Scientific discourse is rife with passages that appear to be ordinary descriptions of systems of interest in a particular discipline. Equally, the pages of textbooks and journals are filled with discussions of the properties and the behavior of those systems. Students of mechanics investigate at length the dynamical properties of a system consisting of two or three spinning spheres with homogenous mass distributions gravitationally interacting only with each other. Population biologists study the evolution of one species procreating at a constant (...) rate in an isolated ecosystem. And when studying the exchange of goods, economists consider a situation in which there are only two goods, two perfectly rational agents, no restrictions on available information, no transaction costs, no money, and dealings are done immediately. Their surface structure notwithstanding, no competent scientist would mistake descriptions of such systems as descriptions of an actual system: we know very well that there are no such systems. These descriptions are descriptions of a model-system, and scientists use model-systems to represent parts or aspects of the world they are interested in. Following common practice, I refer to those parts or aspects as target-systems. What are we to make of this? Is discourse about such models merely a picturesque and ultimately dispensable façon de parler? This was the view of some early twentieth century philosophers. Duhem (1906) famously guarded against confusing model building with scientific theorizing and argued that model building has no real place in science, beyond a minor heuristic role. The aim of science was, instead, to construct theories, with theories understood as classificatory or representative structures systematically presented and formulated in precise symbolic.. (shrink)

Change is the fundamental idea of evolution. Explaining the extraordinary biological change we see written in the history of genomes and fossil beds is the primary occupation of the evolutionary biologist. Yet it is a surprising fact that for the majority of evolutionary research, we have rarely studied how evolution typically unfolds in nature, in changing ecological environments, over space and time. While ecology played a major role in the eventual acceptance of the population genetic viewpoint of evolution in the (...) synthetic era (circa 1918-1956), it held a lesser role in the development of evolutionary theory until the 1980s, when we began to systematically study the evolutionary dynamics of natural populations in space and time. As a result, early evolutionary theory was initially constructed in an abstract vacuum that was unrepresentative of evolution in nature. The subtle synthesis between ecology with evolutionary biology (eco-evo synthesis) over the past 40 years has progressed our knowledge of natural selection dynamics as they are found in nature, thus revealing how natural selection varies in strength, direction, form, and, more surprisingly, level of biological organization. Natural selection can no longer be reduced to lower levels of biological organization (i.e., individuals, selfish genes) over shorter timescales but should be expanded to include adaptation at higher levels and over longer timescales. Long-term and/or emergent evolutionary phenomena, such as multilevel selection or evolvability, have thus become tenable concepts within an evolutionary biology that embraces ecology and spatiotemporal change. Evolutionary biology is currently suspended at an intermediate stage of scientific progress that calls for the organization of all the recent knowledge revealed by the eco-evo synthesis into a coherent and unified theoretical framework. This is where philosophers of biology can be of particular use, acting as a bridge between the subdisciplines of biology and inventing new theoretical strategies to organize and accommodate the recent knowledge. Philosophers have recommended transitioning away from outdated philosophies that were originally derived from physics within the philosophical zeitgeist of logical positivism (i.e., monism, reductionism, and monocausation) and toward a distinct philosophy of biology that can capture the natural complexity of multifaceted biological systems within diverse ecosystems—one that embraces the emerging philosophies of pluralism, emergence, and multicausality. Therefore, I see recent advances in ecology, evolutionary biology, and the philosophy of biology as laying the groundwork for another major biological synthesis, what I refer to as the Second Synthesis because, in many respects, it is analogous to the aims and outcomes of the first major biological synthesis (but is notably distinct from the inorganic and contrived progressive movement known as the extended evolutionary synthesis). With the general development of a distinctive philosophy of science, biology has rightfully emerged as an autonomous science. Thus, while the first synthesis legitimized biology, the Second Synthesis autonomized biology and afforded biology its own philosophy, allowing biology to finally realize its full scientific potential. (shrink)

The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)

