In this paper, I outline a heuristic for thinking about the relation between explanation and understanding that can be used to capture various levels of “intimacy”, between them. I argue that the level of complexity in the structure of explanation is inversely proportional to the level of intimacy between explanation and understanding, i.e. the more complexity the less intimacy. I further argue that the level of complexity in the structure of explanation also affects the explanatory depth in a similar way (...) to intimacy between explanation and understanding, i.e. the less complexity the greater explanatory depth and vice versa. (shrink)

Explanation is asymmetric: if A explains B, then B does not explain A. Tradition- ally, the asymmetry of explanation was thought to favor causal accounts of explanation over their rivals, such as those that take explanations to be inferences. In this paper, we develop a new inferential approach to explanation that outperforms causal approaches in accounting for the asymmetry of explanation.

__In this paper I investigate unification as a virtue of explanation. I the first part of the paper I give a brief exposition of the unification account of Schurz and Lambert and Schurz. I illustrate the advantages of this account in comparison to the older unification accounts of Friedman and Kitcher. In the second part I discuss several comments and objections to the Schurz-Lambert account that were raised by Weber and van Dyck, Gijsberg and de Regt. In the third and (...) final part, I argue that explanation should be understood as a prototype concept which contains nomic expectability, causality and unification as prototypical virtues of explanations, although none of these virtues provides a sufficient and necessary "defining condition" of explanation. (shrink)

Philosophers of science have by and large neglected technology. In this book, I have tried to do something about this lacuna by analyzing a few aspects of technical artifacts from a philosophical angle. The project was part of the research program "The Dual Nature of Technical Artifacts" based at Delft University of Technology in the Netherlands. Technical artifacts are both plain physical objects and objects that have been purposefully made for a purpose; which is to say they have a physical (...) structure and a technical function. As a result, they belong equally in a purely physical conceptualisation of the world "in which human intentions and goals seem to have no place" and in an intentional conceptualisation, which is used to describe and understand people and their mental lives. My main goal was to find out how these two philosophically very different aspects of artifacts are related to one another. To achieve this goal, I looked at two contexts in which these aspects are regularly brought together in a systematic fashion. First, the context of design; design can be characterized as a transition from a desired function or goal to a physical structure. In particular, I have studied and analyzed the role of functional decomposition in design processes. The second context is the explanation of how artifacts are able to fulfill their technical function in virtue of their specific physical structure. The result of this part of the project is a general account of such explanations. (shrink)

This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation model and the (...) results of the simulation. I also argue that our epistemic gain goes beyond the unificationist account, encompassing a practical dimension as well. (shrink)

According to Michael Friedman’s theory of explanation, a law X explains laws Y1, Y2, …, Yn precisely when X unifies the Y’s, where unification is understood in terms of reducing the number of independently acceptable laws. Philip Kitcher criticized Friedman’s theory but did not analyze the concept of independent acceptability. Here we show that Kitcher’s objection can be met by modifying an element in Friedman’s account. In addition, we argue that there are serious objections to the use that Friedman makes (...) of the concept of independent acceptability. (shrink)

In their attempt to defend philosophy from accusations of uselessness made by prominent scientists, such as Stephen Hawking, some philosophers respond with the charge of ‘scientism.’ This charge makes endorsing a scientistic stance, a mistake by definition. For this reason, it begs the question against these critics of philosophy, or anyone who is inclined to endorse a scientistic stance, and turns the scientism debate into a verbal dispute. In this paper, I propose a different definition of scientism, and thus a (...) new way of looking at the scientism debate. Those philosophers who seek to defend philosophy against accusations of uselessness would do philosophy a much better service, I submit, if they were to engage with the definition of scientism put forth in this paper, rather than simply make it analytic that scientism is a mistake. (shrink)

