This article situates current debates about transdisciplinarity within the deeper history of academic disciplinarity, in its difference from the notions of inter- and multi-disciplinarity. It offers a brief typology and history of established conceptions of transdisciplinarity within science and technology studies. It then goes on to raise the question of the conceptual structure of transdisciplinary generality in the humanities, with respect to the incorporation of the 19th- and 20th-century German and French philosophical traditions into the anglophone humanities, under the name (...) of ‘theory’. It identifies two distinct – dialectical and anti-dialectical, or dialectical and transversal – transdisciplinary trajectories. It locates the various contributions to the special issue of which it is the introduction within this conceptual field, drawing attention to the distinct contribution of the French debates about structuralism and its aftermath – those by Serres, Foucault, Derrida, Guattari and Latour, in particular. It concludes with an appendix on Foucault’s place within current debates about disciplinarity and academic disciplines. (shrink)

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)

Recent years have seen an explosion of interest in the field of ‘art-science’ collaborations for their perceived capacity to develop new cultural understandings of technology and science. In this article, and through an engagement with the philosophy of Gilbert Simondon, I argue that if art-science represents an important site for the formation of an alternate technical culture today, then it is because of the new technical mentalities that such practices might cultivate. Here, creating a new technical mentality is more than (...) just a representational concern with enhancing ‘public awareness’ of technology, instead referring to more material transformations in our embodied capacities for perceiving and affectively engaging with technologies. I flesh this potential out through an encounter with work of Art Orienté objet, whose art-science collaborations challenge the anthropocentric and utilitarian mentalities of contemporary bioscience through explorations of the transindividual conditions of human embodiment and its material immersion within nonhuman ecologies. (shrink)

Despite all the attention to Big Data and the claims that it represents a “paradigm shift” in science, we lack understanding about what are the qualities of Big Data that may contribute to this revolutionary impact. In this paper, we look beyond the quantitative aspects of Big Data and examine it from a sociotechnical perspective. We argue that a key factor that distinguishes “Big Data” from “lots of data” lies in changes to the traditional, well-established “control zones” that facilitated clear (...) provenance of scientific data, thereby ensuring data integrity and providing the foundation for credible science. The breakdown of these control zones is a consequence of the manner in which our network technology and culture enable and encourage open, anonymous sharing of information, participation regardless of expertise, and collaboration across geographic, disciplinary, and institutional barriers. We are left with the conundrum—how to reap the benefits of Big Data while re-creating a trust fabric and an accountable chain of responsibility that make credible science possible. (shrink)