but we presume that similar mechanisms are at work within
the much larger collectives that populate street demonstrations. If this is feasible, we may find
participants in a demonstration who deduce a collective identity in a top-down manner from
their membership of an organization which is staging the demonstration next to participants
who induce a collective identity in a bottom-up manner from their interaction with likeminded people at the demonstration. We propose that unaffiliated demonstrators adhere to the
latter category and affiliated demonstrators to the former, which we expect to reflect in the
fact that unaffiliated demonstrators identify stronger with the other participants, whereas
affiliated demonstrators identify stronger with the organizers.
We assume furthermore that top-down formation of politicized collective identity is
more structured than bottom-up formation, as it is steered and controlled by organizations
disseminating their view in a process of consensus mobilization. Bottom-up formation of
politicized collective identity, on the other hand, is more a matter of consensus formation
(Klandermans 1988), searching a common denominator—presumably to be found in the
grievances people share. As top-down processes are by definition steered and controlled more
than bottom-up processes, we also expect unaffiliated participants to have more
heterogeneous collective identities than affiliated participants.
Affiliation and motivation
Next to identification Van Stekelenburg and Klandermans (2007) distinguish instrumental and
ideological motives, and anger as parameters in a motivational framework for collective
action participation. The model they propose integrates their own take with two other but
similar social psychological approaches to collective action: Simon and colleagues’ model
comprising instrumental and identity pathways to protest participation (Simon et al. 1998) and
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Van Zomeren and colleagues’ model which combines instrumentality and emotions as
determinants of collective action participation (Van Zomeren et al. 2004). Van Stekelenburg
and Klandermans’ integrated model assumes that people participate in collective action
because they want to promote or protect interests or principles. Identification processes
occupy a central position in the model as it takes as its point of departure that some measure
of collective identity is needed for people to share interests or principles with other members
of society (see also van Stekelenburg, Klandermans and Van Dijk (2009). The authors
presume that threatened interests feed instrumental motives while violated principles spur
ideological motives, while anger amplifies and accelerates protest activity. The angrier people
are the more they are motivated to take action and the more likely that their motivation is
actually turned into action.
The question that interests us here is whether in addition to mobilization and
identification unaffiliated and affiliated participants differ in terms of motivation as well. The
relationship between affiliation and motivation is more complicated than one would expect. In
fact, there are two opposite arguments. On the one hand, one could argue that people who are
member of an organization that is staging the demonstration display stronger motivation to
take part in that demonstration than people who are not a member, especially if they identify
strongly with that organization. On the other hand, mobilizing without organization is more
likely to succeed among people who are highly motivated (Boekkooi 2012; Verhulst 2011).
This would make one to expect unaffiliated participants to be more determined to participate
than affiliated participants.
Next to the strength of people’s motivation we also expected demonstrators to differ in
terms of the configuration of motives. As a rule, movement organizations make an effort to
disseminate their views and mobilize consensus among their members. The more members
identify with the organization the more susceptible they are for such persuasive
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communication (Van Stekelenburg and Klandermans 2012). Therefore, we expect the
motivation of affiliated participants, especially of those who identify strongly with the
organization to be more homogeneous than that of unaffiliated demonstrators. But there is
more. We made a distinction between instrumental and ideological motives. Although
organizers usually appeal to both motives at the same time, we take it for granted that the
emphasis varies per demonstration. As a consequence, we expect affiliated participants in
demonstrations that emphasize instrumental rather than ideological causes to be more
instrumentally motivated, especially if they identify strongly with the organizers (Van
Stekelenburg and Klandermans, under review). If, however, the organizers emphasize
ideological causes more than instrumental we expect affiliated participants to be more
ideologically motivated, again especially if they identify strongly with the organizers. Finally,
we suppose that unaffiliated participants will be less influenced by the organizers’ appeals and
thus will reveal more varied motives.
In sum
Some participants in collective action are member of an organization that stages the
demonstration, while others are not. We wondered how being a member or not matters and
hypothesized about the implication of being unaffiliated for processes of mobilization,
identification, and motivation. A unique comparative study of 60 street demonstrations in
seven different countries comprising 13.000 participants will serve to test our assumptions.
We will show that demonstrations differ widely in terms of the affiliation of their participants
to the organizers and we will show that being affiliated or not causes significant differences
between participants in terms of mobilization, identification and motivation.
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The CCC-projecti
Caught in the Act of Protest: Contextualizing Contestation (CCC) is a comparative study of
street demonstrations in 7 European countries (Belgium, Italy, the Netherlands, Spain,
Sweden, Switzerland, and the U.K.). This paper is based on the 60 demonstrations that were
covered between November 2009 and May 2012. Close to 13.000 participants completed
questionnaires distributed during the demonstration. In addition, organizers and police
officers were interviewed before and after the event; fact sheets on the course of events were
completed and newspaper coverage was coded. All questionnaires and procedures are
standardized. The same questions and indicators are employed in each country and for each
demonstration.
Sampling demonstrations
Obviously, at the start of the project we did not know what to expect in terms of
demonstrations. It was decided that between 2009 and 2012 each national team was to study
between 8 and 12 demonstrations with at least 3.000 participants according to an agreed upon
grid including events staged by new and old social movements, migrants and transnational
protest events. But history overtook us, the financial-economic crisis burst onto stage. Each
European government was taking austerity measures and each was confronted with protests
(including street demonstrations) in opposition. As a consequence, a substantial proportion of
the demonstrations covered are anti-austerity demonstrations. Next, we discussed at length in
our team whether to cover ritual parades such as May Day Parades, Gay Prides, and Climate
Day Marches. We decided to include those for three reasons. First, almost always—be it
sometimes more, sometimes less—such parades have moments of politicization to it; second,
we were curious to see in what respect such parades were different from modal street
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demonstrations. Third, as such parades were staged in most countries they meant ideal
opportunities to compare between countries. Next, our sample included a third category of
demonstrations regarding a variety of socio-cultural issues such as anti-abortion, anti-racism,
anti-nuclear energy, language and cultural issues. Appendix A gives an overview of the 60
demonstrations our analyses are based on. Table 1 contains the main demonstration categories
we distinguished. Ritual Parades are further broken down into Women’s Marches, Peace
Marches, Gay Prides, Climate Day Marches and May Day Parades. As half of the parades are
May Day Parades, these types of parades dominate the global picture of the ritual parades.
The anti-austerity protests concern particularistic claims by specific groups (mostly workers
and students) in defense of their interests and universalistic claims against austerity measures
and policies in general. The socio-cultural demonstrations were further categorized as
demonstrations against nuclear energy mostly responding to the Fukushima disaster, Antiracism marches, Demonstrations against the political culture and for more democratic
societies, an Anti-abortion demonstration and Demonstrations regarding regional issues.
Each global category (parade, anti-austerity and socio-cultural issue) roughly contains
one third of the demonstrations and demonstrators. Whether this is a representative sample of
the demonstrations staged during the years 2009-2012 in the seven countries is difficult to
say. Naturally, it is not a random sample. In some countries our sample was nearly all
demonstrations that took place in the period our fieldwork lasted, in other it was a selection of
the demonstrations staged. We kept track of the demonstrations that were not included but we
did not see any systematic gap. On the whole, we think that our 60 demonstrations provide a
fair picture of the dynamics of street demonstrations as we know them.
