In a series of important papers, A. Fine has developed and defended the view that the proper reading of scientific practice is neither realist nor antirealist. Instead, he argues that realism and antirealism both add something extra to a core position which is neither. In this discussion I reexamine his claim in the light of some criticisms. Fine's position contains an important insight, but to draw that point out requires shifting the way in which Fine poses the argument. I (...) do so by examining an argument by H. Stein. (shrink)

argumentation has been shown to be a powerful tool within many fields such as artificial intelligence, logic and legal reasoning. In this paper we enhance Dung’s well-known abstract argumentation framework with explanatory capabilities. We show that an explanatory argumentation framework (EAF) obtained in this way is a useful tool for the modeling of scientific debates. On the one hand, EAFs allow for the representation of explanatory and justificatory arguments constituting rivaling scientific views. On the other hand, different procedures (...) for selecting arguments, corresponding to different methodological and epistemic requirements of theory evaluation, can be formulated in view of our framework. (shrink)

The aim of this essay is to emphasize a number of important points that will provide a better understanding of the history of philosophical thought concerning scientific knowledge. The main points made are: (a) that the principal way of viewing abstraction which has dominated the history of thought and epistemology up to the present is influenced by the original Aristotelian position; (b) that with the birth of modern science a new way of conceiving abstraction came into being (...) which is better characterized by the term idealization, the name that was later, in fact, to be used by scientists to describe their scientific activity; (c) that, however, on account of the influence of empirical and inductive philosophy, scientists have often not had sufficient methodological awareness of this new way of viewing abstraction; (d) that this new concept of abstraction has frequently been expressed in the framework of philosophies that lie outside the mainstream of contemporary epistemology or even exhibit marked anti-scientific tendencies; (e) that the theme of idealization has been taken up again in the last few decades and a great contribution in this direction has been made by the so-called Pozna school of methodology. (shrink)

In philosophy of science, abstraction tends to be subsumed under representation, often being described as the omission of a target’s features when it is represented. This approach to abstraction sidesteps cognitive aspects of abstraction processes. However, cognitive aspects of abstraction are important in understanding the role of historically grounded epistemic criteria supporting modeling in science. Drawing on recent work on the relation between metaphor and abstraction, we introduce the concept of paths of abstraction, and (...) use historical and contemporary examples to point to their role in guiding the development of relevance criteria which support modeling strategies in science. (shrink)

Abstraction and generalization are two processes of reasoning that have a special role in the construction of scientific theories and models. They have been important parts of the scientific method ever since the nineteenth century. A philosophical and historical analysis of scientific practices shows how abstraction and generalization found their way into the theory of the logic of science of the nineteenth-century philosopher Charles S. Peirce. Our case studies include the scientific practices of Francis (...) Galton and John Herschel, who introduced composite photographs and graphical methods, respectively, as technologies of generalization and thereby influenced Peirce’s logic of abstraction. Herschel’s account of generalization is further supported by William Whewell, who was very influential on Peirce. By connecting Herschel’s scientific technology of abstraction to Peirce’s logical technology of abstraction—namely, diagrams—we highlight the role of judgments in scientific observation by hypostatic abstractions. We also relate Herschel’s discovery-driven logic of science and Peirce’s open-ended diagrammatic logic to the use of models in science. Ultimately, Peirce’s theory of abstraction is a case of showing how logic applies to reality. (shrink)

ion is one of the important processes in scientific modeling. It has always been implied that abstraction is an agent-centric activity that involves the cognitive processes of scientists in model building. I contend that there is an autonomous aspect of abstraction in many modeling activities. I argue that the autonomous process of abstraction is continuous with the agent-centric abstraction but capable of evolving independently from the modeler’s abstraction activity.

