Dominant social sciences approaches to complexity suggest that awareness of complexity in late-modern society comes from various recent scientific insights. By examining today’s plant and human genomics sciences, I question this from both ends: first suggesting that typical public culture was already aware of particular salient forms of complexity, such as limits to predictive knowledge ; second, showing how up-to-date genomics science expresses both complexity and its opposites, predictive determinism and reductionism, as coexistent representations of nature and scientific knowledge. I (...) suggest we can understand this self-authored epistemic confusion in modern science by avoiding ‘the usual suspects’ – fading simpler discourses left over from previous scientific times; media oversimplifications; or the need to ‘simplify’ to essentials, for ignorant publics – and looking instead at the silent imaginations of extra-scientific reference groups reflected and projectively performed in scientific discourses-practices themselves. Thus contradictions of complex scientific understandings are systematically created by science’s own embodiment of epistemic commitments influenced by commercial cultures, and by imagined publics who are important new constructed objects of institutional scientific concerns – over authority and trust. New dimensions of complexity thus come alive through paying attention to neglected tacit dimensions of science–society interrelations. (shrink)

This article contributes to the revision of the concept of system in social theory using complexity theory. The old concept of social system is widely discredited; a new concept of social system can more adequately constitute an explanatory framework. Complexity theory offers the toolkit needed for this paradigm shift in social theory. The route taken is not via Luhmann, but rather the insights of complexity theorists in the sciences are applied to the tradition of social theory inspired by Marx, Weber, (...) and Simmel. The article contributes to the theorization of intersectionality in social theory as well as to the philosophy of social science. It addresses the challenge of theorizing the intersection of multiple complex social inequalities, exploring the various alternative approaches, before rethinking the concept of social system. It investigates and applies, for the first time, the implications of complexity theory for the analysis of multiple intersecting social inequalities. Key Words: complexity theory • inequality • intersectionality • social theory. (shrink)

‘Complexity theory’ seems to provide some metaphors, concepts and theories essential for examining the intractable disorderliness of the contemporary world. Relations across that world are complex, rich and non-linear, involving multiple negative and, more significantly, positive feedback loops. This article shows how globalization should be conceptualized as a series of adapting and co-evolving global systems, each characterized by unpredictability, irreversibility and co-evolution. Such systems lack finalized ‘equilibrium’ or ‘order’; and the many pools of order heighten overall disorder. They do not (...) exhibit and sustain unchanging structural stability. Complexity elaborates how there is order and disorder within these various global systems. The global order is a complex world, unpredictable and irreversible, disorderly but not anarchic. (shrink)

The proliferation of digital data has been the impetus for the emergence of a new discipline for the study of social life: ‘computational social science’. Much research in this field is founded on the premise that society is a complex system with emergent structures that can be modeled or reconstructed through digital data. This paper suggests that computational social science serves practical and legitimizing functions for digital capitalism in much the same way that neoclassical economics does for neoliberalism. In recognition (...) of this homology, this paper develops a critique of the complexity perspective of computational social science and argues for a heterodox computational social science founded on the meta-theory of critical realism that is critical, methodological pluralist, interpretative and explanative. This implies diverting computational social science’ computational methods and digital data so as to not be aimed at identifying invariant laws of social life, or optimizing state and corporate practices, but to instead be used as part of broader research strategies to identify contingent patterns, develop conjunctural explanations, and propose qualitatively different ways of organizing social life. (shrink)

In this article, the author argues that complexity theories have limited use in the study of society, and that social processes are too complex and particular to be rigorously modeled in complexity terms. Theories of social complexity are shown to be inadequately developed, and typical weaknesses in the literature on social complexity are discussed. Two stronger analyses, of Luhmann and of Harvey and Reed, are also critically considered. New considerations regarding social complexity are advanced, on the lines that simplicity, complexity (...) that can be modeled, and incondensible complexity permeate society simultaneously. The difficulty of establishing complexity models for processes involving ongoing interpretation is discussed. It is argued that the notions of system and environment need recasting in social studies. Existing social studies and literature, it is argued, reflect a polymorphous, contextual, contingent, labyrinthine, dramatic and political face to social complexity. Students of social complexity must be literate in such studies. (shrink)

