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)

Agent-based accounts of scientific representation all agree that the representational relationship is constituted by the actions of scientists. Despite this agreement, there are several differences in how agent-based accounts describe scientific representation. In this essay, I argue that these differences do not undercut the compatibility between the accounts. I make my argument by examining the nature of human agency and demonstrating that scientific, representational actions are multiply describable. I then argue that the differences between the accounts are valuable because they (...) help to bring different parts of the representational practices of science into greater focus. (shrink)

How is scientific knowledge used, adapted, and extended in deriving phenomena and real-world systems? This paper aims at developing a general account of 'applying science' within the exemplar-based framework of Data-Oriented Processing (DOP), which is also known as Exemplar-Based Explanation (EBE). According to the exemplar-based paradigm, phenomena are explained not by deriving them all the way down from theoretical laws and boundary conditions but by modelling them on previously derived phenomena that function as exemplars. To accomplish this, DOP proposes to (...) maintain a corpus of derivation trees of previous phenomena together with a matching algorithm that combines subtrees from the corpus to derive new phenomena. By using a notion of derivational similarity, a new phenomenon can be modelled as closely as possible on previously explained phenomena. I will propose an instantiation of DOP which integrates theoretical and phenomenological modelling and which generalises over various disciplines, from fluid mechanics to language technology. I argue that DOP provides a solution for what I call Kuhn's problem and that it redresses Kitcher's account of explanation. (shrink)

This paper deals with the problem of derivational redundancy in scientific explanation, i.e. the problem that there can be extremely many different explanatory derivations for a natural phenomenon while students and experts mostly come up with one and the same derivation for a phenomenon (modulo the order of applying laws). Given this agreement among humans, we need to have a story of how to select from the space of possible derivations of a phenomenon the derivation that humans come up with. (...) In this paper we argue that the problem of derivational redundancy can be solved by a new notion of “shortest derivation”, by which we mean the derivation that can be constructed by the fewest (and therefore largest) partial derivations of previously derived phenomena that function as “exemplars”. We show how the exemplar-based framework known as “Data-Oriented Parsing” or “DOP” can be employed to select the shortest derivation in scientific explanation. DOP’s shortest derivation of a phenomenon maximizes what is called the “derivational similarity” between a phenomenon and a corpus of exemplars. A preliminary investigation with exemplars from classical and fluid mechanics shows that the shortest derivation closely corresponds to the derivations that humans construct. Our approach also proposes a concrete solution to Kuhn’s problem of how we know on which exemplar a phenomenon can be modeled. We argue that humans model a phenomenon on the exemplar that is derivationally most similar to the phenomenon, i.e. the exemplar from which the largest subtree(s) can be used to derive the phenomenon. (shrink)

In the course of researching the question ‘What does it mean for knowledge to grow?’, the author has developed a large and unique compendium of components, some of which are knowledge systems that serve as research and creativity support systems. The self-modifying, self-effecting creative process and the results of developing and working with these systems, using novel methods and drawing on eclectic sources, is discussed.

Some have argued that chaos, with its characteristic feature of sensitive dependence on initial conditions, should be sensitive to quantum events (Hobbs 1991; Kellert 1993). The upshot of these arguments is that classical chaos would then be indeterministic, but such a conclusion is dependent on which versions of quantum theory and solutions to the measurement problem are adopted (Bishop and Kronz 1999). In this essay, the relationship between quantum mechanics and sensitive dependence is placed in the general context of nonlinear (...) dynamics and is investigated in detail, revealing further limitations and quali…cations on these sensitive dependence arguments. (shrink)

Recently some philosophers have urged that connectionist artificial intelligence is (potentially) eliminative for the propositional attitudes of folk psychology. At the same time, however, these philosophers have also insisted that since philosophy of science has failed to provide criteria distinguishing ontologically retentive from eliminative theory changes, the resulting eliminativism is not principled. Application of some resources developed within the semantic view of scientific theories, particularly recent formal work on the theory reduction relation, reveals these philosophers to be wrong in this (...) second contention, yet by and large correct in the first. (shrink)