This paper argues for two related theses. The first is that mathematical abstraction can play an important role in shaping the way we think about and hence understand certain phenomena, an enterprise that extends well beyond simply representing those phenomena for the purpose of calculating/predicting their behaviour. The second is that much of our contemporary understanding and interpretation of natural selection has resulted from the way it has been described in the context of statistics and mathematics. I argue for (...) these claims by tracing attempts to understand the basis of natural selection from its early formulation as a statistical theory to its later development by R.A. Fisher, one of the founders of modern population genetics. Not only did these developments put natural selection of a firm theoretical foundation but its mathematization changed the way it was understood as a biological process. Instead of simply clarifying its status, mathematical techniques were responsible for redefining or reconceptualising selection. As a corollary I show how a highly idealised mathematical law that seemingly fails to describe any concrete system can nevertheless contain a great deal of accurate information that can enhance our understanding far beyond simply predictive capabilities. (shrink)

I argue that we cannot adequately characterize idealization and abstraction and the distinction between the two on the grounds that they have distinct semantic properties. By doing so, on the one hand, we focus on the conceptual products of the two processes in making the distinction and we overlook the importance of the nature of the thought processes that underlie model-simplifying assumptions. On the other hand, we implicitly rely on a sense of abstraction as subtraction, which is unsuitable (...) for explicating scientific model construction. Instead, I argue that a sense of abstraction as extraction is more suitable. Finally, I suggest a different way to distinguish the two processes that avoids these problems. Namely, that both idealization and abstraction could be understood as particular modes of application of the same cognitive process: selective attention. (shrink)

The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, (...) we select position and momentum and establish a relation amongst the two variables, which we call Newton’s 2nd law. The specification of the unspecified elements of scientific laws, e.g. the force function in Newton’s 2nd law, is what would establish the link between the assertions of the theory and physical systems. In order to unravel how and with what conceptual resources scientific models are constructed, how they function and how they relate to theory, we need a view of theory-application that can accommodate our constructions of representation models. For this we need to expand our understanding of the process of abstraction to also explicate the process of specifying force functions etc. This is the second principal level at which abstraction enters in our theorising and in which I focus. In this paper, I attempt to elaborate a general analysis of the process of abstraction and concretisation involved in scientific- model construction, and argue why it provides an explication of the construction of models of the nuclear structure. (shrink)

Learning about a scientific concept often occurs in the context of unfamiliar examples. Mutual alignment analogy ? a type of analogical comparison in which the analogues are only partially understood ? has been shown to facilitate learning from unfamiliar examples . In the present study, we examined the role of mutual alignment analogy in the abstraction and transfer of a complex scientific concept from examples presented in expository texts. Our results provide evidence that (a) promoting comparison between (...) two examples and (b) orienting the learner toward relational commonalities result in greater abstraction and transfer. These findings suggest that mutual alignment analogy is an effective means of promoting abstraction and transfer of complex scientific concepts, and may thus be used in the classroom to promote learning from unfamiliar examples. (shrink)

Recent metaphysics of science has been fuelled significantly by an interest in causal powers or dispositions. A number of authors have made realism about dispositions central to their projects in the epistemology of science, suggesting that the existence of irreducible powers is a commitment entailed by taking scientific practice seriously. This paper strikes a cautionary note with respect to the two most common arguments for this view, concerning the putative requirement of dispositional properties in the contexts of scientific (...) explanation and scientific abstraction. I contend that neither argument is successful, but that nevertheless, realism about powers better accords with an arguably scientific consideration of property identity, thus affirming the importance of dispositions to the epistemology of science. (shrink)

Scientific models invariably involve some degree of idealization, abstraction, or nationalization of their target system. Nonetheless, I argue that there are circumstances under which such false models can offer genuine scientific explanations. After reviewing three different proposals in the literature for how models can explain, I shall introduce a more general account of what I call model explanations, which specify the conditions under which models can be counted as explanatory. I shall illustrate this new framework by applying (...) it to the case of Bohr's model of the atom, and conclude by drawing some distinctions between phenomenological models, explanatory models, and fictional models. (shrink)

