The thesis is a philosophical analysis of the consumption based capital asset pricing model, investigating in particular its epistemological and methodological foundations. Financial markets are integral parts of advanced and developing economies. They matter because they channel unspent household income into banks’ savings accounts and assets such as bonds and stocks. Financial economists have traditionally taken interest in the pricing mechanism that underlies this capital allocation. The consumption based capital asset pricing model is a prominent effort to describe, explain and (...) predict such prices. It tells a story of investors’ trade-off between consumption now and later and which portfolio of assets to hold. The CCAPM based narrative intuitively makes sense, and the chosen methodology involving theoretical assumption, mathematical models and empirical tests follows the professions’ standards of good scientific practise. But does CCAPM’s research programme provide knowledge for use? My thesis seeks to answer this question in a novel way. Instead of embarking on yet another asset pricing research project, I let Philosophy of Science inform my analysis. Following a “primer” introducing essential CCAPM topics and notations, I discuss, in turn, its theoretical foundation, mathematical model, and empirical test results from a philosophy of science perspective. I find that a few fundamental principles and several auxiliary assumptions combine to develop a simplified, partial and idealized theory of investors, financial markets and assets. The model reflects and represents this theory but also makes narrow claims that are distances away from the real situations they target. Unsurprisingly, ideal model assertions fail standard statistical tests of significance. I conclude that mathematical deductive modelling rooted in orthodox, a priori based fundamental principles create ideal and fictional settings that limit their scope and portability. The development of even more granular models within this orthodox paradigm that searches for “event regularities” will not render the desired knowledge for use. The real situations are possibly too complex to be captured in simplified assumptions, ideal theories and mathematical structures. Novel methodological and ontological approaches to asset pricing are in demand. Hence, claims about tendencies in the real data might replace the current focus on point-forecasts. (shrink)

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

The paper addresses charges of risk and loss aversion as well as of irrationality directed against the precautionary principle (PP), by providing an epistemic analysis of its specific role in the safety law system. In particular, I contend that: 1) risk aversion is not a form of irrational or biased behaviour; 2) both risk and loss aversion regard the form of the utility function, whereas PP rather regards the information on which to base the decision; 3) thus PP has formally (...) nothing to do with risk or loss aversion but rather with risk awareness; 4) PP removes a fictional construct in the legal system, according to which any hazard should be ignored and denied until it is scientifically proven; 5) the quandary originates in the tension between current methods of evidence evaluation, and the logic underlying PP which demands for a probabilistic epistemology. (shrink)

In this article I give an overview of some recent work in philosophy of science dedicated to analysing the scientific process in terms of (conceptual) mathematical models of theories and the various semantic relations between such models, scientific theories, and aspects of reality. In current philosophy of science, the most interesting questions centre around the ways in which writers distinguish between theories and the mathematical structures that interpret them and in which they are true, i.e. between scientific theories as linguistic (...) systems and their non-linguistic models. In philosophy of science literature there are two main approaches to the structure of scientific theories, the statement or syntactic approach -- advocated by Carnap, Hempel and Nagel -- and the non- statement or semantic approach --advocated, among others, by Suppes, the structuralists, Beth, Van Fraassen, Giere, Wojcicki. In conclusion, I briefly review some of the usual realist inspired questions about the possibility and character of relations between scientific theories and reality as implied by the various approaches I discuss in the course of the article. The models of a scientific theory should indeed be adequate to the phenomena, but if the theory is 'adequate' to (true in) its conceptual (mathematical) models as well, we have a model-theoretic realism that addresses the possible meaning and reference of 'theoretical entities' without relapsing into the metaphysics typical of the usual scientific realist approaches. (shrink)

The concept of natural kind is center stage in the debates about scientific realism. Champions of scientific realism such as Richard Boyd hold that our most developed scientific theories allow us to “cut the world at its joints” (Boyd, 1981, 1984, 1991). In the long run we can disclose natural kinds as nature made them, though as science progresses improvements in theory allow us to revise the extension of natural kind terms.

