The concepts of adaptation and fitness have such an appeal that they have been used in other scientific domains, including the social sciences. One particular aspect of this theory transfer concerns the so-called fitness landscape models. At first sight, fitness landscapes visualize how an agent, of any kind, relates to its environment, how its position is conditional because of the mutual interaction with other agents, and the potential routes towards improved fitness. The allure of fitness landscapes is first and foremost (...) that it represents a complex story about adaptation and fitness in one coherent image. Different accounts of fitness landscapes in different domains in the social sciences suggest that the properties and functions of fitness landscapes are attributed rather freely. These differences are testimony of the model’s versatility. At the same time, one will notice that the different approaches can also create ambiguity about the exact meaning and role of fitness landscapes in the social sciences. This article presents an extensive literature survey of the diverging interpretations and uses of fitness landscapes in the social sciences and discusses the implications in terms of how these models inform scientific inquiry. (shrink)

The aim of this paper is to engage with the interplay between representational content and design in chemistry and to explore some of its epistemological consequences. Constraints on representational content arising from the aspectual structure of representation can be manipulated by design. Designs are epistemologically important because representational content, hence our knowledge of target systems in chemistry, can change with design. The significance of this claim is that while it has been recognised that the way one conveys information makes a (...) difference to the inferences one can draw from representations in spite of the invariance of informational content, the present paper argues that in chemistry and biochemistry it is often the case that designs have cognitive priority relative to informational content. (shrink)

Several prominent philosophers of science, most notably Ron Giere, propose that scientific theories are collections of models and that models represent the objects of scientific study. Some, including Giere, argue that models represent in the same way that pictures represent. Aestheticians have brought the picturing relation under intense scrutiny and presented important arguments against the tenability of particular accounts of picturing. Many of these arguments from aesthetics can be used against accounts of representation in philosophy of science. I rely on (...) Dominic Lopes' recent summary of arguments against various views of picturing and reformulate some of them to fit the philosophy of science context. My specific targets here are Giere and Steven French. I go on to argue that assuming all scientific models and images represent in the same way is not the best guide to understanding scientific practice. (shrink)

While many recent accounts of scientific representation have given a central role to the agency and intentions of scientists in explaining representation, they have left these agential concepts unanalyzed. An account of scientific, representational actions will be a useful piece in offering a more complete account of the practice of representation in science. Drawing on an Anscombean approach to the nature of intentional actions, the Means-End Account of Scientific, Representational Actions describes three features of scientific, representational actions: the final description (...) in the means-end ordering of descriptions is some scientific aim; that interaction with a vehicle distinct from its target stands as an earlier description which is ordered toward the final description as means to end; and the means-end structure is licensed by scientific practice. After describing each of the components of the Means-End Account in greater detail through the example of the representational use of a mathematical model, I explain how it can demarcate scientific, representational actions from other sorts of actions. I close by describing some payoffs of the account, showing how it contributes to a more thorough understanding of the practice of representation in science and how it can be of use in understanding the close connection between representation and other forms of scientific activity. (shrink)

While many recent accounts of scientific representation have given a central role to the agency and intentions of scientists in explaining representation, they have left these agential concepts unanalyzed. An account of scientific, representational actions will be a useful piece in offering a more complete account of the practice of representation in science. Drawing on an Anscombean approach to the nature of intentional actions, the Means-End Account of Scientific, Representational Actions describes three features of scientific, representational actions: (I) the final (...) description in the means-end ordering of descriptions is some scientific aim; (II) that interaction with a vehicle distinct from its target stands as an earlier description which is ordered toward the final description as means to end; and (III) the means-end structure is licensed by scientific practice. After describing each of the components of the Means-End Account in greater detail through the example of the representational use of a mathematical model, I explain how it can demarcate scientific, representational actions from other sorts of actions. I close by describing some payoffs of the account, showing how it contributes to a more thorough understanding of the practice of representation in science and how it can be of use in understanding the close connection between representation and other forms of scientific activity. (shrink)