Uncertainty is recognized as a key issue in water resources research, amongst other sciences. Discussions of uncertainty typically focus on tools and techniques applied within an analysis, e.g. uncertainty quantification and model validation. But uncertainty is also addressed outside the analysis, in writing scientific publications. The language that authors use conveys their perspective of the role of uncertainty when interpreting a claim —what we call here “framing” the uncertainty. This article promotes awareness of uncertainty framing in four ways. 1) (...) It proposes a typology of eighteen uncertainty frames, addressing five questions about uncertainty. 2) It describes the context in which uncertainty framing occurs. This is an interdisciplinary topic, involving philosophy of science, science studies, linguistics, rhetoric, and argumentation. 3) We analyze the use of uncertainty frames in a sample of 177 abstracts from the Water Resources Research journal in 2015. This helped develop and tentatively verify the typology, and provides a snapshot of current practice. 4) Provocative recommendations promote adjustments for a more influential, dynamic science. Current practice in uncertainty framing might be described as carefully-considered incremental science. In addition to uncertainty quantification and degree of belief (present in ~5% of abstracts), uncertainty is addressed by a combination of limiting scope, deferring to further work (~25%) and indicating evidence is sufficient (~40%) – or uncertainty is completely ignored (~8%). There is a need for public debate within our discipline to decide in what context different uncertainty frames are appropriate. Uncertainty framing cannot remain a hidden practice evaluated only by lone reviewers. (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)

In the recent literature on causal and non-causal scientific explanations, there is an intuitive assumption according to which an explanation is non-causal by virtue of being abstract. In this context, to be ‘abstract’ means that the explanans in question leaves out many or almost all causal microphysical details of the target system. After motivating this assumption, we argue that the abstractness assumption, in placing the abstract and the causal character of an explanation in tension, is misguided in ways that (...) are independent of which view of causation or causal explanation one takes to be most accurate. On major accounts of causation, as well as on major accounts of causal explanation, the abstractness of an explanation is not sufficient for it being non-causal. That is, explanations are not non-causal by dint of being abstract. (shrink)

This volume explores the roles and uses of abstraction in scientific and artistic practice. Conceived as an interdisciplinary dialogue between experts across histories and philosophies of art and science, this collection of essays draws on the shared premise that abstraction is a rich and generative process, not reducible to the mere omission of details in a representation. When scientists attempt to make sense of complex natural phenomena, they often produce highly abstract models of them. In the history (...) and philosophy of art, there is a long tradition of debate on the function of abstraction, and - more recently - its relation with theories of depiction. Adopting a process-oriented perspective, the chapters in this volume explore the epistemic potential of a diversity of practices of abstracting. The systematic analysis of a wide range of historical cases, from early twentieth-century abstractionist painting to contemporary abstract photography, and from nineteenth-century physics to recent research in biology and neurosciences, invites the reader to reflect on the material lives of abstraction through concrete artefacts, experimental practices and theoretical and aesthetic achievements. Abstraction in Science and Art: Philosophical Perspectives will be of interest to scholars and advanced students working in aesthetics, philosophy of science, and epistemology, as well as to historians of science and art, and to practicing artists and scientists interested in exploring foundational questions at the heart of the creative practice of abstracting. (shrink)

Beginning at the end of the nineteenth century, systematic scientific abstracting played a crucial role in reconfiguring the sciences on an international scale. For mathematicians, the 1931 launch of the Zentralblatt für Mathematik and 1940 launch of Mathematical Reviews marked and intensified a fundamental transformation, not just to the geographic scale of professional mathematics but to the very nature of mathematicians’ research and theories. It was not an accident that mathematical abstracting in this period coincided with an embrace across (...) mathematical research fields of a distinctive form of symbolic and conceptual abstraction. This essay examines the historical, institutional, embodied, and conceptual bases of mathematical abstracting and abstraction in the mid-twentieth century, placing them in historical context within the first half of the twentieth century and then examining their consequences and legacies for the second half of the twentieth century and beyond. Focused on scale, media, and the relationship between mathematical knowledge and its forms of articulation, my analysis connects the changing social structure of modern mathematical research communities to their changing domains of investigation and resources for representation and collective understanding. (shrink)

A natural way to think of models is as abstract entities. If theories employ models to represent the world, theories traffic in abstract entities much more widely than is often assumed. This kind of thought seems to create a problem for a scientific realist approach to theories. Scientific realists claim theories should be understood literally. Do they then imply the reality of abstract entities? Or are theories simply—and incurably—false? Or has the very idea of literal understanding to be (...) abandoned? Is then fictionalism towards scientific theories inevitable? This paper argues that scientific realism can happily co-exist with models qua abstracta. (shrink)

