Most philosophical accounts of scientific models assume that models represent some aspect, or some theory, of reality. They also assume that interpretation plays only a supporting role. This paper challenges both assumptions. It proposes that models can be used in science to interpret reality. (a) I distinguish these interpretative models from representational ones. They find new meanings in a target system’s behaviour, rather than fit its parts together. They are built through idealisation, abstraction and recontextualisation. (b) To show how interpretative (...) models work, I offer a case study on the scientific controversy over foetal pain. It highlights how pain scientists use conflicting models to interpret the human foetus and its behaviour, and thereby to support opposing claims about whether the foetus can feel pain. (c) I raise a sceptical worry and a methodological challenge for interpretative models. To address the latter, I use my case study to compare how interpretative and representational models ought to be evaluated. (shrink)

Research on computational models of scientific discovery investigates both the induction of descriptive laws and the construction of explanatory models. Although the work in law discovery centers on knowledge‐lean approaches to searching a problem space, research on deeper modeling tasks emphasizes the pivotal role of domain knowledge. As an example, our own research on inductive process modeling uses information about candidate processes to explain why variables change over time. However, our experience with IPM, an artificial intelligence system that implements this (...) approach, suggests that process knowledge is insufficient to avoid consideration of implausible models. To this end, the discovery system needs additional knowledge that constrains the model structures. We report on an extended system, SC‐IPM, that uses such information to reduce its search through the space of candidates and to produce models that human scientists find more plausible. We also argue that although people carry out less extensive search than SC‐IPM, they rely on the same forms of knowledge—processes and constraints—when constructing explanatory models. (shrink)

Scientific models are used to predict and understand the target phenomena in the reality. The kind of epistemic relationship between the model and the reality is always regarded by most of the philosophers as a representational one. I argue that, complementary to this representational role, some of the scientific models have a constructive role to play in altering and reconstructing the reality in a physical way. I hold that the idealized model assumptions and elements bestow the constructive force of a (...) model on the reality. By recognizing the physical constructive force of some scientific models, the merit of these models could be judged by how successful they are in the reality construction, rather than by the traditional criterion of model-world representation. (shrink)

In this paper, I discuss the discovery of the DNA structure by Francis Crick and James Watson, which has provoked a large historical literature but has yet not found entry into philosophical debates. I want to redress this imbalance. In contrast to the available historical literature, a strong emphasis will be placed upon analysing the roles played by theory, model, and evidence and the relationship between them. In particular, I am going to discuss not only Crick and Watson's well-known model (...) and Franklin's x-ray diffraction pictures (the evidence) but also the less well known theory of helical diffraction, which was absolutely crucial to Crick and Watson's discovery. The insights into this groundbreaking historical episode will have consequences for the ‘new’ received view of scientific models and their function and relationship to theory and world. The received view, dominated by works by Cartwright and Morgan and Morrison ([1999]), rather than trying to put forth a ‘theory of models’, is interested in questions to do with (i) the function of models in scientific practice and (ii) the construction of models. In regard to (i), the received view locates the model (as an idealized, simplified version of the real system under investigation) between theory and the world and sees the model as allowing the application of the former to the latter. As to (ii) Cartwright has argued for a phenomenologically driven view and Morgan and Morrison ([1999]) for the ‘autonomy’ of models in the construction process: models are determined neither by theory nor by the world. The present case study of the discovery of the DNA structure strongly challenges both (i) and (ii). In contrast to claim (i) of the received view, it was not Crick and Watson's model but rather the helical diffraction theory which served a mediating purpose between the model and the x-ray diffraction pictures. In particular, Cartwright's take on (ii) is refuted by a comparison of Franklin's bottom-up approach with Crick and Watson's top-down approach in constructing the model. The former led to difficulties, which only a strong confidence in the structure incorporated in the model could circumvent. How to Get to the Structure 1.1 X-ray diffraction and its synthesis 1.2 Model building and Pauling's panache 1.3 The structure of proteins 1.3.1 A failed inference to the best explanation 1.3.2 The misleading 5.1 Å spot in proteins and how to get rid of it 1.3.3 Derived predictions from Pauling's alpha-helix of protein molecules The CCV Theory of Helical X-Ray Diffraction 2.1 The role of the CCV theory in the discovery of the DNA structure Killing the Helix 3.1 Appreciating all evidence—in vain Conclusion Epilogue: Chargaff's Ratios CiteULike Connotea Del.icio.us What's this? (shrink)