In this essay, I will expand the philosophical discussion about the representational practice in science to examine its role in science education through four case studies. The cases are of what I call ‘educational laboratory experiments’, performative models used representationally by students to come to a better understanding of theoretical knowledge of a scientific discipline. The studies help to demonstrate some idiosyncratic features of representational practices in science education, most importantly a lack of novelty and discovery built into the ELEs (...) as their methodology is solidified when it becomes a widely spread educational tool within a discipline. There is thus an irreducible role for the historical development of ELEs in understanding their representational nature and use. The important role of the historical development of ELEs leads to an interesting way that educators can use ELEs as a means of connecting students to important historical developments within their disciplines. (shrink)

Generative models have been proposed as a new type of non-representational scientific models recently. A generative model is characterized with the capacity of producing new models on the basis of the existing one. The current accounts do not explain sufficiently the mechanism of the generative capacity of a generative model. I attempt to accomplish this task in this paper. I outline two antecedent accounts of generative models. I point out that both types of generative models function to generate new homogenous (...) models in the sense that the latter is a straightforward derivative of the former, both of which share many similar features. Unfortunately, both accounts are implicit about the generative capacity of generative models. Using a case study, I articulate that a two-staged process of abstraction and idealization in modeling may contribute to the generative capacity of a scientific model. I also demonstrate that this two-staged process may go beyond the capacity of generating new homogenous models to generating new heterogeneous models. (shrink)

This article offers a characterization of what I call multiple-models juxtaposition, a strategy for managing trade-offs among modeling desiderata. MMJ displays models of distinct phenomena to...

What features will something have if it counts as an explanation? And will something count as an explanation if it has those features? In the second half of the 20th century, philosophers of science set for themselves the task of answering such questions, just as a priori conceptual analysis was generally falling out of favor. And as it did, most philosophers of science just moved on to more manageable questions about the varieties of explanation and discipline-specific scientific explanation. Often, such (...) shifts are sound strategies for problem-solving. But leaving fallow certain basic conceptual issues can also result in foundational debates. (shrink)

There is considerable correspondence between theories and models used in biology and the social sciences. One type of model that is in use in both biology and the social sciences is the fitness landscape model. The properties of the fitness landscape model have been applied rather freely in the social domain. This is partly due to the versatility of the model, but it is also due to the difficulties of transferring a model to another domain. We will demonstrate that in (...) order to transfer the biological fitness landscape model to the social science it needs to be substantially modified. We argue that the syntactic structure of the model can remain unaltered, whilst the semantic dimension requires considerable modification in order to fit the specific phenomena in the social sciences. We will first discuss the origin as well as the basic properties of the model. Subsequently, we will demonstrate the considerations and modifications pertaining to such a transfer by showing how and why we altered the model to analyse collective decision-making processes. We will demonstrate that the properties of the target domain allow for a transfer of the syntactic structure but don’t tolerate the semantic transfer. (shrink)

Moti Mizrahi has argued that Thomas Kuhn does not have a good argument for the incommensurability of successive scientific paradigms. With Rouse, Andersen, and others, I defend a view on which Kuhn primarily was trying to explain scientific practice in Structure. Kuhn, like Hilary Putnam, incorporated sociological and psychological methods into his history of science. On Kuhn’s account, the education and initiation of scientists into a research tradition is a key element in scientific training and in his explanation of incommensurability (...) between research paradigms. The first part of this paper will explain and defend my reading of Kuhn. The second part will probe the extent to which Kuhn’s account can be supported, and the extent to which it rests on shaky premises. That investigation will center on Moti Mizrahi’s project, which aims to transform the Kuhnian account of science and of its history. While I do defend a modified kind of incommensurability, I agree that the strongest version of Kuhn’s account is steadfastly local and focused on the practice of science. (shrink)

The recent literature in philosophy of biology has drawn attention to the different sorts of explanations proffered in the biological sciences—we have molecular, biomedical, and evolutionary explanations. Do these explanations all have a common structure or relation that they seek to capture? This paper will answer in the negative. I defend a pluralistic and pragmatic approach to explanation. Using examples from classical population genetics, I argue that formal demonstrations, and even strictly “mathematical truths,” may serve as explanatory in different historical (...) contexts. (shrink)

