Erik Weber

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

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.

In this paper, we analyse the fruitfulness of Ronald Giere’s comparative model for causation in populations. While the original model was primarily developed to capture the meaning of causal claims in the biomedical and health sciences, we want to show that the model is not only useful in these domains, but can also fruitfully be applied to other scientific domains. Specifically, we demonstrate that the model is fruitful for characterizing the meaning of causal claims found in classical genetics, epidemiology and electoral sociology. Additionally, we propose an adapted comparative model which is needed to get a grip on higher level causal claims. We show that such claims are present in population genetics, epidemiology and electoral systems research. We conclude with some reflections on the implications of our findings for the issue of causal pluralism.

RésuméComment devons‐nous appliquer notre savoir scientifique pour qu'il contribue à mieux comprendre les phénomènes que nous observons? Le modèle déductif‐nomologique d'explication scientifique, dans lequel Carl Hempel construit le concept d'explication déductive‐nomologique, ne procure pas une réponse complète à cette question. Un des problèmes est que Hempel nous dit ce que nous devons construire quand nous voulons comprendre un phéomène , mais ne nous dit pas comment une explication de ce type est construite. Afin de réoudre ce problème, une méthode pour construire des explications déductives‐nomologiques est développée

Instances of explanatory reduction are often advocated on metaphysical grounds; given that the only real things in the world are subatomic particles and their interaction, we have to try to explain everything in terms of the laws of physics. In this paper, we show that explanatory reduction cannot be defended on metaphysical grounds. Nevertheless, indispensability arguments for reductive explanations can be developed, taking into account actual scientific practice and the role of epistemic interests. Reductive explanations might be indispensable to address some epistemic interest answering a specific explanation-seeking question in the most accurate, adequate and efficient way. Just like explanatory pluralists often advocate the indispensability of higher levels of explanation pointing at the pragmatic value of the explanatory information obtained on these higher levels, we argue that explanatory reduction—traditionally understood as the contender of pluralism—can be defended in a similar way. The pragmatic value reductionist, lower level explanations might have in the biomedical sciences and the social sciences is illustrated by some case studies.

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

In a recent paper on realism and pragmatism published in this journal, Osmo Kivinen and Tero Piiroinen have been pleading for more methodological work in the philosophy of the social sciences—refining the conceptual tools of social scientists—and less philosophically ontological theories. Following this de-ontologizing approach, we scrutinize the debates on social explanation and contribute to the development of a pragmatic social science methodology. Analyzing four classic debates concerning explanation in the social sciences, we propose to shift the debate away from (a) the ontologizing defenses of forms of social explanation, and (b) a winner-takes-all-approach. Instead, we advocate (c) a pragmatic approach towards social explanation, elaborating a rigorous framework for explanatory pluralism detached from the debates on social ontology.

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.

Casuistry, which involves analogical reasoning, is a popular methodological approach in bioethics. The method has its advantages and challenges, which are widely acknowledged. Meta-philosophical reflection on exactly how bioethical casuistry works and how the challenges can be addressed is limited. In this paper we propose a framework for structuring casuistry and analogical reasoning in bioethics. The framework is developed by incorporating theories and insights from the philosophy of science: Mary Hesse’s ideas on horizontal and vertical relations in analogical reasoning in the sciences, Paul Bartha’s articulation model of analogical reasoning and Daniel Steel’s insights on mechanism-based extrapolation in biomedical research. Adopting our framework results in two practical benefits: it sets methodological standards for analogical reasoning and enables us to compare and evaluate diverging lines of analogical reasoning in a systematic way. Adopting the framework also has theoretical benefits: it helps to understand how analogical reasoning can have moral normativity; it pinpoints exactly where moral principles or theories enter analogical reasoning; and it helps to understand why casuistry is an attractive method in bioethics and in applied ethics more generally.

When scientist investigate why things happen, they aim at giving an explanation. But what does a scientific explanation look like? In the first chapter (Theories of Scientific Explanation) of this book, the milestones in the debate on how to characterize scientific explanations are exposed. The second chapter (How to Study Scientific Explanation?) scrutinizes the working-method of three important philosophers of explanation, Carl Hempel, Philip Kitcher and Wesley Salmon and shows what went wrong. Next, 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 and clarify briefly what this approach consists in. The third chapter (A Toolbox for Describing and Evaluating Explanatory Practices) elaborates the pragmatic approach by presenting a toolbox for analysing scientific explanation. In the last chapter (Examples of Descriptions and Evaluations of Explanatory Practices) the approach is illustrated with real-life examples of scientists aiming at explaining

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.