Policymakers who seek to make scientifically informed decisions are constantly confronted by scientific uncertainty and expert disagreement. This thesis asks: how can policymakers rationally respond to expert disagreement and scientific uncertainty? This is a work of non-ideal theory, which applies formal philosophical tools developed by ideal theorists to more realistic cases of policymaking under scientific uncertainty. I start with Bayesian approaches to expert testimony and the problem of expert disagreement, arguing that two popular approaches— supra-Bayesianism and the standard model of (...) expert deference—are insufficient. I develop a novel model of expert deference and show how it can deal with many of these problems raised for them. I then turn to opinion pooling, a popular method for dealing with disagreement. I show that various theoretical motivations for pooling functions are irrelevant to realistic policymaking cases. This leads to a cautious recommendation of linear pooling. However, I then show that any pooling method relies on value judgements, that are hidden in the selection of the scoring rule. My focus then narrows to a more specific case of scientific uncertainty: multiple models of the same system. I introduce a particular case study involving hurricane models developed to support insurance decision-making. I recapitulate my analysis of opinion pooling in the context of model ensembles, confirming that my hesitations apply. This motivates a shift of perspective, to viewing the problem as a decision theoretic one. I rework a recently developed ambiguity theory, called the confidence approach, to take input from model ensembles. I show how it facilitates the resolution of the policymaker’s problem in a way that avoids the issues encountered in previous chapters. This concludes my main study of the problem of expert disagreement. In the final chapter, I turn to methodological reflection. I argue that philosophers who employ the mathematical methods of the prior chapters are modelling. Employing results from the philosophy of scientific models, I develop the theory of normative modelling. I argue that it has important methodological conclusions for the practice of formal epistemology, ruling out popular moves such as searching for counterexamples. (shrink)

Scientific realism is a doctrine that was both in and out of fashion several times during the twentieth century. I begin by noting three presuppositions of a succinct characterization of scientific realism offered initially by the foremost critic in the latter part of the century, Bas van Fraassen. The first presupposition is that there is a fundamental distinction to be made between what is “empirical” and what is “theoretical”. The second presupposition is that a genuine scientific realism is committed to (...) their being “a literally true story of what the world is like”. The third presupposition is that there are methods for justifying a belief in the empirical adequacy of a theory which do not also suffice to justify beliefs in its literal truth. Each of these presuppositions raises a number of problems, some of which are quite old and others rather newer. In each case, I briefly review some of the old problems and then elaborate the newer problems. (shrink)

The incompatibility within the context of modeling cannot be established simpliciter. The fact that modeling is understood as an activity whose representational power can only be partially established, may minimize the supposed existence of incompatible models. Indeed, it is argued from perspectivism that incompatibility can be dissolved, meaning that it becomes trivial or simply false due to the inherently pragmatic and partial nature of the act of representation and modeling. From this perspective, incompatibility can only be a consequence of a (...) misunderstanding of the very nature of modeling and representation In this sense, in order to tackle this strategy at its root from perspectivism, we will first need to outline the maximal perspectivism thesis, attempting to identify the possible escape routes that perspectivism could find in order to explain incompatibility as an illusory incompatibility. Then, we will analyze Valence Bond Model and Molecular Model of covalent bonds, and we will conclude that the dissuasive strategies used to minimize and/or disregard incompatibility prove to be fruitless. (shrink)

Cancer is a paradigmatic case of a complex causal process; causes of cancer operate at a variety of temporal and spatial scales, and the respects in which these causes act and interact are diverse. There are, for instance, temporal order effects, organizational effects, structural effects, and dynamic relationships between causes operating at different temporal and spatial scales. Because of this complexity, models of cancer initiation and progression often involve deliberate choices to focus on one time scale, one causal pathway, or (...) one aspect of cancer’s dynamics. As in most of biology, modeling cancer involves simplification and idealization. At the same time, theoretical perspectives inform the construction of these models. Such perspectives might involve viewing cancer ‘as’ a genetic disease, metabolic disease, stem cell disease, an infectious disease, or a disease of tissue disorganization. This paper will argue that purportedly competing theoretical views of cancer are not at odds, but can be viewed as mutually informative. Models are most often developed in the service of asking very specific questions, and this requires limiting our view of the phenomena to a specific temporal or spatial scale, a particular cause, or a particular outcome, dynamic, or pattern. Thus, while some models may seem at odds, often they are simply concerned with different questions, or, they are complementary and mutually informative. I hope to bring this case to bear on debates among philosophers of science over perspectivism and realism, as well pluralism about the aims and scope of scientific theory. (shrink)

