In recent years there have been an increasing number of contributions to economic methodology that develop or seek to reveal ontological positions. Despite this there is no agreement about either what ontology is or how it can contribute to economics. For some ontological theorising reveals the presuppositions of economists and its role is largely descriptive. Others see ontology as primarily engaged in setting out and defending a general account of some domain of reality and suggest that such a conception can (...) help us evaluate the appropriateness of the methods economists deploy. In this paper I clarify the scope and role of such theorising in economics by considering two projects with ontological orientations, namely critical realism in economics as developed by Tony Lawson and Nancy Cartwright’s work on the nature of economic theory. I argue that there are similarities between these two projects but also differences and show that these can be better understood once we recognise that each draws on a distinct conception of the legitimate scope of ontological theorising. I use Peirce’s writings on the nature of sustainable metaphysical analysis to clarify certain aspects of the approach to ontological theorising that Lawson favours. (shrink)

There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. In my view, continuing, widespread idealization (...) calls into question the idea that science aims for truth. I argue that understanding must replace truth as the ultimate epistemic aim of science. Additionally, science has a wide variety aims, epistemic and non-epistemic, and these aims motivate different kinds of scientific products. Finally, I show how these diverse aims---all rather distant from truth---result in the expanded influence of social values on science. (shrink)

Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory share the (...) fundamental assumption that it is possible to model cognition on the basis of formal, probabilistic principles. But why consider a QP approach? The answers are that (1) there are many well-established empirical findings (e.g., from the influential Tversky, Kahneman research tradition) that are hard to reconcile with CP principles; and (2) these same findings have natural and straightforward explanations with quantum principles. In QP theory, probabilistic assessment is often strongly context- and order-dependent, individual states can be superposition states (that are impossible to associate with specific values), and composite systems can be entangled (they cannot be decomposed into their subsystems). All these characteristics appear perplexing from a classical perspective. However, our thesis is that they provide a more accurate and powerful account of certain cognitive processes. We first introduce QP theory and illustrate its application with psychological examples. We then review empirical findings that motivate the use of quantum theory in cognitive theory, but also discuss ways in which QP and CP theories converge. Finally, we consider the implications of a QP theory approach to cognition for human rationality. (shrink)

An historically important conception of the unity of science is explanatory reductionism, according to which the unity of science is achieved by explaining all laws of science in terms of their connection to microphysical law. There is, however, a separate tradition that advocates the unity of science. According to that tradition, the unity of science consists of the coordination of diverse fields of science, none of which is taken to have privileged epistemic status. This alternate conception has roots in Otto (...) Neurath’s notion of unified science. In this paper, I develop a version of the coordination approach to unity that is inspired by Neurath’s views. The resulting conception of the unity of science achieves aims similar to those of explanatory reductionism, but does so in a radically different way. As a result, it is immune to the criticisms facing explanatory reductionism. This conception of unity is also importantly different from the view that science is disunified, and I conclude by demonstrating how it accords better with scientific practice than do conceptions of the disunity of science. (shrink)

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

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

Natural Categories and Human Kinds is a recent and timely contribution to current debate on natural kinds. Because of the growing sophistication of this debate, it is necessary to make careful distinctions in order to appreciate the originality of Khalidi’s position. Khalidi’s view on natural kinds is naturalistic: if we want to know what Nature’s joints really are, we should look at the actual carving job carried out by our best scientific practices. Like LaPorte, Khalidi is a fallibilist: our best (...) scientific theories may be revised or abandoned and so can our current classifications of natural kinds. Unlike LaPorte, however, Khalidi is an anti-essentialist: he argues against the idea that membership in a natural kind is a matter of possessing an essential set of necessary and sufficient properties. Like Dupré, Khalidi is a pluralist and anti-reductionist: he does not believe that there is only one true classification system and that there are natural kinds only at the so-called "fundamental level" of microphysics. Khalidi develops his pluralistic and anti-reductionistic position on the basis of a deep appreciation for the special sciences but, unlike Dupré, he thinks that only the scientific inquiry, which is driven by epistemic purposes, discover natural kinds and that, therefore, there are important differences between scientific and folk classifications. Khalidi’s conception of natural kinds has both an epistemic and a metaphysical component. (shrink)

