Tarja Knuuttila

Models, Representation, and Mediation

Representation has been one of the main themes in the recent discussion of models. Several authors have argued for a pragmatic approach to representation that takes users and their interpretations into account. It appears to me, however, that this emphasis on representation places excessive limitations on our view of models and their epistemic value. Models should rather be thought of as epistemic artifacts through which we gain knowledge in diverse ways. Approaching models this way stresses their materiality and media‐specificity. Focusing on models as multifunctional artifacts releases them from any preestablished and fixed representational relationships and leads me to argue for a twofold approach to representation.

A Parser as an Epistemic Artifact: A Material View on Models

The purpose of this paper is to suggest that models in scientific practice can be conceived of as epistemic artifacts. Approaching models this way accommodates many such things that working scientists themselves call models but that the semantic conception of models does not duly recognize as such. That models are epistemic artifacts implies, firstly, that they cannot be understood apart from purposeful human activity; secondly, that they are somehow materialized inhabitants of the intersubjective field of that activity; and thirdly, that they can function also as knowledge objects. We argue that models as epistemic artifacts provide knowledge in many other ways than just via direct representative links. To substantiate our view we use a language‐technological artifact, a parser, as an example.

Models and Modelling in Economics

This paper surveys and analyses the current literature on the nature of economic models and the functioning of models in economics from the standpoint of philosophy of science.

Intermingling Academic and Business Activities: A New Direction for Science and Universities?

The growing role of universities in the knowledge economy as well as technology transfer has increasingly been conceptualized in terms of the hybridization of public academic work and private business activity. In this article, we examine the difficulties and prospects of this kind of intermingling by studying the long-term trajectories of two research groups operating in the fields of plant biotechnology and language technology. In both cases, the attempts to simultaneously pursue academic and commercial activities led to complicated boundary maintenance, which arose from the conflicting procedures and requirements of the two activities as well as from the double roles assumed by the actors involved. We, thus, argue that the construction of boundaries is not as contingent and strategic as has often been assumed but is built, instead, on the characteristic goals and tasks of the activities in question. Moreover, we suggest that the discussion on university—industry relationships and the entrepreneurial university has by and large neglected the fact that most universities are either public sector entities or tax-exempt organizations thereby being subject to strict rules and regulations that govern the ways in which they may become engaged in commercial activities. Furthermore, several other enduring cultural features, such as the university’s commitment to open scholarly communication, make the boundary between university and commerce relatively stable. As a consequence, the results of this study lend support to the thesis according to which boundaries in science are not always created at will but reflect the long history and multifaceted societal relevance of this particular institution. This in turn implies that the commodification of university research is bound to be more difficult than what the proponents of the entrepreneurial university seem to assume.

Models as Epistemic Tools in Engineering Sciences

Publisher Summary This chapter focuses on scientific models in engineering as epistemic tools for creating or optimizing concrete devices or materials. From this pragmatist and functional perspective, scientific models appear as things that are used by scientists to do some work, in other words, to fulfill some purposes. Consequently, one approaches modeling as a specific scientific practice in which concrete entities, i.e. models, are constructed with the help of specific representational means and used in various ways for the purposes of scientific reasoning, theory construction and design of other artifacts and instruments. The key to the epistemic value of models does not lie in their being accurate representations of some real target systems but rather in their independent systemic construction that enables scientists to draw inferences and reason through constructing models and manipulating them. Although this way of looking at models makes sense especially in the context of engineering sciences because of their intervening and constructive character.

Determining the Norms of Science: From Epistemological Criteria to Local Struggle on Organizational Rules?

Universities in the Western countries have become complex organizations involving many kinds of activities. Since the Second World War, the traditional functions of universities – academic research and higher education – have expanded simultaneously as universities have taken on a whole variety of societal service functions often termed the university’s third mission (Clark 1998). From the beginning of the 1980s, a central part of this changed landscape has been the commercialization of university research results. According to a number of analysts, this alteration, fostered by competitiveness-oriented national innovation policies (Slaughter and Rhoads 1996), has led to the intermingling of public university and private business activities. Four different conceptions of such hybridization can be identified. First, the concept of the “Mode 2” knowledge production (Gibbons et al. 1994) claims that traditional academic research has merged with the rest of society, including politics and the markets. Scientific knowledge has become “contextualized”, meaning that its scope has been expanded so that problems of various societal groups and organizations are set as the starting points of research, instead of purely scientific questions (Nowotny et al. 2001, pp. 65, 106). Second, the intertwinement of science, politics, and business life has created what David Guston (1999) has called boundary organizations, i.e., organizations that are responsible for more than one social world at once. Such organizations operate as initiators and sponsors of new projects, thus enhancing interaction across the boundaries of various activities. Third, the commercial potential of university research has given rise to university– industry research relationships, especially in the quickly developing fields of knowledge-based industries, such as information and communication technology and biotechnology (e.g., Powell and Owen-Smith 1998). In these networks, research is often distributed between three closely related organizations, i.e., public research institutes, companies and universities (Fransman 2001). Fourth, entire universities have sought to redirect their activities, giving birth to what was termed

