The Diffusion of Scientific Innovations: A Role Typology Catherine Herfeld* 1,2 and Malte Doehne 2 1 Institute of Philosophy, University of Zurich 2 Institute of Sociology, University of Zurich Abstract How do scientific innovations spread within and across scientific communities? In this paper, we propose a general account of the diffusion of scientific innovations. This account acknowledges that novel ideas must be elaborated on and conceptually translated before they can be adopted and applied to field-specific problems. We motivate our account by examining an exemplary case of knowledge diffusion, namely, the early spread of theories of rational decision-making. These theories were grounded in a set of novel mathematical tools and concepts that originated in John von Neumann and Oskar Morgenstern’s Theory of Games and Economic Behavior (1944, 1947) and subsequently spread widely across the social and behavioral sciences. Introducing a network-based diffusion measure, we trace the spread of those tools and concepts into distinct research areas. We furthermore present an analytically tractable typology for classifying publications according to their roles in the diffusion process. The proposed framework allows for a systematic examination of the conditions under which scientific innovations spread within and across both preexisting and newly emerging scientific communities. * Both authors contributed equally; order of authorship was determined by coin-flip. We thank the audiences of the workshops Decisions, Groups, and Networks held in 2014 at the Center for Advanced Studies at Ludwig- Maximilians-University, Munich and of the workshop on Social Simulation held 2015 at the University of Bayreuth. We are particularly grateful to Jeff Biddle, Nicola Giocoli, Stephan Hartmann, Rainer Hegselmann, Paul Humphreys, Chiara Lisciandra, Thomas Sturm, Paul Teller, and two anonymous referees for their feedback on earlier drafts of this paper. This project was funded by the Alexander von Humboldt Foundation. 1 1. Introduction The development and dissemination of new ideas lie at the heart of scientific inquiry, and drawing upon such novel ideas is a constitutive element of scholarly activity. Scientific innovations - be they new theories, models, methods, techniques, or concepts - can diffuse widely and systematically, over long periods of time, and across a broad range of contexts. Such diffusion processes, which can be understood as instances of knowledge transfer, have long been of interest in the history and philosophy of science (e.g., Ash 2006, Howlett/Morgan 2011, Kaiser 2004, Morgan 2014).2 But to date, philosophers and historians of science have rarely drawn on the literature from innovation studies to further analyze processes of knowledge diffusion in science, nor have they made extensive use of quantitative-empirical methods to systematically analyze how particular scientific innovations spread. In this paper, we address this gap in the literature by offering a novel account of the diffusion of knowledge in general and of scientific innovations in particular. We combine concepts and methods from contemporary innovation studies and empirical network analysis with a set of philosophical ideas derived from Thomas Kuhn’s study of the emergence of innovations in science. Innovation scholars have long argued that the diffusion of innovations takes place in networks of actors who engage with the innovation in virtue of the different roles they play in the networks of which they are a part (Coleman et al. 1966, Valente 1995, Rogers 2003). In developing this argument, they have generally taken the innovation itself to remain unchanged as it spreads from one adopter to the next. Although that premise may hold true for innovations in general, it does not hold true, we argue, for scientific innovations. As Kuhn notes, novel ideas in science must be elaborated upon and conceptually translated before scientists can adopt and apply them to field-specific problems (1977 [1959]). The 2 See, e.g., the special issues on interdisciplinarity in Synthese (2013), Vol. 190, and on model transfer in Studies in History and Philosophy of Science (2014), Vol. 48. 2 framework presented in this paper acknowledges this aspect as a precondition for the diffusion of scientific innovations, not only within but across preexisting and newly-forming fields. Our aim is to identify and further characterize the roles played by network actors by combining the insights of both bodies of literature - innovation studies and Kuhn - that have so far been worked out separately. Specifically, we take Kuhn’s idea of translation to be essential for the adoption of scientific innovations. We assume that this translation process is undertaken step-wise by scientists engaging in different ways with the scientific innovation in their written contributions. Those contributions actively promote the diffusion of a novel idea in virtue of different roles they play in the modification of the scientific innovation. In particular, we identify four different roles that scientific contributions (either published and unpublished) can play in extending upon and modifying the scientific innovation and thereby facilitating its spread: innovator, elaborator, translator, and specialist. Beyond the scientific innovation itself, contributions can take the role of elaborating on and experimenting with the innovation to better understand its potentials and limitations for their field. Contributions can then take the role of translating the innovation - often in its elaborated form - for new fields of enquiry. Translation aligns a scientific innovation with previous research traditions. It reveals the innovation’s potential for particular disciplinary problems and establishes the basis for its application in specialist research, the fourth role that contributions can occupy. Against this background, the contribution of this paper is twofold. First, we introduce a network-based diffusion measure that is empirically tractable and that allows researchers to reconstruct the extent to which a given scientific innovation has spread across preexisting and newly forming academic disciplines and fields. Specifically, we use co-citation analysis to identify topical overlaps among scholarly contributions that relate to the scientific innovation and were published in the years following its initial publication. The network of topical overlaps among these publications yields an empirical basis for measuring the spread of the 3 scientific innovation into different domains. Second, we present a rule-based typology for classifying academic contributions in terms of their roles in facilitating the diffusion of the innovation. More specifically, we identify publications whose content was related to, and that were published in the wake of, the initial innovation and we classify these publications according to their role in facilitating stepwise modifications of the scientific innovation. Our classification distinguishes between ‘innovator’-, ‘elaborator’-, ‘translator’-, and ‘specialist’- roles, each of which have distinct parts in promoting the adoption and modification of the scientific innovation. We characterize those roles systematically in terms of salient positions in the co-citation network that represents the diffusion outcome. This typology allows us to formulate general conjectures about the conditions under which scientific innovations diffuse across research fields. We illustrate our approach by applying it to the well-documented case of axiomatic theories of rational decision-making, which originated in a set of highly innovative concepts and mathematical tools introduced by the mathematician John von Neumann and the economist Oskar Morgenstern in the mid-1940s. While these concepts and tools were initially considered to be too challenging mathematically by social scientists, they spread widely throughout the second half of the 20th century, both within and beyond the behavioral and social sciences. In this process, those innovative tools and concepts were extended, elaborated upon, sometimes transformed, and ultimately applied to a variety of problems across a wide range of fields. The application of our framework to the spread of rational choice theories (hereafter: RCTs) showcases its usefulness for addressing questions about knowledge diffusion within and across scientific communities more generally. 2. Thomas Kuhn on Scientific Innovations While many core contributions to the philosophy of science have been concerned with questions of rational theory choice, scientific discovery, and progress in science, this 4 literature has largely sought to develop theories of scientific rationality and the formulation of demarcation criteria for scientific knowledge (Lakatos 1978, Popper 1963, 2002 [1935]). In so doing, this literature has generally neglected how scientists actually come to accept and adopt a scientific innovation, and has tended to focus on logical and epistemological or, more broadly, rational features of theory choice and scientific change.3 However, since Thomas Kuhn (1962), we know that non-rational factors can lead to the emergence of new paradigms and influence theory choice. While Kuhn is most well-known for his account of how science proceeds by way of alternations between normal science and scientific revolutions (Kuhn 1962), he offered an important insight on this matter in a lecture entitled ‘The Essential Tension: Tradition and Innovation in Scientific Research’ (Kuhn 1977