In this essay, I provide normative guidelines for developing a philosophically interesting and plausible version of social constructivism as a philosophy of science, wherein science aims for social-epistemic values rather than for truth or empirical adequacy. This view is more plausible than the more radical constructivist claim that scientific facts are constructed. It is also more interesting than the modest constructivist claim that representations of such facts emerge in social contexts, as it provides a genuine rival to the scientific axiologies (...) of scientific realists and constructive empiricists. I further contrast my view with positions holding that the aims of science are context dependent, that the unit of normative analysis is the scientific community, and that the aims of science are non-epistemic social values. (shrink)

In this paper, I explore the relationship between epistemic rationality and instrumental rationality, and I attempt to delineate their respective roles in typical instances of theoretical reasoning. My primary concern is with the instrumentalist conception of epistemic rationality: the view that epistemic rationality is simply a species of instrumental rationality, viz. instrumental rationality in the service of one's cognitive or epistemic goals. After sketching the relevance of the instrumentalist conception to debates over naturalism and 'the ethics of belief', I argue (...) that, despite enjoying considerable popularity among both epistemologists and philosophers of science, it is ultimately indefensible. Having thus argued for the distinctness of epistemic and instrumental rationality, I attempt to clarify the role played by each in typical instances of theoretical reasoning. I suggest that being theoretically rational--that is, being proficient with respect to theoretical reasoning--is best construed as a hybrid virtue, inasmuch as it involves manifesting sensitivity to two very different kinds of reasons. (shrink)

Ronald N. Giere’s Perspectival realism is one among the various approaches in philosophy of science claiming to offer an alternative understanding of scientific realism. In various writings, Giere has claimed that scientific knowledge is perspectival, and that models represent some aspects of the world based on the relation of fit. This paper argues that Giere’s perspectivism does not offer a genuine alternative as he claims, due to its difficulties in accounting for truth and the objective nature of scientific knowledge. In (...) an attempt to salvage perspectivism, I propose an alternative understanding based on a Syntactic Approach to theories. (shrink)

This paper explores varieties of scientific structuralism. Central to our investigation is the notion of `shared structure'. We begin with a description of mathematical structuralism and use this to point out analogies and disanalogies with scientific structuralism. Our particular focus is the semantic structuralist's attempt to use the notion of shared structure to account for the theory-world connection, this use being crucially important to both the contemporary structural empiricist and realist. We show why minimal scientific structuralism is, at the very (...) least, a powerful methodological standpoint. Our investigation also makes explicit what more must be added to this minimal structuralist position in order to address the theory-world connection, namely, an account of representation. (shrink)

ArgumentIn the theory-dominated view of scientific experimentation, all relations of theory and experiment are taken on a par; namely, that experiments are performed solely to ascertain the conclusions of scientific theories. As a result, different aspects of experimentation and of the relations of theory to experiment remain undifferentiated. This in turn fosters a notion of theory-ladenness of experimentation (TLE) that is toocoarse-grainedto accurately describe the relations of theory and experiment in scientific practice. By contrast, in this article, I suggest that (...) TLE should be understood as anumbrella conceptthat has different senses. To this end, I introduce a three-fold distinction among the theories of high-energy particle physics (HEP) as background theories, model theories, and phenomenological models. Drawing on this categorization, I contrast two types of experimentation, namely, “theory-driven” and “exploratory” experiments, and I distinguish between the “weak” and “strong” senses of TLE in the context of scattering experiments from the history of HEP. This distinction enables identifying the exploratory character of the deep-inelastic electron-proton scattering experiments – performed at the Stanford Linear Accelerator Center (SLAC) between the years 1967 and 1973 – thereby shedding light on a crucial phase of the history of HEP, namely, the discovery of “scaling,” which was the decisive step towards the construction of quantum chromo-dynamics as a gauge theory of strong interactions. (shrink)

General Relativity and the Standard Model often are touted as the most rigorously and extensively confirmed scientific hypotheses of all time. Nonetheless, these theories appear to have consequences that are inconsistent with evidence about phenomena for which, respectively, quantum effects and gravity matter. This paper suggests an explanation for why the theories are not disconfirmed by such evidence. The key to this explanation is an approach to scientific hypotheses that allows their actual content to differ from their apparent content. This (...) approach does not appeal to ceteris-paribus qualifiers or counterfactuals or similarity relations. And it helps to explain why some highly idealized hypotheses are not treated in the way that a thoroughly refuted theory is treated but instead as hypotheses with limited domains of applicability. (shrink)

How can mathematical models which represent the causal structure of the world incompletely or incorrectly have any scientific value? I argue that this apparent puzzle is an artifact of a realist emphasis on representation in the philosophy of modeling. I offer an alternative, pragmatic methodology of modeling, inspired by classic papers by modelers themselves. The crux of the view is that models developed for purposes other than explanation may be justified without reference to their representational properties.

