Social networks and inequality

Social capital has the ability to enhance as well as constrain the capabilities of the individuals and/or the group. Serageldin (1996, p. 196) describes social capi-tal as ‘the glue that holds societies together’. If there is little civic engagement, commonly shared norms, trust or reciprocity then society can disintegrate; vio-lence increases and structural change and economic development is hampered (Putnam 2000). However, participation or inclusion in networks may not always be good for the freedom and human development of the individuals within and/

or outside of the network, for instance in the case of a drug trade network. By their very definition, social networks also tend to introduce inequalities between people and groups, because different network contacts leads to different levels of power and social capital. Sociological research shows that networks differentiate between groups and lead to different sets of preferences, choices and capabili-ties (e.g. Bourdieu 1983). Research on social networks illustrates that a different number of contacts and positions within a network structure have a strong influence on the role, prestige and power of the corresponding agents, be they individuals, groups, regions or countries. Indeed, networks usually have hierarchies and there may be an unequal number of connections of nodes in a network.

One well-known example of structural dependence and inequality reproduc-tion is that of centre-periphery structures in the world economy (Singer 1949;

Prebisch 1949; Wallerstein 1974). Centre-periphery structures can lead to dete-riorating terms of trade for the countries that merely export primary resources to the dynamic and economically diversified centre of the global economy. Their dependence on the demand from the centre limits their bargaining power in price negotiations; thus their position within a network can lead to dependence and inequality. It is important to note, however, that any social system (be it large countries and the global economy or a small families and friends circle), require some type of social organization, which almost by definition leads to different social roles and the existence of hierarchies at least within different activities. In the words of Georg Simmel (1908, cited in Blau 1964, p. 168):

Any social order requires a hierarchy of superordinations and subordinations, even if only for technical reasons. Therefore, equality in the sense of justice can only be the exact correspondence of personal qualification with position in this hierarchy. Yet, this harmonious correspondence is in principle impos-sible for the very simple reason that there always are more persons qualified for superior positions than there are superior positions.

In other words, complete equality in societies is virtually impossible, or at least impracticable, because the bigger a society becomes, the more inequality in the network position and power emerges. Four friends may have virtually equal rights and power within their small circle. A hundred and fifty persons may form a fairly equalitarian society, but the larger the society gets the more organizations are nec-essary and the more hierarchies emerge, in which different people have different positions and power over the network. These hierarchies and power inequalities introduce competition, as typically more people may be willing and/or are capable of fulfilling powerful roles in the network management. In addition, the hetero-geneity of capabilities, traits, luck, roles and the inheritance of individuals lead to inequality in the embeddedness of individuals in social networks. Conversely, the embeddedness in social networks affects the opportunities, choices and capabil-ity formation of the individuals. Complete network equalcapabil-ity seems to be virtually impossible in large networks. Essentially it would mean that every single person would need to know everybody else or have exactly the same access to informa-tion and power over their social network. This is a rather unrealistic scenario, considering the millions of people with different interests, desires, skills and social contacts.

This tendency towards an unequal distribution of power in large networks requires an ethical debate about distributional justice and the equality of initial opportunities resulting in political and societal actions that enable the agency of all citizens and prevents socially unacceptable injustice. While this is beyond the scope of this book, the structural tendency for inequality and the hierarchies within large networks should be taken into account. Research on large natural, social and physical networks (such as the World Wide Web, power grids cita-tion networks and innovacita-tion networks) show a power law distribucita-tion in the number of contacts of the elements (nodes) in the network (Albert and Barabasi 2002). This means that most nodes (e.g. researcher, web pages, Facebook mem-bers) have relatively few links (e.g. social contacts, citations) whereas some nodes (called hubs) have many contacts. This of course leads to inequality in access to information and power over information flow and prestige. Empirical research shows that many large networks are scale free (Barabasi and Albert 1999; Albert and Barabasi 2002), meaning that there is no typical number of linkages and that some hubs connect the network and make a fast transmission within the network possible. Scale-free networks go on to show a low probability of systemic failure and a faster information flow than random networks. If failures occur at random, the likelihood that the network disaggregates is very low. Even if a small number of hubs fail, the system remains connected. The simultanous failure of all hubs in a large scale free network as a result of random causes, errors, or disasters is very low. However, targeted simultaneous attacks on all key hubs could easily disrupt the entire network breaks it into pieces. The robustness against random failure and fast information diffusion seem to be a main reason why many physical network structures in the real world (including both physical and social networks) show a scale-free attribute (Albert and Barabasi 2002).

Researchers from physics have explained the emergence of such scale free characteristics and power law distributions in large networks by preferential attachment and ‘success-breeds-success’ mechanisms (de Solla Price 1965;

Merton 1968; Barabasi and Albert 1999). Nodes with many links have a higher probability of getting more links. Or conversely, the probability of new nodes connecting with nodes that are already highly connected is higher than that of connecting with nodes that have few links. This is also happening in societies, where network effects tend to create stars, be it in science, life style, politics or any other field of human life. In most cases the effect is partly associated with the intrinsic quality of the nodes (e.g. skills, sociability etc.); however, to a significant extent it is a network effect. For example, film stars, internet companies, local leaders or scientists not only become successful due to the quality of their work, but also because of the fact that people know them. Then the diversity of network contacts enables these popular nodes to access more resources, learn and upgrade their capabilities. This leads to ‘the rich-get-richer’ mechanisms and endogenous inequality reproduction.

Thus network structures and dynamics, such as preferential attachment, have a strong influence on the evolution and distribution of choices, opportunities and capability upgrading within a system and between individuals. The intrin-sic reproduction of inequality through network dynamics has both positive and negative implications. The same negative implications of varying power and capabilities may be partly positive in that they create a fast information flow as well as introducing competition and fighting for position/social struggle, which leads to innovation and socioeconomic change, a crucial driver of capability expansion. In social market economies the constant competitive struggles (e.g.

between unions and employees, capitalists and philanthropists), as well as the natural force of people cooperating, is an essential driver of social innovation and economic, technological and societal progress. This constant interplay between competition and cooperation leads to higher economic specialization as well as variety of choices and opportunities, higher average incomes and better educa-tion and health. The problem is how these outcomes of progress are distributed between different people and groups. The initial position of individuals in a net-work determines their capabilities to contribute, adapt and gain from the outcome of the creative destruction processes of the socioeconomic environment they are living in. From a human, ethical and also economic perspective, however, a high level of inequality can have negative effects on long-run economic and human development, leading to risk-aversion, a lack of aggregated demand and demand multipliers, corruption and nepotism, under- and over-representation of the inter-ests of particular groups, a lack of trust, social instability and crime. For reasons of both justice and human development, but also for better system functioning and knowledge flow, policy makers need to make great efforts to connect people to the networks of information and power. Access to ICT and the establishment of democratic structures, among other things, are essential policy measures that can impede social exclusion, reduce harmful levels of inequality and foster societal progress and human development.