Current philosophical theorizing about technical functions is mainly focused on specifying conditions under which agents are justified in ascribing functions to technical artifacts. Yet, assessing the precise explanatory relevance of such function ascriptions is, by and large, a neglected topic in the philosophy of technical artifacts and technical functions. We assess the explanatory utility of ascriptions of technical functions in the following three explanation-seeking contexts: why was artifact x produced?, why does artifact x not have the expected capacity to ϕ?, (...) how does artifact x realize its capacity to ϕ? We argue that while function ascriptions serve a mere heuristic role in the first context, they have substantial explanatory leverage in the second and third context. In addition, we assess the relevance of function ascriptions in the context of engineering redesign. Here, function ascriptions also play a relevant role: they enable normative statements of the sort that component b functions better than component a. We unpack these claims by considering philosophical theories of technical functions, in particular the ICE theory, and engineering work on function ascription and explanation. We close the paper by relating our analysis to current debates on the explanatory power of mechanistic vis-à-vis functional explanations. (shrink)
In this paper we argue that in recent literature on mechanistic explanations, authors tend to conflate two distinct features that mechanistic models can have or fail to have: plausibility and richness. By plausibility, we mean the probability that a model is correct in the assertions it makes regarding the parts and operations of the mechanism, i.e., that the model is correct as a description of the actual mechanism. By richness, we mean the amount of detail the model gives about the (...) actual mechanism. First, we argue that there is at least a conceptual reason to keep these two features distinct, since they can vary independently from each other: models can be highly plausible while providing almost no details, while they can also be highly detailed but plainly wrong. Next, focusing on Craver's continuum of ?how-possibly,? to ?how-plausibly,? to ?how-actually? models, we argue that the conflation of plausibility and richness is harmful to the discussion because it leads to the view that both are necessary for a model to have explanatory power, while in fact, richness is only so with respect to a mechanism's activities, not its entities. This point is illustrated with two examples of functional models. (shrink)
The International Agency for Research on Cancer (IARC) is an organization which seeks to identify the causes of human cancer. Per agent, such as betel quid or Human Papillomaviruses, they review the available evidence deriving from epidemiological studies, animal experiments and information about mechanisms (and other data). The evidence of the different groups is combined such that an overall assessment of the carcinogenicity of the agent in question is obtained. In this paper, we critically review the IARC’s carcinogenicity evaluations. First (...) we show that serious objections can be raised against their criteria and procedures – more specifically regarding the role of mechanistic knowledge in establishing causal claims. Our arguments are based on the problem of confounders, of the assessment of the temporal stability of carcinogenic relations, and of the extrapolation from animal experiments. Then we address a very important question, viz. how we should treat the carcinogenicity evaluations that were based on the current procedures. After showing that this question is important, we argue that an overall dismissal of the current evaluations would be too radical. Instead, we argue in favour of a stepwise re-evaluation of the current findings. (shrink)
In a recent article in this journal, Federica Russo and Jon Williamson argue that an analysis of causality in terms of probabilistic relationships does not do justice to the use of mechanistic evidence to support causal claims. I will present Ronald Giere's theory of probabilistic causation, and show that it can account for the use of mechanistic evidence (both in the health sciences—on which Russo and Williamson focus—and elsewhere). I also review some other probabilistic theories of causation (of Suppes, Eells, (...) and Humphreys) and show that they cannot account for the use of mechanistic evidence. I argue that these theories are also inferior to Giere's theory in other respects. (shrink)
Explanatory pluralism has been defended by several philosophers of history and social science, recently, for example, by Tor Egil Førland in this journal. In this article, we provide a better argument for explanatory pluralism, based on the pragmatist idea of epistemic interests. Second, we show that there are three quite different senses in which one can be an explanatory pluralist: one can be a pluralist about questions, a pluralist about answers to questions, and a pluralist about both. We defend the (...) last position. Finally, our third aim is to argue that pluralism should not be equated with “anything goes”: we will argue for non-relativistic explanatory pluralism. This pluralism will be illustrated by examples from history and social science in which different forms of explanation (for example, structural, functional, and intentional explanations) are discussed, and the fruitfulness of our framework for understanding explanatory pluralism is shown. (shrink)
In a 2008 paper, Walmsley argued that the explanations employed in the dynamical approach to cognitive science, as exemplified by the Haken, Kelso and Bunz model of rhythmic finger movement, and the model of infant preservative reaching developed by Esther Thelen and her colleagues, conform to Carl Hempel and Paul Oppenheim’s deductive-nomological model of explanation (also known as the covering law model). Although we think Walmsley’s approach is methodologically sound in that it starts with an analysis of scientific practice rather (...) than a general philosophical framework, we nevertheless feel that there are two problems with his paper. First, he focuses only on the deductivenomological model and so neglects the important fact that explanations are causal. Second, the explanations offered by the dynamical approach do not take the deductive-nomological format, because they do not deduce the explananda from exceptionless laws. Because of these two points, Walmsley makes the dynamical explanations in cognitive science appear problematic, while in fact they are not. (shrink)