Weisberg (2006) and Godfrey-Smith (2006, 2009) distinguish between two forms of theorising: data-driven ‘abstract direct representation’ and modeling. The key difference is that when using a data-driven approach, theories are intended to represent specific phenomena, so directly represent them, while models may not be intended to represent anything, so represent targets indirectly, if at all. The aim here is to compare and analyse these practices, in order to outline an account of model-based theorising that involves direct representational relationships. This is (...) based on the way that computational templates Humphreys (2002, 2004) are now used in cognitive neuroscience, and draws on the dynamic and tentative process of any kind of theory construction, and the idea of partial, purpose-relative representation. (shrink)

This paper starts with an intuitive notion of representational spaces, which is intended to provide an improved version of Kuhn's concept of paradigms. It then proceeds to study the following topics in terms of this new notion: incommensurability, paradigm change, explanation of anomalies, explanation of regularities, explanation of irregularities, and physical necessity. In the course of the investigation, "representational space" gets clarified and defined. It is envisaged that this new concept should throw light on many issues in the philosophy of (...) science. (shrink)

The point of this paper is to provide a principled framework for a naturalistic, interactivist-constructivist model of rational capacity and a sketch of the model itself, indicating its merits. Being naturalistic, it takes its orientation from scientific understanding. In particular, it adopts the developing interactivist-constructivist understanding of the functional capacities of biological organisms as a useful naturalistic platform for constructing such higher order capacities as reason and cognition. Further, both the framework and model are marked by the finitude and fallibility (...) that science attributes to organisms, with their radical consequences, and also by the individual and collective capacities to improve their performances that learning organisms display. Part A prepares the ground for the exposition through a critique of the dominant Western analytic tradition in rationalising science, followed by a brief exposition of the naturalist framework that will be employed to frame the construction. This results in two sets of guidelines for constructing an alternative. Part B provides the new conception of reason as a rich complex of processes of improvement against epistemic values, and argues its merits. It closes with an account of normativity and our similarly developing rational knowledge of it, including (reflexively) of reason itself. (shrink)

Between the fourth and the recent fifth IPCC report, science as well as policy making have made great advances in dealing with uncertainties in global climate models. However, the uncertainties public decision making has to deal with go well beyond what is currently addressed by policy makers and climatologists alike. It is shown in this paper that within an anthropocentric framework, a whole hierarchy of models from various scientific disciplines is needed for political decisions as regards climate change. Via what (...) is sometimes referred to as ‘uncertainty cascade’ in the technical literature, the uncertainties of various models accumulate in the input to political decision making. This paper aims to chart the uncertainties in the multi-disciplinary enterprise of current climate modeling in broad strokes. It is shown that the uncertainty cascade makes it impossible to quantify uncertainties in the form of probability estimates. Moreover the paper highlights how global climate models fail to provide probability estimates. A better treatment of the uncertainties of climate predictions on the political level would require an overhaul of the current IPCC practice that separates the various scientific fields in various working groups. (shrink)

The following article treats the 'applicational turn' of modern fluid dynamics as it set in at the beginning of the 20th century with Ludwig Prandtl's concept of the boundary layer. It seeks to show that there is much more to applying a theory in a highly mathematical field like fluid dynamics than deriving a special case from a general explanatory theory under particular antecedent conditions. In Prandtl's case, the decisive move was to introduce a model that provided a physical/causal conception (...) of viscous flow at high Reynolds numbers. It facilitated an approximate solution to the Navier-Stokes equations, which in turn gave rise to many special applications. After a detailed account of Prandtl's achievement, the article discusses the role of the physical model and its experimental and mathematical significance. It is shown that the mathematical simplification provided by the physical model greatly expanded the explanatory capacity of the theory which the Navier-Stokes equations alone could not provide. (shrink)

There are a number of research fields that exhibit a special connection to some particular activist movement. Typically in these cases, we observe a remarkable degree of personnel overlap between the movements and the scientific communities. I have two primary aims. First, I shall explore the reasons why there are such close entanglements between some research fields and some activist movements. I argue that both scientists and activists have specific epistemic interests that help explain why both practices tend to intersect (...) functionally. Second, I shall evaluate these entanglements from an epistemological point of view. Drawing on a conception of science that has science consisting of two essential tasks—asking significant questions and adequately answering them—, I argue that activists’ contribution to science is ambivalent with regard to the first task because they can help to overcome the unjust distribution of resources, but they can also be the source of new inequalities. Regarding the second task, I similarly suggest that activists can serve a useful purpose in science, since they tend to exhibit certain epistemically valuable properties and can help compensate for what I call collective biases, although in certain situations they tend to reinforce collective biases. (shrink)