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Collecting data and sampling participantsii
The protest surveys employed printed questionnaires (500-1000) handed out at the
demonstration to be returned to the university using prepaid envelopes. In order to control for
response biases we also conducted short (2-3 minutes) interviews with a subsample of the
respondents (100-200) at the demonstrations comprising questions identical to those in the
printed questionnaire.iii The refusal rate for the face-to-face interviews is relatively low
(10%). By comparing the answers in the face-to-face interviews with those to the identical
questions in the returned questionnaires and by comparing the face-to-face interviews of those
who returned their questionnaire with the interviews of those who did not, we can make fairly
accurate estimates of the response bias. Overall 32% of the participants turned in their
questionnaire. The response rate for the 60 demonstrations fluctuated between 13 and 52%.
Comparison of those who did and did not return the questionnaire revealed that those who did
return the questionnaire were on average somewhat older and higher educated than those who
did not. Important for the current paper, respondents and non-respondents did not differ in
terms of the affiliation to organizations that staged the demonstration. The analyses we
conducted to assess whether the non-response could have resulted in biased findings and
conclusions did not reveal any deviating outcomes.
As for the sampling of participants, we designed a sampling strategy such that each
participant had the same chance to be selected. Although circumstances inevitably necessitate
variation we aimed to keep sampling procedures as identical as possible for the various
demonstrations. A demonstration is covered by a team consisting of a fieldwork coordinator,
3-4 so called pointers, and 12-15 interviewers. Each pointer has a team of 4-5 interviewers.
The pointers select the interviewees, while interviewers conduct the interviews and hand out
the questionnaires. Separating these two roles appeared to be crucial in preventing sampling
biases (Walgrave et al. 2012). As interviewers tend to select people they belief to be willing to
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cooperate, they end up producing biased samples. The fieldwork coordinator oversees the
employment of the pointer-interviewer teams. At the start of the event s/he makes an estimate
of the number of participants. This defines the ratio at which participants are approached for
interviews and to hand out questionnaires. In demonstrations that move through the streets
teams start at different points of the procession and work towards each other approaching
every n-th person in every n-th row. At demonstrations that stay at the same area, the space is
divided into smaller areas; in each area a pointer selects interviewees taking the density of the
crowd in that area into account. The result of all this is samples that we believe to be
representative of the demonstrators present.
Measuresiv
Affiliation to organizers and embeddedness in organizational fields. We distinguished
affiliation to organizations that staged the demonstration from embeddedness in broader
organizational fields. As for affiliation to organizations we first asked respondents to name
organizations that are staging the demonstration they were taking part in. Respondents who
mentioned one or more organizations were asked whether they are a member of any of those
organizations. As for embeddedness in multi-organizational fields we asked our respondents
in how many organizations they have been actively involved during the past 12 months.
Communication channels. We asked our respondents via which communication channels they
found out about the demonstration. They could tick as many as applied of the following list:
radio or television, newspapers, alternative online media, advertisements, flyers, and/or
posters, partner and/or family, friends and/or acquaintances, people at one’s school or
workplace, (Fellow)members of an organization or association, an organization’s (magazine,
meeting, website, mailing list, etc. online social networks (e.g. facebook, twitter, etc.). Next
we asked them which of these channels was the most important as a source of information.
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Finally, we assessed if someone was specifically asked by some other person to take part in
the demonstration (no-one, partner or family, relatives, friends, acquaintances, colleagues or
fellow students, co-members of an organization they are a member of). They could again tick
as many as applied.
Decision time. We asked our respondents when they made a firm decision to take part
in the demonstration (the day of the demonstration, a few days before the demonstration, a
few weeks before the demonstration, over a month ago).
Identification. We made a distinction between identification ‘with any organization
staging the demonstration’ and identification ‘with the other people present at the
demonstration’ (not at all, not very much, somewhat, quite, very much). The two forms of
identification correlate (.48), but the pattern of correlations of the two with other variables are
significantly different. Therefore, we treat them separately.
Determination, motivation, and anger. We asked the participants how determined they
were to participate in the demonstration (not very, rather, somewhat, quite, very much). In
order to assess what motivated the participant to take part, we asked them to agree or disagree
with reasons to participate. We offered them two reasons related to instrumentality: ‘defend
my interest’ and ‘pressure politicians’ and two reasons reflecting ideology: ‘express my
view’, and ‘raise public awareness’ (strongly disagree, disagree, neither, agree, strongly
agree). The two instrumental reasons correlate .22; the two ideological .37. We collapsed the
four into measures of instrumental and ideological motives (each ranging from 2 ‘not at all
motivated’ to 10 ‘very much motivated.’ Finally, we asked participants whether they felt
angry when they thought about the issue of the demonstration (not at all, not very much,
somewhat, quite, very much).
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Data processing
The data were entered in the central data base by the national teams. They were checked
centrally and corrected if needed by the national teams. For this paper our focal variable is
affiliation to organizations staging the demonstration. We employ descriptive analyses,
anova’s, manova’s, regression analyses, and structural equation modeling. As our sample of
individuals is large small effects are significant, therefore we will apply additional power
criteria and effect sizes.
Results
Affiliated and unaffiliated demonstrators
Fifty-one percent of the participants in the 60 demonstrations covered by our study was not
affiliated to any of the organizations that were staging the demonstration; forty-nine percent
was member of one or more of these organizations. The differences between the
demonstrations are enormous, as depicted in Appendix A, which lists the proportion
unaffiliated participants of all demonstrations included in our analyses. The 60
demonstrations vary widely in terms of affiliation of the participants to the organizers from
97.1% unaffiliated at a demonstration regarding the political impasse in Belgium (28) until
3.1% unaffiliated at an anti-austerity demonstration by workers in Brussels (4). Table 1
presents the proportions of the participants for the categories we distinguished. Almost half of
the participants in the parades, one-third of those in the anti-austerity protests, and over twothirds of the demonstrations on socio-cultural issues were unaffiliated demonstrators.
Table 1
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Among these three types of demonstrations numbers of unaffiliated demonstrators vary:
among the parades from a high of 67% for the Gay Pride to a low of 42% for May Day and
Climate Marches; among the anti-austerity protests from 68% for the students to 26% for the
workers; and among the demonstrations regarding socio cultural issues from 86% for the antiabortion demonstration to 46% for the anti nuclear energy demonstration. As labor unions
play an important role as organizers of anti-austerity demonstrations many of the
demonstrators in these protests are union members. Students as a category are much less
organized as the figures in Table 1 evidence although one of the two student demonstration in
London had a high proportion of affiliated demonstrators as well. Labor unions, social
democratic and socialist parties play an important role in organizing May Day Parades. Next
to the labor movement, the environmental movement ranks among the more densely
organized movement sectors as revealed by the numbers for the Climate Marches and the
Anti-nuclear energy demonstrations. The rest of the categories display similar degrees of
organization (roughly one-third) with the exception of the demonstrations for more
democracy and the anti-abortion demonstration which are predominantly populated by
unaffiliated demonstrators. In this paper we are not aiming to explain the variance of
affiliation between demonstrations, but to understand the impact of such variance on the
social psychological dynamics of participation in street demonstrations.
Embeddedness in organizational fields
Are unaffiliated demonstrators also less involved in broader organizational fields? At first
glance this seems to be the case, but more careful observation suggests a different story.