Some social scientists and philosophers (e.g., James Coleman and Jon Elster) claim that all social facts are best explained by means of a micro-explanation. They defend a micro-reductionism in the social sciences: to explain is to provide a mechanism on the individual level. The first aim of this paper is to challenge this view and defend the view that it has to be substituted for an explanatory pluralism with two components: (1) structural explanations of P-, O- and T-contrasts between social (...) facts are more efficient than the competing micro-explanations; and (2) whether a plain social fact (as opposed to a contrast) is best explained in a micro-explanation or a structural explanation depends on the explanatory interest. The second aim of the paper is to show how this explanatory pluralism is compatible with ontological individualism. This paper is motivated by our conviction that explanatory pluralism as defended by Frank Jackson and Philip Pettit is on the right track, but must be further elaborated. We want to supplement their contribution, by (1) introducing the difference between explanations of facts and explanations of contrasts; (2) giving examples from the social sciences, instead of mainly from the natural sciences or common sense knowledge; and (3) emphasizing the pragmatic relevance of explanations on different levels –social, psychological, biological, etc. – which is insufficiently done by Jackson and Pettit. (shrink)
Although interest in them is clearly growing, most professional historians do not accept thought experiments as appropriate tools. Advocates of the deliberate use of thought experiments in history argue that without counterfactuals, causal attributions in history do not make sense. Whereas such arguments play upon the meaning of causation in history, this article focuses on the reasoning processes by which historians arrive at causal explanations. First, we discuss the roles thought experiments play in arriving at explanations of both facts and (...) contrasts. Then, we pinpoint the functions thought experiments fulfill in arriving at weighted explanations of contrasts. (shrink)
The general view is that metaphysical explanation is asymmetric. For instance, if resemblance facts can be explained by facts about their relata, then, by the asymmetry of explanation, these latter facts cannot in turn be explained by the former. The question however is: is there any reason to hold on to the asymmetry? If so, what does it consist in? In the paper we approach these questions by comparing them to analogous questions that have been investigated for scientific explanations. Three (...) main asymmetry criteria have been proposed for the latter: (i) causation, (ii) unification, and (iii) explanatory dependence. We argue that the last criterion, but not the former two, can be of help to metaphysical explanation: metaphysical explanations are asymmetric if the explanatory dependence criterion (in modified format) holds of them. (shrink)
The paper has two aims. First, to show that we need social mechanisms to establish the policy relevance of causal claims, even if it is possible to build a good argument for those claims without knowledge of mechanisms. Second, to show that although social scientists can, in principle, do without social mechanisms when they argue for causal claims, in reality scientific practice contexts where they do not need mechanisms are very rare. Key Words: social mechanisms causal inference social (...) policy. (shrink)
This paper investigates the working-method of three important philosophers of explanation: Carl Hempel, Philip Kitcher and Wesley Salmon. We argue that they do three things: construct an explication in the sense of Carnap, which then is used as a tool to make descriptive and normative claims about the explanatory practice of scientists. We also show that they did well with respect to, but that they failed to give arguments for their descriptive and normative claims. We think it is the responsibility (...) of current philosophers of explanation to go on where Hempel, Kitcher and Salmon failed. However, we should go on in a clever way. We call this clever way the “pragmatic approach to scientific explanation.” We clarify what this approach consists in and defend it. (shrink)
This article has three aims. The first is to give a partial explication of the concept of unification. My explication will be partial because I confine myself to unification of particular events, because I do not consider events of a quantitative nature, and discuss only deductive cases. The second aim is to analyze how unification can be reached. My third aim is to show that unification is an intellectual benefit. Instead of being an intellectual benefit unification could be an intellectual (...) harm, i.e., a state of mind we should try to avoid by all means. By calling unification an intellectual benefit, we claim that this form of understanding has an intrinsic value for us. I argue that unification really has this alleged intrinsic value. (shrink)
This paper deals with the "functions of intentional explanations" of actions (IEAs), i.e., explanations that refer to intentional states (beliefs, desires, etc.) of the agent. IEAs can have different formats. We consider these different formats to be instruments that enable the explainer to capture different kinds of information. We pick out two specific formats, i.e. "contrastive" and "descriptive", which will enable us to discuss the functions of IEAs. In many cases the explanation is contrastive, i.e. it makes use of one (...) or more contrasts between real intentional states and ideal intentional states (ideal from the point of view of the explainer). In many other cases IEAs have a descriptive (covering-law) format. The aim of this paper is to analyze the functions the two kinds of explanations can have. We will show that certain functions are better served by one rather than the other format. This leads to pluralism with respect to formats. We argue that both formats are necessary and that their functions are complementary. (shrink)
