The paper explicates the stages of the author’s philosophical evolution in the light of Kopnin’s ideas and heritage. Starting from Kopnin’s understanding of dialectical materialism, the author has stated that category transformations of physics has opened from conceptualization of immutability to mutability and then to interaction, evolvement and emergence. He has connected the problem of physical cognition universals with an elaboration of the specific system of tools and methods of identifying, individuating and distinguishing objects from a scientific theory (...) domain. The role of vacuum conception and the idea of existence (actual and potential, observable and nonobservable, virtual and hidden) types were analyzed. In collaboration with S.Crymski heuristic and regulative functions of categories of substance, world as a whole as well as postulates of relativity and absoluteness, and anthropic and self-development principles were singled out. Elaborating Kopnin’s view of scientific theories as a practically effective and relatively true mapping of their domains, the author in collaboration with M. Burgin have originated the unified structure-nominative reconstruction (model) of scientific theory as a knowledge system. According to it, every scientific knowledge system includes hierarchically organized and complex subsystems that partially and separately have been studied by standard, structuralist, operationalist, problem-solving, axiological and other directions of the current philosophy of science. 1) The logico-linguistic subsystem represents and normalizes by means of different, including mathematical, languages and normalizes and logical calculi the knowledge available on objects under study. 2) The model-representing subsystem comprises peculiar to the knowledge system ways of their modeling and understanding. 3) The pragmatic-procedural subsystem contains general and unique to the knowledge system operations, methods, procedures, algorithms and programs. 4) From the viewpoint of the problem-heuristic subsystem, the knowledge system is a unique way of setting and resolving questions, problems, puzzles and tasks of cognition of objects into question. It also includes various heuristics and estimations (truth, consistency, beauty, efficacy, adequacy, heuristicity etc) of components and structures of the knowledge system. 5) The subsystem of links fixes interrelations between above-mentioned components, structures and subsystems of the knowledge system. The structure-nominative reconstruction has been used in the philosophical and comparative case-studies of mathematical, physical, economic, legal, political, pedagogical, social, and sociological theories. It has enlarged the collection of knowledge structures, connected, for instance, with a multitude of theoreticity levels and with an application of numerous mathematical languages. It has deepened the comprehension of relations between the main directions of current philosophy of science. They are interpreted as dealing mainly with isolated subsystems of scientific theory. This reconstruction has disclosed a variety of undetected knowledge structures, associated also, for instance, with principles of symmetry and supersymmetry and with laws of various levels and degrees. In cooperation with the physicist Olexander Gabovich the modified structure-nominative reconstruction is in the processes of development and justification. Ideas and concepts were also in the center of Kopnin’s cognitive activity. The author has suggested and elaborated the triplet model of concepts. According to it, any scientific concept is a dependent on cognitive situation, dynamical, multifunctional state of scientist’s thinking, and available knowledge system. A concept is modeled as being consisted from three interrelated structures. 1) The concept base characterizes objects falling under a concept as well as their properties and relations. In terms of volume and content the logical modeling reveals partially only the concept base. 2) The concept representing part includes structures and means (names, statements, abstract properties, quantitative values of object properties and relations, mathematical equations and their systems, theoretical models etc.) of object representation in the appropriate knowledge system. 3) The linkage unites a structures and procedures that connect components from the abovementioned structures. The partial cases of the triplet model are logical, information, two-tired, standard, exemplar, prototype, knowledge-dependent and other concept models. It has introduced the triplet classification that comprises several hundreds of concept types. Different kinds of fuzziness are distinguished. Even the most precise and exact concepts are fuzzy in some triplet aspect. The notions of relations between real scientific concepts are essentially extended. For example, the definition and strict analysis of such relations between concepts as formalization, quantification, mathematization, generalization, fuzzification, and various kinds of identity are proposed. The concepts «PLANET» and «ELEMENTARY PARTICLE» and some of their metamorphoses were analyzed in triplet terms. The Kopnin’s methodology and epistemology of cognition was being used for creating conception of the philosophy of law as elaborating of understanding, justification, estimating and criticizing legal system. The basic information on the major directions in current Western philosophy of law (legal realism, feminism, criticism, postmodernism, economical analysis of law etc.) is firstly introduced to the Ukrainian audience. The classification of more than fifty directions in modern legal philosophy is suggested. Some results of historical, linguistic, scientometric and philosophic-legal studies of the present state of Ukrainian academic science are given. (shrink)

This dissertation challenges two prevalent views on the topic of scientific explanation: that science explains by revealing causal mechanisms, and that science explains by unifying our knowledge of the world. ;My methodological strategy is to compare our best current philosophical accounts of scientific explanation with evidence from contemporary scientific research. In particular, I focus on evidence from dynamical explanations, that is, explanations which appeal to nonlinear dynamical modeling for their force. Nonlinear dynamical modeling is (...) a type of mathematical modeling which is used by scientists in many different disciplines, including population biology, ecology, physics, and psychology. ;Chapter 1 argues that dynamical explanations are a philosophically important class of explanations, based on their prevalence and their close relationship with the semantic view of theories. ;Chapters 2 and 3 conclude that extant causal and unification accounts encounter serious difficulties when applied to dynamical explanations. Chapter 2 argues that causal relevance is neither a necessary nor a sufficient condition for explanatory relevance. Chapter 3 clarifies and evaluates different claims about the unifying power of science. Here, I argue that dynamical explanations provide some support for the thesis that unification is constitutive of explanation. However, dynamical explanations also indicate that some of the intuitions embodied in extant unification accounts are untenable. ;Chapter 4 concludes by advancing diagnostic criticisms of existing causal and unification accounts. I explore the relationships between dynamical explanations and three conceptions of scientific explanation, as well as the relationships between different types of inference and scientific understanding. I suggest that philosophers look to cognitive science and the semantic view of theories for aid in constructing a viable positive account of explanation. ;The technical appendix introduces several key definitions and concepts of dynamical systems theory. (shrink)