Questions concerning the epistemological status of computer science are, in this paper, answered from the point of view of the formal verification framework. State space reduction techniques adopted to simplify computational models in model checking are analysed in terms of Aristotelian abstractions and Galilean idealizations characterizing the inquiry of empirical systems. Methodological considerations drawn here are employed to argue in favour of the scientific understanding of computer science as a discipline. Specifically, reduced models gained by Dataion are acknowledged as (...) Aristotelian abstractions that include only data which are sufficient to examine the interested executions. The present study highlights how the need to maximize incompatible properties is at the basis of both Abstraction Refinement, the process of generating a cascade of computational models to achieve a balance between simplicity and informativeness, and the Multiple Model Idealization approach in biology. Finally, fairness constraints, imposed to computational models to allow fair behaviours only, are defined as ceteris paribus conditions under which temporal formulas, formalizing software requirements, acquire the status of law-like statements about the software systems executions. (shrink)

In this paper, I distinguish scientific models in three kinds on the basis of their ontological status—material models, mathematical models and fictional models, and develop and defend an account of fictional models as fictional objects—i.e. abstract objects that stand for possible concrete objects.

Scientific models describe natural phenomena at different levels of abstraction. Abstract descriptions can provide the basis for interventions on the system and explanation of observed phenomena at a level of granularity that is coarser than the most fundamental account of the system. Beckers and Halpern (2019), building on work of Rubenstein et al. (2017), developed an account of abstraction for causal models that is exact. Here we extend this account to the more realistic case where an abstract (...) causal model offers only an approximation of the underlying system. We show how the resulting account handles the discrepancy that can arise between low- and high-level causal models of the same system, and in the process provide an account of how one causal model approximates another, a topic of independent interest. Finally, we extend the account of approximate abstractions to probabilistic causal models, indicating how and where uncertainty can enter into an approximate abstraction. (shrink)

ABSTRACT: Decision-theoretic approach and a nonlinguistic theory of norms are applied in the paper in an attempt to explain the nature of scientific rationality. It is considered as a normative system accepted by scientific community. When we say that a certain action is rational, we express a speaker’s acceptance of some norms concerning a definite action. Scientists can choose according to epistemic utility or other rules and values, which themselves have a variable nature. Rationality can be identified with (...) a decision to accept a norm. This type of decision cannot be reduced only to its linguistic formulation; it is an act of evolvement of the normative regulation of human behavior. Norms are treated as decisions of a normative authority: a specific scientific community is the normative authority in science. These norms form a system and they are absolutely objective in the context of individual scientists. There exists an invariant core in all the norms of rationality, accounting for their not being liable to change, as compared with the flexibility of legal norms. The acceptance of and abidance by these norms is of social importance – it affects the aims of the community. A norm only defines the common framework and principles of scientific problem-solving; its application is a matter of professional skills and creative approach to a particular problem. It is of no importance at all, if an agent’s cognitive abilities do not live up to the requirements of a norm. Such discrepancy can be compensated for by the fact that a scientist carries out work in a conceptual and normative framework established by a respective scientific community. (shrink)

Scientific representation is a booming field nowadays within the philosophy of science, with many papers published regularly on the topic every year, and several yearly conferences and workshops held on related topics. Historically, the topic originates in two different strands in 20th-century philosophy of science. One strand begins in the 1950s, with philosophical interest in the nature of scientific theories. As the received or “syntactic” view gave way to a “semantic” or “structural” conception, representation progressively gained the center (...) stage. Yet, there is another, older, strand that links representation to fin de siècle modeling debates, particularly in the emerging Bildtheorie of Boltzmann and Hertz, and to the ensuing discussion among philosophers thereafter. Both strands feed into present-day philosophical work on scientific representation. There are a number of different orthogonal questions that philosophers ask regarding representation. One set of questions concerns the nature of the representational relation between theories or models, on the one hand, and the real-world systems they purportedly represent. Such questions lie at the more metaphysical and abstract end of the spectrum—and they are often addressed with the abstract tools of the analytical metaphysician. They constitute what we may refer to as the “analytical inquiry” into representation. On the other hand there are questions regarding the use that scientists put some representations to in practice—these are questions that are best addressed by means of some of the favorite tools of the philosopher of science, including descriptive analysis, illustration by means of case studies, induction, exemplification, inference from practice, etc., and are best referred to as the “practical inquiry” into representation. The notion of representation invoked in such inquiries may be “deflationary” or “substantive”—depending on whether it construes representation as a primitive notion, or as susceptible to further reduction or analysis in terms of something else. (shrink)