My aim in this paper is to articulate an account of scientific modeling that reconciles pluralism about modeling with a modest form of scientific realism. The central claim of this approach is that the models of a given physical phenomenon can present different aspects of the phenomenon. This allows us, in certain special circumstances, to be confident that we are capturing genuine features of the world, even when our modeling occurs independently of a wholly theoretical motivation. This framework is illustrated (...) using a recent debate from meteorology. (shrink)

Mathematical idealizations are scientific representations that result from assumptions that are believed to be false, and where mathematics plays a crucial role. I propose a two stage account of how to rank mathematical idealizations that is largely inspired by the semantic view of scientific theories. The paper concludes by considering how this approach to idealization allows for a limited form of scientific realism. ‡I would like to thank Robert Batterman, Gabriele Contessa, Eric Hiddleston, Nicholaos Jones, and Susan Vineberg for helpful (...) discussions and encouragement. †To contact the author, please write to: Department of Philosophy, Beering Hall, Purdue University, 100 N. University Street, West Lafayette, IN 47907-2098; e-mail: [email protected]. (shrink)

Conflicting accounts of the role of mathematics in our physical theories can be traced to two principles. Mathematics appears to be both (1) theoretically indispensable, as we have no acceptable non-mathematical versions of our theories, and (2) metaphysically dispensable, as mathematical entities, if they existed, would lack a relevant causal role in the physical world. I offer a new account of a role for mathematics in the physical sciences that emphasizes the epistemic benefits of having mathematics around when we do (...) science. This account successfully reconciles theoretical indispensability and metaphysical dispensability and has important consequences for both advocates and critics of indispensability arguments for platonism about mathematics. (shrink)

I argue for the causal character of modeling in data-intensive science, contrary to widespread claims that big data is only concerned with the search for correlations. After discussing the concept of data-intensive science and introducing two examples as illustration, several algorithms are examined. It is shown how they are able to identify causal relevance on the basis of eliminative induction and a related difference-making account of causation. I then situate data-intensive modeling within a broader framework of an epistemology of scientific (...) knowledge. In particular, it is shown to lack a pronounced hierarchical, nested structure. The significance of the transition to such “horizontal” modeling is underlined by the concurrent emergence of novel inductive methodology in statistics such as non-parametric statistics. Data-intensive modeling is well equipped to deal with various aspects of causal complexity arising especially in the higher level and applied sciences. (shrink)

Making sense of modeling: beyond representation Content Type Journal Article Category Original paper in Philosophy of Science Pages 335-352 DOI 10.1007/s13194-011-0032-8 Authors Isabelle Peschard, Philosophy Department, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number 3.

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in contradiction. The second variety offers (...) a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations. (shrink)

This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent of (...) the notion of law, and can easily be adapted to account for such characteristics of mechanisms. The idea of tropes as mechanisms is worked out in some detail. According to the resulting picture, there is still an opportunity to link mechanisms and laws. But while the predominant law view conceives of mechanistic approaches as special kinds of law accounts, this study indicates that the converse may be true. Law accounts are special cases of mechanistic accounts, and they work only in those worlds where the mechanisms are of the right kind. (shrink)

Laws, Mind, and Free Will is a highly valuable book for anyone interested in philosophy of science, philosophy of mind, or in the problem of free will and moral responsibility. The book has three distinct but related parts. The first presents an anti-empiricist position on the laws of nature, according to which the point of the laws is not primarily to predict kinematic outcomes, but rather to characterize dynamics. One upshot of the account is that the laws have an attenuated (...) role in determining and prediction of actual motion, and this has an important consequence for the relevance of the laws to the prospects for libertarian free will. This consequence is developed in detail in the second part of the book. A further feature of the account is that proposed laws and the theories in which they are embedded are models in a sense that reflects our interests and involves idealization. In Horst’s view, this is true for theories and laws across the sciences—from physics to psychology. The l .. (shrink)

Most of the regularities that get represented as ‘laws’ in our sciences arise from, and are to be found regularly associated with, the successful operation of a nomological machine. Reference to the nomological machine must be included in the cp-clause of a cp-law if the entire cp-claim is to be true. We agree, for example, ‘ceteris paribus aspirins cure headaches’, but insist that they can only do so when swallowed by someone with the right physiological makeup and a headache. Besides (...) providing a necessary condition on the truth of the cp-law claim, recognising the nomological machine has great practical importance. Referring to the nomological machine makes explicit where the regularities are to be found, which is of central importance to the use of cp-laws for prediction and manipulation. Equally important, bringing the nomological machine to the fore brings into focus the make-up of the machine—its parts, their powers and their arrangements—and its context case-by-case. (shrink)