Across all demonstrations affiliation correlates .27 with reported involvement in broader
organizational fields. The correlations for the various types of demonstrations fluctuates from
.20 for the peace and climate marches to .34/.35 for the May Day parades and the
21
demonstrations against racism and regarding regional issues; however, most fluctuations stay
within a range from .23 to .28. This suggests that affiliation in the mobilizing structure is
positively related to embeddedness in broader organizational fields. This is seemingly
confirmed by the reported number of organizations people were actively involved in over the
past 12 months. On average unaffiliated participants report to have been less involved in
broader organizational fields the past year than participants who were affiliated to organizers’
network (Munaffiliated: 2.0; Sd 1.0 versus Maffiliated: 2.5; Sd 0.9). But there is a caveat. The
difference between the two groups of demonstrators is smaller than one would expect had the
difference been the affiliation to the organizers’ only. Taking that affiliation into account,
unaffiliated demonstrators are in fact on average more rather than less embedded in broader
organizational fields which may be one answer to the question of how they were mobilized.
Mobilization
A common finding with regard to affiliation to organizers concerns the effectiveness of the
communication channels that are employed during mobilization campaigns. Weak ties, strong
ties, interpersonal communication (whether or not via social media), impersonal media such
as television or newspapers are all employed in campaigns to mobilize participants. Table 2 A
presents the percentages of affiliated and unaffiliated participants who through a specific
channel found out about the demonstration. Respondents could tick as many as apply. All
channels forwarded in the questionnaire were used by smaller or larger proportions of the
participants. In the third column the Gamma’s reflect the strength of the relation between
affiliation and communication channels used. A negative Gamma signifies that a specific
channel is mentioned more frequent by unaffiliated than affiliated demonstrators and a
positive Gamma vice versa.
22
Table 2
The figures for the two groups are what we expected. Large proportions (83.2%) of the
unaffiliated demonstrators mentioned open channels; while, on the other hand, 79.1% of the
affiliated demonstrators mentioned closed channels. In response to our question which of the
listed channels was most important, 65.4% of the affiliated participants mentioned a closed
channel. The pattern of communication channels that were employed by the unaffiliated
participants is far more diverse. 73.6% mentioned one of the following channels as the most
important: radio, television, newspapers, and online media, friends, acquaintances,
communication channels of an organization, and social media .
As for the question by whom people were specifically asked to take part, the expected
pattern emerged as well (Table 2B). Over 40% of the affiliated demonstrators were
specifically asked by co-members of an organization compared to 10.9% of the unaffiliated;
on the other hand, 38.1% of the unaffiliated demonstrators were specifically asked by a
partner, family-member or friend against 19.4% of the affiliated demonstrators.
For the analyses that follow we concentrate on the channels mentioned as the most
important and collapsed the communication channels into the three categories mentioned in
the theoretical introduction: open channels, that is mass media (radio, television, newspapers)
and interpersonal channels (partner, family, friends, people at school or workplace, social
media); semi-open channels (online media, advertisement, flyers, posters), and closed
channels (fellow members of an organization, an organization’s magazine, website, mailing
list, etc.). Table 3 presents the percentages of the affiliated and unaffiliated participants who
employed these channels.
Table 3
23
The two groups of participants differed clearly and in the expected manner in the
communication channels they have used. 62.0 % of the affiliated demonstrators mentioned
closed channels as the most important channel as opposed to 19.7% of the non-affiliated
participants. On the other hand, 63.5 % of the unaffiliated demonstrators mentioned open
channels as the most important source of information about the demonstration as compared to
28.3% of the affiliated participants. Semi-open channels were used primarily by 16.8% of the
unaffiliated demonstrators and by 9.7% of the affiliated participants. Table 4 gives the
breakdown for the types of demonstrations we discerned ritual parades, anti-austerity
demonstrations, and socio-cultural demonstrations. Again the pattern is what one would
expect in view of the proportions of unaffiliated participants in the three types of
demonstrations. Almost half of the participants in the ritual parades and the anti-austerity
demonstrations have used closed channels whereas almost 60% of the participants in the
socio-cultural demonstrations has used open channels.
Table 4
We hypothesized that the more distanced from the initial organizer a person is located, the
longer it takes for mobilization attempts to arrive and, therefore, the longer it takes for a
person to decide to take part in the event. Indeed, this is what Table 5 shows. Participants who
are reached by closed channels are the first to decide, followed by those who are reached by
semi-open channels. Those reached via open channels are the last to decide. This makes one
expect that unaffiliated demonstrators have decided later to take part in a demonstration than
affiliated. This is what we found indeed, as the lower half of Table 5 shows.
Table 5
24
Identification
We assessed two types of identification: ‘identification with any organization staging the
demonstration’ and ‘identification with the other people present at the demonstration’ and
presumed that the former type of identification is formed deductively in a top-down process
and the latter inductively in a bottom-up process. We hypothesized that affiliated participants
would be more likely to identify with the organizers, while unaffiliated participants would
more likely identify with the other participants. The two forms of identification are correlated
(Pearson r = .48), a correlation that varies for the various types of demonstrations between .28
for the peace march and .64 for the gay pride. The remaining correlations fluctuate between
.42 and .59. Therefore, it is safe to say that the two forms of identifications go together.
Nonetheless, Table 6 reveals significant differences between participants who are affiliated to
the organizers and participants who are not and between the types of demonstrations.
Table 6
The table contains means and standard deviations of the two forms of identification for
affiliated and unaffiliated participants in the various types of demonstrations. In addition, we
calculated a mean difference score by deducing identification with the organizers from
identification with the other participants. The findings are interesting and theoretically
significant. First, the global pattern: affiliated participants identify stronger than unaffiliated
participants with both the organizers and the other participants. Among the affiliated
demonstrators the level of identification with the organizers is slightly higher than that with
the other participants. Indeed, the difference score is negative suggesting that as expected
affiliated demonstrators identify more with the organizers that the other participants. But the
difference is small. This pattern repeats itself for the different types of demonstrations. On the
25
whole, the levels of identification among affiliated demonstrators are high (4.2 and 4.3 on a 5point scale) both with organizers and with other participants.
A very different pattern we encounter among the unaffiliated participants. As we
hypothesized, their identification with the organizers is much lower than that of the affiliated
participants—around one full scale point on the 5-point scale. Theoretically important and
hypothesized as well, their identification with the other participants is much higher than their
identification with the organizers. The difference scores underline this finding. We did expect
this pattern as a consequence of the fact that unaffiliated demonstrators supposedly form a
shared identity inductively, rather than deductively. This pattern holds for the various types of
demonstrations
Equally important in view of the pathways to shared identity is the fact that the
standard deviations of both identification with the organizers and identification with the other
participants are higher for the unaffiliated participants.v This is, of course, what we expected.
As the collective identity of the unaffiliated demonstrators is formed in a bottom-up manner
we expected those to be more heterogeneous than that of the affiliated demonstrators.
Next, a few more detailed observations. On average and compared to those taking part
in the ritual parades (3.9) and the anti-austerity demonstrations (3.8), unaffiliated participants
in demonstrations regarding socio-cultural issues display a high level of identification with
other participants (4.0). A finding which fits with the low levels of affiliation to the organizers
observed for these demonstrators. The lowest level of identification with the organizers we
found among the unaffiliated participants in anti-austerity demonstrations (3.1 compared to
3.5 for the parades and socio cultural issues protest). This is partly due to the student
demonstrations. Two of the four student demonstrations had low levels of affiliation in
combination with very low levels of identification with the organizers among the unaffiliated
participants. On the other hand, many anti-austerity demonstrations were staged by labor
26
unions. Large proportions of the participants in these demonstrations were union members.
