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Modes of coordination in civic fields: Insights from South Africa (and occasionally Britain) Mario Diani (University of Trento, Italy & ICREA-UPF Barcelona) Henrik Ernstson (KTH, Stockholm and UCT, Cape Town) Lorien Jasny (SESYNC, Annapolis, USA) Correspondence to mario.diani@unitn.it NB: This is not really a paper, rather, a series of mainly descriptive notes on very preliminary findings. It is distributed only for the sake of facilitating discussion in the seminar. I am usually indifferent on this issue, but this particular document is STRICTLY not for citation or quotation. Comparative analysis of social networks is remarkably rare (Entwisle et al. 2007; Fischer 2011; Vera and Schupp 2006). In the field of political networks, scarcity of properly comparable data is compounded by the traditional objections raised against large scale comparison (see e.g. Edwards, Foley, and Diani 2001 on the difficulty of comparing social capital measured on standard individual indicators). This is often done in the name of the uniqueness of specific cases and the superiority of thick description. In this paper we profile civil society networks in three quite different contexts (Cape Town, Glasgow, and Bristol) and try to get some steps towards laying out some criteria (in the form of basic network parameters) that may guide a comparison of political networks. For the time being at least, we refrain from attempting casual arguments. Hence, our effort can be seen as an exercise in “thick description”, although obviously not of the kind advocated by the late Clifford Geertz (1987). Our focus is on the structure of civil society conceived as the pattern of ties that link organizations acting on collective and/or public issues. We emphasize the relational over the aggregative dimension, whereby structure is given by relational patterns, not by the distribution of properties. The methodological implication is that in order to identify structure we need to rely on explorations of networks as well as on the measurement of actors’ individual properties (Diani 2015, chap. 1). To this purpose, after presenting some basic parameters of network structure, we engage in a comparison of relational structures in the three cities focusing on the concept of mode of coordination (Diani 2013; 2015, chap. 1), namely, on the different relational patterns through which practical and symbolic resources are exchanged in civil society fields. For the purpose of this paper we look in particular at the variable combinations of ties which imply some kind of resource allocation, and ties (a section of the former) that imply a stronger connection, as reflected in the ties created by core individuals’ multiple memberships or friendship links to other groups’ members (in our language, social bonds: see again Diani 2015). One obvious question refers to the rationale of the specific comparison proposed here. An exploration of SA and UK may be regarded as an instance of a most dissimilar design. They share a relatively similar institutional system given SA’s colonial past as part of the Commonwealth but at the same time are quite different in terms of

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a) Consolidation of a universalistic democratic process b) Levels of inequality c) apartheid legacy d) persisting influence of intra-racial/tribal divisions e) domination of one party linked to its role in the anti-apartheid struggle difficulty to link

local grievances and protests into broader agendas These differences may be expected to affect network patterns in a number of ways:

a. the overall higher instability of the political system in SA may require collaboration ties to be more strongly embedded in trust. In turn, this can lead to greater overlap between more instrumental and more symbolically charged ties like those resulting from shared core members (in general, purely instrumental exchanges in pursuit of very specific goals should require lower levels of trust than most demanding, longer-term collaborations);

b. inequality, often linked to apartheid, space organization, and ethnic divisions may all activate homophily mechanisms and thus affect the composition of network positions;

c. groups with limited resources may be unable to engage in broad alliance building and operate on a more isolated basis (the opposite can also apply, of course, as coalition building may be seen as the only visible option for organizations unable to engage in effective lobbying on their own). The studies Evidence comes from field work conducted in Cape Town between 2012-2014 under the leadership of Henrik Ernstson, in the context of the project “Socioecological Movements and Transformative Collective Action in Urban Ecosystems (MOVE)”, funded by Formas-Swedish Research Council (contract 211-2011-1519), and from an earlier project on “Networks of civic organizations in Britain”, conducted in Bristol and Glasgow between 2001-2003 by Diani and collaborators (ESRC contract L215 25 2006). In the UK, data were collected among organizations working on environmental, social exclusion, inequality and ethnic and migrants’ issues in the UK (124 in Glasgow, 134 in Bristol: Diani 2015, ch.2), while in Cape Town the focus was primarily on environmental issues and urban issues, yet broadly conceived (129 organizations interviewed). Basic network measures: patterns of cohesion and integration A cursory exploration of basic indicators of network cohesion (Table 1) suggests differences between UK and South African civic networks to be overall modest: The Cape Town network falls in between the other two in terms of density, and also as in overall fragmentation, as reflected in number of isolates, network components, range of degree scores and network centralization. The UK networks seem to be slightly more connected, yet with a higher average distance between non-isolated organizations. Tendencies to clustering are also very comparable.