David Armstrong argues that necessitation relations among universals are the best explanation of some of our observations. If we consequently accept them into our ontologies, then we can justify induction, because these necessitation relations also have implications for the unobserved. By embracing Armstrongian universals, we can vindicate some of our strongest epistemological intuitions and answer the Problem of Induction. However, Armstrong’s reasoning has recently been challenged on a variety of grounds. Critics argue against both Armstrong’s usage of inference to the (...) best explanation and even whether, by Armstrong’s own standards, necessitation relations offer a potential explanation of this explanandum, let alone the best explanation. I defend Armstrong against these particular criticisms. Firstly, even though there are reasons to think that Armstrong’s justification fails as a self-contained defence of induction, it can usefully complement several other answers to Hume. Secondly, I argue that Armstrong’s reasoning is consistent with his own standards for explanation. (shrink)

Computer simulation has become important in ecological modeling, but there have been few assessments on how complex simulation models differ from more traditional analytic models. In Part I of this paper, I review the challenges faced in complex ecological modeling and how models have been used to gain theoretical purchase for understanding natural systems. I compare the use of traditional analytic simulation models and point how that the two methods require different kinds of practical engagement. I examine a case study (...) of three models from the insect resistance literature in transgenic crops to illustrate and explore differences in analytic and computer simulation models. I argue that analyzing simulation models has been often inappropriately managed with expectations derived from handling analytic models. In Part II, I look at simulation as a hermeneutic practice. I argue that simulation models are a practice or techné. I the explore five aspects of philosophical hermeneutics that may be useful in complex ecological simulation: (1) an openness to multiple perspectives allowing multiple levels of scientific pluralism, (2) the hermeneutic circle, a back and forth in active communication among both modelers and ecologists; (3) the recognition of human factors and the nature of human practices as such, including recognizing the role of judgments and choices in the modeling enterprise; (4) the importance of play in modeling; (5) the non-closed nature of hermeneutic engagement, continued dialogue, and recognizing the situatedness, incompleteness, and tentative nature of simulation models. (shrink)

Legal doctrine is a kind of legal research, occupying the central position in professional legal writing, e.g., handbooks, monographs, commentaries and legal textbooks etc. It consists of a description of the literal sense of legal statutes, precedents etc., intertwined with many moral and other substantive reasons. Legal doctrine has normative components, and produces coherence in the law in many aspects. It also produces some justice. However, legal doctrine has faced repeated criticism, not least from minimalist philosophers.The author proposes a “Copernican (...) revolution” as regards the relation of legal theory to philosophy. Instead of attempting to make legal theory follow one of the notoriously controversial moral theories, he tries to adjust philosophy to legal theory. In the search for philosophy adjusted to legal doctrine, he prefers cautious (weak) philosophical positions to courageous (strong) ones. He also assumes a society‐centered theory of normativity, a coherentist theory of legal knowledge and a coherentist theory of justice.However, a law theorist has no chance to elaborate such theories in detail. Hence, the author poses the following questions to philosophers: How can a law theorist assume society‐centered normativity without being forced to enter the controversies around collectivism? How can a law theorist assume the common core of morality for society without being forced to enter technical controversies in political philosophy? How can the law theorist base his thinking on the coherence theory of law without being forced to enter technical controversies around the concept of coherence? How can the law theorist avoid hopeless ontological controversies? (shrink)

In this article, I aim at showing how powers may ground different types of probability in the universe. In Section 1 I single out several dimensions along which the probability of something can be determined. Each of such dimensions can be further specified at the type-level or at the token-level. In Section 2 I introduce some metaphysical assumptions about powers. In Section 3 I show how powers can ground single-case probabilities and frequency-probabilities in a deterministic setting. Later on, in Section (...) 4, I move to a theoretical framework where the falsity of determinism is assumed. Within such a framework, I first argue that some probabilities are grounded on basic powers. Moreover, in Section 5, I introduce tendencies and suggest that they are endowed with specific degrees of activation that may change over time. Such degrees explain why tendencies are more likely to be activated than non-activated, or vice versa. In Section 6 I compare my account of tendencies with other accounts. Finally, in Section 7, I anticipate some general objections against my account – objections that it shares with propensity-accounts of probability – and against degrees of activation of tendencies. (shrink)