We may assume that workers who are not member of a union do not identify with the
organizers. After all, had they identified strongly with the union they would have been a
member. As a result, these unaffiliated participants display low levels of identification with
the organizers, but high levels of identification with other participants compensating for it.
Summing up, as expected unaffiliated demonstrators have more heterogeneous
identities than affiliated demonstrators. Expected as well, are the findings that unaffiliated
demonstrators identify primarily with the other participants, while affiliated demonstrators
identified more with the organizers than the other participants, although the differences are
small for the latter.
Motivation
Table 7 gives the means and standard deviations of the four measures concerning our
motivational framework for unaffiliated and affiliated demonstrators. As one would expect of
participants, all means are fairly high, both for the affiliated and the unaffiliated
demonstrators. Yet, affiliated and unaffiliated demonstrators differ systematically on all
accounts: unaffiliated demonstrators are less motivated both instrumentally and ideologically,
they are less angry and less determined to take part than affiliated demonstrators. This
confirms our expectation that unaffiliated demonstrators are to a lesser extent persuaded by
the organizers’ rhetoric than affiliated demonstrators. But the differences are small and all
means are at the upper end of the scale. Obviously, it did not keep the unaffiliated away from
the demonstration. Apparently, sufficient motivation ensures that also unaffiliated people turn
into participants.
Table 7
27
Our assumption regarding the heterogeneity of the motives of the unaffiliated demonstrators
is confirmed as well. With anger as the only exception all measures had higher standard
deviation for the unaffiliated demonstrators confirming that they formed a more
heterogeneous crowd than the affiliated demonstrators.vi
Table 8 breaks the motives down across parades, anti-austerity demonstrations, and
soci-cultural demonstrations. The figures are interesting in several respects. First, the two
findings reported for all demonstrations in Table 7 are repeated for the three types of
demonstrations: unaffiliated demonstrators are less motivated than affiliated demonstrators,
but again it is variation at the high end of the scale; also the standard deviations among
unaffiliated demonstrators are higher than those of the affiliated participants evidencing more
heterogeneity among the unaffiliated demonstrators.
Table 8
But there is more to observe. Participants in parades are the least instrumentally motivated of
the three types of demonstrators, especially the unaffiliated demonstrators. Obviously, parades
are about ideology and less about interests. Anti-austerity protests, on the other hand, are the
most instrumentally oriented, especially for the affiliated demonstrators. That makes of course
sense; these are the people whose interests are threatened by the imminent austerity measures.
Participants in the socio-cultural demonstrations are the most ideological motivated,
especially the affiliated participants.
In order to further explore the motivational dynamics among affiliated and unaffiliated
demonstrators we conducted regression analyses first and structural equation modeling next.
Table 9 reports results from an analysis in which people’s determination to participate in the
demonstration is regressed on affiliation, identification, motives and anger and the interaction
terms of affiliation and the other independent variablesvii. Model 1 once more shows that
28
affiliated demonstrators were more determined to participate in the demonstration than
unaffiliated demonstrators. Model 2 reveals that the determination of participants is very
much influenced by identification with the organizers and especially the other participants.
The lowering of the beta for affiliation indicates that identification mediates the impact of
affiliation. In separate steps (not reported) we entered the types of identification separately
alternating the order in which the two were entered in the equation. It appears that the impact
of affiliation is mediated especially by identification with the organizers. Model 3 reveals that
ideological motives are more of influence on people’s determination to participate than
instrumental motives. Entering the two motives reduces the effect of both identification
variables, implying that the impact of identification is mediated by the two motives as van
Stekelenburg and Klandermans’ integrated model suggests indeed. Entering anger in the
equation does not change the other beta’s, suggesting that anger has an independent influence
on the determination to participate (Model 4). In Model 5 the interaction terms are entered in
the equation. As we hypothesized, the more unaffiliated demonstrators identify with the other
participants the more determined they were to participate; in contrast the affiliated
demonstrators, were more determined to participate if they identified with the organizers;
also, unaffiliated demonstrators are more than affiliated demonstrators ideologically
motivated. Unexpectedly, the determination to participate of affiliated and unaffiliated
demonstrators is equally affected by instrumental motivation. We come back to this in the
report on the Structural Equation Modeling.
The regression analysis demonstrated main effects of being affiliated, identification,
motivation, anger, and of interactions of affiliation and these variables on the determination to
participate. The various models also revealed how identification mediated the impact of
affiliation and how the instrumental and ideological motives mediated the impact of
identification. Anger appeared to have an independent influence on determination. In our
29
discussion of the impact of affiliation on motivation we conceived of diverging path models
built of identification, instrumental and ideological motivation, and anger influencing
people’s determination to participate for affiliated and unaffiliated demonstrators. In a final
step, we will test these path models by means of Structural Equation Modeling (SEM). We
assessed how being affiliated to the organizers or not moderates the influence of
identification, motivation and anger on people’s determination to participate. The two models
in Figure 1 fit the data well (Affiliated model: 2=91,58, df 3, CFI .982, NFI .982, RMSEA
.071; Unaffiliated model: 2=229,46, df 4, CFI .961, NFI .961 RMSEA .097).
Figure 1
Anger made both affiliated and unaffiliated demonstrators more determined to participate. For
both types of demonstrators anger was driven by instrumental and ideological motives.
However, affiliated participants were more driven by instrumental motives than unaffiliated
participants, while unaffiliated participants were more driven by ideological motives than
affiliated participants. Note that the effect of instrumental motivation is only indirect via
anger, instrumental motives do not directly affect people’s determination to participate. This
explains why the interaction between affiliation and instrumental motivation was not
significant. SEMhowever, does reveal that instrumental motives makes affiliated
demonstrators angrier than unaffiliated demonstrators. This replicates the findings of Van
Stekelenburg et al, 2009 that instrumental motives only indirectly impact on determination
and, in the context of this study perhaps more important, it indicates that instrumental motives
are indeed more important for affiliated than unaffiliated individuals. The direct path from
identification with the other participants to determination to participate is stronger for
unaffiliated participants than for affiliated, while the direct path from identification with the
organizers is even non-significant among the unaffiliated. The link between the two
30
identification measures and the two motivation measures are similar for the two groups with
one important exception: among affiliated demonstrators identification with the organizers
steers identification with the other participants, while among the unaffiliated demonstrators
the pattern is the other way around—identification with the other participants steers
identification with the organizers. Other than that, the two forms of identification strengthen
ideological motivation, while only identification with the organizers strengthens instrumental
motives. Finally, via a strong link ideological motives relate to instrumental motives. All in
all, identification with the other participants and ideological motivation are the drivers of both
groups of participants but more of the unaffiliated demonstrators than of the affiliated. The
affiliated, on the other hand, are also motivated by identification with the organizers and
instrumental motives.
Conclusions
The literature on collective action participation amply documents how being affiliated to the
organizers fosters collective action participation. However, in every instance of collective
action we encounter next to participants who are affiliated to the organizers participants who
are not. This raise the questions of how do these unaffiliated participants become involved in
the event and whether their involvement differs from that of affiliated participants. Exploiting
the data of a unique study of participants in 60 street demonstrations in seven European
countries we have tried to answer these questions. How were unaffiliated demonstrators
mobilized, who did they identify with, and what did motivate them to participate? The first
and perhaps most amazing finding is the tremendous variation in the proportion of unaffiliated
demonstrators across the demonstrations. The 60 demonstrations this paper is based on span
the whole spectrum from hardly anybody who is unaffiliated to almost everybody. As
31
comparative studies of street demonstrations of the scope of ours did not exist before, we did
not know what to expect in this respect but apparently any possible number of unaffiliated
demonstrators goes.