This paper draws on the phenomenological-hermeneutical approaches to philosophy of science to develop realist perspectivism, an integration of experimental realism and perspectivism. Specifically, the paper employs the distinction between “manifestation” and “phenomenon” and it advances the view that the evidence of a real entity is “explorable” in order to argue that instrumentally-mediated robust evidence indicates real entities. Furthermore, it underpins the phenomenological notion of the horizonal nature of scientific observation with perspectivism, so accounting for scientific pluralism even in the cases (...) of inconsistent models. Overall, realist perspectivism is proposed as the way to go for (phenomenologically-hermeneutically minded) philosophers of science. (shrink)

In this article I examine the perceptual metaphor at the heart of perspectivism, discussing three elements: partiality, interestedness, and interaction. I argue that perspectivists should drop the visual metaphor in favor of a haptic one. Because the sense of touch requires contact and purposeful exploration on the part of the perceiver, it is obvious that with touch one apprehends an extradermal reality in virtue of and not in spite of its interactive and interested nature. By analogy, perspectivists should investigate the (...) thesis that scientific representations inform us about the natural world in virtue of their interactive and interested qualities. (shrink)

In current debates, many philosophers of science have sympathies for the project of introducing a new approach to the scientific realism debate that forges a middle way between traditional forms of scientific realism and anti-realism. One promising approach is perspectivism. Although different proponents of perspectivism differ in their respective characterizations of perspectivism, the common idea is that scientific knowledge is necessarily partial and incomplete. Perspectivism is a new position in current debates but it does have its forerunners. Figures that are (...) typically mentioned in this context include Dewey, Feyerabend, Leibniz, Kant, Kuhn, and Putnam. Interestingly, to my knowledge, there exists no work that discusses similarities to the phenomenological tradition. This is surprising because here one can find systematically similar ideas and even a very similar terminology. It is startling because early modern physics was noticeably influenced by phenomenological ideas. And it is unfortunate because the analysis of perspectival approaches in the phenomenological tradition can help us to achieve a more nuanced understanding of different forms of perspectivism. The main objective of this paper is to show that in the phenomenological tradition one finds a well-elaborated philosophy of science that shares important similarities with current versions of perspectivism. Engaging with the phenomenological tradition is also of systematic value since it helps us to gain a better understanding of the distinctive claims of perspectivism and to distinguish various grades of perspectivism. (shrink)

Adopting the stage metaphor suggested in Brown’s review, and treating Scientific perspectivism as a play in five acts, I respond to his review as a playwright might respond to a generally favorable review. Taking the reader behind the stage door, I discuss the playwright’s intentions for each act, paying special attention to the expected audience for the play as a whole. The result, therefore, supplements the review from the standpoint of the playwright. It also provides answers to some of the (...) reviewer’s questions.Keywords: Matthew Brown; Scientific perspectivism. (shrink)

It is widely recognized that scientific theories are often associated with strictly inconsistent models, but there is little agreement concerning the epistemic consequences. Some argue that model inconsistency supports a strong perspectivism, according to which claims serving as interpretations of models are inevitably and irreducibly perspectival. Others argue that in at least some cases, inconsistent models can be unified as approximations to a theory with which they are associated, thus undermining this kind of perspectivism. I examine the arguments for perspectivism, (...) and contend that its strong form is defeasible in principle, not merely in special cases. The argument rests on the plausibility of scientific knowledge concerning non-perspectival, dispositional facts about modelled systems. This forms the basis of a novel suggestion regarding how to understand the knowledge these models afford, in terms of a contrastive theory of what-questions. (shrink)

My aim in this paper is to propose a way to study the role of perspectives in both the production and justification of experimental knowledge claims. My starting point for this will be Anjan Chakravartty’s claim that Ronald Giere’s perspectival account of the role of instruments in the production of such claims entails relativism in the form of irreducibly incompatible truths. This led Michela Massimi to argue that perspectivism, insofar as it wants to form a realist position, is only concerned (...) with the justification of such claims: whether they are produced reliably is, on her view, a perspective-independent fact of the matter. Following a suggestion by Giere on how scientists handle incompatible experimental results, I will then argue that Massimi’s perspectivism can be extended to also cover the production of such claims, without falling into relativism. I will elaborate this suggestion by means of Uljana Feest’s work on how scientists handle incompatible experimental results. I will argue that, if we reconceptualize perspectives as embodied and situated ways of going about in experimentation that can be made explicit through interpretation, we can obtain a fruitful understanding of the role of perspectives in both the production and justification of experimental knowledge. While this role is primarily exploratory, it can still allow for a substantial form of realism. (shrink)

Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate and (...) I argue that the objection does not stand up to scrutiny. This is because it is riddled with a number of conceptual inconsistencies. By attempting to resolve the tensions, I also draw several general lessons regarding the difficulties of applying abstraction and idealization in scientific practice. Finally, I argue that more care is needed only when speaking of abstraction and idealization in a context in which these concepts play an important role in an argument, such as that on mechanistic explanation. (shrink)

According to a widely held view, scientific modelling consists in entertaining a set of model descriptions that specify a model. Rather than studying the phenomenon of interest directly, scientists investigate the phenomenon indirectly via a model in the hope of learning about some of the phenomenon’s features. I call this view the description-driven modelling (DDM) account. I argue that although an accurate description of much of scientific research, the DDM account is found wanting as regards the mechanistic modelling found in (...) many branches of biology. By analysing research practices in cancer immunology concerning the development of mechanistic models of the process of cancer metastasis, this paper presents and argues for a complementary account of scientific modelling, herein called the experimentation-driven modelling (EDM) account. In EDM, scientists investigate a set of experimental systems and then integrate the results obtained from experiments into a mechanistic model. While EDM shares some key features with DDM, the two are epistemically very different approaches to research. (shrink)

This paper examines the relevance of philosophical work on consciousness to its scientific study. Of particular concern is the debate over whether consciousness can be naturalized, which is typically taken to have consequences for the prospects for its scientific investigation. It is not at all clear that philosophers of consciousness have properly identified and evaluated the assumptions about scientific activity made by both naturalization and anti- naturalization projects. I argue that there is good reason to think that some of the (...) assumptions about physicalism and explanation made by the parties to the debate are open to serious doubt. Thus this paper is an invitation for those inquiring into whether consciousness can be naturalized to more carefully consider the expected payoff of such efforts. (shrink)

Simulation and Similarity: Using Models to Understand the World is an account of modeling in contemporary science. Modeling is a form of surrogate reasoning where target systems in the natural world are studied using models, which are similar to these targets. My book develops an account of the nature of models, the practice of modeling, and the similarity relation that holds between models and their targets. I also analyze the conceptual tools that allow theorists to identify the trustworthy aspects of (...) models. Taken as a whole, I try to account for the ways that modeling is actually practiced by theorists, while abstracting sufficiently to understand the similarities and differences among examples of concrete, mathematical, and computational modeling.I am grateful to Wendy Parker, Jay Odenbaugh, and Bill Wimsatt for their careful and interesting reading of my book, as well as their constructive criticisms. Although I naturally disagree with some of their critiques, I have learned much .. (shrink)

Many explanations in physics rely on idealized models of physical systems. These explanations fail to satisfy the conditions of standard normative accounts of explanation. Recently, some philosophers have claimed that idealizations can be used to underwrite explanation nonetheless, but only when they are what have variously been called representational, Galilean, controllable or harmless idealizations. This paper argues that such a half-measure is untenable and that idealizations not of this sort can have explanatory capacities.

Highly idealized models may serve various epistemic functions, notably explanation, in virtue of representing the world. Inferentialism provides a prima facie compelling characterization of what constitutes the representation relation. In this paper, I argue that what I call factive inferentialism does not provide a satisfactory solution to the puzzle of model-based—factive—explanation. In particular, I show that making explanatory counterfactual inferences is not a sufficient guide for accurate representation, factivity, or realism. I conclude by calling for a more explicit specification of (...) model-world mismatches and properties imputation. (shrink)

In a recent special issue dedicated to Dani Rodrik’s (2015) influential monograph Economics Rules, Grüne-Yanoff and Marchionni (2018) raise a potentially damning problem for Rodrik’s suggestion that progress in economics should be understood and measured laterally, by a continuous expansion of new models. They argue that this could lead to an “embarrassment of riches”, i.e. the rapid expansion of our model library to such an extent that we become unable to choose between the available models, and thus needs to be (...) solved to make ‘model pluralism’ viable. Drawing on Veit’s (2019a) ‘model pluralism’ account, this paper argues that model pluralism as a thesis about the relationship between science and nature undermines the very idea of a general model selection framework for policy making. (shrink)