This paper sets out to analyze how causation works by focusing on biology, as represented by epidemiology and by scientific information on how the body works (“physiology”). It starts by exploring the specificity of evolved physiological systems, in which evolutionary, developmental and proximal causes all fit together, and the concept of function is meaningful; in contrast, this structure does not apply in epidemiology (or outside biology). Using these two contrasting branches of biology, I examine the role both of mechanism and (...) of difference making in causation. I find that causation necessarily involves both mechanism and difference making, and that they play complementary roles. Both are seen as ontologically necessary, even if the evidence is not always available for both. Influential monist accounts that focus on one of these, at the expense of ignoring the other, are found to be inadequate on these and on other grounds. Recent attempts to combine them are reviewed, notably that of Russo and Williamson (Int Stud Philos Sci 21:157–170, 2007), and it is argued that their epistemic view requires there to be a source of the different types of evidence that a rational agent would consider, and that this source must be ontic. I then analyze how causal relationships work in evolved physiological systems and in those studied by epidemiology, with a particular focus on how mechanism interacts with input. Finally, I consider this concept of causation from the perspective of everyday language, and of its possible generalisability outside biology. (shrink)

This essay presents a model-theoretic account of dispositional properties, according to which dispositions are not ordinary properties of real entities; dispositions capture the behavior of abstract, idealized models. This account has several payoffs. First, it saves the simple conditional analysis of dispositions. Second, it preserves the general connection between dispositions and regularities, despite the fact that some dispositions are not grounded in actual regularities. Finally, it brings together the analysis and the explanation of dispositions under a unified framework.

According to certain kinds of semantic dispositionalism, what an agent means by her words is grounded by her dispositions to complete simple tasks. This sort of position is often thought to avoid the finitude problem raised by Kripke against simpler forms of dispositionalism. The traditional objection is that, since words possess indefinite (or infinite) extensions, and our dispositions to use words are only finite, those dispositions prove inadequate to serve as ground for what we mean by our words. I argue (...) that, even if such positions (emphasizing simple tasks) avoid the traditional form of Kripke's charge, they still succumb to special cases of the finitude problem. Furthermore, I show how such positions can be augmented so as to avoid even these special cases. Doing so requires qualifying the dispositions of interest as those possessed by the abstracted version of an actual agent (in contrast to, say, an idealized version of the agent). In addition to avoiding the finitude problem in its various forms, the position that results provides new materials for appreciating the role that abstracting models can play for a dispositionalist theory of meaning. (shrink)

The Scientific Revolution spawned not just one methodology, but two. We have emphasized Bacon's inductivism at the expense of Galileo's more abstract, sophisticated method of successive approximation, and so have failed to appreciate Galileo's contribution to the ceteris paribus problem in philosophy of science. My purpose here is to help redress this imbalance. I first briefly review the old unsolved problems, and then point out the Baconian basis of ceteris paribus, as this clause is conventionally understood, and its history from (...) Aristotle to twentieth century Positivism. Then I explore Galileo's method of dealing with unwanted impediments, and the more general problem of 'accidents.' I trace his methodology back to Archimedes and forward through the economic theories of Adam Smith (18th century), J. S. Mill (19th) and Milton Friedman (20th). Finally, I point out ways in which I think Galileo's scientific method sheds light on, and provides a partial solution to, the ceteris paribus problem. (shrink)

Developments in biomedical science continue to transform our understanding of concepts such as health and disease. The creation of this expertise has also had a substantive role in changing the veterinary approach to animal diseases. Traditionally, companion animal veterinarians modelled their practices on developments in the diagnosis and treatment of human patients. As science and technology have realigned the boundaries between normalcy, intra-species variation and pathology in particular domains of expertise such as orthopaedic surgery, these patterns of knowledge translation have (...) changed. Not so long ago, treatments for the rupture of the cruciate ligament in human and canine patients were based on pathoanatomical comparison and designed to reestablish the stability of the joint by the functional restoration of ligament anatomy. Recently, a radically different characterization of the canine injury—with a corresponding alternative intervention—has been proposed within the field of veterinary orthopaedics. It views the normal anatomy of the canine knee as being in some way inherently pathogenic and proposes the surgical creation of an idealized structure as a remedy to dysfunction and disease. The veterinary focus on an ideal of patient performance, rather than a specific pathology, is now influencing how orthopaedists choose to approach analogous human injuries. In this article, I chart the history of canine ‘cruciate disease’ therapies as a means to map some of the epistemic assumptions, interplays of idealized and analogical reasoning and patterns of knowledge translation central to the biomedicalization of the science and practice of orthopaedic surgery. (shrink)