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In a nutshell, there seems to be no ground to think that the overall structures be substantially different in the three cities; if anything, what stands out is the disconnectedness and low density of the social bonds network in Glasgow. Table 1 about here Modes of coordination By ‘mode of coordination’ we mean the mechanisms through which resources are allocated within fields, decisions taken, collective representations elaborated, feelings of solidarity and mutual obligation forged. We can identify at least two broad classes of mechanisms, different combinations of which define different modes. They may be associated to resource allocation and boundary definition. Resource allocation includes the whole set of procedures through which decisions are taken regarding the use of resources – from choice of agendas, strategies and tactics to selection of leadership and resource mobilization. Within specific organizations, such decisions may be taken and implemented through formal as well as informal procedures, although in most cases through a combination of the two. We can extend this logic, however, to organizational fields, by noting that resource allocation may also take place through informal exchanges between groups and organizations (and even individuals, the more so the more they can control specific resources) that maintain their independence and autonomy. In some cases, actors may concentrate most of their resources on their own project and devote a very limited amount of resources to collaborative projects, which results in fairly sparse exchange networks. In other cases, resources invested in collaboration may be substantial and are more likely to lead to fairly dense networks. At the same time, mechanisms of boundary definition are relevant for both specific organizations and for broader organizational fields. Boundaries are criteria that classify elements of social life in different groups and categories, while shaping the relations between elements both within and between those groups (Abbott 1995; Tilly 2005). Boundary definition may be generated through ideational elements, social representations, framing processes, as well as through relational mechanisms (e.g, multiple involvements in groups by individuals). For example, “the environmental justice movement [in SA] contains pockets of strong personal relations, collective identities, thick social networks marked by a social cohesiveness ….. for many activists social interactions have a depth that contrast with the thin, atomized identities of citizen and consumer” (Cock 2006, 214). Similar remarks may apply to very diverse instances of collective action (Diani 2015). Boundary definition may be regarded as an essential component of processes of identity building, helping to establish connections across time and space: e.g., between phases in individual or organizational lives, or between different generations, or between events occurring simultaneously in different locations, etc. (Somers 1994; Melucci 1996, chap. 4; Pizzorno 2008). These processes are often located at the level of specific organizations, regardless of their level of formalization, as people identify with a distinct corporate actor and interact with its members in ways that are significantly different from what regulates relations to outsiders. At the same time, organizations and individuals within a field may develop mechanisms of identification and boundedness that are not restricted to specific organizations – again, more or less formal – but come instead to include a multiplicity of groups and organizations, that still maintain their specificity and distinctiveness. We may see, in other words, the emergence of ‘double boundaries’, some focusing on specific

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groups/organizations, others involving broader subsets of a field (it may also happen that identification by individuals with specific groups disappears, to be replaced exclusively by identification with broader entities – such as a ‘subcultural community’ or, indeed, a ‘social movement’). It is possible to think of different MoC as different combinations of mechanisms of resource allocation and boundary definition, both classified in terms of their focus being primarily on specific groups/organizations or on the multiplicity of actors involved in a collective action field (or at least in a subset of them). This generates a four-fold typology that differentiates between social movement, coalitional, subcultural/communitarian and organizational MoC (see table 2 below). Table 2 about here Looking at different combination of these two types of mechanisms makes it explicit that having many people interested in a given cause, many protest events occurring on issues that seem more or less related to a set of common problems, and/or a set of organizations mobilizing on similar issues does not warrant per se the existence of a social movement. It is certainly difficult to think of a movement in the absence of such elements, but the reverse does not automatically apply. A movement is in place when we have a particular form of coordinating those elements, consisting of informal exchanges between multiple actors on the basis of a shared definition of boundaries (what in earlier work I referred to as collective identity (Diani 1992). In a social movement mode of coordination, the terms of inter-organizational collaboration are informal, and have to be renegotiated each time a new issue/opportunity/ threat emerges. In other words, each collective action event is the product of a specific negotiation between a multiplicity of formally independent, and often highly heterogeneous, actors. This does not mean that practices of repeated collaboration between different organizations may not generate informal routines that reduce the costs of the negotiation, however, these routines are not formalized. Negotiations between movement actors refer to several aspects of mobilization campaigns, including the articulation of their specific goals, the choice of the most appropriate tactics and mobilizing messages, the identification of the social sectors from which to search for support, the contributions that each coalition partner is expected to give. Mechanisms of boundary definition1 are crucial in social movements for a number of reasons, the most obvious being that movements have no formal boundaries and no formally defined criteria for inclusion or exclusion. There are no formal ‘social movement members’, as the only criterion for ‘membership’ – better: for being part - is direct involvement with activities and/or organizations that are associated with the movement. By ‘associated’ we mean that they are socially constructed as linked to a broader collective experience called ‘movement’. Therefore, the boundaries of a movement are defined by processes of mutual recognition whereby social actors recognize different elements as part of the same collective experience and identify some criteria that differentiate them from the rest. Those elements may be individuals or organizations, but also events.

1 Tilly (2005, 137-146) lists a number of specific mechanisms associated to boundary definition.

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Mechanisms of boundary construction secure the continuity of collective action over time and space. Social movements exist, in other words, because both actors mobilized in them and (more or less sympathetic or interested) observers are capable of locating in a broader picture actors and events that operate in different points in space and time (e.g. environmentalism exist to the extent that people are capable of providing a common interpretation for actions on nuclear energy, industrial pollution, animal protection, occurring in different localities and at different time points). Like resource coordination, boundary definition also often takes a multidimensional, complex form. We only rarely have clear cut identities and boundaries, neatly separating movements from their environment. Rather, we have boundaries that are often permeable. It is important to stress the dual nature of boundary definition, at the organizational level and the movement level. The fact that there is a movement-level identity, that is, a boundary encompassing all the actors associated with a movement, does not mean a demise of organizational identity. To the contrary, feelings of belongingness, solidarity, and obligations may be, and often are, addressed to both specific organizations and a movement taken as a whole (Lofland 1996, 11). In general, there is some kind of balance between organizational and broader identities. Summing up this discussion, it is precisely the coupling of informal resource exchanges and boundary definitions encompassing multiple actors that defines the analytical properties of a ‘social movement mode of coordination’. However, social movement scholars are the first to agree that “social movements are only one of numerous forms of collective action” (Snow, Soule, and Kriesi 2004, 6). More broadly, within fields it is usually possible to identify multiple modes of coordination.In terms of resource allocation, coalitions are actually very similar to social movements, as both consist of multiple, often heterogeneous, independent actors, sharing resources in pursuit of some shared goals. However, they differ in the nature and scope of the boundary definition mechanisms on which coalitions are founded. In contrast to social movements, the boundary work taking place in coalitions is temporary and locally circumscribed. Given their instrumental, goal-oriented nature, coalitions exhaust their function when their goal is either achieved, or when it is clear that the cause has been lost. However, it is certainly true that in practice coalitions, originally set up by organizations focusing each on its own identity, may gradually see the emergence of broader feelings of solidarity among their proponents, and thus contribute to the formation of broader social movements. It is also important to remember that a huge chunk of protest activity as well as voluntary action (actually the largest part of it) follows the logic of organizational modes. These consist of modes of resource allocation and boundary definition that do not involve systematic inter-organizational networking and take largely place within specific groups or organizations. This model actually accommodates quite diverse organizational forms, that range from extremely hierarchical and formalized mass parties to extremely decentralized and informal grassroots groups; from the extremely endowed with resources, such as business associations, to the extremely deprived, such as neighborhood action groups. For all the current rhetoric on the spread of network organizational forms, it is striking to notice how many civil society associations even of the grassroots type work mainly on their own. A systematic exploration of civil society networks in San Paulo for example found the majority of neighborhood associations (‘Associações de Bairro’) to have no ties to other groups of the same kind (Gurza Lavalle, Castello, and Bichir 2007; 2008).2