This is an introduction to the volume "Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations", edited by A. Reutlinger and J. Saatsi (OUP, forthcoming in 2017). -/- Explanations are very important to us in many contexts: in science, mathematics, philosophy, and also in everyday and juridical contexts. But what is an explanation? In the philosophical study of explanation, there is long-standing, influential tradition that links explanation intimately to causation: we often explain by providing accurate information about the causes of the (...) phenomenon to be explained. Such causal accounts have been the received view of the nature of explanation, particularly in philosophy of science, since the 1980s. However, philosophers have recently begun to break with this causal tradition by shifting their focus to kinds of explanation that do not turn on causal information. The increasing recognition of the importance of such non-causal explanations in the sciences and elsewhere raises pressing questions for philosophers of explanation. What is the nature of non-causal explanations - and which theory best captures it? How do non-causal explanations relate to causal ones? How are non-causal explanations in the sciences related to those in mathematics and metaphysics? This volume of new essays explores answers to these and other questions at the heart of contemporary philosophy of explanation. The essays address these questions from a variety of perspectives, including general accounts of non-causal and causal explanations, as well as a wide range of detailed case studies of non-causal explanations from the sciences, mathematics and metaphysics. (shrink)

Any division between scientific practice and a metalevel of the methods and goals of science is largely a false dichotomy. Since a priori, foundationist or logicist approaches to normative principles have proven unequal to the task of representing actual scientific practice, methodologies of science must be abstracted from episodes in the history of science. Of course, it is possible that such characteristics could prove universal and constant across various eras. But, case studies show that they are not in (...) anything beyond the strictures applied to everyday, commonsense reasoning (e.g., a requirement of noncontradiction in a deductive argument). Hence, even if some presently-on-offer methodology or description of past scientific practice were adequate, it need not remain so for current (‘frontier’) areas of science. For this reason, it is important to examine recent episodes in, say, high-energy physics. Results from case studies of several episodes in that field are used to argue that successful practice leads scientists to countenance essential changes in the methodological framework at the levels of the criteria employed in judging theories (i.e., what counts for an explanation and what are canons of rationality) and of the goals of science. *Partial support for this research was provided by the History and Philosophy of Science Program of the National Science Foundation under grants Nos. SES-8606472 and SES-8705469. A preliminary version of this paper was given at an HPS seminar at King's College, London University in May 1988. Helpful comments and useful criticisms were made by several colleagues, especially Ernan McMullin, Heinz Post and Simon Saunders (none of whom are to be held responsible for or necessarily even in agreement with the views expressed here.). (shrink)

We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage and (...) analyze the differential impact of evidence and credence change at different points within a single network and across different theoretical structures. (shrink)

Abstract Criteria of scientific value are of different kinds. This paper concerns ultimate criteria, i.e. the axiology of science. Most ultimate criteria are multi?dimensional. This gives rise to an aggregation problem, which cannot be adequately solved with reference to attitudes and behaviour within the scientific community. Therefore, in many cases, there is no fact of the matter as to whether one theory is better than another. This, in turn, creates problems for methodology.