In this paper we have tried to understand the differential social psychological
dynamics of participation for affiliated and unaffiliated demonstrators. We focused on the
processes of mobilization, identification, and motivation. Each of these processes evolves
differentially for affiliated and unaffiliated demonstrators. To begin with mobilization,
affiliated and unaffiliated demonstrators were reached via different channels. Unlike affiliated
demonstrators, who were primarily reached through closed channels, unaffiliated
demonstrators were reached via open channels and to a lesser extent via semi-open channels.
As a consequence, they were reached later than affiliated demonstrators and therefore were at
a later point in time decided to take part in the demonstration. These findings replicate
Boekkooi’s study which similarly reports that the timing of the decision to participate is
related to the social distance between the core organizers and the individual participants
(2012). This is now replicated in a much larger sample of demonstrations and demonstrators,
adding to the robustness of this finding.
Regarding identification we referred to a social psychological approach to identity
formation that distinguished a top-down pathway and a bottom-up pathway to shared identity
(Swaab et al. 2008). We transposed the small-group phenomenon Swaab and colleagues
conceived of to the larger scale of collectivities encountered in street demonstrations. In that
setting the two paths are akin to the processes of consensus mobilization and consensus
formation Klandermans distinguished (1988). The first, top-down process presumes
organizations that disseminate their view and build a politicized collective identity relying on
people’s membership of the same organization; the second, bottom-up process presumes
interpersonal interaction in which a politicized collective identity is formed in a much more
32
diffuse search for common denominators. The patterns of identification were clearly different
for affiliated and unaffiliated demonstrators. First, and in line with the top-down versus
bottom-up mechanisms of identity formation, our findings suggest that the collective identity
of the affiliated demonstrators is more homogeneous than that of the unaffiliated. Furthermore
and as expected, affiliated demonstrators identified more with the organizers than with the
other participants, but the differences were small although significant. Unaffiliated
participants, on the other hand and also expected, identified much more with the other
participants than with the organizers.
The motivational configuration of the two types of participants varied as well. We
employed the motivational framework developed by van Stekelenburg and Klandermans
(2007), consisting of identification, instrumental and ideological motivation, and anger as the
drivers of participation. We assumed that affiliation would work as a moderator, which indeed
it did. In the first place, unaffiliated demonstrators were lower than affiliated demonstrators
on all accounts: identification with the organizers, identification with the other participants,
instrumental and ideological motivation, anger and determination to participate in the
demonstration. Interestingly, the effect of affiliation on determination to participate was
predominantly mediated by the identification with the organizers. In addition, unaffiliated
demonstrators were more heterogeneous in terms of motivation than affiliated demonstrators.
Moreover, unaffiliated demonstrators’ motivation was weaker than that of affiliated
demonstrators. This holds both for the instrumental and ideological motivation, and for how
determined they were to participate. Anger is the only motivational factor that is almost the
same for the affiliated and unaffiliated participants. The assumption that unaffiliated
participants would display stronger motivation than affiliated as mobilization without
organization requires stronger intrinsic motivation (Walgrave and Manssens 2000; Boekkooi
2012) to be successful was not affirmed. Apparently, socialization by the mobilizing
33
organization weighs more than compensation for the lack of strong ties. We assumed that
unaffiliated demonstrators would be more ideologically motivated, and the affiliated more
instrumental. This did not show in a comparison of the means, but it did in regressions of
determination on identification and motivation and in the structural equations modeling.
Among both affiliated and unaffiliated demonstrators ideological motivation influenced
determination more than instrumental motivation, but for the unaffiliated the effects were
stronger than for the affiliated. In sum, our model of how dynamics of participation vary due
to differences in affiliation appears to hold across the 60 demonstrations included in our
analysis. Our findings regarding the relationship between identification, motivation and
emotions replicate findings reported by van Stekelenburg et al. (2009, 2011), but while their
study comprises two demonstrations in a single country only, ours encompasses 60
demonstrations in seven different countries underscoring the robustness of the findings.
We made a distinction between ritual parades, anti-austerity demonstrations, and
demonstrations regarding socio-cultural issues. The affiliated-unaffiliated ratio differed
significantly between these three types of demonstrations. As a consequence, the dynamics of
mobilization, identification and motivation of the demonstrations differed as well. As they
had much higher proportions of affiliated participants than the socio-cultural demonstrations,
parades and anti-austerity demonstrations could rely more on closed channels. Socio-cultural
demonstration on the other hand had to rely much more on open channels. In terms of
identification we found only moderate differences among the affiliated demonstrators in the
various demonstrations. However, among the unaffiliated demonstrators identification
patterns differed substantially between the three types of demonstrations. As for the
motivational configuration we found significant and meaningful differences between the three
types of demonstrations as well. Parades appear to be about ideology rather than
instrumentality. For obvious reasons anti-austerity demonstrations are about instrumentality.
34
These demonstrators want to stop the austerity plans which threaten their interests.
Demonstrations about socio-cultural issues are again about ideology. All this is not to say that
instrumental motivation is irrelevant. In fact, although ideological motivation is the most
important for each type of demonstration for both affiliated and unaffiliated participants, even
the lowest level of instrumental motivation is still substantial. Indeed, both instrumental and
ideological motivations are always relevant but the mixture varies across affiliated and
unaffiliated demonstrators and demonstrations.
Some organizers happen to mobilize densely organized mobilization potentials, while
others try to mobilize potentials that are hardly organized. Mobilizing densely organized
mobilization potential requires other mechanisms than mobilizing a scarcely organized
potential. One can rely on organizational channels which are faster. Although much depends,
of course, on the coalition one has been able to forge (Boekkooi 2012). Semi-open and open
channels are more difficult to control. Mobilizing scarcely organized potentials implies that
one must calculate with strong identification with other participants and weaker identification
with organizers. This implies a process of collective identity formation which is bottom-up
rather than top-down. The result will be that collective identity is more heterogeneous.
Mobilizing scarcely organized potentials will also make motivation more heterogeneous, less
instrumental, and more ideological.
As unique as it may be, our study has limitations as well. First, we would have loved
to have more countries involved. But our funding institution the European Science Foundation
(ESF) only subsidizes research in countries affiliated to the ESF. While Italy managed to
secure the funds to join otherwise, we failed to do the same for countries like France,
Germany, or the U.S. Furthermore, although we did whatever we could to design proper
sampling procedures, random sampling of street demonstrations is just impossible. Similarly,
we did our utmost to develop sampling procedures that give every single participant an equal
35
chance to be selected. Yet, even the best organized street demonstration is too chaotic to draw
perfect samples. Less than ideal return rates are yet another source of additional biases. But,
we applied all kinds of tests and procedures to estimate the possible bias resulting from it
(Walgrave, et al. 2012). Altogether, we feel that the potential biases stay within acceptable
limits. A second limitation concerns causality. As everything is correlational we are not able
to formulate and test strict causal reasoning. Nonetheless, we do think that the data we have
collected are of unquestionable value because of their scope, their comparative character and
because of the rigorous standardization.