Science advances by means of argument and debate. Based on a formal model of complex argumentation, this article assesses the interplay between evidential and inferential drivers in scientific controversy, and explains, in particular, why both evidence accumulation and argumentation are veritistically valuable. By improving the conditions for applying veritistic indicators , novel evidence and arguments allow us to distinguish true from false hypotheses more reliably. Because such veritistic indicators also underpin inductive reasoning, evidence accumulation and argumentation enhance the reliability of (...) inductive inference, for example, inference to the best explanation. 1 Introduction2 Theory of Dialectical Structures3 Debate Simulations4 From Evidence and Arguments to Truth: The First Route5 From Evidence to Truth: The Second Route6 Conclusion. (shrink)

Climate models don’t give us probabilistic forecasts. To interpret their results, alternatively, as serious possibilities seems problematic inasmuch as climate models rely on contrary-to-fact assumptions: why should we consider their implications as possible if their assumptions are known to be false? The paper explores a way to address this possibilistic challenge. It introduces the concepts of a perfect and of an imperfect credible world, and discusses whether climate models can be interpreted as imperfect credible worlds. That would allow one to (...) use models for possibilistic prediction and salvage widespread scientific practice. (shrink)

This paper argues for the theoretical and practical validity of similarity as a useful epistemological tool in scientific knowledge generation, specifically in chemistry. Classical analyses of similarity in philosophy of science do not account for the concept’s practical significance in scientific activities. We recur to examples from chemistry to counter the claim of authors like Quine or Goodman to the effect that similarity must be excluded from scientific practices . In conclusion we argue that more recent conceptualizations of the notion (...) of similarity, particularly Giere’s one, are appropriate for a philosophical analysis that considers scientific practices on equal terms with scientific theory. (shrink)

Probabilistic realism and syntactical positivism were two among outdated theories that Feigl criticised on account of their semantical poverty. In this paper, I argue that a refined version of probabilistic realism, which relies on what Feigl specified as the pragmatic description of the symbolic behaviour of scientists’ estimations and foresight, is defendable. This version of statistical realism does not need to make the plausibility of realist thesis dependent on the conventional acceptance of a constructed semantic metalanguage. I shall rely on (...) the Prediction Error Minimisation theory to support my probabilistic version of realism with a scientifically-informed and naturalistically plausible statistical account of the theories-world relationship which has a pragmatic ring to it. (shrink)

The paper aims to provide a detailed assessment of Tim Crane’s recent invocation of the notion of scientific models in the way of dealing with the issue of the brain’s representational states. In this paper, I assess Crane’s proposal under a charitable and a less charitable reading. I argue that Crane’s use of scientific models is at best compatible with his expression of psychological realism. However, Crane’s use of model-based strategy by no means underlay, support, or strengthen his psychological realism. (...) Rather, traditional reasons from the metaphysics of mind, acting quite separately from empirical scientific reasons, must be used to support this realism, and Crane has merely removed the threat posed to these metaphysical arguments by the existence of the so-called mereological fallacy in empirical neuroscience. Therefore, while he has saved the neuroscientific language from philosophical attack, he has perhaps even strengthened the divide between neuroscience and philosophy. I conclude the paper by outlining the sketch of a broadbrush scientifically informed strategy for defending psychological realism. (shrink)

This paper offers an interpretation of Quine's naturalized epistemology through the lens of Jaegwon Kim's influential critique of the same. Kim argues that Quine forces a false choice between traditional deductivist foundationalism and naturalized epistemology and contends that there are viable alternative epistemological projects. However it is suggested that Quine would reject these alternatives by reference to the same fundamental principles (underdetermination, indeterminacy of translation, extensionalism) that led him to reject traditional epistemology and propose naturalism as an alternative. Given this (...) interpretation of Quine, it is essential that a successful critic of naturalism also examine Quine's aforementioned principles. The divide between naturalist and nonnaturalist epistemology turns out to be defined by the divide between more fundamental naturalist and nonnaturalist approaches to semantics. (shrink)

We clarify the notions scientific process and social process with structuralist means. Three questions are formulated, and answered in the structuralistic, set-theoretic framework. What is a scientific process, and a process in science? What can be meant by a non-social process? In which sense a non-social process can be a part of a scientific process in social science? We are specifically interested in social processes. Our answers use the notion of the generalized subset relation applied to set-theoretical structures, and the (...) set of structuralistically reconstructed empirical theories. (shrink)

: This paper contains the analysis of nine interviews with UK scientists on the topic of scientific models. Scientific models are an important, very controversially discussed topic in philosophy of science. A reasonable expectation is that philosophical conceptions of models ought to be in agreement with scientific practice. Questioning practicing scientists on their use of and views on models provides material against which philosophical positions can be measured.