In lieu of an abstract, here is a brief excerpt of the content:Journal of the History of Philosophy 41.1 (2003) 123-124 [Access article in PDF] Andrew Barker. Scientific Method in Ptolemy's Harmonics. New York: Cambridge University Press, 2001. Pp. viii + 281. Cloth, $69.95. Ptolemy's Harmonics is an important source not only for the history of music, but also for the history and philosophy of science. Two recent monographs, by J. Solomon, and A. Barker, now provide a basis for (...) a more widespread discussion of this much neglected work. Barker focuses on the part that is concerned with musical science proper (I, 1-III, 3), and more specifically on the scientific method it displays.Barker uses an analysis of Ptolemy's programmatic statements in I, 1/2, as a key to a reading of Ptolemy's treatise. His exposition has the format of a commentary, with special emphasis on the methodologically relevant passages. For the most part, he follows the order of Ptolemy's text closely, providing historical background information in excursus form. One needs to read a complete text of Ptolemy's treatise along with Barker's exposition in order to understand some of his arguments. It is preferable to also use Düring's [End Page 123] edition of the Greek text. One is rewarded with a detailed and in-depth analysis of the passages that helps one understand Ptolemy's method in harmonics as it unfolds in his treatise. This is so even if one disagrees with Barker's claims concerning Ptolemy's methodology.These claims are outlined in chapter 2, on the basis of I, 1/2 of the Harmonics. The methodological program Barker filters out of the text remains vague in a number of important respects. One misses, for example, a clear exposition on what will count as a sufficient integration of "empirical and theoretical phases," and on what will count as "empirical." This is a serious drawback, since Barker claims that Ptolemy instantiates a complex scientific methodology with a decisive, fully integrated empiricist trait. The drawback is aggravated by the fact that the already vague terms of the postulated methodology have to be watered down considerably in the subsequent chapters to make them fit with Ptolemy's actual procedures. Ptolemy does not seem to deliver even on the vague terms. One may very well remain unconvinced both by Barker's initial arguments concerning Ptolemy's methodology, and by his attempts to show that Ptolemy's procedure in the Harmonics can count as a satisfactory instantiation. Perhaps Ptolemy's intentions are less ambitious. When he states (5.13 ff. Düring, ed.) that "the aim of the student of harmonics must be to preserve the hupotheseis..., as never in any way conflicting with the perceptions that correspond to most people's estimation," he may just mean that he intends to vindicate an essentially Pythagorean (locally modified) account by showing it does not conflict with the phenomena. In my view, he certainly delivers on this less ambitious program. In fact, it seems to me that the understanding of Ptolemy's argumentative path is impeded by Barker's interpretation of Ptolemy's goal of "saving the hupotheseis" as a commitment to the integration of a genuine empiricist trait.Chapters 7 and 8 give an exposition of Ptolemy's tetrachord divisions. For the reader interested in an evaluation of the theoretical aspect of Ptolemy's scientific method, these are the central chapters of Barker's book. Barker provides a detailed analysis, together with an exposition of the historical and technical information needed for a non-specialist to follow both his and Ptolemy's argument. Barker's analysis reveals inter alia that a considerable part of Ptolemy's theory has no counterpart in the realm of phenomena perceived as musical, and that another part, concerning the single most important division of musical practice, is not justified, and not justifiable, by derivation from the principles. It is difficult to see how Ptolemy's account can nevertheless be viewed as a genuine integration of empirical and theoretical aspects. It appears to be an attempt at showing that an essentially Pythagorean theory... (shrink)

What is the best way to analyse abstraction in scientific modelling? I propose to focus on abstracting as an epistemic activity, which is achieved in different ways and for different purposes depending on the actual circumstances of modelling and the features of the models in question. This is in contrast to a more conventional use of the term ‘abstract’ as an attribute of models, which I characterise as black-boxing the ways in which abstraction is performed and to (...) which epistemological advantage. I exemplify my claims through a detailed reconstruction of the practices involved in creating two types of models of the flowering plant Arabidopsisthaliana, currently the best-known model organism in plant biology. This leads me to distinguish between two types of abstraction processes: the ‘material abstracting’ required in the production of Arabidopsis specimens and the ‘intellectual abstracting’ characterising the elaboration of visual models of Arabidopsis genomics. Reflecting on the differences between these types of abstracting helps to pin down the epistemic skills and research commitments used by researchers to produce each model, thus clarifying how models are handled by researchers and with which epistemological implications. (shrink)

