The Structure Of Interdisciplinary Science
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The Structure of Interdisciplinary Science
This book presents a novel approach to the analysis of interdisciplinary science based on the contemporary philosophical literature on scientific representation. The basic motivation for developing this approach is that epistemic issues are insufficiently dealt with in the existing literature on interdisciplinarity. This means that when interdisciplinary science is praised (as it often is), it is far from clear to what extent this praise is merited – at least if one cares about various more or less standardised measures of scientific quality. To develop a more adequate way of capturing what is going on in interdisciplinary science, the author draws inspiration from the rich philosophical literature on modelling, idealisation, perspectivism, and scientific pluralism. The discussion hereof reveals a number of critical pitfalls related to transferring mathematical and conceptual tools between scientific contexts, which should be relevant and interesting for anyone actively engaged in funding, evaluating, or carrying out interdisciplinary science.
Cognitive Patterns in Science and Common Sense
This collection of 17 articles offers an overview of the philosophical activities of a group of philosophers (who have been) working at the Groningen University. The meta-methodological assumption which unifies the research of this group, holds that there is a way to do philosophy which is a middle course between abstract normative philosophy of science and descriptive social studies of science. On the one hand it is argued with social studies of science that philosophy should take notice of what scientists actually do. On the other hand, however, it is claimed that philosophy can and should aim to reveal cognitive patterns in the processes and products of scientific and common sense knowledge. Since it is thought that those patterns can function as guidelines in new research and/or in research in other disciplines, philosophy can nevertheless hold on to the normative aim which is characteristic of 'classical' philosophy of science. Compared to this common assumption, there is a diversity of subjects. Some papers deal with general problems of science, knowledge, cognition and argumentation, others with topics relating to foundational problems of particular sciences. Therefore this volume is of interest to philosophers of science, to philosophers of knowledge and argumentation in general, to philosophers of mind, as well as for scientists working in the physical and applied sciences, biology, psychology and economy who are interested in the foundations of their disciplines. After a foreword by Leszek Nowak and a general introduction by the editors, the book is divided into four parts, with special introductions. - I: Conceptual Analysis in Service of Various Research Programmes (Henk Zandvoort, Rein Vos, Rick Looijen, Gerben Stavenga, Renée Dalitz); - II: The Logic of the Evaluation of Arguments, Hypotheses, Default Rules, and Interesting Theorems (Erik Krabbe, Theo Kuipers, Alfons Keupink, Maarten Janssen/Yao-Hua Tan, Bert Hamminga); - III: Three Challenges to the Truth Approximation Programme (Sjoerd Zwart, Hinne Hettema/Theo Kuipers, Roberto Festa); - IV: Explicating Psychological Intuitions (Anne-Ruth Mackor, Jeanne Peijnenburg, Lex Guichard, Michel ter Hark). The Groningen research group was recently qualified, by an official international assessment committee, as one of the best philosophy research groups in the Netherlands.
Complex Networks & Their Applications XII
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2023). The carefully selected papers cover a wide range of theoretical topics such as network embedding and network geometry; community structure, network dynamics; diffusion, epidemics and spreading processes; machine learning and graph neural networks as well as all the main network applications, including social and political networks; networks in finance and economics; biological networks and technological networks.