How does God govern the world? For many theists “laws of nature” play a vital role. But what are these laws, metaphysically speaking? I shall argue that laws of nature are not external to the objects they govern, but instead should be thought of as reducible to internal features of properties. Recent work in metaphysics and philosophy of science has revived a dispositionalist conception of nature, according to which nature is not passive, but active and dynamic. Disposition theorists see particulars (...) as being internally powerful rather than being governed by external laws of nature, making external laws in effect ontologically otiose. I will argue that theists should prefer a dispositionalist ontology, since it leads them toward the theory of concurrentism in divine conservation, rather than occasionalism, and revives the distinction between internal and external teleology. God on this view does not govern the world through external laws of nature, but rather through internal aspects of powerful properties. (shrink)

Elliott Sober and Ken Waters both raise interesting and difficult challenges for various aspects of the position I set out in Evolution and the Levels of the Selection. I am grateful to them for their penetrating criticisms of my work, and find myself in agreement with many of their points.

Theoretical biology and economics are remarkably similar in their reliance on mathematical models, which attempt to represent real world systems using many idealized assumptions. They are also similar in placing a great emphasis on derivational robustness of modeling results. Recently philosophers of biology and economics have argued that robustness analysis can be a method for confirmation of claims about causal mechanisms, despite the significant reliance of these models on patently false assumptions. We argue that the power of robustness analysis has (...) been greatly exaggerated. It is best regarded as a method of discovery rather than confirmation. (shrink)

The objective probability of every physical event is fixed by prior physical events and laws alone. (This thesis is sometimes expressed in terms of explanation: In tracing the causal history of any physical event, one need not advert to any non-physical events or laws. To the extent that there is any explanation available for a physical event, there is a complete explanation available couched entirely in physical vocabulary. We prefer the probability formulation, as it should be acceptable to any physicalist, (...) though some reject the explanation formulation.) (3) Causal Exclusion. (shrink)

Recent research suggests that language evolution is a process of cultural change, in which linguistic structures are shaped through repeated cycles of learning and use by domain-general mechanisms. This paper draws out the implications of this viewpoint for understanding the problem of language acquisition, which is cast in a new, and much more tractable, form. In essence, the child faces a problem of induction, where the objective is to coordinate with others (C-induction), rather than to model the structure of the (...) natural world (N-induction). We argue that, of the two, C-induction is dramatically easier. More broadly, we argue that understanding the acquisition of any cultural form, whether linguistic or otherwise, during development, requires considering the corresponding question of how that cultural form arose through processes of cultural evolution. This perspective helps resolve the “logical” problem of language acquisition and has far-reaching implications for evolutionary psychology. (shrink)

Theories of explanation seek to tell us what distinctively explanatory information is. The most ambitious ones, such as the DN-account, seek to tell us what an explanation is, tout court. Less ambitious ones, such as causal theories, restrict themselves to a particular domain of inquiry. The least ambitious theories constitute outright skepticism, holding that there is no reasonably unified phenomenon to give an account of. On these views, it is impossible to give any theories of explanation at all. I argue (...) that both the less ambitious and outright skeptical varieties are committed to a certain context-sensitivity of our explanatory discourse. And though this discourse is almost certainly context-sensitive in some respects, it does not exhibit the context-sensitivity less than fully ambitious theories are committed to. Therefore, all accounts that seek to restrict themselves in scope, including causal accounts of explanation, fail. (shrink)

