Compared to the massive literature from other disciplinary perspectives on interdisciplinarity, philosophy of science is only slowly beginning to pay systematic attention to this powerful trend in contemporary science. The paper provides some metaphilosophical reflections on the emerging “Philosophy of Interdisciplinarity”. What? I propose a conception of PhID that has the qualities of being broad and neutral as well as stemming from within the agenda of philosophy of science. It will investigate features of science that reveal themselves when scientific disciplines (...) are viewed in comparison or in contact with one another. PhID will therefore generate two kinds of information: comparative and contactual. Comparative information is about the similarities and differences between disciplines, while contactual information is about what happens and why when disciplines get in contact with each other. Virtually all issues and resources within the philosophy of science can be mobilized to bear on the project, including philosophical accounts of models, explanations, justification, evidence, progress, values, demarcation, incommensurability, and so on. Given that scientific disciplines are institutional entities, resources available in social epistemology and social ontology will also have to be invoked. Why? Establishing PhID is presently an obvious step to take for several reasons, including the following two. First, ID is an increasingly powerful characteristic of contemporary science and its management, and so it would be inappropriate for an empirically informed philosophy of science to ignore it. Second, contemporary philosophy of science happens to be particularly well equipped for addressing issues of ID thanks to the recent massive work in the more specialized fields of philosophies of special disciplines. How? Given the breadth and heterogeneity of its domain and tasks, the practice of PhID must be heavily collective. It must mobilize multiple competences and it must keep elaborating a systematic agenda. While a lot of new conceptual work is needed, the approach is bound to be emphatically empirical, with a cumulative and mutually complementary series of case studies to be conducted. Among the methods to be employed, good old textual analysis of scientific publications will be supplemented with interviews, ‘experimental’ techniques, participant observation as well as various interventionist approaches. The published work in PhID will often be authored jointly by philosophers and other scholars in science studies as well as practitioners in various scientific disciplines. (shrink)

Some scholars see interdisciplinarity as a special case of a broader unificationist program. They accept the unification of the sciences as a regulative ideal, and derive from this the normative justification of interdisciplinary research practices. The crucial link for this position is the notion of integration: integration increases the cohesion of concepts and practices, and more specifically of explanations, ontologies, methods and data. Interdisciplinary success then consists in the integration of fields or disciplines, and this constitutes success in the sense (...) that unification is epistemically desirable. In contrast to this account, I defend the thesis that successful interdisciplinary interaction does not necessarily imply the integration of these disciplines. I show this at the hand of two cases. In both the case of evolutionary game theory and the case of hyperbolic discounting, genuine interdisciplinary exchange took place. From both exchanges, the respective economic fields emerged substantially altered – it wasn’t just a juxtaposition of disciplines in which disciplinary identities remained unchanged. Yet in neither case did the disciplines integrate. Rather, they developed their own concepts and methods, their own explanations, own ontologies, and their own views of what proper data standards were. Furthermore, the fields that emerged from these exchanges were very successful, if measured at the hand of properties like explanatory success, increase of control, bibliometrics and grant yields. Thus, I argue, there are cases of interdisciplinary success without integration. (shrink)

Cognitive science is a child of the 1950s, the product of a time when psychology, anthropology and linguistics were redefining themselves and computer science and neuroscience as disciplines were coming into existence. Psychology could not participate in the cognitive revolution until it had freed itself from behaviorism, thus restoring cognition to scientific respectability. By then, it was becoming clear in several disciplines that the solution to some of their problems depended crucially on solving problems traditionally allocated to other disciplines. Collaboration (...) was called for: this is a personal account of how it came about. (shrink)

The purpose of this article is to develop an epistemology of scientific models in scientific research practices, and to show that disciplinary perspectives have crucial role in such an epistemology. A transcendental approach is taken, aimed at explanations of the kinds of questions relevant to the intended epistemology, such as “How is it possible that models provide knowledge about aspects of reality?” The approach is also pragmatic in the sense that the questions and explanations must be adequate and relevant to (...) concrete scientific practice. First it is explained why the idea of models as representations in terms of similarity or isomorphism between a model and its target is too limited as a basis for this epistemology. An important finding is that the target-phenomenon is usually not something that can be observed in a straightforward manner, but requires both characterization in terms of measurable variables and subsumption under concepts. The loss of this basis leads to a number of issues, such as: how can models be interpreted as representations if models also include conceptually meaningful linguistic content; how can researchers identify non-observable real-world target-phenomena that are then represented in the model; how do models enable inferential reasoning in performing epistemic tasks by researchers; and, how to justify scientific models. My proposal is to deal with these issues by analyzing how models are constructed, rather than by looking at ready-made models. Based on this analysis, I claim that the identification of phenomena and the construction of scientific models is guided and also confined by the disciplinary perspective within which researchers in a scientific discipline have learned to work. I propose a Kuhnian framework by which the disciplinary perspective can be systematically articulated. Finally, I argue that harmful forms of subjectivism, due to the loss of the belief that models objectively represent aspects of reality, can be overcome by making the disciplinary perspective in a research project explicit, thereby enabling its critical assessment, for which the proposed Kuhnian framework provides a tool. (shrink)

