The five studies of this special section investigate the role of models and similar representational tools in interdisciplinarity. These studies were all written by philosophers of science, who focused on interdisciplinary episodes between disciplines and sub-disciplines ranging from physics, chemistry and biology to the computational sciences, sociology and economics. The reasons we present these divergent studies in a collective form are three. First, we want to establish model-exchange as a kind of interdisciplinary event. The five case studies, which are summarized (...) in Section 2 below, show the relevance of this kind. Arguing for the relative unity of these cases will, we hope, re-orient the current debate over interdisciplinarity so as to reflect more appropriately the importance of this kind. We discuss our view of the current state of the debate in Section 3. The evidence from these cases also helps us to develop a taxonomy of interdisciplinary model exchanges in Section 4da taxonomy, we would like to add, that might be useful for the discussion of interdisciplinary exchanges beyond the context of models and their transfer. The second reason for presenting these studies together is that they provide an important source of evidence for the philosophy of science. Over the last three decades, philosophy of science has increasingly differentiated into philosophies of various disciplines. This differentiation in our view has greatly increased our understanding of the scientific practices of the respective disciplines, including the epistemological and methodological standards and conventions on which these practices are based and by which they are evaluated. But it has also made it harder to compare these practices and standards across disciplines. The studies we present here are case studies of interdisciplinary exchange: they focus on the transfer, collaborative construction or parallel use of models and similar representational tools. They therefore provide a unique opportunity to investigate various disciplinary treatments of the same or at least similar representational tools. This allows the identification and comparison of different disciplinary practices and their underlying conventions as well as of the respective normative standards of their evaluation. By tracing the paths along which models travel between disciplines and research fields we can observe to which extent discipline-external practices associated with an adopted tool are retained or replaced by disciplineinternal practices. This generates invaluable information about both disciplinarity and interdisciplinarity. We develop this argument further in Section 5. The third reason for presenting these studies in collective form is that their philosophical analysis also has important normative implications for the notion of interdisciplinarity itself. Too often in the current (non-philosophical) discourse is interdisciplinarity cast as an exclusively integrative project: interdisciplinary exchange is often claimed to be successful only if the involved disciplines become mutually more integrated as a consequence of this process. In contrast to this, many of the cases presented here show that interdisciplinary exchange can be scientifically highly successful, even if at the end of the exchange disciplinary borders remain fully intact. Indeed, borders can be fruitfully crossed without any integration across these borders. Such considerations of divergence in scientific practices and tools offer arguments against a naïve plea for unitarian or non-pluralist versions of interdisciplinarity. Disciplinary divergences may have their justifications, and attempting exchanges that require the reduction of these divergences may consequently not be justified. We pursue this argument further in Section 6. (shrink)

In a recent article in this Journal, Fumagalli argues that economists are provisionally justified in resisting prominent calls to integrate neural variables into economic models of choice. In other articles, various authors engage with Fumagalli’s argument and try to substantiate three often-made claims concerning neuroeconomic modelling. First, the benefits derivable from neurally informing some economic models of choice do not involve significant tractability costs. Second, neuroeconomic modelling is best understood within Marr’s three-level of analysis framework for information-processing systems. And third, (...) neural findings enable choice modellers to confirm the causal relevance of variables posited by competing economic models, identify causally relevant variables overlooked by existing models, and explain observed behavioural variability better than standard economic models. In this paper, I critically examine these three claims and respond to the related criticisms of Fumagalli’s argument. Moreover, I qualify and extend Fumagalli’s account of how trade-offs between distinct modelling desiderata hamper neuroeconomists’ attempts to improve economic models of choice. I then draw on influential neuroeconomic studies to argue that even the putatively best available neural findings fail to substantiate current calls for a neural enrichment of economic models. (shrink)

This is the second of two articles in which I reflect on “generalized Darwinism” as currently discussed in evolutionary economics. In the companion article (Callebaut, Biol Theory 6. doi: 10.1007/s13752-013-0086-2, 2011, this issue) I approached evolutionary economics from the naturalistic perspectives of evolutionary epistemology and the philosophy of biology, contrasted evolutionary economists’ cautious generalizations of Darwinism with “imperialistic” proposals to unify the behavioral sciences, and discussed the continued resistance to biological ideas in the social sciences. Here I assess Generalized Darwinism (...) as propounded by Geoffrey Hodgson, Thorbjørn Knudsen, and others, concentrating on the roles of theory and model building in science (and the roles of analogy and metaphor therein), generative replication, and the relation between selection and self-organization. I then point to advances in current biology that promise to be more fruitful as sources of inspiration for evolutionary economics than the project to generalize Darwinism in its current, “hardened Modern Synthesis” form; and I draw some conclusions. (shrink)