Social Epistemology, as formulated by Steve Fuller, is based on the suggestion that rational knowledge policy must be held accountable to ‘brute facts’ about the nature of our human cognitive pursuits, whatever these may be. One difficulty for Fuller concerns the conception of the social which underwrites social epistemology. I argue that social epistemology conflates the social with human psychological properties that are available for public scrutiny and, accordingly, that social epistemology is best viewed as a brand of psychologism. Though (...) Fuller's proposal signifies an important step in the ongoing attempt by scholars to eradicate the last traces of Descartes' epistemological device of a disembodiedres cogitans, I conclude that his conception of the social is too weak to serve as the basis for a socially-embedded discipline in anything but name only. (shrink)

A survey of models in immunology is conducted and distinct kinds of models are characterized based on whether models are material or conceptual, the distinctiveness of their epistemic purpose, and the criteria for evaluating the goodness of a model relative to its intended purpose. I argue that the diversity of models in interdisciplinary fields such as immunology reflects the fact that information about the phenomena of interest is gathered from different sources using multiple methods of investigation. To each model is (...) attached a description specifying how information about a phenomenon of interest has been acquired, highlighting points of commonality and difference between the methodological and epistemic histories of the information encapsulated in different models. These points of commonality and difference allow investigators to integrate findings from different models into more comprehensive explanatory accounts, as well as to troubleshoot anomalies and faulty accounts by going back to the original building blocks. (shrink)

First, I discuss the older “theory-centered” and the more recent semantic conception of scientific theories. I argue that these two perspectives are nothing more than terminological variants of one another. I then offer a new theory-centered view of scientific theories. I argue that this new view captures the insights had by each of these earlier views, that it’s closer to how scientists think about their own theories, and that it better accommodates the phenomenon of inconsistent scientific theories.

It is no longer necessary to defend current historiography of psychology against the strictures aimed at its early text book incarnations in the 1960s and 1970s. At that time, Robert Young and others denigrated then standard textbook histories of psychology for their amateurism and their justifications propaganda for specific standpoints in current psychology, disguised as history. Since then, at least some textbooks writers and working historians of psychology have made such criticisms their own. The demand for textbook histories continues nonetheless. (...) Psychology, at least in the United States, remains the only discipline that makes historical representations of itself in the form of “history and systems” courses an official part of its pedagogical canon, required, interestingly enough, for the license in clinical practice.1In the meantime, the professionalization of scholarship in history of psychology has proceeded apace. All of the trends visible in historical and social studies of other sciences, as well as in general cultural and intellectual history, are noe present in the historical study of psychology. Yet despite the visibility and social importance of psychology's various applications, and the prominence of certain schools of psychological thought such as behaviorism and psychoanalysis in contemporary cultural and political debate, the historiography of psychology has continued to hold a marginal position in history and social studies of science. (shrink)

There is nowadays consensus in the community of didactics of science regarding the need to include the philosophy of science in didactical research, science teacher education, curriculum design, and the practice of science education in all educational levels. Some authors have identified an ever-increasing use of the concept of ‘theoretical model’, stemming from the so-called semantic view of scientific theories. However, it can be recognised that, in didactics of science, there are over-simplified transpositions of the idea of model. In this (...) sense, contemporary philosophy of science is often blurred or distorted in the science education literature. In this paper, we address the discussion around some meta-theoretical concepts that are introduced into didactics of science due to their perceived educational value. We argue for the existence of a ‘semantic family’, and we characterise four different versions of semantic views existing within the family. In particular, we seek to contribute to establishing a model-based didactics of science mainly supported in this semantic family. (shrink)