Processes constitute the world of human experience - from nature to cognition to social reality. Yet our philosophical and scientific theories of nature and experience have traditionally prioritized concepts for static objects and structures. The essays collected here call for a review of the role of dynamic categories in the language of theories. They present old and new descriptive tools for the modelling of dynamic domains, and argue for the merits of process-based explanations in ontology, cognitive (...) science, semiotics, linguistics, philosophy of mind, robotics, theoretical biology, music theory, and philosophy of chemistry and physics. The collection is of interest to professional researchers in any of these fields; it establishes - for the very first time - crossdisciplinary contact among recent process-based research movements and might witness a conceptual paradigm shift in the making. (shrink)

The scientific methodology underlying model-building is critically investigated. The modeling views of Popper and Samuelson and their prototypes are critically examined in the light of the theme of the moral law of unity of knowledge and unity of the world-system configured by the meta-epistemology of organic unity of knowledge. Upon such critical examination of received methodology of model-building in economics, the extended perspective?namely of integrating the moral law derived from the divine roots as the meta-epistemology?is rigorously studied. The (...) example of the Islamic prerogative in interpreting the holistic world-system through model-building in economics is highlighted. A religio-philosophical approach is adopted to exemplify some approaches in Islamic model-building. An especial focus is placed here on grassroots types of financing and activities. The critique of these models within the existing Islamic scholarship is carried out. The result is new dimensions of macroeconomic analysis that emanate in a logical way from the meta-epistemological approach, and oppose the mainstream ideas, both in received and Islamic economic thinking as of now. (shrink)

There are two distinct approaches to Bayesian modelling in cognitive science. Black-box approaches use Bayesian theory to model the relationship between the inputs and outputs of a cognitive system without reference to the mediating causal processes; while mechanistic approaches make claims about the neural mechanisms which generate the outputs from the inputs. This paper concerns the relationship between these two approaches. We argue that the dominant trend in the philosophical literature, which characterizes the relationship between black-box and mechanistic approaches (...) to Bayesian cognitive science in terms of the dichotomy between instrumentalism and realism, is misguided. We propose that the two distinctions are orthogonal: black-box and mechanistic approaches to Bayesian modelling can each be given either an instrumentalist or a realist interpretation. We argue that the current tendency to conflate black-box approaches with instrumentalism and mechanistic approaches with realism stems from unwarranted assumptions about the nature of scientific explanation, the ontological commitments of scientific theories, and the role of abstraction and idealization in scientific models. We challenge each of these assumptions to reframe the debates over Bayesian modelling in cognitive science. (shrink)

Since the late 1980s, the neglect of experiment by philosophers and historians of science has been replaced by a keen interest in the subject. In this volume, a number of prominent philosophers of experiment directly address basic theoretical questions, develop existing philosophical accounts, and offer novel perspectives on the subject, rather than rely exclusively on historical cases of experimental practice. Each essay examines one or more of six interconnected themes that run throughout the collection: the philosophical implications of (...) actively and intentionally interfering with the material world while conducting experiments; issues of interpretation regarding causality; the link between science and technology; the role of theory in experimentation involving material and causal intervention; the impact of modeling and computer simulation on experimentation; and the philosophical implications of the design, operation, and use of scientific instruments. (shrink)

Philosophers’ traditional emphasis on theories, theoretical modeling, and explanation misguides research in philosophy of science. Articulating and applying core theories is part of scientific practice, but it is not the essence of scientific practice. Insofar as science has an essence, it is to systematically investigate and learn about what is not yet understood. This lecture analyzes genetics to articulate a broad-practice-centered approach to philosophy of science. It concludes by arguing that this approach can lead to (...) richer, deeper, and more useful philosophies of science, philosophies that can better inform science policy and the public’s understanding of science. (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 argues for a representational semantic conception of scientific theories, which respects the bare claim of any semantic view, namely that theories can be characterised as sets of models. RSC must be sharply distinguished from structural versions that assume a further identity of ‘models’ and ‘structures’, which we reject. The practice-turn in the recent philosophical literature suggests instead that modelling must be understood in a deflationary spirit, in terms of the diverse representational practices in the (...) sciences. These insights are applied to some mathematical models, thus showing that the mathematical sciences are not in principle counterexamples to RSC. (shrink)

