Catherine Herfeld

Scientific research is highly specialized, yet modern science increasingly involves interdisciplinary interactions. One key aspect of this is the transfer of models across domains, raising questions about how such transfers relate to successful interdisciplinary research. This chapter examines processes of model transfer, particularly the movement of mathematical models between fields, as instances of research across disciplines that occur alongside increasing specialization. Model transfer processes are manifold in that models from some source domain undergo different kinds of modification processes in order to become applicable in a new domain. We sketch a taxonomy of different modification procedures that enable cross-domain model transfer. The goal is to learn from model transfer something about the different ways in which interdisciplinarity manifests itself in a highly specialized scientific landscape.

By the second half of the twentieth century, rational choice models—formal frameworks representing decision-making through quantified preferences, utilities, and probabilistic expectations—had risen to unprecedented prominence. These models became central not only to social and behavioral scientific inquiry but also influenced a broad array of rather unrelated fields such as philosophy, psychology, computer science, and biology. Yet as their reach expanded, so too did skepticism among scientists about modeling individuals as rational actors, quantifying human behavior, and modeling non-human entities as rational decision-makers. This development—that I refer to as the “rational choice phenomenon”—raises a central question: how did these mathematically driven, extensively disputed models of human behavior gain such wide scientific traction? Focusing on the case of economics, I argue that the appeal of rational choice models lay not merely in their flexibility and capacity to quantify human choice for the purposes of formal analysis and modeling. Their extensive transfer was also shaped by a historically contingent constellation of non-epistemic factors—social, institutional, and political—that enabled their adoption across disciplinary boundaries.

This study examines gender diversity among authors in philosophy and methodology of economics, comparing it to the disciplines of economics and philosophy. Using bibliometric methods, we find that philosophy and methodology of economics, as an interdisciplinary field, consistently had a lower share of women authors than its parent disciplines, which are the two social sciences and humanities disciplines that are the furthest from gender parity. Although homogeneity compounding generally characterizes the whole field of philosophy and methodology of economics, one small and temporary subfield, making contributions to heterodox economics, structural realism, and the discussion on pluralism in economics, constituted a pocket of gender diversity. Alongside a more general discussion of possible reasons behind the striking gender imbalance in the field, we also elaborate on possible reasons for the limited size and duration of this pocket of diversity.

In this paper, we examine how a research institution’s social structure and academic opinion leaders’ presence shaped the early adoption of a scientific innovation. Our case considers the early engagement of mathematical economists at the Cowles Commission with John von Neumann and Oskar Morgenstern’s Theory of Games and Economic Behavior. We argue that scholars with administrative leadership functions who were not only scientifically but also organizationally central – in our case the director of research Jacob Marschak – played a crucial role in promoting the adoption of the Theory of Games. We support our argument with a scientometric analysis of all acknowledgments made in 488 papers published from 1944 to 1955 in the two main paper series at Cowles. We apply blockmodeling techniques to the acknowledgments network to reconstruct the formal and informal social structure at Cowles at the time. Our findings suggest that studies of the early adoption of scientific theories benefit from complementary perspectives on the role of academic leaders and scientists. Our study reveals the importance of formal and informal social structures and the agenda of administrative leaders in these structures to explain their adoption.

This chapter introduces empirical network analysis (ENA) as a toolbox to complement other methods in philosophy of science. It aims to provide a hands-on introduction to ENA for philosophers of science and to discuss the usefulness of ENA for addressing questions of interest to philosophy of science. We accompany our account by an in-depth consideration of two examples of ENA to reflect not only on the potentials but also on the challenges of ENA. The chapter concludes by outlining skills required for concrete applications and pointing to several resources that can be consulted to acquire those skills.

Philosophers of science have recently started to discuss the role of scientific methods for their field. Those tendencies have immediate methodological implications for Integrated History and Philosophy Science (&HPS) as an area that contributes to philosophy of science while drawing heavily on historical case studies. This paper addresses the questions whether and if so in which way scientific methods can be useful for research in &HPS by discussing the usefulness of one such method, namely network analysis. By focusing on the example of model transfer in science, I argue that network analysis is particularly useful for doing research in &HPS because it allows for addressing a set of methodological issues arising from the use of case studies. More specifically, my claim is that network analysis can enhance the core functions of case studies in &HPS, namely those of concept generation, of concept refinement, and of empirical justification of concepts. While I discuss the advantages of network analysis for &HPS, I close by cautioning that it cannot replace more traditional philosophical methods. Rather, network analysis must rely on them to fully develop its potentials.