This paper argues that, as all available accounts of how scientific and non-scientific goals might be distinguished rely upon distinctions as much in need of explication as the notion of scientific goals itself, naturalized accounts of science should reject the notion that there are characteristically scientific goals for a given time and place and instead countenance only the goals which happen to be had by individual scientists or their communities. This argument and the recommendation that follows from it are illustrated (...) by reference to Watson and Crick's discovery of the structure of DNA. (shrink)

This article serves as an introduction to the laws-of-biology debate. After introducing the main issues in an introductory section, arguments for and against laws of biology are canvassed in Section 2. In Section 3, the debate is placed in wider epistemological context by engaging a group of scholars who have shifted the focus away from the question of whether there are laws of biology and toward offering good accounts of explanation(s) in the biological sciences. Section 4 introduces two relatively new (...) pieces of science – metabolic scaling theory and ecological stoichiometry – that have not been topics of much discussion by philosophers but are relevant because they have at least some of the hallmarks of laws of nature. Section 5 concludes by pointing out that discovering laws of biology, if any there be, will not necessarily answer the questions raised by the debate in the first place: we will still want to know how biology compares to other sciences, how to characterize its systems and processes, and whether accounts in terms of laws always or usually constitute adequate explanations in various sciences. (shrink)

The ability to develop and use models to explain phenomena is a key component of the Next Generation Science Standards, and without examples of what modeling instruction looks like in the reality of classrooms, it will be difficult for us as a field to understand how to move forward in designing curricula that foreground the practice in ways that align with the epistemic commitments of modeling. In this article, we illustrate examples drawn from a model-based curriculum development project to problematize (...) and bring to the fore issues and tensions we observed through the course of modeling instruction. In doing so, we argue that instruction that is model-based may not be actualizing modeling as an epistemic practice to support student sensemaking. We suggest that this kind of enactment may be a result of the tensions between viewing models as content to be learned and modeling as a scientific practice in which the end products are not known ahead of time. We discuss the implications of our analysis for teacher learning and curriculum development. (shrink)

El presente escrito se propone presentar el modelo de tres niveles del conocimiento científico (datos, fenómenos y teorías) desde los recientes resultados de la filosofía de la ciencia obtenidos por dos perspectivas filosóficas particulares: el nuevo experimentalismo y el enfoque semántico de las teorías. Para ello contrasta los planteamientos principales de estas dos perspectivas con el modelo de dos niveles del conocimiento científico (observación y teoría) del positivismo lógico, que dominó el panorama de la filosofía de la ciencia en las (...) primeras seis décadas del siglo XX. (shrink)

The answer in a nutshell is: Yes, five years ago, but nobody has noticed. Nobody noticed because the majority of social scientists subscribe to one of the following views: (1) the ‘anomalous’ behaviour observed in standard prisoner’s dilemma or ultimatum game experiments has refuted standard game theory a long time ago; (2) game theory is flexible enough to accommodate any observed choices by ‘refining’ players’ preferences; or (3) it is just a piece of pure mathematics (a tautology). None of these (...) views is correct. This paper defends the view that GT as commonly understood is not a tautology, that it suffers from important (albeit very recently discovered) empirical anomalies, and that it is not flexible enough to accommodate all the anomalies in its theoretical framework. It also discusses the experiments that finally refuted game theory, and concludes trying to explain why it took so long for experimental game theorists to design experiments that could adequately test the theory. (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the (...) transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

Accounts of the relation between theories and models in biology concentrate on mathematical models. In this paper I consider the dual role of models as representations of natural systems and as a material basis for theorizing. In order to explicate the dual role, I develop the concept of a remnant model, a material entity made from parts of the natural system(s) under study. I present a case study of an important but neglected naturalist, Joseph Grinnell, to illustrate the extent to (...) which mundane practices in a museum setting constitute theorizing. I speculate that historical and sociological analyses of institutions can play a specific role in the philosophical analysis of model-building strategies. (shrink)

Exact sciences are described as sciences whose theories are formalized. These are contrasted to inexact sciences, whose theories are not formalized. Formalization is described as a broader category than mathematization, involving any form/content distinction allowing forms, e.g., as represented in theoretical models, to be studied independently of the empirical content of a subject-matter domain. Exactness is a practice depending on the use of theories to control subject-matter domains and to align theoretical with empirical models and not merely a state of (...) a science. Inexact biological sciences tolerate a degree of “mismatch” between theoretical and empirical models and concepts. Three illustrations from biological sciences are discussed in which formalization is achieved by various means: Mendelism, Weismannism, and Darwinism. Frege’s idea of a “conceptual notation” is used to further characterize the notion of a form/content distinction. (shrink)