What does this paper contribute to our knowledge? First and foremost the recognition
that the demonstration does not exist. We tend to treat demonstrations as a univocal
phenomenon, but our study shows that they are not. We put one of the factors that vary centre
stage namely that each collective action includes participants who are affiliated to the
organizers and participants who are not. As far as affiliated demonstrators are concerned our
findings basically replicate the existing knowledge, which underscores the validity of our
results. The contribution to our knowledge regards the unaffiliated demonstrators and our
understanding of what drives their participation. We reasoned and actually demonstrated that
the relative prominence of affiliated and unaffiliated participants has profound consequences
for the social psychological dynamics of participation, be it mobilization, identification or
motivation. It is not always foreseeable what the circumstances will be like. A movement’s
mobilization potential may be densely or scarcely organized, an organizer may fail to co-opt
key-organizations. Obviously, a mismatch, that is to say a mobilization campaign that
miscalculates the proportion of affiliated and unaffiliated would-be participants in the
mobilization potential might fail as it probably employs the wrong mix of mobilization
techniques. In terms of research it is important to know whether participants are affiliated or
unaffiliated and what is the affiliated-unaffiliated ratio as this may explain the observed
36
dynamics of participation. In a recent paper Bennett and Segerberg (2012) theoretically
distinguish what they call collective and connective action. The authors define collective
action as staged by organizationally brokered networks and connective action as staged by
organizationally enabled networks or self organizing networks. Their distinction is akin to
what we discern in terms of the proportion of affiliated and unaffiliated demonstrators.
Collective action in our framework encompasses large numbers of affiliated demonstrators,
while connective action comprises large numbers of unaffiliated demonstrators. Future
research could combine the two theoretical frameworks into a seminal approach.
37
References
Aarts, Cees W.A.M. 1990. Bodemverontreiniging en collectieve actie. Enschede: Universiteit
Twente, Faculteit Bestuurskunde.
Azzi, Assaad, Xenia Chryssochoou, Bert Klandermans & Bernd Simon (eds). 2010. Identity
and Participation in Cultural Diverse Societies. Oxford: Blackwell Wiley.
Bennett W. Lance and Alexandra Segerberg. 2012. “The logic of Connective Action. Digital
Media and the Personalization of Contentious Politics.” Information, Communication
and Society. 15: 739–768.
Boekkooi, Marije. 2012. Mobilizing Protest. The Influence of Organizers on Who Participates
and Why. PhD-Dissertation, Dept. of Sociology, Amsterdam: VU-University.
Boekkooi, Marije, Bert Klandermans and Jacquelien van Stekelenburg. 2011. “Quarrelling
and Protesting. How Organizers Shape a Demonstration.” Mobilization, 16: 223-242.
Corrigall-Brown, Catherine. 2012. Patterns of Protest. Trajectories of Participation in Social
Movements. Stanford: Stanford University Press.
Diani, Mario. 1997. “Social Movements and Social Capital: A Network Perspective on
Movement Outcomes.” Mobilization, 2: 129-148.
Diani, Mario and Doug McAdam (eds). 2003. Social Movements and Networks. Relational
Approaches to Collective Action. Oxford: Oxford University Press.
Earl, Jennifer and Katrina Kimport. 2011. Activism in the Internet Age. Cambridge: MIT
Press.
Hutter, Swen. 2013. Protest Politics and the Right-Populist Turn in Western Europe.
Minneapolis: University of Minnesota Press.
38
Jansen, Giedo. 2011. Social Cleavages and Political Choices. Large-scale Comparisons of
Social Class, Religion and Voting Behaviour in Western Democracies. PhD Diss.,
Dept. of Sociology, Radboud University Nijmegen.
Kitts, James, A. 2000. “Mobilizing in Black Boxes: Social Networks and Participation in
Social Movement Organizations.” Mobilization, 5: 241-257.
Klandermans, Bert. 2013. “The dynamics of demand.” Pp. xx in The future of social
movement research: Dynamics, mechanisms and processes edited by Jacquelien van
Stekelenburg, Conny Roggeband, Conny and Bert Klandermans (eds). Minneapolis:
University of Minnesota Press.
Klandermans, Bert and Dirk Oegema. 1987. “Potentials, Networks, Motivations and Barriers:
Steps toward Participation in Social Movements.” American Sociological Review
5:519-531.
Klandermans, Bert, Jojanneke van der Toorn, and Jacquelien van Stekelenburg. 2008.
“Embeddedness and Identity: How Immigrants Turn Grievances into Action.”
American Sociological Review 73: 992-1012.
Klandermans, Bert, Jacquelien Van Stekelenburg Stefaan Walgrave, Dunya Van Troost
Anouk Van Leeuwen, Jeroen Van Laer, Joris Verhulst, & Ruud Wouters. 2011.
Manual for data collection on protest demonstrations. Caught in the act of protest:
Contextualizing Contestation (CCC-project), Version 3.0. Amsterdam, VU
University/Antwerp, University of Antwerp.
Knutsen, O. 2007. “The decline of social class.” Pp. 457-80 in Oxford Handbook of Political
Behaviour, edited by R.J. Dalton and H-D. Klingemann,. New York: Oxford Un.
Press.
Kriesi, Hanspeter, Ruud Koopmans, Jan-Willem Duyvendak, and Marco G. Giugni. 1995.
39
The Politics of New Social Movements in Western Europe. A Comparative Analysis.
Minneapolis/London: Un. of Minnesota Press.
Kriesi, Hanspeter, Edgar Grande, Romain Lachat, Martin Dolezal, Simon Bornschier and
Timotheos Frey. 2008. West European Politics in the Age of Globalization.
Cambridge: Cambridge University Press.
Lipset, S. M. and S. Rokkan. 1967. “Cleavage Structures, Party Systems & Voter Alignments:
An Introduction.” Pp. 1-64 in Party Systems and Voter Alignments: Cross-National
Perspectives, edited by S. M. Lipset and S. Rokkan, New York: The Free Press.
McAdam, Doug. 1986. “Recruitment to High-Risk Activism: The Case of Freedom Summer.”
American Journal of Sociology 92:64-90.
McCarthy, John D. 1996. “Constraints and Opportunities in Adopting, Adapting, and
Inventing.” Pp. 141-151 in Comparative Perspectives on Social Movements. Political
Opportunities, Mobilizing Structures, and Cultural Framing. edited by McAdam,
Doug, John McCarthy and Mayer N. Zald. Cambridge: Cambridge University Press.
Passy, Florence. 2003. Social networks matter. But how? Pp. 21-49 in Social Movements and
Networks. Relational Approaches to Collective Action edited by Mario Diani and
Doug McAdam. Oxford: Oxford University Press.
Simon, Bernd. 1998. “Individuals, Groups, and Social Change: On the Relationship between
Individual and Collective Self-Interpretations and Collective Action.” Pp. 257-282 in
Intergroup Cognition and Intergroup Behavior, edited by C. Sedikides, J. Schopler
and C. Insko. Mahwah, NJ: Lawrence Erlbaum.
Simon, Bernd. 1999. “A Place in the World: Self and Social Categorization.” Pp. 47-69 in The
Psychology of the Social Self, edited by T. R. Tyler, R. M. Kramer, and O. P. John.
Mahwah, NJ: Lawrence Erlbaum.
Simon, Bernd and Bert Klandermans. 2001. “Towards a Social Psychological Analysis of
40
Politicized Collective Identity: Conceptualization, Antecedents, and Consequences.”
American Psychologist, 56: 319-331.
Simon, Bernd, Michael Loewy, Stefan Stürmer, Ulrike Weber, Claudia Kampmeier, Peter
Freytag, Corinna Habig and Peter Spahlinger. 1998. “Collective Identity and Social
Movement Participation.” Journal of Personality and Social Psychology, 74: 646-658.