2 We do not comment here on the fourth, “subcultural/communitarian” mode of coordination as it has neither been empirically identified in Cape Town, nor in the UK, and is therefore not

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Our exploration of “modes of coordination” in Cape Town replicates the procedure followed by Diani in the UK study (2015; Diani and Bison 2004). We conduct a structural equivalence analysis on the ties that imply resource allocation using the routine Concor. This enables us to identify positions (“blocks”) of organizations that are involved in relatively similar patterns of ties to other actors, regardless of whether they are directly linked to each other or not.3 Two splits in the matrix identify the four structural positions marked with different colors in figure 1. As shown by the main diagonal in table 3, each block shows a higher density of ties among its incumbents than between them and other organizations. There are two exceptions to this pattern: one is obviously block 1, that includes isolated or poorly connected organizations (at least within this particular field); the other is block 3 that sends quite a good share of its overall ties to organizations in block 2 (density 0.063). As a result, incumbents of blocks 2 and 3 have a much higher share of ties outside their own position than among themselves (Table 4: we keep these two positions distinct as they differ on a number of important properties, as the following analysis will show). While Diani (2015) tests the significance of distributions of ties with a variable homophily auto-correlation model, here we rely exclusively on relational contingency tables, which are easier to interpret (Table 5). We look in particular at the ratio between observed and expected ties under the hypothesis of random distribution. The blockmodel shown in figure 2 summarizes this relational pattern, with high internal connectedness to most blocks and less significant connections across blocks. Figure 1, tables 3-5, and figure 2 about here In order to identify different modes of coordination (henceforth, MoCs) we need to look at how the strongest ties, social bonds, distribute across the network. Table 6 confirms that groups and associations in block 1 follow an “organizational” MoC, namely, not only they are not linked by resource exchanges, they do not rely on personal connections either. On the other hand, all the other blocks present traits of a social movement logic of coordination, as social bonds are significantly over-represented among the incumbents of each block. This sets Cape Town civil society apart from the pattern found in British cities, where dense resource exchanges did not always correspond to dense social bonds. In other words, both Glasgow and Bristol displayed sectors of civil society that coordinated through a “social movement MoC” (determined by the overlap of dense resource exchanges and dense social bonds), while others operated closer to a “coalitional” Moc, in which dense resource exchanges were not matched by dense social bonds (Diani 2015, ch.4; Diani and Bison 2004). In contrast, in Cape Town, barring the exception of groups acting mainly on their own, the rest of civil society seems to coordinated through patterns that in the UK have been found to be closest to a social movement logic of action. The pattern seems particularly pronounced in blocks 2 and 5. The same result is found if we look at the distribution of social bonds as shared memberships in 2-

relevant to the present discussion. See, instead, Diani (2013), as well as, for an empirical illustration, Diani (2012). 3 As Concor is not well suited to deal with disconnected graphs, we first dropped isolates and members of two small (2 nodes each) components, which were assigned to a structural position identified here as “Block 1”. The procedure was then applied to the main component of the graph, consisting of 113 nodes.

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cliques. In other words, organizations that are co-members of one or more 2-clique are more likely to find themselves in the same structural block (again with the exception of block 1). Given that a 2-clique is a set of nodes in a network such that all nodes are connected either directly or through at the most one intermediate step, that means that organizations within each block are more likely to be embedded in cohesive networks in which organizational and personal exchanges reinforce each other. As in the resource allocation network, even in terms of social bonds, dense connections also seem to be operating between blocks 2 and 3. The questions to be addressed in the next section are

a) whether these relational patterns correspond to specific feelings of solidarity and collective identification;

b) whether blocks stand out because of their characteristics. Table 6 about here Indicators of identity and boundary definition There are several ways to assess the extent to which organizations in the same structural position actually share some feelings of belongingness and mutual identification. The first is simply to ask organization representatives whether they feel particularly close to other organizations, regardless of the amount of interaction between them. Answers to this question reproduced the pattern already identified: blocks 2 and 5 were the ones whose incumbents were more strongly connected by solidarity feelings (table 7). The fact that four positions out of five seem close to a social movement MoC, in terms of relational patterns, is reflected in the high identification that Cape Town groups have with some social movements. About half of them indicate their proximity to at least one out of a list that ranges from environmentalism to global justice to working class movements [table 8; ADD FULL LIST AND TABLE]. Interestingly, incumbents of the isolated block 1 are the least inclined to identify; the strongest identification with movements is found among incumbents of blocks 3 and 5. In particular, organizations in block 3 have above the average identification with environmental and climate justice movements, while incumbents of block 5 are close to land claimants and shackdwellers movements (tables 9-10). Finally, while the tendency to identify specific social or political opponents only affects 20% of the organizations interviewed (table 11), the presence of a contentious identity is strongest in block 5, and totally absent from block 1, the most distant from a social movement logic of action. Table 7-11 about here Another type of relation: involvement in events Involvement in events creates ties. Looking at how these ties distribute across blocks represents a useful way to explore the link between forms relational structures and substantive properties. The number of shared specific events distributes very unevenly across the network. One should note that specific events are overwhelmingly of the protest type.

