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«Andrés Gregor Zelman The University of Amsterdam 2002 ii Mediated Communication and the Evolving Science System: Mapping the Network Architecture of ...»

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For Callon (1987), the ANT operates on the principle of two mechanisms:

simplification and juxtaposition. Simplification implies the reduction of all factors into relatable elements, and juxtaposition (like Saussure’s difference) implies a network of associations. He argues that it is possible to outline the network by using sequences of points and lines, through which we view each point as a network that in turn is a series of points held in place by their relationships. The point is not, as in sociology, to emphasize a particular type of element, rather it is to discover the pattern of forces as these are revealed in relationships between different types of elements. The ANT, 8 Importantly, the print and electronic communications of the SOEIS project are intended for different audiences; respectively: the European policy environment, and SOEIS members. ANT assists us in not only bridging this gap, but by drawing connections between the other communicative dimensions of the research project.

9 For an introduction into the central tenets of SCOT, see: Pinch & Bijker (1987).

35 therefore, is a method that seeks to deal with the social, economic, technical, natural and scientific aspects of technological development by using the same vocabulary.

Importantly, Actor Network approaches are often used to describe network features of text; as Callon, Courtial & Laville (1986) argue, word and co-word analyses can be framed conceptually with actor-network approaches. They state that “by having recourse to the quantitative, it thus becomes possible to map the degree to which the efforts of actors to build their worlds are met with success. The maps present a pattern of translations that arises from the interaction between the efforts of many actors.”(1986: 225) The suggestion here is that it is not the content that ‘makes’ the relationship but rather the nature of the interrelationships themselves that determine the outcome of the communication. ANT thereby provides this study with a metaphor to aid the weaving together of the four SOEIS communicative domains, and in understanding the network architectures evident therein. ANT enables us to conceptualize the complex of networked relationships implied with research projects – the network concept provides a means of understanding the role of media in integrating people via texts and emails, thereby forming networks and enabling continued patterns of relation.

Latour Latour’s principle of symmetry provides us with another rich example of an Actor Network Theory. He argues that: “networks of associations replace both the content of science and society. The growth of networks through translations replaces differences of scale between micro- meso-, and macrolevels.” (1992: 275) The notion of translation is important in conceptualizing networks as an emergent phenomenon – they are always in the process of being constructed, they are always in transition, always becoming. From a macro perspective, Latour’s actor-network description aims to harness that aspect of pan semiotic communication that exists above and beyond individual action (Hagendijk, 1999). In a local sense, networks of words and symbols are given factors in social interaction. From a mapping perspective it is the similarities and differences between these networks that are of interest. Latour’s position that actors contribute different things in different contexts and at different times is relevant to our analysis. Accordingly, the SOEIS communications are mapped as networks of translations that are expected to be similar due to the commonality of the discourse exchanged through each medium, and to differ given the biases of each medium employed for the communication.

Wise Wise argues that the ANT perspective “stresses both the contingency of networks (i.e., they are not determined, permanent or universal) and their emergent qualities” and that the approach focuses on “real-time analyses, seeing how the network unfolds and transforms from the perspective of one of its actors.” (1997:32) The analysis of the SOEIS communications is performed in a similar fashion, but importantly, the perspective taken here is that the unfolding or emergence of the network is seen through the lens of the medium as an integral actor in these processes of communication. Wise criticizes the ANT theorists for an inability to deconstruct the ways that capitalism and imperialism continue to dominate, and suggests that we are given a methodology for tracing the multiplicity of actors that constitute networks, but no sense of what to do with them. That perspective motivates this analysis to engage 36 ANT using the strategies they employ to map social processes, but to do so in a way that focuses on the nature of inter-human communication as necessarily mediated.

The overview of Saussure’s Structural Linguistics revealed that the network was perceived as a closed set of relations in which each element has meaning with respect to how they differ. By extension, the ANT notion of juxtaposition suggests a similar interpretation – elements only ‘mean’ in terms of how they differ from (or arguably, relate to) others as processes of translation. Recall that the overview of Lévi-Strauss’ Structural Anthropology identified a qualitatively different network metaphor – many networks that can be compared for their shared, inherent structural features. In this sense the ANT resounds more with Strauss’ structuralism. But importantly the ANT views the network as contingent and as emergent, not static nor transcendental. Thus, the linguistic and anthropological approaches sought to uncover what they considered an unconscious structure of difference (which by definition can never be fully observed). The network metaphor conceived within ANT is neither transcendent nor non-observable, it is concretized and observable. By contrast, the network metaphor employed by Systems Theory, as described below, suggests a way of theorizing both observable and non-observable networks.

Self-Organization Theory

Like Medium Theory, Systems Theory is best understood as having two distinct generations. First order Systems Theory can be traced back to the work of von Bertalanffy (1968), Wiener (1948, 1954), Shannon (1948), and Parsons (1951, 1971).

While each approach is unique, they share a static notion of network that is comparable to the Linguistic and Anthropological use of the metaphor. The shift from first to second-order is best characterized in terms of differing notions of the network metaphor. In the case of the latter, the network is more similar to the ANT notion of contingent and emergent networks. Second order Systems Theory introduces a dynamic network metaphor. Theoretically it is based on Luhmann’s reworking of Parsons’ Social system (1982, 1986, 1990) using the evolutionary metaphor from the theory of autopoiesis (Maturana, 1980; Maturana & Varela, 1987). Luhmann conceptualizes society as composed of interactions, or communications, not individual actions, roles, or persons as Parsonian first-order Systems Theory describes.