The paper studies the nature of understanding in condensed matter physics (CMP), mediated by the successful employment of its models. I first consider two obvious candidates for the criteria of model-based understanding, Van Fraassen's sense of empirical adequacy and Hacking's instrumental utility , and conclude that both are unsatisfactory. Inspired by Hasok Chang's recent proposal to reformulate realism as the pursuit of ontological plausibility in our system of knowledge, we may require the model under consideration to be understood (or intelligible) (...) before claiming model-based understanding. Here the understanding of a model typically consists of the following: figuring out at least one plausible (preferably realistic) physical mechanism for the model, determining the theoretical consequences of the model by mathematically probing it and developing our physical intuitions about the model. I consider the q-state Potts model to illustrate. After having understood a model, we may employ the model to understand its target phenomena in the world. This is done by matching one of the interpretative models of the model with the central features of the phenomena. The matching should be motivated (ideally both theoretically and empirically) in the sense that we have good reason to believe that the central features of the phenomena can be thought of as having more or less the same structure as postulated by the interpretative model. In conclusion, I propose a two-stage account of model-based understanding in CMP: (1) understanding of a model and (2) matching a target phenomenon with a well-motivated interpretative model of the model. Empirical success and instrumental utility both play their roles in the evaluation of how successful the model is, but are not the essential part of model-based understanding. (shrink)

This eprint has been removed by the author's request.

A distinction is made between theory-driven and phenomenological models. It is argued that phenomenological models are significant means by which theory is applied to phenomena. They act both as sources of knowledge of their target systems and are explanatory of the behaviors of the latter. A version of the shell-model of nuclear structure is analyzed and it is explained why such a model cannot be understood as being subsumed under the theory structure of Quantum Mechanics. Thus its representational capacity does (...) not stem from its close link to theory. It is shown that the shell model yields knowledge about the target and is explanatory of certain behaviors of nuclei. Aspects of the process by which the shell model acquires its representational capacity are analyzed. It is argued that these point to the conclusion that the representational status of the model is a function of its capacity to function as a source of knowledge and its capacity to postulate and explain underlying mechanisms that give rise to the observed behavior of its target. (shrink)

Usually within the context of computer simulations in quantum chemistry practices, there is a distinction between ab initio and semi-empirical methods. Related to this, a controversy within the scientific and philosophical communities came about regarding the superiority of the ab initio methods due to their theoretical rigor. In this article we re-evaluate the condition of the semi-empirical simulations in this area of research. We examine some of the aspects of this debate that have been considered in philosophy and provide additional (...) elements to the analysis. (shrink)

Two alternative accounts of quantum spontaneous symmetry breaking (SSB) are compared and one of them, the decompositional account in the algebraic approach, is argued to be superior for understanding quantum SSB. Two exactly solvable models are given as applications of our account -- the Weiss-Heisenberg model for ferromagnetism and the BCS model for superconductivity. Finally, the decompositional account is shown to be more conducive to the causal explanation of quantum SSB.

In this paper, a criticism of the traditional theories of approximation and idealization is given as a summary of previous works. After identifying the real purpose and measure of idealization in the practice of science, it is argued that the best way to characterize idealization is not to formulate a logical model – something analogous to Hempel's D-N model for explanation – but to study its different guises in the praxis of science. A case study of it is then made (...) in thermostatistical physics. After a brief sketch of the theories for phase transitions and critical phenomena, I examine the various idealizations that go into the making of models at three difference levels. The intended result is to induce a deeper appreciation of the complexity and fruitfulness of idealization in the praxis of model-building, not to give an abstract theory of it. (shrink)

This paper argues that historical research is an important tool for modeling problem-solving in scientific invention and discovery. Two important cases in the history of modern physics—the invention of the transistor by John Bardeen and Walter Brattain and the development of the theory of superconductivity by Bardeen, Leon Cooper, and J. Robert Schrieffer—reveal factors essential to include in such a model. The focus is on problem-solving practices: problem decomposition, analogy, bridging principles, team-work, empirical tinkering, and library research. A complete framework (...) must encompass the full range of factors, including contingent individual traits and environmental circumstances. (shrink)

In this paper, a modest version of the Semantic View is motivated as both tenable and potentially fruitful for philosophy of science. An analysis is proposed in which the Semantic View is characterized by three main claims. For each of these claims, a distinction is made between stronger and more modest interpretations. It is argued that the criticisms recently leveled against the Semantic View hold only under the stronger interpretations of these claims. However, if one only commits to the modest (...) interpretation for all the claims, then the view obtained, the Modest Semantic View, is tenable and fruitful for the philosophy of science. (shrink)

Quite rightly, philosophers of physics examine the theories of physics, theories like Quantum Mechanics, Quantum Field Theory, the Special and General Theories of Relativity, and Statistical Mechanics. Far fewer, however, examine how these theories are put to use; that is to say, little attention is paid to the practices of theoretical physicists. In the early 1950s David Bohm and David Pines published a sequence of four papers, collectively entitled, ‘A Collective Description of Electron Interaction.’ This essay uses that quartet as (...) a case study in theoretical practice. In Part One of the essay, each of the Bohm-Pines papers is summarized, and within each summary an overview is given, framing a more detailed account. In Part Two theoretical practice is broken into six elements: (a) the use of models, (b) the use of theory, (c) modes of description and narrative, (d) the use of approximations, (e) experiment and theory, (f) the varied steps employed in a deduction. The last element is the largest, drawing as it does from the earlier ones. Part Three enlarges on the concept of ‘theoretical practice,’ and briefly outlines the subsequent theoretical advances which rendered the practices of Bohm and Pines obsolete, if still respected. (shrink)

: Faraday is often described as an experimentalist, but his work is a dialectical interplay of concrete objects, visual images, abstract, theoretically-informed visual models and metaphysical precepts. From phenomena described in terms of patterns formed by lines of force he created a general explanation of space-filling systems of force which obey both empirical laws and principles of conservation and economy. I argue that Faraday's articulation of situated experience via visual models into a theory capable of verbal expression owed much to (...) his strategy of moving—via conjectural visual models—between the phenomenology of particulars (often displayed as patterns) and the general features of dynamical phenomena which he depicted as structures. (shrink)

Philosophy Compass, Volume 17, Issue 1, January 2022.