The paper provides a systematic overview of recent debates in epistemology and philosophy of science on the nature of understanding. We explain why philosophers have turned their attention to understanding and discuss conditions for “explanatory” understanding of why something is the case and for “objectual” understanding of a whole subject matter. The most debated conditions for these types of understanding roughly resemble the three traditional conditions for knowledge: truth, justification and belief. We discuss prominent views about how to construe these (...) conditions for understanding, whether understanding indeed requires conditions of all three types and whether additional conditions are needed. (shrink)

The articulation of an overarching account of scientific explanation has long been a central preoccupation for the philosophers of science. Although a while ago the literature was dominated by two approaches—a causal account and a unificationist account—today the consensus seems to be that the causal account has won. In this paper, I challenge this consensus and attempt to revive unificationism. More specifically, I aim to accomplish three goals. First, I add new criticisms to the standard anti-unificationist arguments, in order to (...) motivate the need for a revision of the doctrine. Second, and most importantly, I sketch such a revised version. Then I argue that, contrary to widespread belief, the causal account and this revised unificationist account of explanation are compatible. Moreover, I also maintain that the unificationist account has priority, since a most satisfactory theory of explanation can be obtained by incorporating the causal account, as a sub-component of the unificationist account. The driving force behind this reevaluation of the received view in the philosophy of explanation is a reconsideration of the role of scientific understanding. (shrink)

Achieving understanding of nature is one of the aims of science. In this paper we offer an analysis of the nature of scientific understanding that accords with actual scientific practice and accommodates the historical diversity of conceptions of understanding. Its core idea is a general criterion for the intelligibility of scientific theories that is essentially contextual: which theories conform to this criterion depends on contextual factors, and can change in the course of time. Our analysis provides a general account of (...) how understanding is provided by scientific explanations of diverse types. In this way, it reconciles conflicting views of explanatory understanding, such as the causal-mechanical and the unificationist conceptions. (shrink)

What is scientific progress? On Alexander Bird’s epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird’s epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode than at the (...) beginning. This account is shown to be superior to the epistemic account by examining cases in which knowledge and understanding come apart. In these cases, it is argued that scientific progress matches increases in scientific understanding rather than accumulations of knowledge. In addition, considerations having to do with minimalist idealizations, pragmatic virtues, and epistemic value all favor this understanding-based account over its epistemic counterpart. (shrink)

Coherence is a measure of how much our beliefs hang together. Understanding is achieved when we see that something is not just a brute, isolated fact. This suggests that it might be possible to use the extant probabilistic measures of coherence to formulate a measure of understanding. We attempt to do so, but it turns out that a coherence theory runs into trouble with the asymmetry of understanding. We identify four difficulties and show how they have been solved by a (...) unification approach to explanation. We also identify four advantages of the coherence approach, and assess the possibilities of reconciling the strengths of the two approaches.La coherencia es una medida sobre cuanta interdependencia hay entre nuestras creencias. La comprension se obtiene cuando vemos que algo no es un hecho bruto, aislado. Esto sugiere la posibilidad de usar las medidas probabilisticas de coherencia al uso para elaborar una medida de la comprension. Explorare esta posibilidad, a pesar de que una teoria de la coherencia tropieza con problemas aqui dado el caracter asimetrico de la comprension. Identifico cuatro dificultades al respecto y muestro como han sido resueltas mediante un enfoque de la explicacion basado en la nocion de unificacion. Tambien identifico cuatro ventajas en la aproximacion desde la coherencia y examino que perspectivas hay de reconciliar los puntos fuertes de ambos planteamientos. (shrink)