Recent research shows that research programmes (quantitative, qualitative and mixed) in education are not displaced (as suggested by Kuhn) but rather lead to integration. The objective of this study is to present a rationale for mixed methods (integrative) research programs based on contemporary philosophy of science (Lakatos, Giere, Cartwright, Holton, Laudan). This historical reconstruction of episodes from physical science (spanning a period of almost 300 years, 17 th to 20 th century) does not agree with the positivist image of science. (...) Quantitative data (empirical evidence) by itself, does not facilitate progress (despite widespread belief to the contrary), neither in the physical sciences nor in the social sciences (education) A historical reconstruction shows that both Piaget and Pascual-Leone's research programs in cognitive psychology, follow the Galilean idealisation quite closely, similar to the research programs of Newton, Mendeleev, Einstein, Thomson, Rutherford, Millikan and Perl in the physical sciences. This relationship does not imply that researchers in education have to emulate research in the physical sciences. A major argument in favor of mixed methods (integrative) research programs is that it provides a rationale for hypotheses, theories, guiding assumptions and presuppositions to compete and provide alternatives. Similar to the physical sciences, this proliferation of hypotheses leads to controversies and rivalries, and thus facilitates the decision making process of the scientific community. It is concluded that mixed methods research programs (not paradigms) in education can facilitate the construction of robust strategies, provided we let the problem situation (as studied by practicing researchers) decide the methodology. (shrink)

Drawing on ‘interpretational’ accounts of scientific representation, I argue that the use of so-called ‘toy models’ provides no particular philosophical puzzle. More specifically; I argue that once one gives up the idea that models are accurate representations of their targets only if they are appropriately similar, then simple and highly idealized models can be accurate in the same way that more complex models can be. Their differences turn on trading precision for generality, but, if they are appropriately interpreted, toy models (...) should nevertheless be considered accurate representations. A corollary of my discussion is a novel way of thinking about idealization more generally: idealized models may distort features of their targets, but they needn’t misrepresent them. (shrink)

How does mathematics apply to something non-mathematical? We distinguish between a general application problem and a special application problem. A critical examination of the answer that structural mapping accounts offer to the former problem leads us to identify a lacuna in these accounts: they have to presuppose that target systems are structured and yet leave this presupposition unexplained. We propose to fill this gap with an account that attributes structures to targets through structure generating descriptions. These descriptions are physical descriptions (...) and so there is no such thing as a solely mathematical account of a target system. (shrink)

The most serious candidates for common causes that fail to screen off and thus violate the causal Markov condition refer to quantum phenomena. In her seminal debate with Hausman and Woodward, Cartwright early on focussed on unfortunate non-quantum examples. Especially, Hausman and Woodward’s redescriptions of quantum cases saving the CMC remain unchallenged. This paper takes up this lose end of the discussion and aims to resolve the debate in favour of Cartwright’s position. It systematically considers redescriptions of ICC structures, including (...) those by Hausman and Woodward, and explains why these are inappropriate, when quantum mechanics is true. It first shows that all cases of purported quantum ICCs are cases of entanglement and then, using the tools of causal modelling, it provides an analysis of the quantum mechanical formalism for the case that the collapse of entangled systems is best described as a causal model with an ICC. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

This essay examines the relation between causation and causal explanation. It distinguishes two prominent roles that causes play within the sciences. On the one hand, causes may work as metaphysical posits. From this standpoint, mainstream in contemporary philosophy, causation provides the ‘raw material’ for explanation. On the other hand, causes may be conceived as explanatory postulates, theoretical hypotheses lacking any substantial ontological commitment. This unduly neglected distinction provides the conceptual resources to revisit longstanding philosophical issues, such as overdetermination and causal (...) pluralism. It also inspires a provocative reframing of Russell’s famous, if notoriously elusive, remarks on the nature of causation. (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.

Entity realism is the view that ‘a good many theoretical entities do really exist’. The main novelty of entity realism was that it provided an account of scientific realism that did not have to endorse realism about theories—the general proposal was that entity realism is noncommittal about whether we should be realist about scientific theories. I argue that the only way entity realists can resist the pull of straight scientific realism about theories is by endorsing a recent new player in (...) the scientific realism debate: singularist semirealism. (shrink)

Reichenbach’s ‘principle of the common cause’ is a foundational assumption of some important recent contributions to quantitative social science methodology but no similar principle appears in econometrics. Angrist et al. has argued that the principle is necessary for instrumental variables methods in econometrics, and Angrist Krueger builds a framework using it that he proposes as a means of resolving an important methodological dispute among econometricians. Through analysis of instrumental variables methods and the issue of multicollinearity, we aim to show that (...) the relationship of the principle to econometric methods is more nuanced than implied by previous work but nevertheless may make a valuable contribution to the coherence and validity of existing methods. (shrink)