In recent years, the biomedical field has witnessed the emergence of novel tools and modelling techniques driven by the rise of the so-called Big Data. In this paper, we address the issue of predictability in biomedical Big Data models of cancer patients, with the aim of determining the extent to which computationally driven predictions can be implemented by medical doctors in their clinical practice. We show that for a specific class of approaches, called k-Nearest Neighbour algorithms, the ability to draw (...) predictive inferences relies on a geometrical, or topological, notion of similarity encoded in a well-defined metric, which determines how close the characteristics of distinct patients are on average. We then discuss the conditions under which the relevant models can yield reliable and trustworthy predictive outcomes. (shrink)

The similarity view of scientific representation has recently been subjected to strong criticism. Much of this criticism has been directed against a ?naive? similarity account, which tries to explain representation solely in terms of similarity between scientific models and the world. This article examines the more sophisticated account offered by the similarity view's leading proponent, Ronald Giere. In contrast to the naive account, Giere's account appeals to the role played by the scientists using a scientific model. A similar move is (...) often made by defenders of resemblance theories of depiction, who invoke the role played by the artist, or by the viewers of a painting. In this article I look to debates over depiction to assess the difficulties facing those who wish to defend the similarity view of scientific representation. I then turn to examine Giere's account. Ultimately, I argue, this account is unsuccessful: while appealing to the role of scientists offers a promising way to defend the similarity view, Giere's own account does not capture what it is that scientists do when they use a model to represent the world. (shrink)

Call a bit of scientific discourse a description of a missing system when (i) it has the surface appearance of an accurate description of an actual, concrete system (or kind of system) from the domain of inquiry, but (ii) there are no actual, concrete systems in the world around us fitting the description it contains, and (iii) that fact is recognised from the outset by competent practitioners of the scientific discipline in question. Scientific textbooks, classroom lectures, and journal articles abound (...) with such passages; and there is a widespread practice of talking and thinking as though there are systems which fit the descriptions they contain perfectly, despite the recognition that no actual, concrete systems do so—call this the face value practice. There are, furthermore, many instances in which philosophers engage in the face value practice whilst offering answers to epistemological and methodological questions about the sciences. Three questions, then: (1) How should we interpret descriptions of missing systems? (2) How should we make sense of the face value practice? (3) Is there a set of plausible answers to (1) and (2) which legitimates reliance on the face value practice in our philosophical work, and can support the weight of the accounts which are entangled with that practice? In this paper I address these questions by considering three answers to the first: that descriptions of missing systems are straightforward descriptions of abstract objects, that they are indirect descriptions of “property-containing” abstracta, and that they are (in a different way) indirect descriptions of mathematical structures. All three proposals are present in the literature, but I find them wanting. The result is to highlight the importance of developing a satisfactory understanding of descriptions of missing systems and the face value practice, to put pressure on philosophical accounts which rely on the practice, and to help us assess the viability of certain approaches to thinking about models, theory structure, and scientific representation. (shrink)

Many in philosophy understand truth in terms of precise semantic values, true propositions. Following Braun and Sider, I say that in this sense almost nothing we say is, literally, true. I take the stand that this account of truth nonetheless constitutes a vitally useful idealization in understanding many features of the structure of language. The Fregean problem discussed by Braun and Sider concerns issues about application of language to the world. In understanding these issues I propose an alternative modeling tool (...) summarized in the idea that inaccuracy of statements can be accommodated by their imprecision. This yields a pragmatist account of truth, but one not subject to the usual counterexamples. The account can also be viewed as an elaborated error theory. The paper addresses some prima facie objections and concludes with implications for how we address certain problems in philosophy. (shrink)

Knowledge requires truth, and truth, we suppose, involves unflawed representation. Science does not provide knowledge in this sense but rather provides models, representations that are limited in their accuracy, precision, or, most often, both. Truth as we usually think of it is an idealization, one that serves wonderfully in most ordinary applications, but one that can terribly mislead for certain issues in philosophy. This article sketches how this happens for five important issues, thereby showing how philosophical method must take into (...) account the idealized nature of our familiar conception of truth. (shrink)

In this paper I show how certain requirements must be set on any tenable account of scientific representation, such as the requirement allowing for misrepresentation. I then continue to argue that two leading accounts of scientific representation— the inferential account and the interpretational account—are flawed for they do not satisfy such requirements. Through such criticism, and drawing on an analogy from non-scientific representation, I also sketch the outline of a superior account. In particular, I propose to take epistemic representations to (...) be intentional objects that come with reference, semantic contents and a representational code, and I identify faithful representations as representations that act as guides to ontology. (shrink)