It is often claimed—especially by scientific realists—that science provides understanding of the world only if its theories are (at least approximately) true descriptions of reality, in its observable as well as unobservable aspects. This paper critically examines this ‘realist thesis’ concerning understanding. A crucial problem for the realist thesis is that (as study of the history and practice of science reveals) understanding is frequently obtained via theories and models that appear to be highly unrealistic or even completely fictional. So we (...) face the dilemma of either giving up the realist thesis that understanding requires truth, or allowing for the possibility that in many if not all practical cases we do not have scientific understanding. I will argue that the first horn is preferable: the link between understanding and truth can be severed. This becomes a live option if we abandon the traditional view that scientific understanding is a special type of knowledge. While this view implies that understanding must be factive, I avoid this implication by identifying understanding with a skill rather than with knowledge. I will develop the idea that understanding phenomena consists in the ability to use a theory to generate predictions of the target system’s behavior. This implies that the crucial condition for understanding is not truth but intelligibility of the theory, where intelligibility is defined as the value that scientists attribute to the theoretical virtues that facilitate the construction of models of the phenomena. I will show, first, that my account accords with the way practicing scientists conceive of understanding, and second, that it allows for the use of idealized or fictional models and theories in achieving understanding. (shrink)

This paper utilizes a logical correspondence theorem (which has been proved elsewhere) for the justification of weak conceptions of scientific realism and convergence to truth which do not presuppose Putnam's no-miracles-argument (NMA). After presenting arguments against the reliability of the unrestricted NMA in Sect. 1, the correspondence theorem is explained in Sect. 2. In Sect. 3, historical illustrations of the correspondence theorem are given, and its ontological consequences are worked out. Based on the transitivity of the concept of correspondence, a (...) correspondence-based notion of convergence to truth is developed in Sect. 4. In the final Sect. 5 it is argued that the correspondence theorem together with the assumption of ' minimal realism' yields a justification of a weak version of scientific realism, which is then compared to metaphysical realism and to instrumentalism. (shrink)

Peter Lipton has argued that understanding can exist in the absence of explanation. We argue that this does not denigrate explanation's importance to understanding. Specifically, we show that all of Lipton's examples are consistent with the idea that explanation is the ideal of understanding, i.e. other modes of understanding ought to be assessed by how well they replicate the understanding provided by a good and correct explanation. We defend this idea by showing that for all of Lipton's examples of non-explanatory (...) understanding of why p , there exists a correct and reasonably good explanation that would provide greater understanding of p. (shrink)

Recently, several authors have argued that scientific understanding should be a new topic of philosophical research. In this article, I argue that the three most developed accounts of understanding--Grimm's, de Regt's, and de Regt and Dieks's--can be replaced by earlier accounts of scientific explanation without loss. Indeed, in some cases, such replacements have clear benefits.

Scientific understanding, this paper argues, can be analyzed entirely in terms of a mental act of “grasping” and a notion of explanation. To understand why a phenomenon occurs is to grasp a correct explanation of the phenomenon. To understand a scientific theory is to be able to construct, or at least to grasp, a range of potential explanations in which that theory accounts for other phenomena. There is no route to scientific understanding, then, that does not go by way of (...) scientific explanation. (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)

This paper describes the development of theories of scientific explanation since Hempel's earliest models in the 1940ies. It focuses on deductive and probabilistic whyexplanations and their main problems: lawlikeness, explanation-prediction asymmetries, causality, deductive and probabilistic relevance, maximal specifity and homogenity, the height of the probability value. For all of these topic the paper explains the most important approaches as well as their criticism, including the author's own accounts. Three main theses of this paper are: (1) Both deductive and probabilistic explanations (...) are important in science, not reducible to each other. (2) One must distinguish between (cause giving) explanations and (reason giving) justifications and predictions. (3) The adequacy of deductive as well as probabilistic explanations is relative to a pragmatically given background knowledge-which does not exclude, however, the possibility of purely semantic models. (shrink)

This article describes abductions as special patterns of inference to the best explanation whose structure determines a particularly promising abductive conjecture and thus serves as an abductive search strategy. A classification of different patterns of abduction is provided which intends to be as complete as possible. An important distinction is that between selective abductions, which choose an optimal candidate from given multitude of possible explanations, and creative abductions, which introduce new theoretical models or concepts. While selective abduction has dominated the (...) literature, creative abductions are rarely discussed, although they are essential in science. The article introduces several kinds of creative abductions, such as theoretical model abduction, common cause abduction and statistical factor analysis, and illustrates them by various real case examples. It is suggested to demarcate scientifically fruitful abductions from purely speculative abductions by the criterion of causal unification. (shrink)

Knowledge of many facts does not amount to understanding unless one also has a sense of how the facts fit together. This aspect of coherence among scientific observations and theories is usually overlooked in summaries of scientific method, since the emphasis is on justification and verification rather than on understanding. I argue that the inter-theoretic coherence, as the hallmark of understanding, is an essential and informative component of any accurate description of science.