Modelling as Indirect Representation? The Lotka–Volterra Model Revisited

Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s ([2007], [2013]) thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due to two other features of contemporary model construction processes that Weisberg does not explicitly consider: the methods-drivenness and outcome-orientedness of modelling. 1. Introduction2. Modelling as Indirect Representation3. The Design of the Lotka–Volterra Model by Volterra 3.1. Volterra’s method of hypothesis3.2. The construction of the Lotka–Volterra model by Volterra4. The Design of the Lotka–Volterra Model by Lotka 4.1. Physical biology according to Lotka4.2. Lotka’s systems approach and the Lotka–Volterra model5. Philosophical Discussion: Strategies and Tools of Modelling 5.1. Volterra’s path from the method of isolation to the method of hypothesis5.2. The template-based approach of Lotka5.3. Modelling: methods-driven and outcome-oriented6. Conclusion Introduction Modelling as Indirect Representation The Design of the Lotka–Volterra Model by Volterra 3.1. Volterra’s method of hypothesis3.2. The construction of the Lotka–Volterra model by Volterra Volterra’s method of hypothesis The construction of the Lotka–Volterra model by Volterra The Design of the Lotka–Volterra Model by Lotka 4.1. Physical biology according to Lotka4.2. Lotka’s systems approach and the Lotka–Volterra model Physical biology according to Lotka Lotka’s systems approach and the Lotka–Volterra model Philosophical Discussion: Strategies and Tools of Modelling 5.1. Volterra’s path from the method of isolation to the method of hypothesis5.2. The template-based approach of Lotka5.3. Modelling: methods-driven and outcome-oriented Volterra’s path from the method of isolation to the method of hypothesis The template-based approach of Lotka Modelling: methods-driven and outcome-oriented Conclusion

Synthetic Modeling and Mechanistic Account: Material Recombination and Beyond

Recently, Bechtel and Abrahamsen have argued that mathematical models study the dynamics of mechanisms by recomposing the components and their operations into an appropriately organized system. We will study this claim through the practice of combinational modeling in circadian clock research. In combinational modeling, experiments on model organisms and mathematical/computational models are combined with a new type of model—a synthetic model. We argue that the strategy of recomposition is more complicated than what Bechtel and Abrahamsen indicate. Moreover, synthetic modeling as a kind of material recomposition strategy also points beyond the mechanistic paradigm.

Contradictions of Commercialization: Revealing the Norms of Science?

The proponents of the entrepreneurial university have claimed that it implies adjustments in the normative structure of science. In this article, I will critically examine whether a qualitatively new kind of academic ethos can emerge from the commercialization of academic research. The traditional conception of norms of science as institutionalized imperatives is distinguished from the constructivist conception of norms as strategic or ideological resources. An empirical case study on the commercialization of the research of one academic language-technology group is presented. The case study does not support the constructivist conclusion that the norms of science are malleable at will.

Philosophical perspectives on synthetic biology

Although the emerging field of synthetic biology looks back on barely a decade of development, the stakes are high. It is a multidisciplinary research field that aims at integrating the life sciences with engineering and the physical/chemical sciences. The common goal is to design and construct novel biological components, functions and systems in order to implement, in a controlled way, biological devices and production systems not necessarily found in nature. Among the many potential applications are novel drugs and pesticides, cancer treatments, biofuels, and new materials. According to the most optimistic visions, synthetic biology may thus lead to a biotechnological revolution by transforming microorganisms into ‘factories’ of sorts, which could eventually displace conventional industrial methods. Beyond the immediate interest of natural scientists and engineers, synthetic biology has also attracted the attention of social scientists, economists, and philosophers. As early as 2002, Evelyn Fox Keller, drawing on precursor notions such as Stéphane Leduc’s ‘biologie synthétique’, outlined the aims of synthetic biology in her book Making Sense of Life (2002). In 2006, the anthropologist Paul Rabinow became involved in the work of the Synthetic Biology Engineering Research Center (SynBERC), where he created the Center’s Human Practices division, which was itself conceived of as a contribution to ‘anthropological research on the contemporary’ (Rabinow & Bennett, 2009; see www.anthropos-lab.net). By 2007, both the economic potential of synthetic biology (Henkel & Maurer, 2007) and its property rights problems (Rai & Boyle, 2007) had already been explored; simultaneously, over a two-year period in 2007–2008, the European Union’s Synbiosafe project implemented a study on the safety and ethical aspects of the nascent discipline (Schmidt, 2009; Schmidt, Kelle, Ganguli-Mitra, & de Vriend, 2009; see www.synbiosafe.eu). In 2008, a group of researchers at the University of Exeter’s ESRC Centre for Genomics in Society (Egenis), which included philosopher Maureen O’Malley, sociologist Jane Calvert, and a pair of research students, characterized synthetic biology as a high-profile area of research, driven by the challenge of DNA-based device construction, genome-driven cell engineering and protocell creation (O’Malley, Powell, Davies,