This paper explores the influence of Søren Kierkegaard upon Paul Feyerabend by examining their common criticisms of totalising accounts of human nature. Both complained that philosophical and scientific theories of human nature which were methodologically committed to objectivity and abstraction failed to capture the richness of human experience. Kierkegaard and Feyerabend argued that philosophy and the science were threatening to become obstacles to human development by imposing abstract theories of human nature and reality which denied the complexities of (...) both. In both cases, this took the form of asserting an ‘existential’ criterion for the assessment of philosophical and scientific theories. Kierkegaard also made remarks upon the inappropriateness of applying natural scientific methods to human beings which Feyerabend later expanded and developed in his criticisms of the inability of the ‘scientific worldview’ to accommodate the values necessary to a flourishing human life. I conclude by noting some differences between Kierkegaard and Feyerabend’s positions and by affirming the value of existential criticisms of scientific knowledge.Keywords: Feyerabend; Kierkegaard; Objectivity;ion; Human nature. (shrink)

One of the vividly discussed topics in the contemporary philosophy of science (especially physics) is the opposition between realism and Anti-Realism. The supporters of the first way of thinking trust in the objective existence of realities studied by science. They consider theories as approximate descriptions of these realities (Psillos 1999, xvii), whereas their opponents do not. However, both sides base their argumentation on simplified notions of scientific theories. In this paper, we present a more general approach, which can be (...) coined as “Theoretical Physics Realism” (TPR). It is based on the detailed reconstruction of the polysystemic nature of physical theories. The consequences of this reconstruction for understanding the genuine relationship between theories and experiments in studying the realities are indicated. The paper distinguishes between abstract (general) and domain-dependent theories and appeals to specific physical theories together with their application domains rather than to general speculations. (shrink)

Can a constructive empiricist make sense of scientific representation? Usually, a scientific model is an abstract entity, and scientific representation is conceptualized as an intentional relation between scientific models and certain aspects of the world. On this conception, since both the models and the representation relation are abstract, a constructive empiricist, who is not committed to the existence of abstract entities, would be unable to invoke these notions to make sense of scientific representation. In this (...) paper, instead of understanding representation as a relation between abstract entities, I focus on the activity of representing, and argue that it provides a way of making sense of representation within the boundaries of empiricism. The activity of representing doesn’t deal with abstract entities, but with concrete ones, such as inscriptions, templates, and blueprints. In the end, by examining the practice of representing, rather than an artificially reified product—the representation—the constructive empiricist has the resources to make sense of scientific representation in empiricist terms. (shrink)

In addition to their core explanatory and predictive assumptions, scientific models include simplifying assumptions, which function as idealizations, approximations, and abstractions. There are methods to investigate whether simplifying assumptions bias the results of models, such as robustness analyses. However, the equally important issue – the focus of this paper – has received less attention, namely, what are the methodological and epistemic strengths and limitations associated with different simplifying assumptions. I concentrate on one type of simplifying assumption, the use of (...) mega parameters as abstractions in ecological models. First, I argue that there are two kinds of mega parameters qua abstractions, sufficient parameters and aggregative parameters, which have gone unnoticed in the literature. The two are associated with different heuristics, holism and reductionism, which many view as incompatible. Second, I will provide a different analysis of abstractions and the associated heuristics than previous authors. Reductionism and holism and the accompanying abstractions have different methodological and epistemic functions, strengths, and limitations, and the heuristics should be viewed as providing complementary research perspectives of cognitively limited beings. This is then, third, used as a premise to argue for epistemic and methodological pluralism in theoretical ecology. Finally, the presented taxonomy of abstractions is used to comment on the current debate whether mechanistic accounts of explanation are compatible with the use of abstractions. This debate has suffered from an abstract discussion of abstractions. With a better taxonomy of abstractions the debate can be resolved. (shrink)

