The ArgumentWhat kind of objects are computer programs used for simulation purposes in scientific settings? The current investigation treats a special case. It focuses on “event generators,” the program packages that particle physicists construct and use to simulate mechanisms of particle production. The paper is an attempt to bring the multiplex and unfolding character of such knowledge objects to the fore: Multiple meanings and functions are embodied in the object and can be drawn out selectively according to the requirements of (...) a work setting. The object's conceptual complexity governs its application in some contexts, while the object is considered a mere “black box,” transparent and ready-to-hand, in others. These two poles span a full spectrum of object aspects, functions, and conceptions. Event generators are ideas turned into software, testing grounds for models, just a tool to study the performance of a detector, etc. The object's multiplex nature is submitted to negotiation among different actors. (shrink)

Interdisciplinarity is one of the most prominent ideas driving science and research policy today.1 It is applied widely as a conception of what particularly creative and socially relevant research processes should consist of, whether in the natural sciences, the social sciences, the humanities, or elsewhere. Its advocates, many of whom are located in current science and research administration themselves, are using ideas of interdisciplinarity to reshape university organization and research funding. For the last 40 years, researchers studying interdisciplinarity have built (...) up a substantial body of literature constructing various visions of what it should be and how to taxonomize the different forms it can... (shrink)

Studies on ‘Big Science’ have shifted our perspective from the complexity of scientific objects and their representations to the complexity of sociotechnical arrangements. However, how scientists in large-scale research attend to this complexity to facilitate and afford knowledge production has rarely been considered to date. In this article, we locate organizational complexity on the level of organizing practices that follow multiple and divergent logics. We identify three strategies of managing organizational complexity, drawing on existing literature on large-scale research as well (...) as own empirical research. The three strategies are: segmenting research infrastructure, introducing elements of bureaucratic governance, and implementing standards and standardization. We illustrate these strategies with examples from our empirical case study on experimental particle physics research at CERN’s Large Hadron Collider. While the strategies we identified help to cope with the complexity of some organizational tasks by dividing, ordering, or mediating between divergent organizational logics, we find that organizational complexity overall is not reduced but rather displaced. We argue that dealing with complexity is a dynamic and ongoing process, which inevitably generates novel organizational complexity. (shrink)

With reference to the recent science studies debate on the nature of science-industry relationship, this article focuses on a novel organizational form: the technological platform. Considering the field of micro- and nanotechnology in Switzerland, it investigates how technological platforms participate in framing science-industry activities. On the basis of a comparative analysis of three technological platforms, it shows that the platforms relate distinctly to academic and to industrial users. It distinguishes three pairs of user models, one model in each pair pertaining (...) to how platforms act toward and conceive of academic users, the other model regarding users from industry. The article then discusses how technological platforms reconfigure the science-economy divide. While the observed platforms provide new institutional contact and interaction between academia and industry, new research collaboration does not necessarily materialize in practice. In this respect, science-industry mediation by way of technological platforms does not make science-industry boundaries more porous. Instead, the declared openness of public research with respect to industry, in the case of technological platforms, may contribute to maintain public science’s autonomy. (shrink)