Snow, David A., Louis A. Zurcher and Sheldon Ekland-Olson. 1980. “Social Networks and
Social Movements: A Microstructural Approach to Differential Recruitment.”
American Sociological Review, 45: 787-801.
Stryker, Sheldon, Timothy J. Owens and Robert W. White (eds.). 2000. Self, Identity, and
Social Movements. Minneapolis: University of Minnesota Press.
Swaab, Roderick I., Tom Postmes and Russell Spears. 2008. “Identity formation in multiparty
negotiations.” British Journal of Social Psychology, (2008), 47: 167–187.
Tindall, D.B. 2004. “Social Movement Participation over Time: An Ego-network Approach to
Micro-mobilization.” Sociological Focus, 37: 163-184.
Van Stekelenburg, Jacquelien and Bert Klandermans. 2007. “Individuals in Movements: A
Social Psychology of Contention.” 157-204. Pp. 157-204 in The Handbook Social
Movements across Disciplines, edited by B. Klandermans and C. Roggeband, Kluwer.
Van Stekelenburg, Jacquelien and Bert Klandermans. “Fitting Demand and Supply: How
Identification Brings Appeals and Motives Together.” Under review.
van Stekelenburg, Jacquelien, Bert Klandermans, and Wilco van Dijk. 2009. “Context
Matters: Explaining How and Why Mobilizing Context Influences Motivational
Dynamics.” Journal of Social Issues, 65: 815-838.
van Stekelenburg, Jacquelien, Bert Klandermans, and Wilco van Dijk. 2011. “Combining
Motivations Emotion: The Motivational Dynamics of Collective Action
Participation.” Revista de Psicologia Social, 26: 91-104.
41
van Zomeren, Martijn, Spears, Russell, Fischer, Agneta H., and Leach, Collin W. (2004). “Put
Your Money Where Your Mouth Is! Explaining Collective Action Tendencies
Through Group-Based Anger and Group Efficacy.” Journal of Personality and Social
Psychology, 87(5), 649-664.
Verhulst, Joris. 2011. Mobilizing issues and the Unity and Diversity of Protest Events. PhD
Diss., University of Antwerp.
Walgrave, Stefaan and Bert Klandermans. 2010. “Open and closed mobilization patterns. The
role of channels and ties.” Pp. 169-193in The World Says No to War. Demonstrations
against the War in Iraq, edited by S. Walgrave Stefaan and D. Rucht,. Minneapolis:
Un. of Minnesota Press.
Walgrave, Stefaan and Jan Manssens. 2000. “The Making of the White March: The Mass
Media as a Mobilization Alternative to Movement Organizations.” Mobilization, 5:
217-240.
Walgrave, Stefaan, Ruud Wouters, Pauline Ketelaars, 2012. “Response problems in the
Protest Survey Design. Evidence from fifty one protest events in seven countries.”
Under review.
42
Tables
Table 1 Unaffiliated demonstrators per type of demonstrations
Unaffiliated
# demos # part.
demonstrators
All
51%
60
12681
Ritual parade
May Day
Climate
Gay
Women
Peace
47%
42%
42%
67%
61%
64%
22
12
5
1
3
1
4152
1708
1449
197
534
264
Anti-austerity
Universalistic
Students
Workers
34%
33%
68%
26%
20
5
4
11
3969
866
686
2417
Socio-cultural Issues
Anti nuclear energy
Anti racism
Democracy
Anti abortion
Regional issue
68%
46%
69%
84%
86%
68%
18
5
4
5
1
3
4560
1235
678
1411
301
934
43
Table 2 Communication channels by affiliation (percentages and Gamma’s)
Affiliated Unaffiliated Gamma
%
%
Panel A
Open channels
Radio/television
15.7
23.5
-.25
Newspapers
23.6
30.0
-.16
Online social networks (e.g. facebook, twitter)
16.2
26.9
-.31
Partner, family
9.4
18.2
-.36
Friends, acquaintances
19.5
35.8
-.40
People at school or workplace
17.1
13.4
.14
Semi-open channels
Online media
19.6
26.4
-.19
Advertisements, flyers, posters
26.2
22.4
.10
Closed channels
(Fellow) members of organization, association
50.9
15.8
.69
An organization’s magazine, meeting, website, mailing list, etc.
51.1
23.3
.55
Panel B
No-one
28.3
35.8
-.17
Partner, family
8.6
16.1
-.34
Relatives
2.6
4.8
-.27
Friends,
12.9
25.8
-.40
Acquaintances
6.0
6.8
-.07ns
Colleagues or fellow students
15.3
11.1
.18
(Fellow) members of organization, association
43.6
10.9
.73
44
Table 3 Affiliation and communication channels employed (percentages)
Affiliated
Unaffiliated
Gamma
Open channels
28.3
63.5
-.63
Semi-open channels
9.7
16.8
-.31
Closed channels
62.0
19.7
.74
Table 4 Demonstrations and communication channels (percentages)
Open
Semi-open
Closed
Ritual parade
40.0
12.9
47.1
Anti-austerity
38.5
11.6
49.9
Socio-cultural
59.5
15.0
25.5
Total
3519
3278
4096
Table 5 Decision time by communication channels and affiliation1
Communication channels
Open channels
2.6 (1.0)
Semi-open channels
2.8 (1.0)
Closed channels
3.1 (0.9)
Affiliation
Affiliated demonstrators
3.1 (0.9)
Unaffiliated demonstrators
2.6 (1.0)
1
on a scale from 1 ‘the day of the demonstration’ to 4 ‘over a month ago’
45
Table 6 Patterns of identification by affiliation: Means and standard deviations1
Affiliated
Unaffiliated
Identificatio
n
w.
organizers
4.3 (0.8)
Identificatio
n
w. other
participants
4.2 (0.8)
Difference
s
Ritual
parade
May Day
Climate
Gay
Women
Peace
4.3 (0.8)
Antiausterity
All
Universalisti
c
Students
Workers
Sociocultural
Issues
Antinuclear
energy
Antiracism
Identificatio
n
w. other
participants
3.9 (0.9)
Difference
s
-.06 (0.9)
Identificatio
n
w.