Scientific models occupy centre stage in scientific practice. Correspondingly, in recent literature in the philosophy of science, scientific models have been a focus of research. However, little attention has been paid so far to the ontology of scientific models. In this essay, I attempt to clarify the issues involved in formulating an informatively rich ontology of scientific models. Although no full-blown theory—containing all ontological issues involved—is provided, I make several distinctions and point to several characteristic properties exhibited by scientific models (...) that are relevant for individuating scientific models. (shrink)

This paper argues for theoretical modeling and model-construction as central types of activities that philosophers of social ontology engage in. This claim is defended through a detailed case study and revisionary interpretation of Raimo Tuomela’s account of the we-perspective. My interpretation is grounded in Ronald Giere’s account of scientific models, and argued to be compatible with, but less demanding than Tuomela’s own description of his account as a philosophical theory of the social world. My approach is also suggested to be (...) applicable to many other methodologically naturalist accounts of collective intentionality and social ontology. (shrink)

The epistemic conception of scientific progress equates progress with accumulation of scientific knowledge. I argue that the epistemic conception fails to fully capture scientific progress: theoretical progress, in particular, can transcend scientific knowledge in important ways. Sometimes theoretical progress can be a matter of new theories ‘latching better onto unobservable reality’ in a way that need not be a matter of new knowledge. Recognising this further dimension of theoretical progress is particularly significant for understanding scientific realism, since realism is naturally (...) construed as the claim that science makes theoretical progress. Some prominent realist positions are best understood in terms of commitment to theoretical progress that cannot be equated with accumulation of scientific knowledge. (shrink)

The epistemic conception of scientific progress equates progress with accumulation of scientific knowledge. I argue that the epistemic conception fails to fully capture scientific progress: theoretical progress, in particular, can transcend scientific knowledge in important ways. Sometimes theoretical progress can be a matter of new theories ‘latching better onto unobservable reality’ in a way that need not be a matter of new knowledge. Recognising this further dimension of theoretical progress is particularly significant for understanding scientific realism, since realism is naturally (...) construed as the claim that science makes theoretical progress. Some prominent realist positions are best understood in terms of commitment to theoretical progress that cannot be equated with accumulation of scientific knowledge. (shrink)

I erect a framework within the semantic view of theories for explaining the empirical success of internally inconsistent models and theories, with scientific realism in mind. The framework is an instance of the ‘content-driven’ approach to inconsistency, advocated by both Norton (Philos Sci 54:327–350, 1987) and Smith (Stud Hist Philos Sci 19:429–445, 1988a, In: Fine A, Leplin J (eds) PSA1988, 1988b), whose ideas my analysis aims to clarify and substantiate.

I review prominent historical arguments against scientific realism to indicate how they display a systematic overshooting in the conclusions drawn from the historical evidence. The root of the overshooting can be located in some critical, undue presuppositions regarding realism. I will highlight these presuppositions in connection with both Laudan’s ‘Old induction’ and Stanford’s New induction, and then delineate a minimal realist view that does without the problematic presuppositions.

Given that scientific realism is based on the assumption that there is a connection between a model's predictive success and its truth, and given the success of multiple incompatible models in scientific practice, the realist has a problem. When the different models can be shown to arise as different approximations to a unified theory, however, one might think the realist to be able to accommodate such cases. I discuss a special class of models and argue that a realist interpretation has (...) to understand these models of a system as ‘ perspectival ’, in close analogy to different spatial perspectives onto the same object. For this sort of case, I also respond to Morrison's recent claim that in the process of unifying models into an overarching theory, explanatory and descriptive power are lost, leaving the unified theory with less of a claim to a realist interpretation than the models themselves. Introduction Perspectival models from singular perturbation problems Unification of perspectives without losses of explanatory power Perspectives as different levels of a system Perspectival models, idealizations and pluralism. (shrink)