Scientific communities as social groupings and the role that such communities play in scientific change and the production of scientific knowledge is currently under debate. I examine theory change as a complex social interaction among individual scientists and the scientific community, and argue that individuals will be motivated to adopt a more radical or innovative attitude when confronted with striking similarities between model systems and a more robust understanding of specialised vocabulary. Two case studies from the biological sciences, Barbara McClintock (...) and Stanley Prusiner, help motivate the idea that sharing of models and specialised vocabulary fill the gap between discovery and scientific change by promoting the dispersal of important information throughout the scientific community. (shrink)

Scientific models are important, if not the sole, units of science. This thesis addresses the following question: in virtue of what do scientific models represent their target systems? In Part i I motivate the question, and lay out some important desiderata that any successful answer must meet. This provides a novel conceptual framework in which to think about the question of scientific representation. I then argue against Callender and Cohen’s attempt to diffuse the question. In Part ii I investigate the (...) ideas that scientific models are ‘similar’, or structurally morphic, to their target systems. I argue that these approaches are misguided, and that at best these relationships concern the accuracy of a pre-existing representational relationship. I also pay particular attention to the sense in which target systems can be appropriately taken to exhibit a ‘structure’, and van Fraassen’s recent argument concerning the pragmatic equivalence between representing phenomena and data. My next target is the idea that models should not be seen as objects in their own right, but rather what look like descriptions of them are actually direct descriptions of target systems, albeit not ones that should be understood literally. I argue that these approaches fail to do justice to the practice of scientific modelling. Finally I turn to the idea that how models represent is grounded, in some sense, in their inferential capacity. I compare this approach to anti-representationalism in the philosophy of language and argue that analogous issues arise in the context of scientific representation. Part iii contains my positive proposal. I provide an account of scientific representation based on Goodman and Elgin’s notion of representation-as. The result is a highly conventional account which is the appropriate level of generality to capture all of its instances, whilst remaining informative about the notion. I illustrate it with reference to the Phillips-Newlyn machine, models of proteins, and the Lotka-Volterra model of predator-prey systems. These examples demonstrate how the account must be understood, and how it sheds light on our understanding of how models are used. I finally demonstrate how the account meets the desiderata laid out at the beginning of the thesis, and outline its implications for further questions from the philosophy of science; not limited to issues surrounding the applicability of mathematics, idealisation, and what it takes for a model to be ‘true’. (shrink)

Students in interdisciplinary science educations are faced with the challenge of combining knowledge and standards from different disciplines. To help them overcome this challenge it would be helpful to reflect more explicitly on what differences in epistemic aims there may be between the different disciplines. To aid further studies that will strengthen such discussions this paper outlines an empirical method that can be used to expose possible qualitative differences in explanations from different disciplines. The method is based on the use (...) of science textbooks as sources of explanations. I will argue that it is important to be very clear about how explanations are identified in the sources if the aim of the study is to make a strong empirical claim about the nature of explanations. Following a discussion of similar studies I will present an alternative procedure for identifying explanations in written sources that suits the purposes of this study better. A pilot study is then presented to illustrate the method and its limitations. (shrink)

The most common way of studying explanations in philosophy of science and science education is through case studies. Recently these have been supplemented with studies based on empirical methods. This chapter provides an empirical method for collecting and comparing exemplar explanations across scientific disciplines with the aim of exposing possible qualitative differences between them. The method is based on the use of science textbooks as sources of explanations. I discuss a number of possible strategies for identifying explanations in these sources, (...) and specify a set of reliable linguistic indicators that can be used for this purpose. A pilot study is presented to illustrate the method and its limitations. (shrink)

The discussion of the adaptive landscape in the philosophical literature appears to be divided along the following lines. On the one hand, some claim that the adaptive landscape is either “uninterpretable” or incoherent. On the other hand, some argue that the adaptive landscape has been an important heuristic, or tool in the service of explaining, as well as proposing and testing hypotheses about evolutionary change. This paper attempts to reconcile these two views.