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Data show that groups in B1 and even more in B4 are grossly under-represented here, and B5 is massively over-represented (tables 12-13). If we look instead at regular events, the closest to the “civic” type (e.g., Mandela Day, World Environment Day, etc.), we see that there is hardly any differentiation within the sector, with just groups in B4 being somehow more connected through them than the others (tables 14-15). The salient role of protest events in shaping structure of ties across the sector as opposed the lack of such roles for regular, largely ritualistic events is similar to what has been found in the UK cities. Even there, structural positions differ in their incumbents’ involvement in protest events but not in non contentious ones (Diani 2015, ch.6). Table 12-15 about here. An overall picture From the combination of all the relational data, the following overall picture emerges:

Block 1, close to an organizational MoC, hosts organizations with a totally consensual identity and no identification with any movements, and limited involvement in protest events it illustrates a traditional pressure group logic

B2: strong movement dynamic in terms of MoC relational terms is less pronounced at other levels as few opponents are identified, there is only average identification with any movement; average (modest) involvement in both protest and civic events suggest that the prevailing model be one of “consensus movement”

B4: there is a relative proximity to the profile of a social movement MoC, but no involvement in protest events another consensus movement logic prevailing here

B3: a relatively weaker but still significant social movement MoC, with strong identification with environmentalism; average (modest) involvement in protest and civic events closest to an “environmental justice” consensus movement

B5: strong movement MoC, conflict oriented and identification with movements active on inequality; strong involvement in protest events “social justice” protest movement In comparison to the British case, it is worth noting the absence of structural positions characterized by coalitional MoC: in Cape Town, when organizations are densely linked in terms of resource exchanges, they are also connected through the activities and personal relations of their core members. Of course, some inter-organizational exchanges are not embedded in deeper inter-organizational ties, but they tend to spread across the network rather than characterizing some of its clusters. What differentiates between blocks?4 Repertoires

4 NB: For all what follows we need descriptives of how much certain properties are present,

not just of their distributions across blocks. This is particularly important when we use

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Factor analysis identifies four main repertoires: radical protest, including tyre burning, violence against objects, etc.; conventional protest such as demonstrations or sit-ins; pressure; and support electoral candidates. For each factor we constructed 1-100 scales measuring the proportion of tactics, associated to that particular factor, one group claimed to have used or be prepared to use. Of these four factors, only radical protest seems to be differentiate significantly between blocks. Organizations in the “social justice movement” position (block 5) are particularly inclined to engage in that kind of protest, while the opposite applies to pressure groups in block 1 and those in block 2, one of the “consensus movement” positions (table 16). The only other action repertoire for which there seems to be some minimal difference is support to election candidates, particularly popular in block 2 (table 17). Tables 16-17 about here The distribution is quite different than in the UK, where the major difference lay between groups (and position, namely the social movement position) that were particularly inclined to adopt any kind of political action, whether of the pressure or protest type, vs. groups and positions (namely, the one reflecting an “organizational” MoC) that tended to refrain from any (Diani 2015, ch.4). Here, differences across blocks are less pronounced, including those between the organizational block 1 and the others. Moreover, there seem to be differences between radical and conventional protest that were not evident in the UK. Issue priorities How do issue agendas distribute across blocks? Five dichotomous variables measure interest in different types of issues: global justice, urban environmental conservation, efficient democracy, eco-management and urban social issues. 5 Differences between blocks on issue priorities vary depending on issues, in particular, there is a widespread interest in making urban democracy more efficient. Data show different blocks to reflect higher (sometimes, lower) interest in specific issues, as follows (tables 18-22): Block 1 only stands out for a particularly high interest in “social issues” and corresponding low interest in “eco-management”. Block 2 shows high interest in urban conservation Block 3 also shows high interest in urban environmental conservation as well as in global justice, and a more limited interest in urban social issues

synthetic measures such as 1-100 scales. might go in the Studies section, where we can introduce UK data too. 5 Principal component identified four factors (one of them, opposing “Ecomanagement vs. social needs”, reflected

the opposition between a focus, in the handling of urban issues, to “ecomanagement” over the facing of basic inequality issues). After building a more complex 1-100 indexes we have dichotomized variables as the distribution in some cases was so skewed to render any 1-100 scale preposterous.