This is an attempt to take a look at chemistry from the point of view of practical realism. Besides its social–historical and normative aspects, the latter involves a direct reference to experimental research. According to Edward Caldin chemistry depends on our being able to isolate pure substances with reproducible properties. Thus, the very basis of chemistry is practical. Even the laws of chemistry are not stable but are subject to correction. At the same time, these statements do not necessarily make (...) Edward Caldin a predecessor of practical realism. The latter has other predecessors, like Rom Harré’s policy realism or Sami Pihlström’s pragmatic realism. Chemistry is an experimental science. The experiment is a purposeful and critically theory-guided constructive, manipulative, material interference with nature according to Rein Vihalemm, the founder of practical realism. Chemistry is physics-like science but just partly so. This is an important point in the context of the current paper. (shrink)

In spite of the ‘experimental turn’ now fashionable in the philosophy of science, the question of the structure and identity criteria of scientific theories continues to be a central issue for the philosophical analysis of empirical science. We need a precise metatheory of empirical theories to deal with this issue. Metatheoretical structuralism appears to offer the most adequate approach in this sense so far. First, some basic intuitions about what empirical theories are, and how they are structured, are laid out. (...) Then, the main notions used by metatheoretical structuralism to analyze theories are explained, and they are illustrated by applying them to an example of a simple physical theory. Finally, it is argued that the picture of the structure and identity of empirical theories coming out of structuralistic analysis adequately corresponds to the basic intuitions stated at the beginning. (shrink)

In this paper, I propose that the debate in epistemology concerning the nature and value of understanding can shed light on the role of scientific idealizations in producing scientific understanding. In philosophy of science, the received view seems to be that understanding is a species of knowledge. On this view, understanding is factive just as knowledge is, i.e., if S knows that p, then p is true. Epistemologists, however, distinguish between different kinds of understanding. Among epistemologists, there are those who (...) think that a certain kind of understanding—objectual understanding—is not factive, and those who think that objectual understanding is quasi-factive. Those who think that understanding is not factive argue that scientific idealizations constitute cognitive success, which we then consider as instances of understanding, and yet they are not true. This paper is an attempt to draw lessons from this debate as they pertain to the role of idealizations in producing scientific understanding. I argue that scientific understanding is quasi-factive. (shrink)

In his 1987 paper “Truth or Consequences,” Dan Brock describes a deep conflict between the goals and virtues of philosophical scholarship and public policymaking: whereas the former is concerned with the search for truth, the latter must primarily be concerned with promoting good consequences. When philosophers are engaged in policymaking, he argues, they must shift their primary goal from truth to consequences—but this has both moral and methodological costs. Brock’s argument exemplifies a pessimistic, but not uncommon, view of the possible (...) shape and nature of applied philosophy. The present paper paints a richer and more optimistic picture. It argues that the difference between theoretical philosophy and applied philosophy is not best understood as a choice between truth and consequences. On the contrary, applied philosophers engage in forms of truth‐seeking that are properly concerned with consequences—including the consequences of philosophical practice itself. (shrink)

Philosophical accounts of emergence have been explicated in terms of logical relationships between statements (derivation) or static properties (function and realization). Jaegwon Kim is a modern proponent. A property is emergent if it is not explainable by (or reducible to) the properties of lower level components. This approach, I will argue, is unable to make sense of the kinds of emergence that are widespread in scientific explanations of complex systems. The standard philosophical notion of emergence posits the wrong dichotomies, confuses (...) compositional physicalism with explanatory physicalism, and is unable to represent the type of dynamic processes (self-organizing feedback) that both generate emergent properties and express downward causation. (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)

It has long been held that the structure of a protein is determined solely by the interactions of the atoms in the sequence of amino acids of which it is composed, and thus the stable, biologically functional conformation should be predictable by ab initio or de novo methods. However, except for small proteins, ab initio predictions have not been successful. We explain why this is the case and argue that the relationship among the different methods, models, and representations of protein (...) structure is one of integrative pluralism. Our defence appeals to specific features of the complexity of the functional protein structure and to the partial character of representation in general. We present examples of integrative strategies in protein science. 1. Introduction2. Partiality of Representation3. Protein Functional Complexity4. Modelling Protein Structure4.1 Integrating ab initio and experimental models4.2 Integrating multiple experimental models5. Conclusion. (shrink)