In this article, I show the role that the philosopher of cognitive science can cur-rently play in cognitive science research. I argue for the important, and not yet considered, role of the philosophy of cognitive science in cognitive science, that is, the importance of cooperation between philosophers of science with cogni-tive scientists in investigating the research methods and theoretical assump-tions of cognitive science. At the beginning of the paper I point out, how the philosopher of science, here, the philosopher of (...) cognitive science, can participate in interdisciplinary research. I am opting of the cooperation in investigating the so-called reflective problems. Then, I discuss four examples of issues important for the cognitive science, in which the competences possessed by the philosopher are useful. At the ending I point out wider landscape of possible cooperation of philosophers with cognitive scientists. (shrink)

The epistemic barriers to interdisciplinarity are understudied. To fill this gap, we ask whether a university initiative designed to reduce structural barriers to interdisciplinarity also facilitates the dissolution of epistemic ones. Through analytical autoethnography of graduate training in two disciplines, sociology and ecology, we develop the concept of asymmetric epistemology to better understand the unique epistemological position that emerges for interdisciplinarians. Building from feminist science and technology studies (STS) and scholarship on epistemic identities, our work illuminates how epistemologies are embodied (...) by individuals, leading to tensions around identity, materiality, and spatiality during the practice of interdisciplinarity. While some epistemic barriers recede and others remain, we reveal that the navigation of these boundaries deeply impacts individuals’ epistemic identities. (shrink)

Focusing on Harvard's Center for Cognitive Studies as a case, this article uses economies of research tool exchange to develop a new way of characterizing cross-disciplinary research. Throughout its life from 1960 to 1972, the Center for Cognitive Studies hosted scholars from several disciplines. However, there were two different research cultures at the Center. With its directors and patrons committed to a philosophy that equated creative science with eclectic search for and invention of new tools, the Center's initial interdisciplinary research (...) culture emphasized the exchange of ideas and methods. Several years later, once its work was well under way, the Center's culture became multidisciplinary. Rather than emphasizing the sharing, invention, location, discussion and stabilization of new research techniques, the Center's multidisciplinary economy involved researchers working in parallel. (shrink)

Among others, the term problem plays a major role in the various attempts to characterize interdisciplinarity or transdisciplinarity, as used synonymously in this paper. Interdisciplinarity is regarded as problem solving among science, technology and society and as problem orientation beyond disciplinary constraints. The point of departure of this paper is that the discourse and practice of ID have problems with the problem. The objective here is to shed some light on the vague notion of problem in order to advocate a (...) specific type of interdisciplinarity: problem-oriented interdisciplinarity. The outline is as follows: Taking an ex negativo approach, I will show what problem-oriented ID does not mean. Using references to well-established distinctions in philosophy of science, I will show three other types of ID that should not be placed under the umbrella term problem-oriented ID : object-oriented ID, theory-oriented ID, and method-oriented ID. Different philosophical thought traditions can be related to these distinguishable meanings. I will then clarify the notion of problem by looking at three systematic elements: an undesired state, a desired state, and the barriers in getting from the one to the other. These three elements include three related kinds of knowledge: systems, target, and transformation knowledge. This paper elaborates further methodological and epistemological elements of problem-oriented ID. It concludes by stressing that problem-oriented ID is the most needed as well as the most challenging type of ID. (shrink)

This paper considers the past and future of Psychology within Cognitive Science. In the history section, I focus on three questions: (a) how has the position of Psychology evolved within Cognitive Science, relative to the other disciplines that make up Cognitive Science; (b) how have particular Cognitive Science areas within Psychology waxed or waned; and (c) what have we gained and lost. After discussing what’s happened since the late 1970s, when the Society and the journal began, I speculate about where (...) the field is going. (shrink)