Designing models of complex phenomena is a difficult task in engineering that can be tackled by composing a number of partial models to produce a global model of the phenomena. We propose to embed the partial models in software agents and to implement their composition as a cooperative negotiation between the agents. The resulting multiagent system provides a global model of a phenomenon. We applied this approach in modelling two complex physiological processes: the heart rate regulation and the glucose-insulin metabolism. (...) Beyond the effectiveness demonstrated in these two applications, the idea of using models associated to software agents to give reason of complex phenomena is in accordance with current tendencies in epistemology, where it is evident an increasing use of computational models for scientific explanation and analysis. Therefore, our approach has not only a practical, but also a theoretical significance: agents embedding models are a technology suitable both to representing and to investigating reality. (shrink)

I develop an account of scientific representations building on Charles S. Peirce's rich, and still underexplored, notion of iconicity. Iconic representations occupy a central place in Peirce's philosophy, in his innovative approach to logic and in his practice as a scientist. Starting from a discussion of Peirce's approach to diagrams, I claim that Peirce's own representations are in line with his formulation of iconicity, and that they are more broadly connected to the pragmatist philosophy he developed in parallel with his (...) scientific work. I then defend the contemporary relevance of Peirce's approach to iconic representations, and specifically argue that Peirce offers a useful ‘third way’ between what Mauricio Suárez has recently described as the ‘analytical’ and ‘practical’ inquiries into the concept of representation. As a philosophically minded scientist and an experimentally inclined philosopher, Peirce never divorced the practice of representing from questions about what counts as a representation... (shrink)

In “What is it like to be boring and myopic?” Kathleen Akins offers an interesting, empirically driven, argument for thinking that there is nothing that it is like to be a bat. She suggests that bats are “boring” in the sense that they are governed by behavioral scripts and simple, non-representational, control loops, and are best characterized as biological automatons. Her approach has been well received by philosophers sympathetic to empirically informed philosophy of mind. But, despite its influence, her work (...) has not met with any critical appraisal. -/- It is argued that a reconsideration of the empirical results shows that bats are not boring automatons, driven by short input-output loops, instincts, and reflexes. Grounds are provided for thinking that bats satisfy a range of philosophically and scientifically interesting elaborations of the general idea that consciousness is best understood in terms of representational functions. A more complete examination of bat sensory capabilities suggests there is something that it is like after all. -/- The discussion of bats is also used to develop an objection to strongly neurophilosophical approaches to animal consciousness. (shrink)

What sort of claims do scientific models make and how do these claims then underwrite empirical successes such as explanations and reliable policy interventions? In this paper I propose answers to these questions for the class of models used throughout the social and biological sciences, namely idealized deductive ones with a causal interpretation. I argue that the two main existing accounts misrepresent how these models are actually used, and propose a new account. *Received July 2006; revised August 2008. †To contact (...) the author, please write to: Department of Philosophy, University of Missouri, St. Louis, 599 Lucas Hall (MC 73), One University Blvd., St. Louis, MO 63121-4400; e-mail: [email protected]. (shrink)

When is conceptual change so significant that we should talk about a new theory, not a new version of the same theory? We address this problem here, starting from Gould’s discussion of the individuation of the Darwinian theory. He locates his position between two extremes: ‘minimalist’—a theory should be individuated merely by its insertion in a historical lineage—and ‘maximalist’—exhaustive lists of necessary and sufficient conditions are required for individuation. He imputes the minimalist position to Hull and attempts a reductio : (...) this position leads us to give the same ‘name’ to contradictory theories. Gould’s ‘structuralist’ position requires both ‘conceptual continuity’ and descent for individuation. Hull’s attempt to assimilate into his general selectionist framework Kuhn’s notion of ‘exemplar’ and the ‘semantic’ view of the structure of scientific theories can be used to counter Gould’s reductio , and also to integrate structuralist and population thinking about conceptual change. (shrink)