Naturalism in the philosophy of science has proceeded differently than the familiar forms of meta-philosophical naturalism in other sub-fields, taking its cues from “science as we know it” (Cartwright in The Dappled World, Oxford University Press, Oxford, 1999, p. 1) rather than from a philosophical conception of “the Scientific Image.” Its primary focus is scientific practice, and its philosophical analyses are complementary and accountable to empirical studies of scientific work. I argue that naturalistic philosophy of science is nevertheless criterial for (...) other versions of meta-philosophical naturalism; relying on a conflicting conception of scientific understanding would constitute a “first philosophy” imposed on the sciences. Moreover, naturalistic philosophy of science provides the basis for a “radically” naturalistic alternative to the familiar forms of orthodox or liberal naturalism. Goodman, Sellars and Hempel had previously challenged empiricist scruples against causal connections or nomological necessity by arguing that scientific concepts already had modal import. The radical naturalism I defend similarly challenges meta-philosophical naturalists’ conception of the Scientific Image as anormative, and instead shows how the normativity of scientific understanding in practice is a scientifically intelligible natural phenomenon. This account then provides a basis for naturalistic reflection on how other practices and normative concerns fit together with the best scientific understanding of human ways of life. (shrink)

The interpretive plasticity of Kuhn’s philosophical work has been reinforced by readings informed by other philosophical, historiographic or sociological projects. This paper highlights several aspects of Kuhn’s work that have been neglected by such readings. First, Kuhn’s early contribution to several subsequent philosophical developments has been unduly neglected. Kuhn’s postscript discussion of “exemplars” should be recognized as one of the earliest versions of a conception of theories as “mediating models.” Kuhn’s account of experimental practice has also been obscured by readings (...) that assimilate his views to Quinean holism. Second, three distinctive Kuhnian themes have been insufficiently recognized. Kuhn’s challenge to received philosophical views has been domesticated by reading him as offering an alternative conception of scientific knowledge. Kuhn is better understood as rejecting knowledge-centric accounts altogether, in favor of understanding the practice of research. Kuhn’s conception of that activity, as conceptual “articulation,” has accordingly also not been given its due. Finally, Kuhn’s career-long insistence on the mutual accountability of philosophy of science and the philosophy of mind and language calls attention to the extent to which these fields have now drifted apart. (shrink)

There is a long-standing debate in the philosophy of action and the philosophy of science over folk psychological explanations of human action: do the (perhaps implicit) generalizations that underwrite such explanations purport to state contingent, empirically established connections between beliefs, desires, and actions, or do such generalizations serve rather to define, at least in part, what it is to have a belief or desire, or perform an action? This question has proven important because of certain traditional assumptions made about the (...) role of law-statements in scientific explanations. According to this tradition, law-statements take the form of generalizations, and the laws we find in well-established sciences are contingent and empirical; as such, if the kinds of generalizations at work in folk psychological explanations of human action act like definitions, or state conceptual connections, then such generalizations could not play the kind of explanatory role we find in mature sciences. This paper argues that the aforementioned way of framing the debate reflects a still powerful but impoverished conception of the role laws play in scientific explanations, a conception that, moreover, cannot be reconciled with a good deal of actual scientific practice. When we update the philosophy of science, we find the concerns that are raised for folk psychological explanations largely evaporate or are found not to be specific to such explanations. (shrink)

This paper proposes a novel distinction between accounts of scientific representation: it distinguishes thin accounts from thick accounts. Thin accounts focus on the descriptive aspect of representation whereas thick accounts acknowledge the evaluative aspect of representation. Thin accounts focus on the question of what a representation as such is. Thick accounts start from the question of what an adequate representation is. In this paper, I give two arguments in favor of a thick account, the Argument of the Epistemic Aims of (...) Modeling and the Argument of the Normativity of the Practice of Modeling. I also discuss possible objections to a thick account: the Argument from Misrepresentation and the Objections from Model Testing. The conclusion will be that the arguments on balance support a thick account of representation. (shrink)

Making sense of modeling: beyond representation Content Type Journal Article Category Original paper in Philosophy of Science Pages 335-352 DOI 10.1007/s13194-011-0032-8 Authors Isabelle Peschard, Philosophy Department, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number 3.