In this paper, I argue that unification is neither necessary nor sufficient for explanation. Focusing on the versions of the unificationist theory of explanation of Kitcher and of Schurz and Lambert, I establish three theses. First, Kitcher’s criterion of unification is vitiated by the fact that it entails that every proposition can be explained by itself, a flaw that it is unable to overcome. Second, because neither Kitcher’s theory nor that of Schurz and Lambert can solve the problems of asymmetry (...) and accidental generalizations, it follows that unification is not sufficient to ground explanation. Third, some good explanations are disunifying, which entails that unification is not necessary for explanation either. (shrink)

It is widely acknowledged in the literature in social epistemology that knowledge has a social dimension: we are epistemically dependent upon one another for most of what we know. Our knowledge can be, and very often is, grounded on the epistemic achievement of somebody else. But what about epistemic aims other than knowledge? What about understanding? Prominent authors argue that understanding is not social in the same way in which knowledge is. Others can put us in the position to understand, (...) but when we understand something, this accomplishment is to be credited mainly if not entirely to us, as it is due to the successful exercise of our own cognitive abilities. In this paper, I show that the social dimension of understanding closely resembles the social dimension of knowledge. I distinguish between three different ways in which a subject can depend upon another subject for (either the acquisition or the possession of) a certain epistemic good. I then argue that all these kinds of epistemic dependence apply to knowledge and understanding alike. If I am right, understanding is not (always) an achievement to be (mainly) credited to the single epistemic agent who understands. (shrink)

In making sense of the world, we typically cooperate, join forces, and draw on one another’s competence and expertise. A group or community in which there is a well-functioning division of cognitive-epistemic labor can achieve levels of understanding that a single agent who relies exclusively on her own capacities would probably never achieve. However, is understanding also collective? I.e., is understanding something that can be possessed by a group or community rather than by individuals? In this paper, I develop an (...) account of understanding phenomena according to which understanding a phenomenon requires reasonably endorsing an adequate and intelligible epistemic mediator that accounts for this phenomenon. I then show that understanding, conceived along these lines, can be attributed to collective entities. An important result of my arguments will be that a collective entity’s understanding cannot (always) be reduced to the sum of the understandings of the individuals belonging to it. This is because a collective entity can sometimes be rightfully claimed to understand a phenomenon while none of its individual members understands it. (shrink)

Wir Menschen streben danach, die Wirklichkeit zu verstehen. Eine Welt, die wir gut verstehen, ist eine, die wir "im Griff" haben, mit der wir gut umgehen können. Aber was heißt es genau, ein Phänomen der Wirklichkeit zu verstehen? Wie sieht unser Weltbild aus, wenn wir ein Phänomen verstanden haben? Welche Bedingungen müssen erfüllt sein, damit Verstehen gelingt? Die Kernthese des Buches ist, dass wir Phänomene der Wirklichkeit durch noetische Integration verstehen. Wir verstehen Phänomene, indem wir den entsprechenden Informationseinheiten eine sinnvolle (...) und angemessene Position in unserem Weltbild zuschreiben und insofern unser Weltbild in gewissem Maße der Wirklichkeit entspricht. (shrink)

What does it take to understand a phenomenon ideally, or to the highest conceivable extent? In this paper, we answer this question by arguing for five necessary conditions for ideal understanding: (i) representational accuracy, (ii) intelligibility, (iii) truth, (iv) reasonable endorsement, and (v) fitting. Even if one disagrees that there is some form of ideal understanding, these five conditions can be regarded as sufficient conditions for a particularly deep level of understanding. We then argue that grasping, novel predictions, and transparency (...) are not reasonable conditions for ideal understanding. (shrink)