I address a question in moral metaphysics: How are conflicts between moral obligations possible? I begin by explaining why we cannot give a satisfactory answer to this question simply by positing that such conflicts are conflicts between rules, principles, or reasons. I then develop and defend the “Dispositional Account,” which posits that conflicts between moral obligations are conflicts between the manifestations of obligating dispositions (obligating powers, capacities, etc.), just as conflicts between physical forces are conflicts between the manifestations of (certain) (...) causal dispositions (causal powers, capacities, etc.). This account combines the so-called “moral forces” interpretation of prima facie obligations with a dispositional moral metaphysic according to which the metaphysical grounds of moral obligations are not rules or laws, but rather real, irreducibly dispositional properties (or powers) of moral agents and patients. My principal aims are to offer a theoretically attractive and suitably metaphysical account of conflicts of obligation, and to show that the dispositional moral metaphysic that grounds the Dispositional Account can explain and accommodate plausible normative views that rule- and law-based alternatives cannot, as well as to answer objections that have been pressed against other accounts of moral conflict (especially Ross’s) that appeal to moral dispositions or forces. (shrink)

The paper is based on ranking theory, a theory of degrees of disbelief (and hence belief). On this basis, it explains enumerative induction, the confirmation of a law by its positive instances, which may indeed take various schemes. It gives a ranking theoretic explication of a possible law or a nomological hypothesis. It proves, then, that such schemes of enumerative induction uniquely correspond to mixtures of such nomological hypotheses. Thus, it shows that de Finetti's probabilistic representation theorems may be transformed (...) into an account of confirmation of possible laws and that enumerative induction is equivalent to such an account. The paper concludes with some remarks about the apriority of lawfulness or the uniformity of nature. (shrink)

Mechanisms have become much-discussed, yet there is still no consensus on how to characterise them. In this paper, we start with something everyone is agreed on – that mechanisms explain – and investigate what constraints this imposes on our metaphysics of mechanisms. We examine two widely shared premises about how to understand mechanistic explanation: (1) that mechanistic explanation offers a welcome alternative to traditional laws-based explanation and (2) that there are two senses of mechanistic explanation that we call ‘epistemic explanation’ (...) and ‘physical explanation’. We argue that mechanistic explanation requires that mechanisms are both real and local. We then go on to argue that real, local mechanisms require a broadly active metaphysics for mechanisms, such as a capacities metaphysics. (shrink)

Do component forces exist in conjoined circumstances? Cartwright (1980) says no; Creary (1981) says yes. I'm inclined towards Cartwright's side in this matter, but find several problems with her argumentation. My primary aim here is to present a better, distinctly causal, argument against component forces: very roughly, I argue that the joint posit of component and resultant forces in conjoined circumstances gives rise to a threat of causal overdetermination, avoidance of which best proceeds via eliminativism about component forces. A secondary (...) aim is to show that rejecting component forces does not require, pace Cartwright, rejecting certain attractive theses about what laws of nature express and the role such laws play in scientific explanations. (shrink)

Eric Alden Smith and Bruce Winterhalder, eds., Evolutionary Ecology and Human Behavior. Aldine de Gruyter, New York, 1992. Pp. xv, 470, tables, boxes, figures, bibliography, author index, subject index, $59.95 (cloth), $29.95 (paper).

Causal analysis in the social sciences takes advantage of a variety of methods and of a multi-fold source of information and evidence. This pluralistic methodology and source of information raises the question of whether we should accordingly have a pluralistic metaphysics and epistemology. This paper focuses on epistemology and argues that a pluralistic methodology and evidence don’t entail a pluralistic epistemology. It will be shown that causal models employ a single rationale of testing, based on the notion of variation. Further, (...) I shall argue that this monistic epistemology is also involved in alternative philosophical theories of causation. (shrink)

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

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)

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 "Bayesian Confirmation of Theories that Incorporate Idealizations", Michael Shaffer argues that, in order to show how idealized hypotheses can be confirmed, Bayesians must develop a coherent proposal for how to assign prior probabilities to counterfactual conditionals. This paper develops a Bayesian reply to Shaffer's challenge that avoids the issue of how to assign prior probabilities to counterfactuals by treating idealized hypotheses as abstract descriptions. The reply allows Bayesians to assign non-zero degrees of confirmation to idealized hypotheses and to capture (...) the intuition that less idealized hypotheses tend to be better confirmed than their more idealized counterparts. (shrink)