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Block 4 stands out for its incumbents’ interest in eco-management issues. Finally, organizations in block 5 only stand out for their lower attention to urban conservation but also urban social issues. The latter is puzzling because groups in this block express a higher than normal identification with shackdwellers and landless people’s movements, i.e., with movements focusing on issues of “social justice.” While this requires further exploration, groups in this position might actually focus on a relatively narrow set of social justice themes, linked to the control of the land (both urban and not-urban), without adopting a broader agenda. Tables 18-22 about here Ties to political actors (also include an analysis of ties across cleavages) Incumbents of the different blocks have some kind of collaborative relationship with ANC in one quarter of the cases, and do not differ significantly in this regard. The same applies to major oppositional force (but currently in government in Cape Town), Democratic Alliance, although the involvement with it is lower, just 15%. The overall relationship to the unions confederation Cosatu is somehow in-between at 21% [NB: we need to look at the specific unions too, which would make the overall relation to the unions more impressive]. However, blocks differ quite significantly on this ground, with blocks 3 and 5 highly, and blocks 1 and 4 minimally involved (table 23). The importance of the relation to Cosatu is also visible in that fact the organizations with a link to Cosatu have significantly higher odds of sharing a tie, both in terms of resource allocation and social bonds, while the same does not apply to groups with ties to ANC/DA. In this sense, Cosatu could be regarded as a pillar of a (modest) cleavage (tables 24-25). Tables 23-25 about here Location and properties The location of these organizations in areas with different racial profiles illustrates the persistent capacity of the apartheid legacy to affect the structure of civil society (not surprising, considering that we are only 20 years away). In any case, organizations in blocks 1 and 2 are mainly located in coloured areas, sometimes in mixed/white ones; organizations in block 3 are predominantly located in white areas; those in blocks 4 and 5, mostly in black areas (occasionally, mixed) (table 26). If we look at the distribution of ties across racial areas, the only area which is not distinct is the mixed one. In other words, organizations located in mixed areas are not more likely to relate to each other than to groups located in other areas. This is not the case for organizations located in areas with a more distinct racial profile. The only instance of significant exchange across areas is between groups located in black areas and in non-white (i.e., mixed black-coloured) ares (table 27). Tables 26-27 about here

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Organizational properties There are no differences in declared budgets across blocks (allowing or the fact that these figures are always shaky). Main differences are the following:

On a 0-12 additive scale of formal organizational properties, blocks 1, 2 and 4 are the most formalized, block 3 the least (also block 5 is below the mean: table 28).

Block 1 and 4 are also the most endowed with professional workers, block 2 the least (table 29)

Blocks 2 and 3 are a bit more membership based, those in block 1 distinctively less so (table 30)

Altogether there do not seem to be dramatic differences, yet we can attempt this profile of incumbents of different blocks; Block 1: coloured, formalized, professionalized, less based on membership Block 2: coloured, formalized, less dependent on staff and more based on membership Block 3: white, less formalized, based on membership (matches its closeness to a conventional protest repertoire) Block 4: black, formalized, professionalized, not particularly based on membership Block 5: black, less formalized, not particularly based on membership nor professionalized Tables 28-30 about here (Very provisional) Conclusions Block 1: close to an organizational MoC, hosts organizations with a totally consensual identity and no identification with any movements, and limited involvement in protest events coloured, formalized, professionalized, less based on membership Reluctant to engage in radical protest high interest in “social issues” and corresponding low interest in “eco-management” . altogether, this position seems to illustrate a traditional pressure group logic by professional organizations focusing on basic social deprivation issues and group rights from a NGO/charity rather than SMO perspective Block 2: strong movement dynamic in terms of MoC relational terms is less pronounced at other levels as few opponents are identified, there is only average identification with any movement; average (modest) involvement in both protest and civic events coloured, formalized, less dependent on staff and more based on membership Reluctant to engage in radical protest, support candidates in elections high interest in urban conservation the overall profile of this block suggests that the prevailing model be one of “consensus movement” mobilizing on the protection of the urban environment

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Block 3: a relatively weaker but still significant social movement MoC, with strong identification with environmentalism; average (modest) involvement in protest and civic events white, less formalized, based on membership (matches its closeness to a moderate, conventional protest repertoire) high interest in urban environmental conservation as well as in global justice, and a more limited interest in urban social issues this is the profile of a white progressive middle-class “environmental justice” movement, not overtly oppositional, yet prepared to engage in some mild (by now pretty conventional) protest, but not in radical actions, with some of the traits of NSMs of the past. Block 4: there is a relative proximity to the profile of a social movement MoC, but no involvement in protest events black, formalized, with staff, not particularly based on membership interest in eco-management issues in this block seem to be over-represented organizations with a relatively professional outlook, interested in the careful management of some aspects of the urban environment. It is interesting that they be nonetheless quite strongly connected to each other on multiple levels, which suggests the prevalence of consensus movement logic of coordination. This was not found in the UK, where a social movement MoC went along with protest, and actors not engaged in protest rather tended to be involved in coalitional MoC . Block 5: strong movement MoC, conflict oriented and identification with movements active on inequality; strong involvement in protest events black, less formalized, not particularly professionalized nor based on membership open to radical protest lower attention to urban conservation but also urban social issues this position comes closest to the European view of the protest social movement. Some aspects of its profile seem puzzling, in particular its indifference to social issues such as access for deprived social groups or women’s rights (the lack of dependence on membership might be due to the fact that the informal nature of these organizations results in them not having formal membership rolls). A final comment: the extent of exchanges between organizations in blocks 2 and 3, and their converging interest in the protection of the urban environment, suggest that it might be meaningful to treat them in future analysis as a single relational block. This would strengthen tendencies to homophily in the network (e.g., the E-I index for the whole network would fall from -0.118 to – 0.485). Most important, it would highlight the profile of civil society in Cape Town as consisting of

a) a cluster of interest groups acting as independent organizations on their won specific agendas,

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b) various clusters with quite high degrees of internal cohesiveness and network multiplexity, each close to a social movement mode of coordination, but largely disconnected from each other. This reflects the difficulty, often highlighted by analysts of SA politics, to merge specific issues and struggles into broader collective action platforms (Ballard, Habib, and Valodia 2006; Mottiar and Bond 2012).

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Sciences, edited by Donatella della Porta and Michael Keating, 162–74. Cambridge: Cambridge University Press.

Snow, David, Sarah Soule, and Hanspeter Kriesi. 2004. “Mapping the Terrain.” In The Blackwell Companion to Social Movements, edited by David Snow, Sarah Soule, and Hanspeter Kriesi, 3–16. Oxford: Blackwell.