It is usually accepted that deductions are non-informative and monotonic, inductions are informative and nonmonotonic, abductions create hypotheses but are epistemically irrelevant, and both deductions and inductions can’t provide new insights. In this article, I attempt to provide a more cohesive view of the subject with the following hypotheses: (1) the paradigmatic examples of deductions, such as modus ponens and hypothetical syllogism, are not inferential forms, but coherence requirements for inferences; (2) since any reasoner aims to be coherent, any inference (...) must be deductive; (3) a coherent inference is an intuitive process where the premises should be taken as sufficient evidence for the conclusion, which on its turn should be viewed as necessary evidence for the premises in some modal range; (4) inductions, properly understood, are abductions, but there are no abductions beyond the fact that in any inference the conclusion should be regarded as necessary evidence for the premises; (5) monotonicity is not only compatible with the retraction of past inferences given new information, but it is a requirement for it; (6) this explanation of inferences holds true for discovery processes, predictions and trivial inferences. (shrink)

In this book, I present the results of an investigation which began with an extended stay at Oxford's Balliol College during the first half of 1995. My visit to Oxford was made possible by a grant from the Spanish Ministerio de Educaci6n y Ciencia. My sincere thanks go to Joseph Raz who served as my supervisor in Oxford. For several points of the present study, conversations with Timothy Endicott in Oxford were also of great help. The book is part of (...) a larger project of investigation, directed by Albert Calsami glia, which is a joint effort of a group of legal philosophers from the Universitat Pom peu Fabra and the Universitat de Girona, and which also receives financial support from the Spanish Ministerio de Educaci6n y Ciencia. An earlier version of the manuscript was presented in June 1996 to the selection committee for a tenured professorship in Legal Philosophy at the Universitat de Girona. The members of the committee were Francisco Laporta, Albert Calsamiglia, Gregorio Peces-Barba, Camilo J. Cela Conde, and Francesca Puigpelat. I am grateful to all of them for their comments, which have been extremely useful in preparing the final ver sion of this book. (shrink)

Can we transmit understanding via testimony in more or less the same way in which we transmit knowledge? The standard view in social epistemology has a straightforward answer: no, we cannot. Three arguments supporting the standard view have been formulated so far. The first appeals to the claim that gaining understanding requires a greater cognitive effort than acquiring testimonial knowledge does. The second appeals to a certain type of epistemic trust that is supposedly characteristic of knowledge transmission (and maybe of (...) the transmission of epistemic goods in general) and that is allegedly incompatible with understanding. The third aims to show that there is a certain aspect of understanding (what epistemologists these days like to call “grasping”) that cannot be passed on to another person via testimony alone. In this article, I show that all of these arguments can be resisted. Thus, there seem to be no compelling reasons to embrace the standard view. (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)

This dissertation starts with a concise overview of what philosophers of science have written about unification and its role in scientific explanation during the last 50 years to provide the reader with some background knowledge. In order to bring unification back into the picture, I have followed two strategies, resulting respectively in Parts I and II of this dissertation. In Part I the idea of unification is used to refine and enrich the dominant causalmechanist and causal-interventionist accounts of scientific explanation. (...) In this part of the dissertation I bracket the classical ideas about unification: deduction and derivation. I do grant, for the sake of argument, that explanations are causal and argue that unification is important from within this causalist perspective. In Part II I continue my strategy of digging into scientific practice to find cases of ontological unification. But here I distance myself from the dominant literature that all explanations must be causal. I will investigate whether explanatory unification is possible in non-causal explanations. Part III contains some further reflections and conclusions. I will formulate my primary results, and I will elaborate on their implications for thinking about unification and explanation. The different forms of ontological unification were quite diverse. This relates to the method I have used. Throughout this dissertation the types of unification that were discussed emerged from digging into scientific practice. This philosophy-of-science-practice approach steered me towards a pluralistic view on unification and on explanation. In this dissertation I do not try to develop a new model of explanation and compare it to existing models. The aim is to show that there are important types of explanatory practice which cannot be properly analyzed if we neglect unification as a desideratum for explanations. (shrink)