Methodological appraisal usually aims at a discourse that contributes to the improvement of knowledge production processes in economics. Attempts by economists, such as that by Gilboa et al. (2022. Economic theories and their dueling interpretations. Journal of Economic Methodology, 1–20) to engage in such a discourse are laudable and needed because they draw on field-specific expertise and experience from economic practice and thereby can steer such discourse into promising directions. However, while Gilboa et al. seem to share the ambition of doing economic methodology in the service of progress, their contribution is not sufficiently self-critical. Instead of seriously considering the diversity of contemporary modeling practices, their position commits them to an outdated view of economics and can be read as licensing the preservation of conceptual and theoretical elements of standard economics that the discipline has long been criticized for. As such, the authors miss out on fully reaching their own ambitions of a practice-based appraisal that pushes economists towards self-critical and forward-looking modeling.

It has been argued persistently that economic models frequently suffer from poor empirical performance because they rely upon empirically inadequate behavioral foundations, i.e. theories of rational choice. In this paper, I argue that much of this criticism misses the point: it assumes that economics is about explaining human behavior when in fact, since Adam Smith, economists have been more interested in explaining patterns that emerge from social interaction. While some minimal account of human behavior is needed for explaining such phenomena, a full-fledged psychological or neurobiological theory of individual behavior might not be. The more pressing yet under-researched challenge for economic models is to arrive at an adequate description of social interaction processes that connect individual choices on the micro-level and robust patterns on the macro-level.

A conspicuous feature of contemporary modelling practices is the use of the same mathematical forms and modelling methods across different scientific domains. This model transfer raises many philosophical questions concerning, for example, the exact object of transfer, the relationship between the model and the target domain, the specific challenges such transfer confronts, and the ways in which model transfer relates to scientific progress. While the interest in studying model transfer has increased among philosophers of science in recent years, the phenomenon has not yet received its due attention. The literature is scattered and much of it has addressed questions around the factors that might explain model transfer, such as whether the different target phenomena to which a model is applied eventually prove to be structurally and dynamically similar, or whether they have to share more fundamental ontological features that explain the interdisciplinary success of distinct models. This chapter surveys the existing literature on model transfer with the main goal of highlighting the main findings of existing discussions and pointing out open issues whose discussion would improve our understanding of this highly relevant phenomenon in science.

Concept formation has recently become a widely discussed topic in philosophy under the headings of “conceptual engineering”, “conceptual ethics”, and “ameliorative analysis”. Much of this work has been inspired either by the method of explication or by ameliorative projects. In the former case, concept formation is usually seen as a tool of the sciences, of formal disciplines, and of philosophy. In the latter case, concept formation is seen as a tool in the service of social progress. While recent philosophical discussions on concept formation have addressed natural sciences such as physics as well as various life sciences, so far there is only little direct engagement with the social sciences. To address this shortcoming is important because many debates about socially relevant concepts such as power, gender, democracy, risk, justice, or rationality, may best be understood as engaging in conceptual engineering. This topical collection addresses the nature and structure of concept formation in the natural, the life, and the social sciences alike, both as a process taking place within science and as an activity that aims at a broader impact in society. This helps to understand how concept formation proceeds not only in the natural sciences but also in disciplines such as psychology, cognitive science, political science, sociology and economics.

It is well known that there has been a steady and significant underrepresentation of women in philosophy on different professional levels. Numerous hypotheses explaining this underrepresentation have been suggested, but empirical analyses are not yet extensive. In particular, studies of the phenomenon in different countries are nonexistent. In this paper, we present findings from an exploratory study in which we analyze the interests, abilities, beliefs, attitudes, perceptions, and goals of bachelor’s students in a semester-long philosophy of science course at a major German university. We furthermore make the first attempt to compare women-only learning environments with mixed-gender learning environments. Our results suggest that while there are generally some gender differences regarding interests, abilities, beliefs, attitudes, perceptions, and goals of students in the classroom, most of the hypotheses we explore to explain dropout rates by gender differences cannot be supported. We conclude that possible factors leading to the underrepresentation of women in philosophy in Germany might be found in the social and institutional environment within which philosophy is taught.