Cases where analogy has played a significant role in the formation of a new scientific concept are well-documented. Yet, how is it that genuinely new representations can be constructed from existing representations? It is argued that the process of ‘generic modeling’ enables abstraction of features common to both the domain of the source of the analogy and of the target phenomena. The analysis focuses on James Clerk Maxwell's construction of the electromagnetic field concept. The mathematical representation Maxwell constructed (...) turned out to be a system of abstract laws that when applied to electromagnetic systems yield laws of a dynamical system that will not map back onto the mechanicals domains used in their construction. (shrink)

This article examines the mutual influence between Ernst Cassirer and his cousin, the neurologist Kurt Goldstein. For both Cassirer and Goldstein, views on the nature of human cognition were fundamental to their understanding of scientific knowledge, and these were informed by both philosophical theorizing and empirical research on pathologies of the nervous system. Following Cassirer, and in agreement with the physicalism of the Vienna Circle, Goldstein held that the physical sciences had progressed by arriving at abstract, mathematical representations to (...) take the place of qualitative characterizations of observable reality. In tension with physicalism, Goldstein was not sanguine about the fruitfulness of the abstractive approach in biology. He proposed that biology must adhere to its own sui generis methods of observation and experimentation in order to obtain knowledge of the “natures” of living organisms. I argue that there is a parallel with Cassirer’s assertion of the differences between physical and cultural sciences, underwritten by the deployment of varying symbolic functions. I also propose that the neurological writings of Goldstein are an important backdrop to Cassirer’s positive evaluation of abstract thought, in contrast to the pessimism regarding a worldview dominated by scientific abstractions expressed by philosophers such as Bergson, Whitehead, and Husserl. (shrink)

According to platonists, entities such as numbers, sets, propositions and properties are abstract objects. But abstract objects lack causal powers and a location in space and time, so how could we ever come to know of the existence of such impotent and remote objects? In Knowledge, Cause, and Abstract Objects, Colin Cheyne presents the first systematic and detailed account of this epistemological objection to the platonist doctrine that abstract objects exist and can be known. Since mathematics has such a central (...) role in the acquisition of scientific knowledge, he concentrates on mathematical platonism. He also concentrates on our knowledge of what exists, and argues for a causal constraint on such existential knowledge. Finally, he exposes the weaknesses of recent attempts by platonists to account for our supposed platonic knowledge. This book will be of particular interest to researchers and advanced students of epistemology and of the philosophy of mathematics and science. It will also be of interest to all philosophers with a general interest in metaphysics and ontology. (shrink)

Cases where analogy has played a significant role in the formation of a new scientific concept are well-documented. Yet, how is it that genuinely new representations can be constructed from existing representations? It is argued that the process of ‘generic modeling’ enables abstraction of features common to both the domain of the source of the analogy and of the target phenomena. The analysis focuses on James Clerk Maxwell's construction of the electromagnetic field concept. The mathematical representation Maxwell constructed (...) turned out to be a system of abstract laws that when applied to electromagnetic systems yield laws of a dynamical system that will not map back onto the mechanicals domains used in their construction. (shrink)

The increasingly lively controversy over scientific realism has become one of the principal themes of recent philosophy. 1 In watching this controversy unfold in the rather technical way currently in vogue, it has seemed to me that it would be useful to view these contemporary disputes against the background of such older epistemological issues as fallibilism, scepticism, relativism, and the traditional realism/idealism debate. This, then, is the object of the present book, which will recon sider the newer concerns about (...) scientific realism in the context of these older philosophical themes. Historically, realism concerns itself with the real existence of things that do not "meet the eye" - with suprasensible entities that lie beyond the reach of human perception. In medieval times, discussions about realism focused upon universals. Recognizing that there are physical objects such as cats and triangular objects and red tomatoes, the medievels debated whether such "abstract objects" as cathood and triangularity and redness also exist by way of having a reality indepen dent of the concretely real things that exhibit them. Three fundamen tally different positions were defended: (1) Nominalism. Abstracta have no independent existence as such: they only "exist" in and through the objects that exhibit them. Only particulars (individual substances) exist. Abstract "objects" are existents in name only, mere thought fictions by whose means we address concrete particular things. (2) Realism. Abstracta have an independent existence as such. (shrink)