The concepts of coherence and confirmation are closely intertwined: according to a prominent proposal coherence is nothing but mutual confirmation. Accordingly, it should come as no surprise that both are confronted with similar problems. As regards Bayesian confirmation measures these are illustrated by the problem of tacking by conjunction. On the other hand, Bayesian coherence measures face the problem of belief individuation. In this paper we want to outline the benefit of an approach to coherence and confirmation based on content (...) elements. It will be shown that the resulting concepts, called genuine coherence and genuine confirmation, can be used in order to solve the two mentioned problems. In a final section we present some results on degrees of genuine coherence and genuine confirmation. (shrink)

Different why-questions emerge under different contexts and require different information in order to be addressed. Hence a relevance relation can hardly be invariant across contexts. However, what is indeed common under any possible context is that all explananda require scientific information in order to be explained. So no scientific information is in principle explanatorily irrelevant, it only becomes so under certain contexts. In view of this, scientific thought experiments can offer explanations, should we analyze their representational strategies. Their representations involve (...) empirical as well as hypothetical statements. I call this the “representational mingling” which bears scientific information that can explain events. Buchanan’s thought experiment from constitutional economics is examined to show how mingled representations explain. (shrink)

Catherine Elgin has recently argued that a nonfactive conception of understanding is required to accommodate the epistemic successes of science that make essential use of idealizations and models. In this paper, I argue that the fact that our best scientific models and theories are pervasively inaccurate representations can be made compatible with a more nuanced form of scientific realism that I call Understanding Realism. According to this view, science aims at (and often achieves) factive scientific understanding of natural phenomena. I (...) contend that this factive scientific understanding is provided by grasping a set of true modal information about the phenomenon of interest. Furthermore, contrary to Elgin’s view, I argue that the facticity of this kind of scientific understanding can be separated from the inaccuracy of the models and theories used to produce it. (shrink)

Opinionated state of the art paper on scientific explanation. Analysis and discussion of the most relevant models and theories in the contemporary literature, namely, the deductive-nomological model, the models of inductive-statistical and statistical relevance, the pragmatic theory of why questions, the unifying theory of standard arguments, and the causal/non-causal counterfactual theory.

Testimony spreads information. It is also commonly agreed that it can transfer knowledge. Whether it can work as an epistemic source of understanding is a matter of dispute. However, testimony certainly plays a pivotal role in the proliferation of understanding in the epistemic community. But how exactly do we learn, and how do we make advancements in understanding on the basis of one another’s words? And what can we do to maximize the probability that the process of acquiring understanding from (...) one another succeeds? These are very important questions in our current epistemological landscape, especially in light of the attention that has been paid to understanding as an epistemic achievement of purely epistemic value. Somewhat surprisingly, the recent literature in social epistemology does not offer much on the topic. The overarching aim of this paper is to provide a tentative model of understanding that goes in-depth enough to safely address the question of how understanding and testimony are related to one another. The hope is to contribute, in some measure, to the effort to understand understanding, and to explain two facts about our epistemic practices: the fact that knowledge and understanding relate differently to testimony, and the fact that some pieces of testimonial information are better than others for the sake of providing one with understanding and of yielding advancements in one’s epistemic standing. (shrink)

This paper analyzes two ways idealized biological models produce factive scientific understanding. I then argue that models can provide factive scientific understanding of a phenomenon without providing an accurate representation of the features of their real-world target system. My analysis of these cases also suggests that the debate over scientific realism needs to investigate the factive scientific understanding produced by scientists’ use of idealized models rather than the accuracy of scientific models themselves.