organizers
3.4 (1.1)
4.2 (0.8)
-.08 (0.8)
3.5 (1.0)
3.9 (0.9)
.37 (1.0)
4.3 (0.8)
4.3 (0.8)
4.0 (0.9)
4.4 (0.7)
4.1 (0.9)
4.2 (0.8)
4.2 (0.8)
4.2 (0.8)
4.4 (0.6)
4.2 (0.8)
-.10 (0.8)
-.13 (0.8)
.15 (0.8)
.03 (0.7)
.13 (1.1)
3.4 (1.0)
3.6 (1.0)
3.2 (1.1)
3.6 (1.1
3.7 (1.0)
3.7 (0.9)
3.8 (0.9)
3.8 (0.9)
4.2 (0.8)
4.1 (0.7)
.36 (1.0)
.25 (0.9)
.55 (0.9)
.54 (1.0)
.37 (1.0)
4.2 (0.9)
4.2 (0.8)
-.00 (0.9)
3.1 (1.1)
3.8 (0.9)
.76 (1.1)
4.2 (0.8)
4.2 (0.7)
.01 (0.8)
3.1 (1.1)
4.0 (0.7)
.93 (1.0)
4.0 (1.0)
4.2 (0.9)
4.1 (0.9)
4.2 (0.9)
.05 (1.1)
-.01 (0.9)
3.0 (1.1)
3.2 (1.1)
3.7 (1.0)
3.9 (1.0)
.77 (1.1)
.66 (1.1)
4.3 (0.8)
4.2 (0.8)
-.12 (0.8)
3.5 (1.0)
4.0 (0.9)
.48 (1.1)
4.2 (0.9)
4.0 (0.8)
-.22 (0.9)
3.4 (1.1)
3.7 (0.9)
.29 (1.0)
4.4 (0.8)
4.5 (0.7)
.08 (0.7)
3.4 (1.1)
3.9 (0.9)
.51 (1.0)
.51 (1.1)
4.4 (0.7)
4.1 (0.8)
-.25 (0.8)
3.4 (1.1)
3.9 (0.9)
.54 (1.1)
Democracy
Anti4.3 (0.8)
4.5 (0.8)
.17 (0.7)
3.9 (0.9)
4.3 (0.7)
.34 (0.8)
abortion
Regional
4.4 (0.8)
4.4 (0.7)
.03 (0.8)
3.7 (1.1)
4.2 (0.7)
.56 (1.0)
issue
1
on a scale from 1 ‘not at all’ to 5 ‘very much’
Standard deviations among unaffiliated demonstrators are significantly larger (Levene’s Test for
Equality of Variances)
except for peace marches, universalistic anti-austerity demonstrations, anti-abortion
demonstrations, and regional
issues demonstrations as far as identification with other participants is concerned.
46
Table 6 Patterns of identification by affiliation: Means and standard deviations1
Affiliated
Unaffiliated
All
Identification Identification Differences Identification Identification Differences
w. organizers
w. other
w. organizers
w. other
participants
participants
4.3 (0.8)
4.2 (0.8)
-.06 (0.9)
3.4 (1.1)
3.9 (0.9)
.51 (1.1)
Ritual
4.3 (0.8)
4.2 (0.8)
-.08 (0.8)
3.5 (1.0)
3.9 (0.9)
.37 (1.0)
parade
Anti4.2 (0.9)
4.2 (0.8)
-.00 (0.9)
3.1 (1.1)
3.8 (0.9)
.76 (1.1)
austerity
Socio4.3 (0.8)
4.2 (0.8)
-.12 (0.8)
3.5 (1.0)
4.0 (0.9)
.48 (1.1)
cultural
Issues
1
on a scale from 1 ‘not at all’ to 5 ‘very much’
Standard deviations among unaffiliated demonstrators are significantly larger (Levene’s Test for
Equality of Variances)
except for peace marches, universalistic anti-austerity demonstrations, anti-abortion
demonstrations, and regional
issues demonstrations as far as identification with other participants is concerned.
47
Table 7 Motivation by affiliation: Means and standard deviations
Affiliated
Unaffiliated
Instrumentality1
8.3 (1.5)
7.9 (1.8)
1
Ideology
8.9 (1.4)
8.6 (1.6)
Anger2
4.3 (1.0)
4.2 (1.0)
3
Determination
4.6 (0.8)
4.3 (0.9)
1
on a scale from 2 ‘not at all’ to 10 ‘very much’; 2on a scale from 1 ‘not at all’ to 5 ‘very much’;
3
on a scale from 1 ‘not very’ to 5 ‘very much’. Except for anger standard deviations among
unaffiliated
demonstrators are significantly larger (Levene’s Test for Equality of Variances)
Table 8 Motivation by type of demonstration and affiliation: Means and standard deviations
Parades
Anti-austerity
Socio-cultural
demonstrations
demonstrations
Affiliated Unaffiliated Affiliated Unaffiliated Affiliated Unaffiliated
1
Instrumentality
7.9 (1.8)
7.4 (1.9)
8.6 (1.5)
8.1 (1.8)
8.4 (1.6)
8.2 (1.7)
Ideology1
8.8 (1.4)
8.6 (1.7)
8.8 (1.4)
8.3 (1.7)
9.1 (1.2)
8.8 (1.3)
2
Anger
4.2 (1.0)
4.2 (1.0)
4.3 (1.0)
4.1 (1.1)
4.3 (1.0)
4.2 (1.0)
Determination3
4.6 (0.7)
4.3 (0.9)
4.6 (0.7)
4.3 (0.9)
4.6 (0.7)
4.4 (0.8)
1
2
on a scale from 2 ‘not at all’ to 10 ‘very much’; on a scale from 1 ‘not at all’ to 5 ‘very much’;
3
on a scale from 1 ‘not very’ to 5 ‘very much’. Except for anger standard deviations among
unaffiliated
demonstrators are significantly larger (Levene’s Test for Equality of Variances)
Table 9 Difference scores of instrumental and ideological motivation: Means and standard deviations
Parade
Anti-austerity
Socio-cultural issues
Affiliated
.91 (1.6)
.15 (1.5)
.70 (1.6)
Unaffiliated
1.12 (1.7)
.17 (1.8)
.68 (1.7)
Table 9 Regression of determination on affiliation, identification, motivation and anger:
Standardized beta’s
Model 1 Model 2 Model 3 Model 4 Model 5
Affiliation
.18**
.07**
.07**
.07**
.07**
Identification w. organizers
.16**
.12**
.12**
.12**
Identification w. participants
.27**
.18**
.16**
.16**
Ideology
.21**
.19**
.19**
Instrumentality
.12**
.10**
.10**
Anger
.12**
.12**
Affiliation X Identification w. organizers
.01
Affiliation X Identification w. participants
-.03*
Affiliation X Ideology
-.05**
Affiliation X Instrumentality
.00
Affiliation X Anger
-.00
2
.03
.16
.23
.24
.24
R
48
Figures
.00 (ns)
.07 *
Identification
organizers
.55*
Instrumental
motives
.13*
11*
.20*
Identification
participants
Identity
.13*
.44*
Anger
.12*
Determination
.14*
.19*
Ideological
motives
.27 *
.17 *
Figure 1a Path model of determination for affiliated demonstrators (* = p <.001)
.00 (ns)
.10 *
Instrumental
motives
Identification
organizers
.00 (ns)
15*
.45*
Identification
participants
Identity
.27 *
.15*
.10*
.43*
Anger
.14*
Determination
.24*
.23*
Ideological
motives
.27 *
Figure 1b Path model of determination for unaffiliated demonstrators
49
Endnotes
i
A detailed description of the project and its tools can be found in the project-manual
(Klandermans et al. 2011). The manual is available on request; see the project website
(www.protestsurvey.eu ). See also Van Stekelenburg et al. (2012).
ii
See Walgrave et al. 2012, for an extensive discussion of the various biases resulting from
sampling and non-response.
iii
The measures included were: decision time, affiliation to organizations that stage the
demonstration, political interest, satisfaction with democracy, participation in demonstrations
in the past, sexe, age, and education.
iv
We applied translation-backtranslation to assure that the questions were identical in the
various languages.The English version of the questionnaire can be found in the project’s
manual.
v
We conducted Levene’s Test for Equality of Variances.
vi
We conducted Levene’s Test for Equality of Variances.
vii
While all variables in this analysis are on the micro-level, and we don’t have assumptions
about aggregated or disaggregated variables, there is not a methodological urgency to perform
multilevel analyses. But since the data are hierarchical nested (demonstrators within
demonstrations within countries), we did perform multilevel analyses to control for this nested
structure (results available on request). The effect sizes are somewhat smaller compared to the
OLS regression analyses (as expected), but the results all point in the same direction.