This paper aims at integrating the work onanalogical reasoning in Cognitive Science into thelong trend of philosophical interest, in this century,in analogical reasoning as a basis for scientificmodeling. In the first part of the paper, threesimulations of analogical reasoning, proposed incognitive science, are presented: Gentner''s StructureMatching Engine, Mitchel''s and Hofstadter''s COPYCATand the Analogical Constraint Mapping Engine, proposedby Holyoak and Thagard. The differences andcontroversial points in these simulations arehighlighted in order to make explicit theirpresuppositions concerning the nature of analogicalreasoning. In the (...) last part, this debate in cognitivescience is applied to some traditional philosophicalaccounts of formal and material analogies as a basisfor scientific modeling, like Mary Hesse`s, and tomore recent ones, that already draw from the work inArtificial Intelligence, like that proposed byAronson, Harré and Way. (shrink)

Numerous articles in top IS journals note as a limitation and lack of generalizability that their findings are specific to a certain type of technology, culture, and so on. We argue that this generalizability concern is about limited scope. The IS literature notes this preference for generalizability as a characteristic of good science and it is sometimes confused with statistical generalizability. We argue that such generalizability can be in conflict with explanation or prediction accuracy. An increase in scope can decrease (...) explanation or prediction accuracy. Thus, in sciences such as cancer research, where explanation and prediction accuracy are highly valued, the cancer accounts have become increasingly narrower. IS thinking has not yet benefitted from these considerations. Whether generalizability is valued should be linked with the research aims. If the aim is practical applicability through explanation or prediction accuracy, then “limited” generalizability could be a strength rather than a weakness. (shrink)

Recently, some philosophers of science (e.g., Gürol Irzik, Michael Friedman) have challenged the ‘received view’ on the relationship between Rudolf Carnap and Thomas Kuhn, suggesting that there is a close affinity (rather than opposition) between their philosophical views. In support of this argument, these authors cite Carnap and Kuhn’s similar views on incommensurability, theory-choice, and scientific revolutions. Against this revisionist view, I argue that the philosophical relationship between Carnap and Kuhn should be regarded as opposed rather than complementary. In particular, (...) I argue that a consideration of the fundamentally disparate nature of the broader philosophical projects of Carnap (logic of science) and Kuhn (providing a theory of scientific revolutions)renders the alleged similarities between their views superficial in comparison to their fundamental differences. In defense of the received view, I suggest that Carnap and Kuhn are model representatives of two contrasting styles of doing philosophy of science, viz., logical analysis and historical analysis respectively. This analysis clarifies the role played by Kuhn’s Structure of Scientific Revolutions in the demise of logical empiricism in the second half of the twentieth-century. (shrink)

In academic contexts the appeal to authority is a quite common but seldom tested argument, either because we accept the authority without questioning it, or because we look for alternative experts or reasons to support a different point of view. But, by putting ourselves side by side an already accepted authority, we often rhetorically manoeuvre to displace the burden of the proof to avoid the fear to present our opinions and to allow face saving.

Upshot: In our response we focus on five questions that point to important common themes in the commentaries: why start in wicked problems, what kind of system is a scientific perspective, what is the nature of second-order research processes, what does this mean for understanding interdisciplinary work, and how may polyocular research help make real-world decisions.

Modern societies depend on a growing production of scientific knowledge, which is based on the functional differentiation of science into still more specialised scientific disciplines and subdisciplines. This is the basis for the paradox of scientific expertise: The growth of science leads to a fragmentation of scientific expertise. To resolve this paradox, the present paper investigates three hypotheses: 1) All scientific knowledge is perspectival. 2) The perspectival structure of science leads to specific forms of knowledge asymmetries. 3) Such perspectival knowledge (...) asymmetries must be handled through second order perspectives. We substantiate these hypotheses on the basis of a perspectivist philosophy of science grounded in Peircean semiotics and autopoietic systems theory. Perspectival knowledge asymmetries are an unavoidable and necessary part of the growth of scientific knowledge, and more awareness of this fact can help avoid blind and futile struggles between scientific perspectives, and direct efforts toward more appropriate ways of handling these fundamental knowledge asymmetries. Concretely, we show how different kinds of scientific knowledge, expertise, disagreement and learning can be correlated to the perspectival structure of science, and propose how polyocular communication based on observations of the observations made by specialised perspectives can be used to handle such perspectival knowledge asymmetries. This can help overcome the observed problems in carrying out cross-disciplinary research and in the collective use of different kinds of scientific expertise, and thereby make society better able to solve complex, real-world problems. (shrink)