In this article I argue that there are two different types of understanding: the understanding we get from explanations, and the understanding we get from unification. This claim is defended by first showing that explanation and unification are not as closely related as has sometimes been thought. A critical appraisal of recent proposals for understanding without explanation leads us to discuss the example of a purely classificatory biology: it turns out that such a science can give us understanding of the (...) world through unification of the phenomena, even though it does not give us any explanations. The two types of understanding identified in this paper, while strictly separate, do have in common that both consist in seeing how the individual phenomena of the universe hang together. Explanations give us connections between the phenomena through the asymmetric, ‘vertical’ relation of determination; unifications give us connections through the symmetric, ‘horizontal’ relation of kinship. We then arrive at a general definition of understanding as knowledge of connections between the phenomena, and indicate that there might be more than two types of understanding. (shrink)

According to conventional wisdom, local gauge symmetry is not a symmetry of nature, but an artifact of how our theories represent nature. But a study of the so-called theta-vacuum appears to refute this view. The ground state of a quantized non-Abelian Yang-Mills gauge theory is characterized by a real-valued, dimensionless parameter theta—a fundamental new constant of nature. The structure of this vacuum state is often said to arise from a degeneracy of the vacuum of the corresponding classical theory, which degeneracy (...) allegedly arises from the fact that “large” (but not “small”) local gauge transformations connect physically distinct states of zero field energy. If that is right, then some local gauge transformations do generate empirical symmetries. In defending conventional wisdom against this challenge I hope to clarify the meaning of empirical symmetry while deepening our understanding of gauge transformations. I distinguish empirical from theoretical symmetries. Using Galileo’s ship and Faraday’s cube as illustrations, I say when an empirical symmetry is implied by a theoretical symmetry. I explain how the theta-vacuum arises, and how “large” gauge transformations differ from “small” ones. I then present two analogies from elementary quantum mechanics. By applying my analysis of the relation between empirical and theoretical symmetries, I show which analogy faithfully portrays the character of the vacuum state of a classical non-Abelian Yang-Mills gauge theory. The upshot is that “large” as well as “small” gauge transformations are purely formal symmetries of non-Abelian Yang-Mills gauge theories, whether classical or quantized. It is still worth distinguishing between these kinds of symmetries. An analysis of gauge within the constrained-Hamiltonian formalism yields the result that “large” gauge transformations should not be classified as gauge transformations; indeed, nor should “global” gauge transformations. In a theory in which boundary conditions are modeled dynamically, “global” gauge transformations may be associated with physical symmetries, corresponding to translations of these extra dynamical variables. Such translations are symmetries if and only if charge is conserved. But it is hard to argue that these symmetries are empirical, and in any case they do not correspond to any constant phase change in a quantum state. (shrink)

In the last couple of years a few seemingly independent debates on scientific explanation have emerged, with several key questions that take different forms in different areas. For example, the question what makes an explanation distinctly mathematical and are there any non-causal explanations in sciences (i.e. explanations that don’t cite causes in the explanans) sometimes take a form of the question what makes mathematical models explanatory, especially whether highly idealized models in science can be explanatory and in virtue of what (...) they are explanatory. These questions raise further issues about counterfactuals, modality and explanatory asymmetries, i.e. do mathematical and non-causal explanations support counterfactuals, and how to understand explanatory asymmetries in non-causal explanations. Even though these are very common issues in the philosophy of physics and mathematics, they can be found in different guises in the philosophy of biology, where there is the statistical interpretation of the Modern Synthesis theory of evolution, according to which the post-Darwinian theory of natural selection explains evolutionary change by citing statistical properties of populations and not the causes of changes. These questions also arise in philosophy of ecology or neuroscience in regard to the nature of topological explanations. The question here is whether in network models in biology, ecology, neuroscience and computer science the mathematical or more precisely topological properties can be explanatory of physical phenomena, or they are just different ways to represent causal structures. The aim of the special issue is to unify all these debates around several overlapping questions. (shrink)