Somers, Margaret. 1994. “The Narrative Constitution of Identity. A Relational and Network Approach.” Theory and Society 23 (5): 605–49.

Tilly, Charles. 2005. Identities, Boundaries, and Social Ties. Boulder, CO: Paradigm. Vera, Eugenia Roldán, and Thomas Schupp. 2006. “Network Analysis in Comparative Social

Sciences.” Comparative Education 42 (3): 405–29. doi:10.1080/03050060600876723.

15

Source: Diani (2013; 2015)

Table 1. Basic network measures

Cape Town Cape Town Bristol Bristol Glasgow Glasgow

Resource

allocation

ties

Social

bonds only

Resource

allocation

ties

Social

bonds

only

Resource

allocation

ties

Social

bonds

only

Density 0.016 0.008 0.015 0.009 .023 .005

Isolates

9% 25% 7% 22% 10% 50%

Components

(except isolates)

3 9 1 5 1 12

Degree range** 0-21 0-10 0-17 0-16 0-22 0-6

Centralization** 13.85% 6.05% 11.39% 10.63% 15.71% 4.17%

Connectedness

(Krackhardt)

0.77 0.35 0.87 0.42 0.82 0.06

Average distance

(between non-

isolates)

3.70 4.51 4.93 4.82 3.93 1.678

Clustering

coefficient

(Watts)

0.167 0.093 0.145 0.124 0.156 .216

Table 2. Modes of coordination of collective action

Focus of

boundary

definition

Field Organization

Field Social

movement

Coalition

Focus of resource

allocation

Organization Subculture/

Community

Organization

16

Figure 1. Structurally equivalent positions in the Cape Town civic network

Pink nodes: block 2; Light blue nodes: block 3; Black nodes: block 4; White nodes: block 5

17

Table 3. Density of ties across blocks (resource_allocation)

1 2 3 4 5

----- ----- ----- ----- -----

1 0.008 0.000 0.000 0.000 0.000

2 0.000 0.053 0.023 0.011 0.005

3 0.000 0.063 0.040 0.010 0.014

4 0.000 0.006 0.004 0.035 0.008

5 0.000 0.009 0.006 0.004 0.062

Table 4. Number of ties (resource_allocation)

Cape Town

Block 1 Block 2 Block 3 Block 4 Block 5 E-I Index*

Block 1 2 0 0 0 0 -1.000

Block 2 0 18 13 7 3 0.304

Block 3 0 36 35 10 13 0.084

Block 4 0 4 4 39 8 -0.333

Block 5 0 5 5 4 54 -0.431

* See Krachkardt and Stern (1988). The index measures hemophilic tendencies for whole networks,

subgroups, and single nodes. It ranges from -1.000, which indicates total homophily (all ties within

group) to +1.000 (no homophily, all ties outside group).

18

Table 5. Distribution of resource allocation ties across structurally equivalent blocks (ratio of ties

observed/expected) in Cape Town***

Blocks Block 1 Block 2 Block 3 Block 4 Block 5 Block 1 0.53 0.00 0.00 0.00 0.00 Block 2 0.00 3.34 1.45 0.69 0.33 Block 3 0.00 4.01 2.55 0.62 0.92 Block 4 0.00 0.39 0.25 2.21 0.50

Block 5 0.00 0.56 0.35 0.25 3.94

N 16 19 30 34 30 *** p < 0.001

Figure 2. Blockmodel of civic network in Cape Town (size of nodes increases

with internal density)

19

Table 6. Distribution of social bonds across structurally equivalent blocks (ratio of ties

observed/expected) in Cape Town***

Blocks Block 1 Block 2 Block 3 Block 4 Block 5 Block 1 1.07 0.00 0.00 0.00 0.00

Block 2 0.00 4.15 2.04 0.80 0.00

Block 3 0.00 3.62 2.67 0.51 0.57

Block 4 0.00 0.00 0.00 2.64 0.13

Block 5 0.00 0.45 0.29 0.13 4.60

N 16 19 30 34 30 *** P < .001

Table 7. Distribution of solidarity ties across structurally equivalent blocks (ratio of ties

observed/expected) in Cape Town***

Blocks Block 1 Block 2 Block 3 Block 4 Block 5 Block 1 0.38 0.00 0.00 0.00 0.00

Block 2 0.00 3.49 1.61 0.85 0.16

Block 3 0.00 3.54 2.64 0.45 0.82

Block 4 0.00 0.00 0.09 2.37 0.81

Block 5 0.00 0.48 0.51 0.27 4.11

N 16 19 30 34 30 *** P < .001

20

Table 8. Identification with at least one movement

|

dch_movid | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 10 11 13 19 12 | 65