The articles discusses the philosophical foundations and the traditions of the theory of the humanitarian and technological revolution. The subject-matter of HTR theory is the description and forecast of the transition from the industrial to the post-industrial phase of civilization development as well as the strategy and the most effective methods of management of various socio-economic systems. This theory, actively developing in recent years, focuses on goal setting and on determining priorities and development criteria in the field of technology, (...) science and education. The current revolution largely justifies the forecast of D. Bell, an author of the theory of post-industrial development, about the transition from the world of technology to the world of people. The human is the main subject and object of the changes. In this regard, we review an interdisciplinary program on human research, initiated in the 1980s by I.T. Frolov. The ongoing scientific revolution in genetics and the transition to autoevolution make these ideas even more relevant. The concept of universal evolutionism proposed by N.N. Moiseev is fundamental. This concept originates from philosophical and methodological generalizations based on the vast experience of computer modeling of “human-dimensional” systems. The principles of co-evolution of man and biosphere, the strategies for finding compromises are very close to the ecology of technologies, developed by the theory of HTR. It is difficult to overestimate the importance of the interdisciplinary concept of self-organization for many scientific fields and, in particular, for the theory of HTR. In our days, proposed by an outstanding mathematician, methodologist and thinker S.P. Kurdyumov, the interpretation of synergetics as a bridge between humanities and natural science, as a common language of natural scientists, mathematicians, scholars has become generally accepted. Kurdyumov predicted that many concepts and ideas of synergetics, through their philosophical understanding, would change the outlook and become an element of scientific culture. We show that this forecast turns into reality and in the process of HTR the ideas of synergetics begin to change our world. We pay special attention to the concept of self-developing systems, the theory of global scientific revolutions and the types of scientific rationality proposed by V.S. Stepin. In this regard, we can say that the HTR brings even more large-scale changes, covering not only science but also technology, society, the inner world of man. Identifying the philosophical foundations of HTR, we contribute to the development of methodology of this approach, enhance intra-scientific reflection and make possible to formulate unsolved problems more accurately. (shrink)

What structure of scientific communication and cooperation, between what kinds of investigators, is best positioned to lead us to the truth? Against an outline of standard philosophical characteristics and a recent turn to social epistemology, this paper surveys highlights within two strands of computational philosophy of science that attempt to work toward an answer to this question. Both strands emerge from abstract rational choice theory and the analytic tradition in philosophy of science rather than postmodern sociology of science. (...) The first strand of computational research models the effect of communicative networks within groups, with conclusions regarding the potential benefit of limited communication. The second strand models the potential benefits of cognitive diversity within groups. Examples from each strand of research are used in analyzing what makes modeling of this sort both promising and distinctly philosophical, but are also used to emphasize possibilities for failure and inherent limitations as well. (shrink)

This article outlines how conceptual spaces theory applies to modeling changes of scientific frameworks when these are treated as spatial structures rather than as linguistic entities. The theory is briefly introduced and five types of changes are presented. It is then contrasted with Michael Friedman’s neo-Kantian account that seeks to render Kuhn’s “paradigm shift” as a communicatively rational historical event of conceptual development in the sciences. Like Friedman, we refer to the transition from Newtonian to relativistic mechanics as (...) an example of “deep conceptual change.” But we take the communicative rationality of radical conceptual change to be available prior to the philosophical meta-paradigms that Friedman deems indispensable for this purpose. (shrink)

Information is a basic structure of the world, while computation is a process of the dynamic change of information. This book provides a cutting-edge view of world's leading authorities in fields where information and computation play a central role. It sketches the contours of the future landscape for the development of our understanding of information and computation, their mutual relationship and the role in cognition, informatics, biology, artificial intelligence, and information technology. -/- This book is an utterly enjoyable and engaging (...) read which gives readers an opportunity to understand and relate phenomena seemingly unrelated in a completely new light — especially the connections between information, computation, cognition and life. -/- Contents: Cybersemiotics and the Question of Knowledge (Søren Brier) Information Dynamics in a Categorical Setting (Mark Burgin) Mathematics as a Biological Process (G J Chaitin) Information, Causation and Computation (John Collier) From Descartes to Turing: The Computational Content of Supervenience (S Barry Cooper) A Dialogue Concerning Two World Systems: Info-Computational vs Mechanistic (Gordana Dodig-Crnkovic & Vincent C Müller) Does Computing Embrace Self-Organization? (Wolfgang Hofkirchner) Analysis of Information and Computation in Physics Explains Cognitive Paradigms: From Full Cognition to Laplace Determinism to Statistical Determinism to Modern Approach (Vladik Kreinovich, Roberto Araiza & Juan Ferret) Bodies — Both Informed and Transformed Embodied Computation and Information Processing (Bruce J MacLennan) Computation on Information, Meaning and Representations: An Evolutionary Approach (Christophe Menant) Interior Grounding, Reflection, and Self-Consciousness (Marvin Minsky) A Molecular Dynamic Network: Minimal Properties and Evolutionary Implications (Walter Riofrio) Super-recursive Features of Evolutionary Processes and the Models for Computational Evolution (Darko Roglic) Towards a Modeling View of Computing (Oron Shagrir) What's Information, for an Organism or Intelligent Machine? How can a Machine or Organism Mean? (Aaron Sloman) Inconsistent Knowledge as a Natural Phenomenon: The Ranking of Reasonable Inferences as a Computational Approach to Naturally Inconsistent (Legal) Theories (Kees (CNJ) de Vey Mestdagh & Jaap Henk (JH) Hoepman) On the Algorithmic Nature of the World (Hector Zenil & Jean-Paul Delahaye) . (shrink)

Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific (...) practitioners are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing. (shrink)

Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal (...) Science. Using automated text mining techniques I measure the frequency and distribution of several groups of philosophically interesting words, such as "explain", "cause", "evidence", "theory", "law", "mechanism", and "model". I show that "explain" words are much more common in scientific writing than in other genres, occurring in roughly half of all articles, and that their use is very often qualified or negated. These results about the use of words complement traditional conceptual analysis. Next I use random samples from the data set to develop a large number of small case studies across a wide range of scientific disciplines. I use a sample of "explain" sentences to develop and defend a new general philosophical account of scientific explanation, and then test my account against a larger set of randomly sampled sentences and abstracts. Five coarse categories can classify the explanans and explananda of my cases: data, entities, kinds, models, and theories. The pair of the categories of the explanans and explanandum indicates the "form" of an explanation. The explain-relation supports counterfactual reasoning about the dependence of qualities of the explanandum on qualities of the explanans. But for each form there is a different "core relation" between explanans and explanandum that supports the explain-relation. Causation, modelling, and argument are the core relations for different forms of scientific explanation between different categories of explanans and explananda. This flexibility allows me to resolve some of the fragmentation in the philosophical literature. I provide empirical evidence to show that my general philosophical account successfully describes a wide range of scientific practise across a large number of scientific disciplines. (shrink)

We discuss ways in which category theory might be useful in philosophy of science, in particular for articulating the structure of scientific theories. We argue, moreover, that a categorical approach transcends the syntax-semantics dichotomy in 20th century analytic philosophy of science.

This book provides a methodological perspective on understanding the essential roles of econometric models in the theory and practice. Offering a comprehensive and comparative exposition of the accounts of models in both econometrics and philosophy of science, this work shows how econometrics and philosophy of science are interconnected while exploring the methodological insight of econometric modelling that can be added to modern philosophical thought. The notion of structure is thoroughly discussed throughout the book. The studies of the consumption function (...) of Trygve Haavelmo, Richard Stone, Milton Friedman, David Hendry and Robert Lucas are taken as the case studies to investigate their methodological implications of model and structure. In addition to the semantic view of the scientific theories, various philosophical accounts concerning scientific models are used to shed light on the methodological nature of these consumption studies in economics. This book will be of great interest to scholars and students of methodology of economics and econometrics as well as anyone interested in the philosophy of science in an economic context. (shrink)

Philosophy of Science; Ukraine; Polysytemic nature of theories; Practical theories; Subsystems of a theory.

Suppe, F. The search for philosophic understanding of scientific theories (p. [1]-241)--Proceedings of the symposium.--Bibliography, compiled by Rew A. Godow, Jr. (p. [615]-646).

The English Synopsis is after the text of the book. The book presents an original and generalizing substantive vision of the philosophy of science through the prism of a detailed analysis of the polysystem structure of scientific theories. Theories are considered, firstly, as complex specialized forms of developed scientific thinking about the realities studied by natural science, secondly, as constantly improving tools for producing new knowledge in interaction with experimental research, and thirdly, as carriers of ordered (...) and verified knowledge. Emphasis is placed on their nominal and ontic subsystems. The book develops personal and joint research of the authors (theoretical physicist and philosopher), the experience of teaching philosophy of physics at NaUKMA, philosophy of science at the Higher School of Philosophy at the H. Skovoroda Institute of Philosophy of the National Academy of Sciences of Ukraine and theoretical physics at the National Technical University "Ihor Sikorsky Kyiv Polytechnic Institute". The research is based on a significant source base covering works of modern Western researchers in natural science and philosophy of science. For students, teachers, and scientists who are interested in the problems of modern philosophy of science and have a certain amount of scientific knowledge. It will also be useful for high school students who are eager to become scientists. (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)

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)

The use of models of scientific theories should not be done without qualifications about the mathematics being used to build the models. This looks obvious, at least for logicians, but generally, it is not to the philosopher of science. Thus, some details about this point seem useful for both. Since any quick revision in the literature shows that in most cases, mainly after the raising of the semantic approach, the models are taken to be set-theoretical structures, in discussing (...) the issue we shall be concerned more with set theories, the locus where the play is usually developed. (shrink)

Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using (...) a recent exchange between two groups of mathematical modelers in plant biology. Scientific debate can arise from different modeling philosophies. (shrink)

The recognition that models and simulations play a central role in the epistemology of science is about fifteen years old. Although models had long been discussed as possible foundational units in the logical analysis of scientific knowledge, the philosophical study of modelling as a distinct epistemic practice really got going in the wake of the Models as Mediators anthology edited by Margaret Morrison and Mary Morgan. In spite of the broad agreement that in fact much of science is (...) model-based, however, there is still little agreement on pretty much anything else. What are models? Are they representations or fictions, abstract entities or concrete artifacts? Which functions do they play? Can they explain.. (shrink)

Philosophy of science has undergone a naturalistic turn, moving away from traditional idealized concerns with the logical structure of scientific theories and toward focusing on real-world scientific practice, especially in domains such as modeling and experimentation. As part of this shift, recent work has explored how the project of philosophically understanding science as a natural phenomenon can be enriched by drawing from different fields and disciplines, including niche construction theory in evolutionary biology, on the one hand, (...) and ecological and enactive views in embodied cognitive science, on the other. But these insights have so far been explored in separation from each other, without clear indication of whether they can work together. Moreover, the focus on particular practices, however insightful, has tended to lack consideration of potential further implications for a naturalized understanding of science as a whole (i.e., above and beyond those particular practices). Motivated by these developments, here we sketch a broad-ranging view of science, scientific practice and scientific knowledge in terms of ecological-enactive co-construction. The view we propose situates science in the biological, evolutionary context of human embodied cognitive activity aimed at addressing the demands of life. This motivates reframing theory as practice, and reconceptualizing scientific knowledge in ecological terms, as relational and world-involving. Our view also brings to the forefront of attention the fundamental link between ideas about the nature of mind, of science and of nature itself, which we explore by outlining how our proposal differs from more conservative, and narrower, conceptions of “cognitive niche construction.”. (shrink)