According to the traditional requirement, formulated by William Whewell in his account of the “consilience of inductions” in 1840, a scientific hypothesis should have unifying power in the sense that it explains and predicts several mutually independent phenomena. Variants of this notion of consilience or unification include deductive, inductive, and approximate systematization. Inference from surprising phenomena to their theoretical explanations was called abduction by Charles Peirce. As a unifying theory is independently testable by new kinds of phenomena, it should also (...) receive confirmation from its empirical success. The study of the prospects of probabilistic Bayesianism to motivate this kind of criterion for abductive confirmation is shown to lead to two quite distinct conceptions of unification. (shrink)

In 1747, James Lind carried out an experiment which proved the usefulness of citrus fruit as a cure for scurvy. Nonetheless, he rejected the earlier hypothesis of Bachstrom that the absence of fresh fruit and vegetables was the only cause of the disease. I explain why it was rational for James Lind not to accept Bachstrom’s explanation. I argue that it was the urge for scientific understanding that guided Lind in his rejection and in the development of his alternative theory (...) that humidity was the primary cause of the disease. Central in this process was the search for causal mechanisms which could provide understanding of how the disease developed and which fitted in with the knowledge of the time. Given that the relevant background knowledge and statistical methods were not yet available to Lind, he was right to prefer his own explanation to that of Bachstrom. Although his explanation turned out to be wrong, and Bachstrom’s right, from a historical point of view it offered deeper causal understanding of both the development of the disease and the preventive and curative effects of fresh vegetable food. This case study illustrates how the search for causal mechanisms can not only be enlightening, but also very misleading. (shrink)

Many have argued that unified theories ought to be pursued wherever possible. We deny this on the basis of social-epistemological and decision-theoretic considerations. Consequently, those seeking a more ubiquitous role for unification must either attend to the scientific community’s social structure in greater detail than has been the case, and/or radically revise their conception of unification.

There is a strong tendency in science to opt for simpler and more unified hypotheses. A view that has often been voiced is that such qualities, though aesthetically pleasing or beautiful, are at best pragmatic considerations in matters of choosing between rival hypotheses. This essay offers a novel conception and an associated measure of unification, both of which are manifestly more than just pragmatic considerations. The discussion commences with a brief survey of some failed attempts to conceptualise unification. It then (...) proceeds to an analysis of the notions of confirmational connectedness and disconnectedness, as these are essential ingredients in the proposed conception of unification and its associated measure. Roughly speaking, the notions attempt to capture the way support flows or fails to flow between the content parts of a hypothesis. Equally roughly, the more the content of a hypothesis is confirmationally connected, i.e. support flows between its content parts, the more that content is unified. Since the confirmational connectedness of two content parts is determined by purely objective matters of fact, the proposed notion and measure of unification are themselves strictly objective, i.e. not merely pragmatic. The essay concludes with a discussion of how the proposed measure handles several examples but also how it relates to the debate over measures of coherence.En la ciencia hay una marcada tendencia a preferir las hipotesis mas simples y unificadas. Una opinion mantenida a menudo es que tales cualidades, aun siendo atractivas o esteticamente satisfactorias, constituyen consideraciones pragmaticas, a lo sumo, en el asunto de la eleccion entre teorias rivales. Este ensayo ofrece una concepcion novedosa de unificacion y una medida asociada a ella, ambas claramente algo mas que meras consideraciones pragmaticas. La discusion comienza con un breve repaso de algunos intentos fallidos de conceptualizar la unificacion. Despues se analizan las nociones de conexion y desconexion confirmacional, componentes esenciales en la nocion de unificacion y la medida asociada que aqui se proponen. Dicho brevemente, esas nociones pretenden captar el modo en que el apoyo discurre o no entre las partes del contenido de las hipotesis. Simplificando, cuanto mas conectado confirmacionalmente esta el contenido de una hipotesis, mas unificado esta. Dado que la conectividad confirmacional de dos partes del contenido esta determinada por cuestiones de hecho objetivas, la nocion y la medida que propongo son tambien estrictamente objetivas, esto es, su valor no es meramente pragmatico. El ensayo concluye con una discusion sobre como la medida propuesta afronta diversos ejemplos y sobre su relacion con el debate sobre las diferentes medidas de coherencia. (shrink)