In the past 25 years, many philosophers have endorsed the view that the practical value of causal knowledge lies in the fact that manipulation of causes is a good way to bring about a desired change in the effect. This view is intuitively very plausible. For instance, we can predict a storm on the basis of a barometer reading, but we cannot avoid the storm by manipulating the state of the barometer (barometer status and storm are effects of a common (...) cause, viz. atmospheric conditions). In Section 1 we present textual evidence which shows that this view is very popular. In Section 2 we show that this standard view is too restrictive: the practical value of causal knowledge is wider. In Section 3 we introduce the distinction between ‘manipulative policy’ and ‘selective policy’ as a theoretical framework to account for this wider practical value. (shrink)
If dispositions are conceived as properties of systems that refer to possible causal relations, dispositions can be used in singular causal explanations. By means of these dispositional explanations, we can explain behavior B of a system x by (i) referring to a situation of type S that triggered B, given that x has a disposition D to do B in S, or (ii) by referring to a disposition D of x to do B in S, given that x is in (...) a situation of type S. Dispositional explanations are adequate and indispensable explanations: they can explain behavior B without explicitly referring to the underlying causal basis in x that constitutes a disposition to do B. Radical Behaviorist explanations are a sort of dispositional explanations, but the dispositional model is not restricted to these explanations. The dispositional model is compatible with, or can be applied to, several research programs. (shrink)
One of the functions of scientific knowledge is to provide the theories and laws we need in order to understand the world. My article deals with the epistemic aspect of understanding, i.e., with understanding as unification. The aim is to explicate what we have to do in order to make our scientific knowledge contribute to an increase of the degree to which the particular events we have observed, fit into our world-picture. The analysis contains two parts. First I define the (...) concept of scientific epistemic explanation. Explanations of these type are the appropriate instruments for increasing the degree of unification of the particular events we have observed. In the second, largest part of the article I analyze the construction process of scientific epistemic explanations, focusing on the application of scientific theories. (shrink)
In the literature on scientific explanation two types of pluralism are very common. The first concerns the distinction between explanations of singular facts and explanations of laws: there is a consensus that they have a different structure. The second concerns the distinction between causal explanations and uni.cation explanations: most people agree that both are useful and that their structure is different. In this article we argue for pluralism within the area of causal explanations: we claim that the structure of a (...) causal explanation depends on the causal structure of the relevant fragment of the world and on the interests of the explainer. (shrink)
In this essay the authors explore the nature of efficient causal explanation in Newton’s "Principia and The Opticks". It is argued that: (1) In the dynamical explanations of the Principia, Newton treats the phenomena under study as cases of Hall’s second kind of atypical causation. The underlying concept of causation is therefore a purely interventionist one. (2) In the descriptions of his optical experiments, Newton treats the phenomena under study as cases of Hall’s typical causation. The underlying concept of causation (...) is therefore a mixed interventionist/mechanicist one. (shrink)
Jonathan Schaffer has argued that a contrastive causal ontology is beneficial in juridical contexts: lawyers and judges should treat the causal relation as a quaternary relation, not as binary one. In this paper we investigate to what extent a contrastive causal ontology is beneficial in genetics and in physics. We conclude that it is beneficial in these scientific domains. We also point out that the nature of the benefit differs in the three context that we discuss. Key words: Contrastive causation, (...) causation in genetics, causation in physics, Jonathan Schaffer. (shrink)
In the literature on scientific explanation, there is a classical distinction between explanations of particular facts and explanations of laws. This paper is about explanations of laws, more specifically about microexplanations of laws in physics. We investigate whether providing unificatory information has a surplus value in micro-explanations of physical laws. Unificatory information is information that provides ontological unification in the sense defined by Uskali Mäki. We argue that providing unificatory information may lead to explanations with more explanatory power and that (...) it may lead to more strongly supported explanations.En la literatura sobre explicación científica hay una distinción clásica entre explicaciones de hechos particulares y explicaciones de leyes. El presente artículo trata de las explicaciones de las leyes, más en concreto, de las microexplicaciones de las leyes en la física. Analizamos si proporcionar información unificadora posee un valor adicional en las microexplicaciones de las leyes físicas. La información unificadora es información que proporciona unificación ontológica en el sentido definido por Uskali Mäki. Argumentamos que proporcionar información unificadora puede llevar a explicaciones con mayor poder explicativo, y también a explicaciones más firmemente apoyadas. (shrink)
The Scottish physician James Lind is the most celebrated name in the history of research into the causes and cures of scurvy. This is due to the famous experiment he conducted in 1747 on H.M.S. Salisbury in order to compare the efficiency of six popular treatments for scurvy. This experiment is generally regarded as the first controlled trial in clinical science (see e.g. Carpenter 1986, p. 52).