This volume reflects the ‘philosophy of science in practice’ approach and takes a fresh look at traditional philosophical problems in the context of natural, social, and health research. Inspired by the work of Nancy Cartwright that shows how the practices and apparatuses of science help us to understand science and to build theories in the philosophy of science, this volume critically examines the philosophical concepts of evidence, laws, causation, and models and their roles in the process of (...) scientific reasoning. Each chapter is an important one in the philosophy of science, while the volume as a whole deals with these philosophical concepts in a unified way in the context of actual scientific practice. This volume thus aims to contribute to this new direction in the philosophy of science.​. (shrink)

In today's philosophy of science, scientific theories are construed as abstract mathematical objects: formal axiomatic systems or classes of set-theoretic models. By focusing exclusively on the logico-mathematical structure of theories, however, this approach ignores their essentially cognitive nature: that theories are conceptualizations of the world produced by some cognitive agents. As a result, traditional philosophical analyses of scientific theories are incapable of coherently accounting for the relevant relations between highly abstract and idealized models (...) in science and concrete empirical phenomena in the world. ;As a more accurate and comprehensive alternative to traditional analyses of scientific theorizing, the dissertation proposes and develops a conception of scientific theories which makes explicit the essential role of cognitive agents--theorizers--in generating abstract scientific models and systematically relating such models to experimentally controlled parts of the world. ;Specifically, by utilizing the conceptually powerful formal framework of the Theory of Categories, the new approach clarifies and makes formally precise the cognitive status of several important aspects of scientific theorizing, including the notion of a scientific model as theorizers' mathematical conceptualization of the world jointly determined by theorizers' physical interactions with the world and their cognitive access to mathematical objects, the distinction between models in science and models in pure mathematics, the distinction between provisional and successful scientific models, the notion of a systematic correspondence between successful scientific models and the world which does not impose upon the world the mathematical structure of scientific models, and the way in which theorizers' modeling strategy determines the general structure of scientific knowledge. (shrink)

This book addresses the logical aspects of the foundations of scientific theories. Even though the relevance of formal methods in the study of scientific theories is now widely recognized and regaining prominence, the issues covered here are still not generally discussed in philosophy of science. The authors focus mainly on the role played by the underlying formal apparatuses employed in the construction of the models of scientific theories, relating the discussion with the so-called semantic (...) approach to scientific theories. The book describes the role played by this metamathematical framework in three main aspects: considerations of formal languages employed to axiomatize scientific theories, the role of the axiomatic method itself, and the way set-theoretical structures, which play the role of the models of theories, are developed. The authors also discuss the differences and philosophical relevance of the two basic ways of aximoatizing a scientific theory, namely Patrick Suppes’ set theoretical predicates and the "da Costa and Chuaqui" approach. This book engages with important discussions of the nature of scientific theories and will be a useful resource for researchers and upper-level students working in philosophy of science. (shrink)

This book presents an elaborate analysis of the widely discussed problem of reconstruction of scientific theory change, based on material from theoretical physics. It gives a detailed , although not complete, analysis of the ideas of such authors as T. Kuhn, I. Lakatos, P. Feyerabend, E. Zahar and G. Holton, the empiristic account of the notion of “crucial experiment”, as well as of some leading Russian philosophers of science such as V. Stepin, E. Mamchur and V. Branskii. On the (...) positive side, the book offers an original model of reconstruction of scientific theory change. As the author himself insists on several occasions, his model does not pretend to completeness. Nugayev’ s model of scientific theory change is extensively tested on the example of the Lorentz-Einstein transition. The result is an empirical justification of his model, which shows not only that it works quite well in this particular reconstruction, but also that it explains some historical facts that have been left aside by some other authors. (shrink)

Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I (...) compare the positions of these two views with respect to four points regarding ontological assumptions: (1) the origin of ontological assumptions, (2) the relation of such assumptions to the formal models of the same theory, (3) their use in integrating and negotiating different formal models of distinct theories, and (4) their employment in explanatory activity. Dialectical is here used in both its Hegelian–Marxist sense of opposition and tension between alternative positions and in its Platonic sense of dialogue between advocates of distinct theories. I investigate three case studies, from Levins and Lewontin as well as from a recent paper of mine, that show the relevance and power of the dialectical understanding of theorizing and modeling. (shrink)

The philosophical interest in experimental practice in neuroscience has brought renewed attention to the study of the development and use of techniques and tools for data production. John Bickle has argued that the construction and progression of theories in neuroscience are entirely dependent on the development and ingenious use of research tools. In Bickle's account, theory plays a tertiary role, as it depends on what the tools allow researchers to manipulate, and the tools, in turn, are developed not (...) in order to test theories but as solutions to engineering problems. However, Bickle's account is not entirely precise in explaining what informs researchers' decision-making in their atheoretical laboratory tinkering. Identifying the sources that guide researchers in tool development and use is crucial if one wishes to contribute to the philosophical or meta-scientific understanding of experimental practice in neuroscience. In the following paper, I claim that decision-making in tools' development and use in neuroscience is doubly guided. Pre-existing theory and concepts determine information's relevance, whereas tools' functioning in controlled situations determines information's reliability. Accordingly, experimenters' decision-making is situated both in the context of analysing, modelling or interpreting information and in the context of producing information. I study the case of the tungsten microelectrode developed by David Hubel during the 1950s. First, I show that pre-existing theory and concepts determine in advance what information would be relevant to obtain from the microelectrode. Second, I show that Hubel's tinkering follows the guidelines derived from the very structure of what we recognise as reliable experimentally produced information. Finally, I suggest that data-production processes allow experimenters to assess what to expect from an experimental system in terms of concept- and theory-generation and confirmation, thereby endorsing Bickle's tenet on the tertiary role of theory in neuroscience. (shrink)