The recent proliferation of types and accounts of experimentation in sustainability science still lacks philosophical reflection. The present paper introduces this burgeoning topic to the philosophy of science by identifying key notions and dynamics in sustainability experimentation, by discussing taxonomies of sustainability experimentation and by focusing on barriers to the transfer of evidence. It integrates three topics: the philosophy of experimentation; the sustainability science literature on experimentation; and discussions on values in science coming from the general philosophy of science, the (...) social sciences, and sustainability science. The aim is to improve understanding of how sustainability experimentation has evolved, from a broader picture of the history and philosophy of science, with a specific focus on understanding evidence production and how evidence traveling in and from sustainability experiments can be improved, particularly in the context of complex and pervasive normative commitments of the research. By engaging in these topics, this research is one of the first philosophical accounts of sustainability experimentation, contributing both to the knowledge on specific philosophies of science and to the further development of an evidence-based sustainability science through a better understanding of the barriers to more relevant and usable knowledge. (shrink)

Science and technology (S&T) policy studies has explored the relationship between the structure of scientific research and the attainment of desired outcomes. Due to the difficulty of measuring them directly, S&T policy scholars have traditionally equated “outcomes” with several proxies for evaluation, including economic impact, and academic output such as papers published and citations received. More recently, scholars have evaluated science policies through the lens of Public Value Mapping, which assesses scientific programs against societal values. Missing from these approaches is (...) an examination of the social activities within the scientific enterprise that affect research outputs and outcomes. We contend that activities that significantly affect research trajectories take place at the levels of individual researchers and their communities, and that S&T policy scholars must take heed of this activity in their work in order to better inform policy. Based on primary research of two scientific communities—ecologists and sustainability scientists—we demonstrate that research agendas are actively shaped by parochial epistemic and normative concerns of the scientists and their disciplines. S&T policy scholarship that explores how scientists balance these concerns, alongside more formal science policies and incentive structures, will enhance understanding of why certain science policies fail or succeed and how to more effectively link science to beneficial social outcomes. (shrink)

Efforts to formalize qualitative accounts of inference to the best explanation (IBE) confront two obstacles: the imprecise nature of such accounts and the unusual logical properties that explanations exhibit, such as contradiction-intolerance and irreflexivity. This paper aims to surmount these challenges by utilising a new, more precise theory that treats explanations as expressions that codify defeasible inferences. To formalise this account, we provide a sequent calculus in which IBE serves as an elimination rule for a connective that exhibits many of (...) the properties associated with the behaviour of the English expression ‘That... best explains why ... ’. We first construct a calculus that encodes these properties at the level of the turnstile, i.e. as a metalinguistic expression for classes of defeasible consequence relations. We then show how this calculus can be conservatively extended over a language that contains a best-explains-why operator. (shrink)

There are two distinct interpretations of the role that Feynman diagrams play in physics: (i) they are calculational devices, a type of notation designed to keep track of complicated mathematical expressions; and (ii) they are representational devices, a type of picture. I argue that Feynman diagrams not only have a calculational function but also represent: they are in some sense pictures. I defend my view through addressing two objections and in so doing I offer an account of representation that explains (...) why Feynman diagrams represent. The account that I advocate is a version of that defended by Kendall Walton, which provides us with a basic characterization of the way that representations in general work and is particularly useful for understanding distinctively pictorial representations - in Walton's terms, depictions. The question of the epistemic function of Feynman diagrams as pictorial representations is left for another time. (shrink)

Meynell’s contention is that feminists should attend to pictures in science as distinctive bearers of epistemic content that cannot be reduced to propositions. Remarks on the practice and function of medical illustration—specifically, images Nancy Tuana used in her discussion of the construction of ignorance of women’s sexual function (2004)—show pictures to be complex and powerful epistemic devices. Their affinity with perennial feminist concerns, the relation between epistemic subject and object, and the nature of social knowledge, are of particular interest.

[full article, abstract in English; only abstract in Lithuanian] In Normativity of Scientific Laws explicit and implicit normativities were discerned and it was shown, following Joseph Rouse, that scientific laws implicitly harbour what Alchourrón and Bulygin imply to be the core of normativity. Here I develop this claim by discerning six aspects of implicit normativity in scientific laws: general and special conceptual normativity, concerning analytical thinking and special scientific terminologies; theoretical and material epistemic normativity, concerning mathematical and experimental accountability of (...) the world; narrow and broad practical normativity, concerning technologies in both narrower and broader senses. (shrink)