In this chapter, we discuss social network analysis as a method for the history of economics. We argue that social network analysis is not primarily a method of data representation but foremost a method of discovery and confirmation. It is as such a promising method that should be added to the toolbox of the historian of economics. We furthermore argue that, to be meaningfully applied in history, social network analysis must be complemented with historical knowledge gained by other means and often by more traditional, mostly qualitative, methods. It should therefore be viewed as a method that complements rather than replaces more established approaches in the history of economics.

One striking observation in the history of rational choice models is that those models have not only been used in economics but spread widely across the social and behavioral sciences. How do such model transfers proceed? By closely studying the early efforts to transfer such models by William Riker – a major protagonist in pushing the adoption of game theoretic models in political science – this article examines the transfer process as one of ‘translation’ by which abstract and mathematical rational choice models were constructed and modified such that they applied to a specific target system in a new domain. In this paper, we argue that to overcome a set of challenges that hampered the straightforward transfer of game theoretic models into political science, Riker complemented theoretical and conceptual modifications of von Neumann and Morgenstern’s game schemes with the use of narratives to turn them into applicable and testable models. As such, those narratives played a crucial role in enabling their transfer and ultimately facilitated the applicability of game theoretic models in political science.

In this chapter, it is described and assessed how political scientists use rational choice theories to offer causal explanations. We observe that the ways in which rational choice theories are considered to be successful in political science differs, depending on the explanandum in question. Political scientists use empirical variants of rational choice theories to explain the political behavior of individual agents and analytical variants to explain the behavior of collective actors. Both variants are used for distinct explananda, which ask for different modes of explanation that raise in turn different explanatory demands toward rational choice theories. We argue that when political scientists discuss the explanatory usefulness of rational choice theories, they should assess them in light of the demands they are supposed to meet. This would enable a more nuanced and problem-oriented appraisal of rational choice theories in political science.

In this chapter, we discuss a specific kind of progress in economics, namely, progress that is pushed by the repeated use of mathematical models in most sub-branches of economics today. We adopt a functional account of progress to argue that progress in economics occurs via the use of what we call ‘common recipes’ and the use of model templates to define and solve problems of relevance for economists. We support our argument by discussing the case of twentieth-century business cycle research. By presenting this case study in detail, we show how model templates are not only re-applied to different phenomena. We also show how scientists come up with them in the first place and how – once they are considered less useful – they are replaced with new ones. Finally, our case also illustrates that it is not only the mathematical structure that is re-used but that such a re-use also requires a shared conceptual vision of core properties of the phenomenon. If that vision is not shared anymore among economists, a model template can become useless and has to be replaced – sometimes through overcoming resistance – with a different one.

Knowledge transfer across different contexts has become an increasingly prevalent feature of current science. As such, it is a relevant topic also for history and philosophy of science. This special issue presents a set of papers that study knowledge transfer in various disciplines. The contributions approach the topic from either an integrated history and philosophy of science perspective, 2) a systematic philosophical perspective, or 3) a historical perspective. This overview article is organized in three sections. The introduction provides some background and context of the topic. The second section specifies the three components of knowledge transfer, i.e., knowledge, context, and the transfer process. It motivates our take on this topic and then outlines the central ideas of each paper. The third section reflects on the kinds of methods used to study processes of knowledge transfer. The article concludes by highlighting some of the features of such processes, some of the main challenges and obstacles that those processes involve, and possible ways of dealing with them.

Theories of rational choice are arguably the most prominent approaches to human behaviour in the social and behavioral sciences. At the same time, they have faced persistent criticism. In this paper, I revisit some of the core criticisms that have for a long time been levelled against them and discuss to what extent those criticisms are still effective, not only in light of recent advancements in the literature but also of the fact that there are different variants of rational choice theories that have not been considered explicitly when criticizing them.

In this paper, we examine the viability of avoiding value judgments encoded in thick concepts when these concepts are used in economic theories. We focus on what implications the use of such thick concepts might have for the tenability of the fact/value dichotomy in economics. Thick concepts have an evaluative and a descriptive component. Our suggestion is that despite attempts to rid thick concepts of their evaluative component, economists are often not successful. We focus on the strategy of explication to remove the evaluative component of thick concepts and argue that often economists either have to make value judgments or are unable to individuate out the phenomenon under analysis. We support our claim with a case study, namely the concept of addiction in Gary Becker and Kevin Murphy’s Theory of Rational Addiction (1988). One consequence of our analysis is that theories containing thick concepts could commit economists to making value judgments and as such undermine the fact/value dichotomy.