In his book “Reconstruction of Scientific Change” R.M. Nugayev proposes a new model of theory change by analyzing the reasons for theory change in science. Nugayev’s theoretical concept is based on a realist’s philosophical attitude. The most important notions of Nugayev’ s conception of theory change are “theories’ cross” and “crossbred objects”, which he takes from the terminology of other Russian philosophers of science (Bransky, Podgoretzky, Smorodinsky). His investigations often refer to several famous Western philosophers. Yet his (...) study is not free of some drawbacks. Nevertheless, Nugayev’s book is worth reading and discussing within the current debate about the structure of scientific revolution and theory changes. (shrink)

What are scientific theories and how should they be represented? In this article, I propose a causal–structural account, according to which scientific theories are to be represented as sets of interrelated causal and credal nets. In contrast with other accounts of scientific theories (such as Sneedian structuralism, Kitcher’s unificationist view, and Darden’s theory of theoretical components), this leaves room for causality to play a substantial role. As a result, an interesting account of explanation is (...) provided, which sheds light on explanatory unification within a causalist framework. The theory of classical genetics is used as a case study. 1 Introduction2 The Theory of Classical Genetics3 Three Philosophical Accounts of the Theory of Classical Genetics3.1 The structuralist account3.2 Kitcher’s unificationism3.3 Darden and theory change in science4 A Common Lacuna: Where is Causality?5 Woodward’s Interventionist Account of Causation6 Causal Bayes Nets and Their Interrelations6.1 Causal Bayes nets6.2 Relations among causal nets6.3 Credal nets and their interrelations7 The Theory of the Gene and its Causal Graph8 A First Exemplar: Stem Length in Pea Plants8.1 Three crosses on stem length in pea plants8.2 The causal graph for stem length in pea plants8.3 Morgan’s explanatory principles and the credal net for stem length in pea plants9 Explaining Mendel’s Crosses: A Causal–Structural Account10 Monohybrid Crosses with Complete Dominance11 Exemplars,Explanatory Patterns, Generic Credal Nets, and Mechanism Schemas12 Incomplete Dominance13 Anomalies14 Multi-hybrid Crosses with Independent Assortment15 Multi-hybrid Crosses with Linkage and Crossing-Over16 Double Crossing-Over and the Linear Order of the Gene17 Causal–Structural Explanation18 Explanatory Unification19 Concluding Remarks. (shrink)

Predictive processing approaches to the mind are increasingly popular in the cognitive sciences. This surge of interest is accompanied by a proliferation of philosophical arguments, which seek to either extend or oppose various aspects of the emerging framework. In particular, the question of how to position predictive processing with respect to enactive and embodied cognition has become a topic of intense debate. While these arguments are certainly of valuable scientific and philosophical merit, they risk underestimating the variety (...) of approaches gathered under the predictive label. Here, we first present a basic review of neuroscientific, cognitive, and philosophical approaches to PP, to illustrate how these range from solidly cognitivist applications—with a firm commitment to modular, internalistic mental representation—to more moderate views emphasizing the importance of ‘body-representations’, and finally to those which fit comfortably with radically enactive, embodied, and dynamic theories of mind. Any nascent predictive processing theory must take into account this continuum of views, and associated theoretical commitments. As a final point, we illustrate how the Free Energy Principle attempts to dissolve tension between internalist and externalist accounts of cognition, by providing a formal synthetic account of how internal ‘representations’ arise from autopoietic self-organization. The FEP thus furnishes empirically productive process theories by which to guide discovery through the formal modelling of the embodied mind. (shrink)

The six essays in this volume discuss philosophical thought on scientific theory including: a call for a realist, rather than instrumentalist interpretation of science; a critique of one of the core ideas of positivism concerning the relation between observational and theoretical languages; using aerodynamics to discuss the representational aspect of scientific theories and their isomorphic qualities; the relationship between the reliability of common sense and the authenticity of the world view of science; removing long-held ambiguities on (...) the theory of inductive logic; and the relationship between the actuality of conceptual revolutions in the history of science and traditional philosophical pictures of scientific theory-building. (shrink)

Earlier in this century, many philosophers of science (for example, Rudolf Carnap) drew a fairly sharp distinction between theory and observation, between theoretical terms like 'mass' and 'electron', and observation terms like 'measures three meters in length' and 'is _2° Celsius'. By simply looking at our instruments we can ascertain what numbers our measurements yield. Creatures like mass are different: we determine mass by calculation; we never directly observe a mass. Nor an electron: this term is introduced in order to (...) explain what we observe. This (once standard) distinction between theory and observation was eventually found to be wanting. First, if the distinction holds, it is difficult to see what can characterize the relationship between theory :md observation. How can theoretical terms explain that which is itself in no way theorized? The second point leads out of the first: are not the instruments that provide us with observational material themselves creatures of theory? Is it really possible to have an observation language that is entirely barren of theory? The theory-Iadenness of observation languages is now an accept ed feature of the logic of science. Many regard such dependence of observation on theory as a virtue. If our instruments of observation do not derive their meaning from theories, whence comes that meaning? Surely - in science - we have nothing else but theories to tell us what to try to observe. (shrink)