Editors’ introduction to the special issue on the Causality and Explanation in the Sciences conference, held at the University of Ghent in September 2011.Presentación del número monográfico sobre el congreso Causality and Explanation in the Sciences, celebrado en la Universidad de Gante en septiembre de 2011.
In this paper we discuss three interrelated questions. First: is explanation in mathematics a topic that philosophers of mathematics can legitimately investigate? Second: are the specific aims that philosophers of mathematical explanation set themselves legitimate? Finally: are the models of explanation developed by philosophers of science useful tools for philosophers of mathematical explanation? We argue that the answer to all these questions is positive. Our views are completely opposite to the views that Mark Zelcer has put forward recently. Throughout this (...) paper, we show why Zelcer’s arguments fail. (shrink)
In the current literature on scientific explanation unification became unfashionable in favour of causal approaches. We want to bring unification back into the picture. In this paper we demonstrate that resemblance questions do occur in scientific practice and that they cannot be properly answered without unification. Our examples show that resemblance questions about particular facts demand what we call causal network unification, while resemblance questions about regularities require what we call mechanism unification. We clarify how these types of unification relate (...) to Philip Kitcher’s account, but also to causal and mechanistic accounts of explanation. (shrink)
In this article we criticize two recent articles that examinethe relation between explanation and unification. Halonen and Hintikka (1999), on the one hand,claim that no unification is explanation. Schurz (1999), on the other hand, claims that all explanationis unification. We give counterexamples to both claims. We propose a pluralistic approach to the problem:explanation sometimes consists in unification, but in other cases different kinds of explanation(e.g., causal explanation) are required; and none of these kinds is more fundamental.
Pluralism with respect to the structure of explanations of facts is not uncommon. Wesley Salmon, for instance, distinguished two types of explanation: causal explanations (which provide insight in the causes of the fact we want to explain) and unification explanations (which fit the explanandum into a unified world view). The pluralism which Salmon and others have defended is compatible with several positions about the exact relation between these two types of explanations. We distinguish four such positions, and argue in favour (...) of one of them. We also compare our results with the views of some authors who have recently written on this subject. (shrink)
In the literature on scientific explanation, there is a classical distinction between explanations of facts and explanations of laws. This paper is about explanations of facts. Our aim is to analyse the role of unification in explanations of this kind. We discuss five positions with respect to this role, argue for two of them and refute the three others.
In this article we criticize two recent articles that examine the relation between explanation and unification. Halonen and Hintikka (1999), on the one hand, claim that no unification is explanation. Schurz (1999), on the other hand, claims that all explanation is unification. We give counterexamples to both claims. We propose a pluralistic approach to the problem: explanation sometimes consists in unification, but in other cases different kinds of explanation (e.g., causal explanation) are required; and none of these kinds is more (...) fundamental. (shrink)
Although there is a consensus among philosophers of mathematics and mathematicians that mathematical explanations exist, only a few authors have proposed accounts of explanation in mathematics. These accounts fit into the unificationist or top-down approach to explanation. We argue that these models can be complemented by a bottom-up approach to explanation in mathematics. We introduce the mechanistic model of explanation in science and discuss the possibility of using this model in mathematics, arguing that using it does not presuppose a Platonist (...) view of mathematics and allows one to gain insight into why a theorem is true by answering what-if-things-had-been-different questions. (shrink)
In this paper I argue against the traditional viewthat in discovery processes there is no place forrational decisions. First I argue that some historicalprocesses in which an empirical law was developed,were rational. Second, I identify some of themethodological rules that we can follow in order to berational when constructing an empirical law. Finally,I argue that people who deny that scientific discoverycan be rational do not understand the nature ofmethodological rules.