| 62.50 57.89 43.33 55.88 40.00 | 50.39

-----------+-------------------------------------------------------+----------

1 | 6 8 17 15 18 | 64

| 37.50 42.11 56.67 44.12 60.00 | 49.61

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 3.6701 Pr = 0.452

Table 9. Identification with environmental or climate justice movement

envjust_movements|

| Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 14 14 15 27 22 | 92

| 87.50 73.68 50.00 79.41 73.33 | 71.32

-----------+-------------------------------------------------------+----------

1 | 2 5 15 7 8 | 37

| 12.50 26.32 50.00 20.59 26.67 | 28.68

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 9.9137 Pr = 0.042

Table 10. Identification with land claimants or shackdweller movements

land_movements | Block1 Block2 Block3 Block4 Block5 |

Total

-----------+-------------------------------------------------------+----------

0 | 15 18 28 31 20 | 112

| 93.75 94.74 93.33 91.18 66.67 | 86.82

-----------+-------------------------------------------------------+----------

1 | 1 1 2 3 10 | 17

| 6.25 5.26 6.67 8.82 33.33 | 13.18

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 14.0382 Pr = 0.007

21

Table 11. Identification of specific opponents

dch_oppone |

nt | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 16 16 24 31 19 | 106

| 100.00 84.21 80.00 91.18 63.33 | 82.17

-----------+-------------------------------------------------------+----------

1 | 0 3 6 3 11 | 23

| 0.00 15.79 20.00 8.82 36.67 | 17.83

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 12.7705 Pr = 0.012

Table 12. Density Table of ties generated by shared participation in specific

(largely protest) events

1 2 3 4 5

0 1 2 3 4

----- ----- ----- ----- -----

1 0 0.058 0.115 0.138 0.066 0.348

2 1 0.115 0.251 0.240 0.048 0.389

3 2 0.138 0.240 0.269 0.079 0.470

4 3 0.066 0.048 0.079 0.025 0.165

5 4 0.348 0.389 0.470 0.165 0.984

Table 13. REGRESSION COEFFICIENTS of blocks’ density through participation in

specific (largely protest) events

Un-stdized Stdized Proportion Proportion

Independent Coefficient Coefficient Significance As Large As Small

----------- ----------- ----------- ------------ ----------- -----------

Intercept 0.209060 0.000000 0.9980 0.9980 0.0018

Group 1 -0.150727 -0.017009 0.2362 0.7636 0.2362

Group 2 0.042402 0.005694 0.3052 0.3052 0.6946

Group 3 0.059905 0.012619 0.2866 0.2866 0.7132

Group 4 -0.184105 -0.043686 0.0208 0.9790 0.0208

Group 5 0.774848 0.163223 0.0002 0.0002 0.9996

22

Table 14. Density Table of ties generated by shared participation in ritual regular

events

1 2 3 4 5

0 1 2 3 4

----- ----- ----- ----- -----

1 0 0.275 0.316 0.296 0.415 0.296

2 1 0.316 0.211 0.251 0.393 0.247

3 2 0.296 0.251 0.310 0.368 0.247

4 3 0.415 0.393 0.368 0.533 0.340

5 4 0.296 0.247 0.247 0.340 0.205

R-square Adj R-Sqr Probability # of Obs

-------- --------- ----------- -----------

0.004 0.003 0.5882 16512

Table 15. REGRESSION COEFFICIENTS of blocks’ density through participation in ritual

regular events

Un-stdized Stdized Proportion Proportion

Independent Coefficient Coefficient Significance As Large As Small

----------- ----------- ----------- ------------ ----------- -----------

Intercept 0.319559 0.000000 0.7794 0.7794 0.2264

Group 1 -0.044559 -0.004991 0.5234 0.4764 0.5234

Group 2 -0.109033 -0.014533 0.3714 0.6286 0.3714

Group 3 -0.009214 -0.001927 0.5470 0.4530 0.5470

Group 4 0.213418 0.050265 0.0930 0.0930 0.9068

Group 5 -0.114962 -0.024037 0.2658 0.7340 0.2658

Table 16. Propensity to use radical protest (1-100 scale) by block

| Summary of protest_radical_100

block5 | Mean Std. Dev. Freq.

------------+------------------------------------

Block1 | 40.25 19.461072 16

Block2 | 39.684211 14.862528 19

Block3 | 44.333333 18.194985 30

Block4 | 47.147059 12.704407 34

Block5 | 55.366667 18.411921 30

------------+------------------------------------

Total | 46.449612 17.328608 129

Analysis of Variance

Source SS df MS F Prob > F

------------------------------------------------------------------------

Between groups 4020.91918 4 1005.22979 3.62 0.0079

Within groups 34415.0033 124 277.540349

------------------------------------------------------------------------

Total 38435.9225 128 300.280644

23

Table 17. Propensity to support electoral candidates (1-100 scale)

by block

. . oneway elections_100 block5, bonferroni tabulate

| Summary of elections_100

block5 | Mean Std. Dev. Freq.

------------+------------------------------------

Block1 | 50.9375 19.129275 16

Block2 | 59.736842 25.946188 19

Block3 | 46.9 13.988542 30

Block4 | 54.382353 13.323515 34

Block5 | 47.133333 20.562325 30

------------+------------------------------------

Total | 51.317829 18.578375 129

Analysis of Variance

Source SS df MS F Prob > F

------------------------------------------------------------------------

Between groups 2779.1512 4 694.787801 2.08 0.0873

Within groups 41400.8178 124 333.877563

------------------------------------------------------------------------

Total 44179.969 128 345.156008

Table 18. global_justice_dch block4, chi2 column

global_jus | Structurally equivalent blocks

tice_dch | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 15 18 23 32 26 | 114