Scientific inquiry has led to immense explanatory and technological successes, partly as a result of the pervasiveness of scientific theories. Relativity theory, evolutionary theory, and plate tectonics were, and continue to be, wildly successful families of theories within physics, biology, and geology. Other powerful theory clusters inhabit comparatively recent disciplines such as cognitive science, climate science, molecular biology, microeconomics, and Geographic Information Science (GIS). Effective scientific theories magnify understanding, help supply legitimate explanations, and assist (...) in formulating predictions. Moving from their knowledge-producing representational functions to their interventional roles (Hacking 1983), theories are integral to building technologies used within consumer, industrial, and scientific milieus. -/- This entry explores the structure of scientific theories from the perspective of the Syntactic, Semantic, and Pragmatic Views. Each of these views answers questions such as the following in unique ways. What is the best characterization of the composition and function of scientific theory? How is theory linked with world? Which philosophical tools can and should be employed in describing and reconstructing scientific theory? Is an understanding of practice and application necessary for a comprehension of the core structure of a scientific theory? How are these three views ultimately related? (shrink)

Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much (...) of Volterra's and Pauling's work involved modeling; much of Darwin's and Mendeleev's did not. In order to capture this distinction, I consider two examples of theory construction in detail: Volterra's treatment of post-WWI fishery dynamics and Mendeleev's construction of the periodic system. I argue that modeling can be distinguished from other forms of theorizing by the procedures modelers use to represent and to study real-world phenomena: indirect representation and analysis. This differentiation between modelers and non-modelers is one component of the larger project of understanding the practice of modeling, its distinctive features, and the strategies of abstraction and idealization it employs. (shrink)

Contents Acknowledgements vii Illustrations ix Preface xi Further Bibliography of A.C. Crombie xiii 1 Designed in the Mind: Western visions of Science, Nature and Humankind 1 2 The Western Experience of Scientific Objectivity 13 3 Historical Perceptions of Medieval Science 31 4 Robert Grosseteste 39 5 Roger Bacon [with J.D. North] 51 6 Infinite Power and the Laws of Nature: A Medieval Speculation 67 7 Experimental Science and the Rational Artist in Early Modern Europe 89 8 Mathematics and Platonism (...) in the Sixteenth-Century Italian Universities and in Jesuit Educational Policy 115 9 Sources of Galileo Galilei’s Early Natural Philosophy 149 10 The Jesuits and Galileo’s Ideas of Science and of Nature [with A. Carugo] 165 11 Galileo and the Art of Rhetoric [with A. Carugo] 231 12 Galileo Galilei: A Philosophical Symbol 257 13 Alexandre Koyré and Great Britain: Galileo and Mersenne 263 14 Marin Mersenne and the Origins of Language 275 15 Le Corps à la Renaissance: Theories of Perceiver and Perceived in Hearing 291 16 Expectation, Modelling and Assent in the History of Optics: i, Alhazen and the Medieval Tradition; ii, Kepler and Descartes 301 17 Contingent Expectation and Uncertain Choice: Historical Contexts of Arguments from Probabilities 357 18 P.-L. Moreau de Maupertuis, F.R.S. : Précurseur du Transformisme 407 19 The Public and Private Faces of Charles Darwin 429 20 The Language of Science 439 21 Some Historical Questions about Disease 443 22 Historians and the Scientific Revolution 451 23 The Origins of Western Science 465 Appendix to Chapter 10: 479 Sources and Dates of Galileos Writings [with A. Carugo] Pietro Redondi, Galileo eretico [with A. Carugo] Mario Biagioli, Galileo, Courtier Corrections to Science, Optics and Music in Medieval and Early Modern Thought 495 Index 497. (shrink)

Rationality - as opposed to 'ad-hoc' - and asymptotics - to emphasize the fact that perturbative methods are at the core of the theory - are the two main concepts associated with the Rational Asymptotic Modeling (RAM) approach in fluid dynamics when the goal is to specifically provide useful models accessible to numerical simulation via high-speed computing. This approach has contributed to a fresh understanding of Newtonian fluid flow problems and has opened up new avenues for tackling real fluid (...) flow phenomena, which are known to lead to very difficult mathematical and numerical problems irrespective of turbulence. With the present scientific autobiography the author guides the reader through his somewhat non-traditional career; first discovering fluid mechanics, and then devoting more than fifty years to intense work in the field. Using both personal and general historical contexts, this account will be of benefit to anyone interested in the early and contemporary developments of an important branch of theoretical and computational fluid mechanics. (shrink)

In this paper we consider the notions of structure and models within the semantic approach to theories. To highlight the role of the mathematics used to build the structures which will be taken as the models of theories, we review the notion of mathematical structure and of the models of scientific theories. Then, we analyse a case-study and argue that if a certain metaphysical view of quantum objects is adopted, namely, that which sees them as non-individuals, (...) then there would be strong reasons to ask for a different mathematical framework for describing the structures that would be the models of the corresponding theory. In departing from the standard frameworks, we hope to bring to the scene, within the scope of the semantic approach, the importance of paying attention to some fundamental concepts usually only superficially touched by philosophers of science. (shrink)