Much of the recent work on the epistemology of causation has centered on two assumptions, known as the Causal Markov Condition and the Causal Faithfulness Condition. Philosophical discussions of the latter condition have exhibited situations in which it is likely to fail. This paper studies the Causal Faithfulness Condition as a conjunction of weaker conditions. We show that some of the weaker conjuncts can be empirically tested, and hence do not have to be assumed a priori. Our results lead to (...) two methodologically significant observations: (1) some common types of counterexamples to the Faithfulness condition constitute objections only to the empirically testable part of the condition; and (2) some common defenses of the Faithfulness condition do not provide justification or evidence for the testable parts of the condition. It is thus worthwhile to study the possibility of reliable causal inference under weaker Faithfulness conditions. As it turns out, the modification needed to make standard procedures work under a weaker version of the Faithfulness condition also has the practical effect of making them more robust when the standard Faithfulness condition actually holds. This, we argue, is related to the possibility of controlling error probabilities with finite sample size (“uniform consistency”) in causal inference. (shrink)

Systems involving many interacting variables are at the heart of the natural and social sciences. Causal language is pervasive in the analysis of such systems, especially when insight into their behavior is translated into policy decisions. This is exemplified by economics, but to an increasing extent also by biology, due to the advent of sophisticated tools to identify the genetic basis of many diseases. It is argued here that a regularity notion of causality can only be meaningfully defined for systems (...) with linear interactions among their variables. For the vastly more important class of nonlinear systems, no such notion is likely to exist. This thesis is developed with examples of dynamical systems taken mostly from mathematical biology. It is discussed with particular reference to the problem of causal inference in complex genetic systems, systems for which often only statistical characterizations exist. (shrink)

It has been claimed that ceteris paribus laws, rather than strict laws are the proper aim of the special sciences. This is so because the causal regularities found in these domains are exception-ridden, being contingent on the presence of the appropriate conditions and the absence of interfering factors. I argue that the ceteris paribus strategy obscures rather than illuminates the important similarities and differences between representations of causal regularities in the exact and inexact sciences. In particular, a detailed account of (...) the types and degrees of contingency found in the domain of biology permits a more adequate understanding of the relations among the sciences. (shrink)

Much of the literature on "ceteris paribus" laws is based on a misguided egalitarianism about the sciences. For example, it is commonly held that the special sciences are riddled with ceteris paribus laws; from this many commentators conclude that if the special sciences are not to be accorded a second class status, it must be ceteris paribus all the way down to fundamental physics. We argue that the (purported) laws of fundamental physics are not hedged by ceteris paribus clauses and (...) provisos. Furthermore, we show that not only is there no persuasive analysis of the truth conditions for ceteris paribus laws, there is not even an acceptable account of how they are to be saved from triviality or how they are to be melded with standard scientific methodology. Our way out of this unsatisfactory situation to reject the widespread notion that the achievements and the scientific status of the special sciences must be understood in terms of ceteris paribus laws. (shrink)

Opponents of ceteris paribus laws are apt to complain that the laws are vague and untestable. Indeed, claims to this effect are made by Earman, Roberts and Smith in this volume. I argue that these kinds of claims rely on too narrow a view about what kinds of concepts we can and do regularly use in successful sciences and on too optimistic a view about the extent of application of even our most successful non-ceteris paribus laws. When it comes to (...) testing, we test ceteris paribus laws in exactly the same way that we test laws without the ceteris paribus antecedent. But at least when the ceteris paribus antecedent is there we have an explicit acknowledgment of important procedures we must take in the design of the experiments — i.e., procedures to control for “all interferences” even those we cannot identify under the concepts of any known theory. (shrink)

Normic Laws and the Significance of Nonmonotonic Reasoning for Philosophy of Science. Normic laws have the form ‘if A then normally B’. They have been discovered in the explanation debate, but were considered as empirically vacuous (§1). I argue that the prototypical (or ideal) normality of normic laws implies statistical normality (§2), whence normic laws have empirical content. In §3–4 I explain why reasoning from normic laws is nonmonotonic, and why the understanding of the individual case is so important here. (...) After sketching some foundations of nonmonotonic reasoning as developed by AI-researchers (§5), Iargue that normic laws are also the best way to understand ceteris paribus laws (§6). §7 deals with the difference between physical and non-physical disciplines and §9 with the difference between normicity and approximation. In §8 it is shown how nonmonotonic reasoning provides a new understanding of the protection of theories against falsification by auxiliary hypotheses. §10, finally, gives a system- and evolution-theoretical explanation of the deeper reason for the omnipresence of normic laws in practice and science, and forthe connection between ideal and statistical normality. (shrink)