| 93.75 94.74 76.67 94.12 86.67 | 88.37

-----------+-------------------------------------------------------+----------

1 | 1 1 7 2 4 | 15

| 6.25 5.26 23.33 5.88 13.33 | 11.63

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 6.3767 Pr = 0.173

Table 19. urban_conservation_dch block4, chi2 column

urban_cons |

ervation_d | Structurally equivalent blocks

ch | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 4 2 4 12 17 | 39

| 25.00 10.53 13.33 35.29 56.67 | 30.23

-----------+-------------------------------------------------------+----------

1 | 12 17 26 22 13 | 90

| 75.00 89.47 86.67 64.71 43.33 | 69.77

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 18.1192 Pr = 0.001

24

Table 20. ecomanagement_dch block4, chi2 column

ecomanagem | Structurally equivalent blocks

ent_dch Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 6 12 18 30 18 | 84

| 37.50 63.16 60.00 88.24 60.00 | 65.12

-----------+-------------------------------------------------------+----------

1 | 10 7 12 4 12 | 45

| 62.50 36.84 40.00 11.76 40.00 | 34.88

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 14.0958 Pr = 0.007

Table 21. social_needs_dch block4, chi2 column

social_nee | Structurally equivalent blocks

ds_dch | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 5 6 21 9 18 | 59

| 31.25 31.58 70.00 26.47 60.00 | 45.74

-----------+-------------------------------------------------------+----------

1 | 11 13 9 25 12 | 70

| 68.75 68.42 30.00 73.53 40.00 | 54.26

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 17.5480 Pr = 0.002

Table 22. efficient_urban_democracy_dch block4, chi2 column

efficient_ |

urban_demo | Structurally equivalent blocks

cracy_dch | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 3 2 9 8 8 | 30

| 18.75 10.53 30.00 23.53 26.67 | 23.26

-----------+-------------------------------------------------------+----------

1 | 13 17 21 26 22 | 99

| 81.25 89.47 70.00 76.47 73.33 | 76.74

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 2.8686 Pr = 0.580

25

Table 23. Cosatu block4, chi2 column

| Structurally equivalent blocks

COSATU | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 15 14 21 31 21 | 102

| 93.75 73.68 70.00 91.18 70.00 | 79.07

-----------+-------------------------------------------------------+----------

1 | 1 5 9 3 9 | 27

| 6.25 26.32 30.00 8.82 30.00 | 20.93

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 8.4101 Pr = 0.078

Table 24. Resource allocation between organizations with or without ties to Cosatu

(observed/expected ratio)

Observed/Expected

1 2

0 1

---- ----

1 0 0.68 1.11

2 1 1.18 4.52

Odds ratio = 2.134

Observed chisquare value = 155.231

Significance = 0.000100

Table 25. Social bonds between organizations with or without ties to Cosatu

(observed/expected ratio)

Observed/Expected

1 2

0 1

---- ----

1 0 0.71 0.80

2 1 1.22 5.15

Odds ratio = 2.361

Observed chisquare value = 101.953

Significance = 0.000100

26

Table 26. Profile of areas of location by blocks

| Structurally equivalent blocks

race_area | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

Black | 0 1 1 7 8 | 17

| 0.00 5.26 3.33 20.59 26.67 | 13.18

-----------+-------------------------------------------------------+----------

Coloured | 8 9 5 9 3 | 34

| 50.00 47.37 16.67 26.47 10.00 | 26.36

-----------+-------------------------------------------------------+----------

White | 1 6 13 7 4 | 31

| 6.25 31.58 43.33 20.59 13.33 | 24.03

-----------+-------------------------------------------------------+----------

Non white | 1 2 2 4 3 | 12

| 6.25 10.53 6.67 11.76 10.00 | 9.30

-----------+-------------------------------------------------------+----------

Mixed | 6 1 9 7 12 | 35

| 37.50 5.26 30.00 20.59 40.00 | 27.13

-----------+-------------------------------------------------------+----------

Total | 16 19 30 34 30 | 129

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(16) = 37.3636 Pr = 0.002

Table 27. Ties between organizations located in areas with different racial profiles

(observed/Expected ratio)

1 2 3 4 5

---- ---- ---- ---- ----

Black 1 3.97 0.33 0.12 1.87 0.96

Coloured 2 0.88 2.32 0.60 0.93 0.21

White 3 0.72 0.36 2.25 0.85 0.94

Non-white 4 1.25 0.93 0.34 2.41 1.36

Mixed 5 0.96 0.37 1.00 0.91 1.28

Observed chisquare value = 143.131

Significance = 0.000100

Table 28. formalization block4, bonferroni tabulate

| Summary of L5_Formalization

Block | Mean Std. Dev. Freq.

------------+------------------------------------

1 | 8.6875 3.3410328 16

2 | 8.7368421 2.0232566 19

3 | 6.5666667 3.8923739 30

4 | 9 2.9746403 34

5 | 7.3 4.2357265 30

------------+------------------------------------

Total | 7.9612403 3.5584475 129

Analysis of Variance

Source SS df MS F Prob > F

------------------------------------------------------------------------

Between groups 128.017824 4 32.0044561 2.66 0.0359

Within groups 1492.78838 124 12.0386159

------------------------------------------------------------------------

Total 1620.8062 128 12.6625484

27

Table 29.Professional staff

| Summary of L6_Workers

block4 | Mean Std. Dev. Freq.

------------+------------------------------------

1 | 2.6 1.183216 15

2 | 1.6111111 .84983659 18

3 | 1.84 1.106044 25

4 | 2.3103448 .84951449 29

5 | 2 1.1126973 22

------------+------------------------------------

Total | 2.0642202 1.0477067 109

Analysis of Variance

Source SS df MS F Prob > F

------------------------------------------------------------------------

Between groups 11.1057844 4 2.7764461 2.69 0.0353

Within groups 107.444674 104 1.03312187

------------------------------------------------------------------------

Total 118.550459 108 1.09768943

Table 30. Membership-based organizations by block

|

Membership

based | Block1 Block2 Block3 Block4 Block5 | Total

-----------+-------------------------------------------------------+----------

0 | 9 4 5 12 8 | 38

| 60.00 22.22 20.00 48.00 40.00 | 36.89

-----------+-------------------------------------------------------+----------

1 | 6 14 20 13 12 | 65

| 40.00 77.78 80.00 52.00 60.00 | 63.11

-----------+-------------------------------------------------------+----------

Total | 15 18 25 25 20 | 103

| 100.00 100.00 100.00 100.00 100.00 | 100.00

Pearson chi2(4) = 9.5759 Pr = 0.048