Luhmann Luhmann (1982) introduces Maturana and Varela’s concept of autopoiesis as a way to conceptualize the self-organizing properties of mediated communication. This method of black-boxing the social (the micro-action level of individuals) permits a higherorder analysis of the distribution of mediated communications. Luhmann’s concern is to shift focus from the number of agents communicating to the complexity of communications among agents. He argues that the “system of society consists of communications. There are no other elements, no further substance but communications. The {sic} society is not built out of human bodies and minds. It is simply a network of communication.” (1990:100) The theory suggests that society be understood as self-organizing. Systems are perceived as closed to their environment 37 and via self-reflection they change their operations for future rounds of communication.

Thus, for Self-Organization Theory individual actors are not of key concern – what we examine are the networks within which we operate. Luhmann (1990) describes social interaction as a recursive operation that systemically (re)organizes society, and in this way he essentially argues that one should not specify the people involved in a communications network, but rather the communications involved in systemic relations. This perspective is relevant for this analysis because it is the role of media, not people, that is understood here to be central to social interaction and more specifically, to the operation of the SOEIS project communications.

Luhmann’s conceptualization is unique because it contends with both observable and non-observable phenomena. Collectively we act upon the world and in this sense there is an observable output to our actions, but for Luhmann the key is how these interactions operate recursively and therefore systemically. From a macro perspective individual actions or communications collectively make up the social world, and this is perceived as the very means whereby the social system recursively produces and reproduces itself. This reflexivity (as opposed to the agency described by Actor Network and Structurational approaches) is precisely what differentiates First from Second-Order Systems Theory. Internally, it is argued, the social system introduces new system / environment distinctions through the functional differentiation of its subsystems, which in turn permits an enhanced capacity for societal evolution through internal simplification. This can be likened to the ANT notion of simplification.

However, the network implied with the recursive and virtual nature of Luhmann’s evolutionary systems differs radically from the conceptions of relatively flat networks outlined above.

Luhmann argues that the system of society consists of a network of communication – all is reducible to communications. Thus, what is revealed by Luhmann’s project is a virtual system like Saussure’s transcendental realm of differentiation. Both suggest a virtual network of associations operating beyond any individual action. The primary difference being that the Saussurian, Lévi-Straussian and Derridean networks are based upon closed or fixed networks, whereas the dynamic networks described by Giddens, Actor Network theorists, and Luhmann are participatory and based on open and recursive networks.

Leydesdorff For Leydesdorff (1996, 1997), the concern is to operationalize these virtual systems into transitional models – he engages Luhmann’s theory by analyzing communication networks between scientists as self-organizing. The theory is operationalized by plotting actors and communications as row and column vectors in a matrix. The matrix is conceived as a three dimensional model in which time (dimension three) is just another dimension of the complex system. He argues that if one “represents communicating actors as the row vectors of a matrix, communication finds its origin in the co-occurrence of these vectors along the column dimension. (1996:4) Thus, “each action with reference to an actor can be considered as a communication with reference to the network. While the uncertainty is relational in terms of the actors involved, it has a position in the network. In other words, the network is spanned in 38 terms of relations, but it develops a specific architecture in which each action has also a position.” (1996:2) Print and electronic media can be understood in this context as two independent but overlapping communication technologies; the theory of self-organization will be employed to describe how these two media are mutually implicated as a single operation of the system of communication. Collectively these perspectives provide useful tools for conceptualizing the dimensions of the SOEIS project as a complex network of communications which have evolved over time via self-reference.

Generally speaking, Self-Organization Theory is useful to our project as the phenomenon of project communications can be seen as operations through which knowledge is recursively produced via collective interaction. Like Medium Theory, the Structural Tradition, and ANT, Self-Organization Theory helps to frame the network dimensions between mediated communications (i.e.: words, publications, threads) as our key units of analysis. More importantly, Self Organization theory provides a means of conceptualizing the largely unobservable (by definition) system of communication by observing patterns in the observable phenomena.

Self-Organization Theory is used to contextualize and describe the systemic properties of SOEIS print and electronic communication. The analytical procedure is informed by theoretical consideration, in the sense that individual actions or communications are understood to collectively behave in a systemic fashion, depending upon one’s frame of reference. The statistical technique has been used to determine critical transitions in scientific communication (Leydesdorff, 1995), and in the evolutionary performance of selected transportation technologies (Frenken & Leydesdorff, 2000). Here we aim to identify systemic behaviour by observing the print and electronic datasets as a time series to determine if there have been significant shifts in the collective word use, journal publication behaviour, and mailing list dynamics of the SOEIS participants. With Self-Organization Theory we lift the notion of information network from local actors and actions to a next-order perspective that treats word and co-word patterns, journal publication, and thread size and frequency as fingerprints of the recursive operation of the SOEIS communications system.

The Theoretic Triad

Each of the theoretical perspectives reviewed here provide a window upon the dynamics of mediated communication. Each approach emphasizes a networked dimension; using this commonality they are best understood collectively as a cohesive framework on which the following analyses and interpretations were based. Clearly each helps frame the context of the analysis of the four dimensions of the SOEIS research project under analysis, and each lends a perspective that permits a more detailed description of the distinction between Mode I and Mode II knowledge production. Together, these theoretical bodies frame this analysis in the sense that the node through which they intersect is the notion of mediated communication: the observation of SOEIS Communications achieves a different meaning with each perspective.

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