Bayesian networks are computer programs which represent probabilitistic relationships graphically as directed acyclic graphs, and which can use those graphs to reason probabilistically , often at relatively low computational cost. Almost every expert system in the past tried to support probabilistic reasoning, but because of the computational difficulties they took approximating short-cuts, such as those afforded by MYCIN's certainty factors. That all changed with the publication of Judea Pearl's Probabilistic Reasoning in Intelligent Systems, in 1988, which synthesized a decade of (...) research making accurate graphical probabilistic reasoning computationally achievable.Bayesian network technology is now one of the fastest growing fields of research in artificial intelligence. That it has become a publication industry in its own right is shown by a search on Google scholar :This development, together with a parallel related growth in the use of causal discovery algorithms which automate the learning of Bayesian networks from sample data, has generated considerable interest, and controversy, within the philosophy-of-science community.Three central questions bringing together AI researchers and philosophers of science are: Are Bayesian networks Bayesian? What is the relation between probability and causality? Are the assumptions behind causal discovery of Bayesian networks realistic or fantastical?Jon Williamson, as a philosopher of science with a keen interest in the technology, asks and answers these questions in his new book. Although it is self-contained, his book is not very likely as an introduction to the technology , nor is it optimal even as an introduction to the philosophical problems in interpreting Bayesian networks . Rather Williamson's book is an attempt to move the debate forward by solving the central problems of the …. (shrink)

This paper argues against Papineau's claim that causal relations can be reduced to correlations and defends Cartwright's thesis that they can be nevertheless boot-strapped from them, given sufficiently rich causal background knowledge.

: The idea of an exact science unified and complete has been advocated throughout the history of thought, but the sciences continue to cover only small patches of the world we live in. We may dream that the exact sciences will some day cover everything. But I argue that the very ways we do our exact sciences when they are most successfully done seems likely to confine them within limited domains. I discuss three cases to illustrate: the use of broad-scale (...) non-experimental statistics for causal modelling across the social sciences, an economic model on skill-loss during unemployment, and the quantum theory of superconductivity. In all cases, where we can expect exact order depends on where we can fit our models. And by the nature of how models do-and should-get constructed in exact science, they fit readily onto only very special bits of the world around us. I also maintain that an ill-supported belief in the universality of our favourite exact science can lead us to adopt bad methodologies for carrying out the central aim of the sciences, namely to make the world the way it ought to be. (shrink)

A common view is that ceteris paribus clauses render lawlike statements vacuous, unless such clauses can be explicitly reformulated as antecedents of ?real? laws that face no counterinstances. But such reformulations are rare; and they are not, we argue, to be expected in general. So we defend an alternative sufficient condition for the non-vacuity of ceteris paribus laws: roughly, any counterinstance of the law must be independently explicable, in a sense we make explicit. Ceteris paribus laws will carry a plethora (...) of explanatory commitments; and claims that such commitments are satisfied will be as (dis) confirmable as other empirical claims. (shrink)

Two recent contributions have discussed, and disagreed, over whether so-called toy models that attempt to represent dispositions have the power to explain. In this paper, I argue that neither of these positions is completely correct. Toy models may accurately represent, satisfy the veridicality condition, yet fail to provide how-actually explanations. This is because some dispositions remain unmanifested. Instead, the models provide how-possibly explanations; they _possibly_ explain.