This paper is a critical response to Andreas Bartels’ sophisticated defense of a structural account of scientific representation. We show that, contrary to Bartels’ claim, homomorphism fails to account for the phenomenon of misrepresentation. Bartels claims that homomorphism is adequate in two respects. First, it is conceptually adequate, in the sense that it shows how representation differs from misrepresentation and non-representation. Second, if properly weakened, homomorphism is formally adequate to accommodate misrepresentation. We question both claims. First, we show that homomorphism (...) is not the right condition to distinguish representation from misrepresentation and non-representation: a “representational mechanism” actually does all the work, and it is independent of homomorphism – as of any structural condition. Second, we test the claim of formal adequacy against three typical kinds of inaccurate representation in science which, by reference to a discussion of the notorious billiard ball model, we define as abstraction, pretence, and simulation. We first point out that Bartels equivocates between homomorphism and the stronger condition of epimorphism, and that the weakened form of homomorphism that Bartels puts forward is not a morphism at all. After providing a formal setting for abstraction, pretence and simulation, we show that for each morphism there is at least one form of inaccurate representation which is not accommodated. We conclude that Bartels’ theory – while logically laying down the weakest structural requirements – is nonetheless formally inadequate in its own terms. This should shed serious doubts on the plausibility of any structural account of representation more generally. (shrink)

According to an adequacy-for-purpose view, models should be assessed with respect to their adequacy or fitness for particular purposes. Such a view has been advocated by scientists and philosophers...

This paper critically examines Weisberg’s weighted feature matching account of model-world similarity. A number of concerns are raised, including that Weisberg provides an account of what underlies scientific judgments of relative similarity, when what is desired is an account of the sorts of model-target similarities that are necessary or sufficient for achieving particular types of modeling goal. Other concerns relate to the details of the account, in particular to the content of feature sets, the nature of shared features and the (...) assumed independence of feature weightings. (shrink)

Two different programmes are in the business of explicating accuracy—the truthlikeness programme and the epistemic utility programme. Both assume that truth is the goal of inquiry, and that among inquiries that fall short of realizing the goal some get closer to it than others. Truthlikeness theorists have been searching for an account of the accuracy of propositions. Epistemic utility theorists have been searching for an account of the accuracy of credal states. Both assume we can make cognitive progress in an (...) inquiry even while falling short of the target. I show that the prospects for combining these two programmes are bleak. A core accuracy principle, proximity, that is universally embraced within the truthlikeness programme turns out to be incompatible with a central principle within the epistemic utility programme, namely propriety. 1Truthlikeness and Epistemic Utility 2Inquiries 3Accuracy for Propositions 4Proximity 5Accuracy for Credal States 6Propriety 7Proximity for Credal States 8Extensionality 9Admissible Weightings 10Propriety Violates Proximity 11Possible Responses 11.1Retreat to convexity 11.2Reject boundedness 11.3Reject additivity 12The Upshot. (shrink)

Theories of verisimilitude have routinely been classified into two rival camps—the content approach and the likeness approach—and these appear to be motivated by very different sets of data and principles. The question thus naturally arises as to whether these approaches can be fruitfully combined. Recently Zwart and Franssen (Synthese 158(1):75–92, 2007) have offered precise analyses of the content and likeness approaches, and shown that given these analyses any attempt to meld content and likeness orderings violates some basic desiderata. Unfortunately their (...) characterizations of the approaches do not embrace the paradigm examples of those approaches. I offer somewhat different characterizations of these two approaches, as well as of the consequence approach (Schurz and Weingartner (Synthese 172(3):415–436, 2010) which happily embrace their respective paradigms. Finally I prove that the three approaches are indeed compatible, but only just, and that the cost of combining them is too high. Any account which combines the strictures of what I call the strong likeness approach with the demands of either the content or the consequence approach suffers from precisely the same defect as Popper’s—namely, it entails the trivialization of truthlikeness. The downside of eschewing the strong likeness constraints and embracing the content constraints alone is the underdetermination of the concept of truthlikeness. (shrink)

I discuss changes of perspective of four kinds in science and about science. Section 2 defends a perspectival nonrealism—something akin to Giere’s perspectival realism but not a realism—against the idea of complete, “Copernican” objectivity. Section 3 contends that there is an inverse relationship between epistemological conservatism and scientific progress. Section 4 casts doubt on strong forms of scientific realism by taking a long-term historical perspective that includes future history. Section 5 defends a partial reversal in the status of so-called context (...) of discovery and context of justification. Section 6 addresses the question of how we can have scientific progress without scientific realism—how progress is possible without the accumulation of representational truth. The overall result is a pragmatic instrumentalist perspective on the sciences and how to study them philosophically, one that contains a kernel of realism—instrumental realism. (shrink)