In this paper I will argue that if physics is to become a coherent metaphysics of nature it needs an “interpretation”. As I understand it, an interpretation of a physical theory amounts to offering (1) a precise formulation of its ontological claims and (2) a clear account of how such claims are related to the world of our experience. Notably, metaphysics enters importantly in both tasks: in (1), because interpreting our best physical theories requires going beyond a merely instrumentalist view (...) of science and therefore using our best metaphysical theories; in (2), because a philosophical elaboration of the theories of the world that are implicit in our experience is one of the tasks of analytic metaphysics, and bridging possible explanatory gaps or even conflicts between the physical image and the manifest image of the world is a typical philosophical task that involves science and metaphysics. (shrink)

Models are a principle instrument of modern science. They are built, applied, tested, compared, revised and interpreted in an expansive scientific literature. Throughout this paper, I will argue that models are also a valuable tool for the philosopher of science. In particular, I will discuss how the methodology of Bayesian Networks can elucidate two central problems in the philosophy of science. The first thesis I will explore is the variety-of-evidence thesis, which argues that the more varied the supporting evidence, the (...) greater the degree of confirmation for a given hypothesis. However, when investigated using Bayesian methodology, this thesis turns out not to be sacrosanct. In fact, under certain conditions, a hypothesis receives more confirmation from evidence that is obtained from one rather than more instruments, and from evidence that confirms one rather than more testable consequences of the hypothesis. The second challenge that I will investigate is scientific theory change. This application highlights a different virtue of modeling methodology. In particular, I will argue that Bayesian modeling illustrates how two seemingly unrelated aspects of theory change, namely the (Kuhnian) stability of (normal) science and the ability of anomalies to over turn that stability and lead to theory change, are in fact united by a single underlying principle, in this case, coherence. In the end, I will argue that these two examples bring out some metatheoretical reflections regarding the following questions: What are the differences between modeling in science and modeling in philosophy? What is the scope of the modeling method in philosophy? And what does this imply for our understanding of Bayesianism? (shrink)

Modeling is central to scientific inquiry. It also depends heavily upon the imagination. In modeling, scientists seem to turn their attention away from the complexity of the real world to imagine a realm of perfect spheres, frictionless planes and perfect rational agents. Modeling poses many questions. What are models? How do they relate to the real world? Recently, a number of philosophers have addressed these questions by focusing on the role of the imagination in modeling. Some have also drawn parallels (...) between models and fiction. This chapter examines these approaches to scientific modeling and considers the challenges they face. (shrink)

This volume argues for a new image of science that understands both natural and social phenomena to be the product of mechanisms, casting the work of science as an effort to understand those mechanisms. Glennan offers an account of the nature of mechanisms and of the models used to represent them in physical, life, and social sciences.

This is a collection of my essays in the philosophy of science which have been translated into Spanish.

Traditional approaches in philosophy of biology focus attention on biological concepts, explanations, and theories, on evidential support and inter-theoretical relations. Newer approaches shift attention from concepts to conceptual practices, from theories to practices of theorizing, and from theoretical reduction to reductive retooling. In this article, I describe the shift from theory-focused to practice-centered philosophy of science and explain how it is leading philosophers to abandon fundamentalist assumptions associated with traditional approaches in philosophy of science and to embrace scientific pluralism. This (...) article comes in three parts, each illustrating the shift from theory-focused to practice-centered epistemology. The first illustration shows how shifting philosophical attention to conceptual practice reveals how molecular biologists succeed in identifying coherent causal strands within systems of bewildering complexity. The second illustration suggests that analyzing how a multiplicity of alternative models function in practice provides an illuminating approach for understanding the nature of theoretical knowledge in evolutionary biology. The third illustration demonstrates how framing reductionism in terms of the reductive retooling of practice offers an informative perspective for understanding why putting DNA at the center of biological research has been incredibly productive throughout much of biology. Each illustration begins by describing how traditional theory-focused philosophical approaches are laden with fundamentalist assumptions and then proceeds to show that shifting attention to practice undermines these assumptions and motivates a philosophy of scientific pluralism. (shrink)