In the current article and contrary to a widespread assumption, I argue that Humeanism and ontological emergence can peacefully coexist. Such a coexistence can be established by reviving elements of John Stuart Mill’s philosophy of science, in which an idiosyncratic account of diachronic emergence is associated with extensions of the Humean mosaic and the correlative coming into being of new best system laws, which have the peculiarity of being temporally indexed. Incidentally, this reconciliation of Humeanism and emergence allows for conceiving (...) the autonomy of the special sciences in an interesting way, consistently with the reductionist ideal of a unified science. (shrink)

In The Concept of Mind, Gilbert Ryle argued that a more sophisticated understanding of the dispositional nature of ‘intelligent capacities’ could bolster philosophical resistance to the tempting view that the human mind is possessed of metaphysically ‘occult’ powers and properties. This temptation is powerful in the context of accounting for the special qualities of responsible agency. Incompatibilists indulge the temptation; compatibilists resist it, using a variety of strategies. One recent strategy, reminiscent of Ryle’s, is to exploit a more sophisticated understanding (...) of dispositional properties to account for these qualities. But ‘new dispositionalists’ run up against a ‘hard problem’ that threatens the approach. This paper argues that the threat may be averted by embracing a yet more radical ‘Rylean’ view of the distinctive dispositional nature of ‘intelligent capacities’. (shrink)

McCaffrey and Danks have posed the challenge of discovering causal relations in data drawn from a mixture of distributions as an impossibility result in functional magnetic resonance. We give an algorithm that addresses this problem for the distributions commonly assumed in fMRI studies and find that in testing, it can accurately separate data from mixed distributions. As with other obstacles to automated search, the problem of mixed distributions is not an impossible one, but rather a challenge. 1Introduction2Background3Addressing the Problem4Discussion.

Philosophy of medicine has traditionally examined two issues: the scientific ontology for medicine and the epistemic significance of the types of evidence used in medical research. In answering each question, philosophers have typically brought to bear tools from traditional analytic philosophy. In contrast, this volume explores medical knowledge from the perspective offered by social epistemology.While many of the same issues are addressed, the approach to these issues generates both fresh questions and new insights into old debates. In addition, the broader (...) purview offered by social epistemology opens up opportunities to address new topics such as the role of consensus conferences, epistemic injustice, the value of medical knowledge, continuing medical education, and industry funding. This article situates and summarizes the contributions to this special issue. (shrink)

In this short inquiry I would like to defend the statement that exact science deals with the explanation of models, but not with the understanding of nature. By the word ‘nature’ I mean nature as physis, not nature as natura naturata. The Estonian philosopher of science Rein Vihalemm has shown with his conception of phi-science that exact science is itself an idealized model or theoretical object derived from Galilean mathematical physics.

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models is that it is an unsettled question what the epistemic goal of toy modeling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this paper is to (...) precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and, then, argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. (shrink)

In The Explanatory Dispensability of Idealizations, Sam Baron suggests a possible strategy enabling the indispensability argument to break the symmetry between mathematical claims and idealization assumptions in scientific models. Baron’s distinction between mathematical and non-mathematical idealization, I claim, is in need of a more compelling criterion, because in scientific models idealization assumptions are expressed through mathematical claims. In this paper I argue that this mutual dependence of idealization and mathematics cannot be read in terms of symmetry and that Baron’s non-causal (...) notion of mathematical difference-making is not effective in justifying any symmetry-breaking between mathematics and idealization. The function of making a difference that Baron attributes to mathematics cannot be referred to physical facts, but to the features of quantities, such as step lengths or time intervals taken into account in the models. It appears, indeed, that it does not follow from Baron’s argument that idealizations do not help to carry the explanatory load at least for two reasons: mathematics is not independent of idealizations in modelling and idealizations help mathematics to carry the explanatory load of a model in different degrees. (shrink)

One way in which to address the intriguing relations between science and reality is to work via the models (mathematical structures) of formal scientific theories which are interpretations under which these theories turn out to be true. The so-called 'statement approach' to scientific theories -- characteristic for instance of Nagel, Carnap, and Hempel --depicts theories in terms of 'symbolic languages' and some set of 'correspondence rules' or 'definition principles'. The defenders of the oppositionist non-statement approach advocate an analysis where the (...) language in which the theory is formulated plays a much smaller role. They hold that foundational problems in the various sciences can in general be better addressed by focusing on the models these sciences employ than by reformulating the products of these sciences in some appropriate language. My model-theoretic realist account of science lies decidedly within the non-statement context, although I retain the notion of a theory as a deductively closed set of sentences (expressed in some appropriate language), in this paper I shall focus -- against the background of a model-theoretic account of science -- on the approach to the reality-science dichotomy offered by Nancy Cartwright and briefly comment on a few aspects of Roy Bhaskar's transcendental realism. I shall, in conclusion, show how a model-theoretic approach such as mine can combine the best of these two approaches. (shrink)