The inclusion of the practice of “developing and using models” in the Framework for K-12 Science Education and in the Next Generation Science Standards provides an opportunity for educators to examine the role this practice plays in science and how it can be leveraged in a science classroom. Drawing on conceptions of models in the philosophy of science, we bring forward an agent-based account of models and discuss the implications of this view for enacting modeling in science classrooms. Models, according (...) to this account, can only be understood with respect to the aims and intentions of a cognitive agent, not solely in terms of how they represent phenomena in the world. We present this contrast as a heuristic—models of versus models for—that can be used to help educators notice and interpret how models are positioned in standards, curriculum, and classrooms. (shrink)

If we view the aim of feminist science as truthlikeness, instead of either absolute or relative truth, then we can explain the sense in which the feminist sciences bring an objective advance in knowledge without implicating One True Theory. I argue that a certain non-linguistic theory of truthlikeness is especially well-suited to this purpose and complements the feminist epistemologies of Harding, Haraway, and Longino.

Economic forms of analysis have penetrated to many disciplines in the last 30 years: political science, sociology, law, social and political philosophy, and so forth. We wish to extend the economic paradigm to certain problems in epistemology and the philosophy of science. Scientific agents, and scholarly inquirers generally, act in some ways like vendors, trying to "sell" their findings, theories, analyses, or arguments to an audience of prospective "buyers". The analogy with the marketplace is imperfect. The ideas or discoveries that (...) a scientist offers are not private goods in the economist's sense. Nonetheless, there are parallels with the marketplace that are worth exploring. (shrink)

Non-actual model systems discussed in scientific theories are compared to fictions in literature. This comparison may help with the understanding of similarity relations between models and real-world target systems. The ontological problems surrounding fictions in science may be particularly difficult, however. A comparison is also made to ontological problems that arise in the philosophy of mathematics.

A number of developmental psychologists have argued for a theory they call the theory theory - a theory of cognitive development that suggests that infants and small children make sense of their world by constructing cognitive representations that have many of the attributes of scientific theories. In this paper I argue that there are indeed close parallels between the activities of children and scientists, but that these parallels will be better understood if one recognizes that both scientists and children are (...) not so much theorists as model builders. (shrink)

Philosophers of science increasingly believe that much of science is concerned with understanding the mechanisms responsible for the production of natural phenomena. An adequate understanding of scientific research requires an account of how scientists develop and test models of mechanisms. This paper offers a general account of the nature of mechanical models, discussing the representational relationship that holds between mechanisms and their models as well as the techniques that can be used to test and refine such models. The analysis is (...) supported by study of two competing models of a mechanism of speech perception. (shrink)

In previous publications I have argued that much scientific activity should be thought of as involving the operation of distributed cognitive systems. Since these contributions to the cognitive study of science appear in venues not necessarily frequented by philosophers of science, I begin with a brief introduction to the notion of a distributed cognitive system. I then describe what I take to be an exemplary case of a scientific distributed cognitive system, the Hubble Space Telescope (HST). I do not here (...) reargue the case for conceiving of systems like the HST as distributed cognitive systems. Rather, I examine a question that arises once one has adopted the perspective of distributed cognitive systems, namely, the role of agency in a distributed cognitive system. Here I argue, contrary to several advocates of distributed cognitive systems, that we should regard the human components of distributed cognitive systems as the only sources of agency within such systems. In particular, we should not extend notions of agency to such systems as a whole. (shrink)

While agreeing that cognition in the sciences is usefully thought of as involving processes encompassing both humans and artifacts, I object to attributing cognitive states to extended systems. I argue that cognitive states, such as ?knowing?, should be confined to the human components of cognitive systems. My argument appeals to the large dimensions, both spatial and temporal, of many scientific cognitive systems, the existence of epistemic norms, and the need for agents in science.

Most recent philosophical thought about the scientific representation of the world has focused on dyadic relationships between language-like entities and the world, particularly the semantic relationships of reference and truth. Drawing inspiration from diverse sources, I argue that we should focus on the pragmatic activity of representing, so that the basic representational relationship has the form: Scientists use models to represent aspects of the world for specific purposes. Leaving aside the terms "law" and "theory," I distinguish principles, specific conditions, models, (...) hypotheses, and generalizations. I argue that scientists use designated similarities between models and aspects of the world to form both hypotheses and generalizations. (shrink)

I argue for an intentional conception of representation in science that requires bringing scientific agents and their intentions into the picture. So the formula is: Agents (1) intend; (2) to use model, M; (3) to represent a part of the world, W; (4) for some purpose, P. This conception legitimates using similarity as the basic relationship between models and the world. Moreover, since just about anything can be used to represent anything else, there can be no unified ontology of models. (...) This whole approach is further supported by a brief exposition of some recent work in cognitive, or usage-based, linguistics. Finally, with all the above as background, I criticize the recently much discussed idea that claims involving scientific models are really fictions. (shrink)