In this paper we discuss two approaches to the axiomatization of scientific theories in the context of the so called semantic approach, according to which (roughly) a theory can be seen as a class of models. The two approaches are associated respectively to Suppes’ and to da Costa and Chuaqui’s works. We argue that theories can be developed both in a way more akin to the usual mathematical practice (Suppes), in an informal set theoretical environment, writing the (...) set theoretical predicate in the language of set theory itself or, more rigorously (da Costa and Chuaqui), by employing formal languages that help us in writing the postulates to define a class of structures. Both approaches are called internal , for we work within a mathematical framework, here taken to be first-order ZFC. We contrast these approaches with an external one, here discussed briefly. We argue that each one has its strong and weak points, whose discussion is relevant for the philosophical foundations of science. (shrink)

This monograph offers a critical introduction to current theories of how scientific models represent their target systems. Representation is important because it allows scientists to study a model to discover features of reality. The authors provide a map of the conceptual landscape surrounding the issue of scientific representation, arguing that it consists of multiple intertwined problems. They provide an encyclopaedic overview of existing attempts to answer these questions, and they assess their strengths and weaknesses. The book also (...) presents a comprehensive statement of their alternative proposal, the DEKI account of representation, which they have developed over the last few years. They show how the account works in the case of material as well as non-material models; how it accommodates the use of mathematics in scientific modelling; and how it sheds light on the relation between representation in science and art. The issue of representation has generated a sizeable literature, which has been growing fast in particular over the last decade. This makes it hard for novices to get a handle on the topic because so far there is no book-length introduction that would guide them through the discussion. Likewise, researchers may require a comprehensive review that they can refer to for critical evaluations. This book meets the needs of both groups. (shrink)

This paper explores a new reason for preferring a model-theoretic approach to understanding the nature of scientific theories. Identifying the models in philosophers' model-theoretic accounts of theories with the concepts in cognitive scientists' accounts of categorization suggests a structure to families of models far richer than has commonly been assumed. Using classical mechanics as an example, it is argued that families of models may be "mapped" as an array with "horizontal" graded structures, multiply hierarchical "vertical" structures, and (...) local "radial" structures. These structures promise important implications for how scientific theories are learned and used in actual scientific practice. (shrink)

This volume is the record of a symposium on the structer of scientific theories held in urbana, Illinois in the spring of 1969. ofSeven main papers, commentaries, discussions, and a postscript form the bulk of the book. The rest is a nearly 240-page monograph-in-the-guise-of-an-introduction by the editor titled “The Search for Philosophic Understanding of Scientific Theories”.

The six essays in this volume discuss philosophical thought on scientific theory including: a call for a realist, rather than instrumentalist interpretation of science; a critique of one of the core ideas of positivism concerning the relation between observational and theoretical languages; using aerodynamics to discuss the representational aspect of scientific theories and their isomorphic qualities; the relationship between the reliability of common sense and the authenticity of the world view of science; removing long-held ambiguities on (...) the theory of inductive logic; and the relationship between the actuality of conceptual revolutions in the history of science and traditional philosophical pictures of scientific theory-building. (shrink)

The behavior/structure methodological dichotomy as locus of scientific inquiry is closely related to the issue of modeling and theory change in scientific explanation. Given that the traditional tension between structure and behavior in scientific modeling is likely here to stay, considering the relevant precedents in the history of ideas could help us better understand this theoretical struggle. This better understanding might open up unforeseen possibilities and new instantiations, particularly in what concerns the proposed technological modification (...) of the human condition. The sequential structure of this paper is twofold. The contribution of three philosophers better known in the humanities than in the study of science proper are laid out. The key theoretical notions interweaving the whole narrative are those of mechanization, constructability and simulation. They shall provide the conceptual bridge between these classical thinkers and the following section. Here, a panoramic view of three significant experimental approaches in contemporary scientific research is displayed, suggesting that their undisclosed ontological premises have deep roots in the Western tradition of the humanities. This ontological lock between core humanist ideals and late research in biology and nanoscience is ultimately suggested as responsible for pervasively altering what is canonically understood as “human”. (shrink)

This volume addresses the question of time from the perspective of the time of nature. Its aim is to provide some insights about the nature of time on the basis of the different uses of the concept of time in natural sciences. Presenting a dialogue between philosophy and science, it features a collection of papers that investigate the representation, modeling and understanding of time as they appear in physics, biology, geology and paleontology. It asks questions such as: whether or (...) not the notions of time in the various sciences are reducible to the same physical time, what status should be given to timescale differences, or what are the specific epistemic issues raised by past facts in natural sciences. The book first explores the experience of time and its relation to time in nature in a set of chapters that bring together what human experience and physics enable metaphysicians, logicians and scientists to say about time. Next, it studies time in physics, including some puzzling paradoxes about time raised by the theory of relativity and quantum mechanics. The volume then goes on to examine the distinctive problems and conceptions of time in the life sciences. It explores the concept of deep time in paleontology and geology, time in the epistemology of evolutionary biology, and time in developmental biology. Each scientific discipline features a specific approach to time and uses distinctive methodologies for implementing time in its models. This volume seeks to define a common language to conceive of the distinct ways different scientific disciplines view time. In the process, it offers a new approach to the issue of time that will appeal to a wide range of readers: philosophers and historians of science, metaphysicians and natural scientists - be they scholars, advanced students or readers from an educated general audience. (shrink)