This paper contrasts and compares strategies of model-building in condensed matter physics and biology, with respect to their alleged unequal susceptibility to trade-offs between different theoretical desiderata. It challenges the view, often expressed in the philosophical literature on trade-offs in population biology, that the existence of systematic trade-offs is a feature that is specific to biological models, since unlike physics, biology studies evolved systems that exhibit considerable natural variability. By contrast, I argue that the development of ever more sophisticated experimental, (...) theoretical, and computational methods in physics is beginning to erode this contrast, since condensed matter physics is now in a position to measure, describe, model, and manipulate sample-specific features of individual systems – for example at the mesoscopic level – in a way that accounts for their contingency and heterogeneity. Model-building in certain areas of physics thus turns out to be more akin to modeling in biology than has been supposed and, indeed, has traditionally been the case. (shrink)

http://dx.doi.org/10.5007/1808-1711.2008v12n1p73 This paper aims at discussing from the point of view of a pragmatic stance the concept of model as an abstract replica. According to this view, scientific models are abstract structures different from set-theoretic models. The view of models argued for here stems from the conceptions of some important philosophers of science who elaborated on the notion of model, such as Suppe, Cartwright, Hempel, and Nagel. Differently from all those authors, however, the conception of model argued for here is (...) typically pragmatic, not semantic, i.e. it has not to do with the interpretation of scientific theories, but with the explanation and construction of given circumstances (both abstract and concrete), from the point of view of the theory. (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)

Today most philosophers of science believe that models play a central role in science and that one of the main functions of scientific models is to represent systems in the world. Despite much talk of models and representation, however, it is not yet clear what representation in this context amounts to nor what conditions a certain model needs to meet in order to be a representation of a certain system. In this thesis, I address these two questions. First, I will (...) distinguish three senses in which something, a vehicle, can be said to be a representation of something else, a target—which I will call respectively denotation, epistemic representation, and faithful epistemic representation—and I will argue that the last two senses are the most important in this context. I will then outline a general account of what makes a vehicle an epistemic representation of a certain target for a certain user—which, according to the account I defend, is the fact that a user adopts what I call an interpretation of the vehicle in terms of the target—and of what makes an epistemic representation of a certain target a faithful epistemic representation of it—which, according to the account I defend, is a specific sort of structural similarity between the vehicle and the target. (shrink)

"Partial realism" is a common position in the contemporary philosophy of science literature. It states that the "essential" elements of empirically successful scientific theories accurately represent corresponding features the world. This thesis makes several novel contributions related to this position. Firstly, it offers a new definition of the concept of “empirical success”, representing a principled merger between the use-novelty and unification accounts. Secondly, it provides a comparative critical analysis of various accounts of which elements are "essential" to the success of (...) a theory, including structural realism and the divide et impera strategy. A novel account of essentialness, entitled the “empirically successful sub-theory "account", is defended. Thirdly, it is argued that the realism/anti-realism debate should put to the side metaphysical questions and focus instead on partial realism's commitment to the continuity of science. Because this commitment lacks metaphysical implications, it is referred to as "deflationary realism". Anti-realists cannot reject deflationary realism as a matter of a priori principle; its overall viability can therefore only be assessed by a careful examination of the history of science. Finally, another consequence of partial realism, named "partial rationalism", is defended. Partial rationalism states that, in cases where several competing theories have been suggested, scientists are rational just in case they accept the essential elements of each of the scientific theories on offer. This novel position subverts the existing literature on scientific "revolutions", as it sometimes demands that scientists devise a synthesis between competing scientific theories, instead of "choosing" only one. The philosophical points defended in this thesis are illustrated and supported by case studies from the history of science, including Fresnel’s wave theory of light, the Copernican revolution, the "neo-Darwinian synthesis" in evolutionary biology, the "prion revolution" in molecular biology, the miasma theory of disease, and the chemical revolution. (shrink)

Scientific models need to be investigated if they are to provide valuable information about the systems they represent. Surprisingly, the epistemological question of what enables this investigation has hardly been investigated. Even authors who consider the inferential role of models as central, like Hughes or Bueno and Colyvan, content themselves with claiming that models contain mathematical resources that provide inferential power. We claim that these notions require further analysis and argue that mathematical formalisms contribute to this inferential role. We characterize (...) formalisms, illustrate how they extend our mathematical resources, and highlight how distinct formalisms offer various inferential affordances. (shrink)