This article contributes to understanding the effect of complexity theory on the social sciences. It analyses the relationships between complex processes of self-organization and the environment or ecology in which these dynamics take place. Two factors are prioritized: the role of information in the formation of complex structure and the development of ‘landscapes’ or topologies of possibility. The authors argue for an ontology that founds both material and informational structures, and for a radical continuity between the general thermodynamics of emergent (...) complex orders, cognitive theory and the complex structures of human thought and culture. (shrink)

This Special Issue of Journal of Critical Realism (JCR) is dedicated to the 2022 International Association for Critical Realism (IACR) Conference, which was hosted by the International Institute of...

In this review essay I offer a critical assessment of the work of David Byrne, an applied social scientist who is one of the leading advocates of the use of complexity theory in the social sciences and who has drawn on the principles of critical realism in developing an ontological position of ‘complex realism’. The key arguments of his latest book, Applying Social Science: The Role of Social Research in Politics, Policy and Practice constitute the frame of the review; however, (...) since these overlap with those of his previous books, Interpreting Quantitative Data and Complexity Theory and the Social Sciences, I consider all three books together. I identify aspects of Byrne’s ontological position that are in tune with the principles of original and dialectical critical realism and aspects that are not. I argue that these inconsistencies, which Byrne must resolve if he is to take his understanding of complexity further, stem from the residual influence of various forms of irrealism in his thinking. (shrink)

Realist synthesis is often offered as a useful strategy to understand intervention complexity. Its unique selling point is its basis in a critical realist philosophy of science. However, we argue t...

Many methods are used in research on complexity. One of these is qualitative comparative analysis. Although many authors allude to the relationships between complexity and QCA, these links are rarely made explicit. We propose that one way of doing so is by using critical realism as a meta-framework. This article discusses the viability of this approach by examining the extent to which QCA is a complexity-informed method. This question is answered in three steps. First, we discuss the nature of complexity (...) and its epistemological implications. Second, we focus on Bhaskar’s perspective on critical realism and show how it can be used as a framework for understanding social complexity. Third, we examine the ontological and epistemological assumptions underlying QCA and synthesize these with our critical realist approach to complexity. We argue that complex reality is non-decomposable, contingent, non-compressible and time-asymmetric. We conclude that, although QCA is inevitably reductive and partial, its core premises are built upon the notions of contingency and time-asymmetry. Therefore, it is not only a powerful method for doing complexity-informed research, but is also a complexity-informed method by itself. (shrink)

How can we make complexity work as part of a programme of engaged social science? This article attempts to answer that question by arguing that one way to do this is through a reconstruction of a central tool of a distinctively social science – the comparative method – understood as a procedure for elucidating the complex and multiple systems of causation that generate particular trajectories towards a desired future from the multiple sets of available futures. The article distinguishes between ‘simplistic (...) complexity’ and ‘complex complexity’. ‘Simplistic complexity’ seeks to explain emergence in complex systems as the product of simple rules and defines complex science as the process of establishing such rules. It can and does serve as the basis of technocratic social engineering in the interest of the powerful. In contrast ‘complex complexity’ recognizes the significance of social structure and willed social agency and does not reduce emergence to the mere working out of a restricted set of rules. Research programmes informed by this second approach must necessarily engage with social actors in context – they must be dialogical. This opens up the possibility of ‘complex complexity’ as a frame of reference for action-research directed towards the transformation of complex social systems. Comparative methods, and in particular Ragin’s qualitative comparative analysis approach, when deployed as part of such a programme, can provide meaningful information about the range of possible futures and the different configurations of causes which might generate particular desired social outcomes. (shrink)