Introduction: Scientific Explanation Beyond Causation

This is an introduction to the volume "Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations", edited by A. Reutlinger and J. Saatsi (OUP, forthcoming in 2017). Explanations are very important to us in many contexts: in science, mathematics, philosophy, and also in everyday and juridical contexts. But what is an explanation? In the philosophical study of explanation, there is long-standing, influential tradition that links explanation intimately to causation: we often explain by providing accurate information about the causes of the phenomenon to be explained. Such causal accounts have been the received view of the nature of explanation, particularly in philosophy of science, since the 1980s. However, philosophers have recently begun to break with this causal tradition by shifting their focus to kinds of explanation that do not turn on causal information. The increasing recognition of the importance of such non-causal explanations in the sciences and elsewhere raises pressing questions for philosophers of explanation. What is the nature of non-causal explanations - and which theory best captures it? How do non-causal explanations relate to causal ones? How are non-causal explanations in the sciences related to those in mathematics and metaphysics? This volume of new essays explores answers to these and other questions at the heart of contemporary philosophy of explanation. The essays address these questions from a variety of perspectives, including general accounts of non-causal and causal explanations, as well as a wide range of detailed case studies of non-causal explanations from the sciences, mathematics and metaphysics

Explanation Beyond Causation? New Directions in the Philosophy of Scientific Explanation

In this paper, I aim to provide access to the current debate on non-causal explanations in philosophy of sciences. I will first present examples of non-causal explanations in the sciences. Then, I will outline three alternative approaches to non-causal explanations – that is, causal reductionism, pluralism and monism – and, corresponding to these three approaches, different strategies for distinguishing between causal and non-causal explanation. Finally, I will raise questions for future research on non-causal explanations

Natural Law and Universality in the Philosophy of Biology

Several philosophers of biology have argued for the claim that the generalizations of biology are historical and contingent.1–5 This claim divides into the following sub-claims, each of which I will contest: first, biological generalizations are restricted to a particular space-time region. I argue that biological generalizations are universal with respect to space and time. Secondly, biological generalizations are restricted to specific kinds of entities, i.e. these generalizations do not quantify over an unrestricted domain. I will challenge this second claim by providing an interpretation of biological generalizations that do quantify over an unrestricted domain of objects. Thirdly, biological generalizations are contingent in the sense that their truth depends on special (physically contingent) initial and background conditions. I will argue that the contingent character of biological generalizations does not diminish their explanatory power nor is it the case that this sort of contingency is exclusively characteristic of biological generalizations

Do Statistical Laws Solve the ‘Problem of Provisos’?

Earman and Roberts propose to interpret non-strict special science generalizations as statistical generalizations about correlations. Earman and Roberts claim that these statistical generalizations are not qualified by ceteris paribus (henceforth, cp) conditions. I present two challenges to the statistical account. According to the first challenge, the statistical account does not get rid of so-called "non-lazy" cp-conditions. This result undermines one of the alleged advantages of the statistical account. The second challenge is that the statistical account, qua general theory of special science laws, is weakened by the fact that idealized law statements resist a purely statistical interpretation

What is epistemically wrong with research affected by sponsorship bias? The evidential account

Biased research occurs frequently in the sciences. In this paper, I will focus on one particular kind of biased research: research that is subject to sponsorship bias. I will address the following epistemological question: what precisely is epistemically wrong (that is, unjustified) with biased research of this kind? I will defend the evidential account of epistemic wrongness: that is, research affected by sponsorship bias is epistemically wrong if and only if the researchers in question make false claims about the (degree of) evidential support of some hypothesis H by data E. I will argue that the evidential account captures the epistemic wrongness of three paradigmatic types of sponsorship bias

Explanation Beyond Causation? New Directions in the Philosophy of Scientific Explanation

In this paper, I aim to provide access to the current debate on non-causal explanations in philosophy of sciences. I will first present examples of non-causal explanations in the sciences. Then, I will outline three alternative approaches to non-causal explanations – that is, causal reductionism, pluralism and monism – and, corresponding to these three approaches, different strategies for distinguishing between causal and non-causal explanation. Finally, I will raise questions for future research on non-causal explanations

What is Epistemically Wrong with Research Affected by Sponsorship Bias? The Evidential Account

Biased research occurs frequently in the sciences. In this paper, I will focus on one particular kind of biased research: research that is subject to sponsorship bias. I will address the following epistemological question: what precisely is epistemically wrong (that is, unjustified) with biased research of this kind? I will defend the evidential account of epistemic wrongness: that is, research affected by sponsorship bias is epistemically wrong if and only if the researchers in question make false claims about the (degree of) evidential support of some hypothesis H by data E. I will argue that the evidential account captures the epistemic wrongness of three paradigmatic types of sponsorship bias

Is There A Monist Theory of Causal and Non-Casual Explanations? The Counterfactual Theory of Scientific Explanation

The goal of this paper is to develop a counterfactual theory of explanation (for short, CTE). The CTE provides a monist framework for causal and non-causal explanations, according to which causal and non-causal are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I argue that the CTE is applicable to two paradigmatic examples of non-causal explanations: Euler's explanation and renormalization group explanations of universality

Do Statistical Laws Solve the ‘Problem of Provisos’?

Earman and Roberts propose to interpret non-strict special science generalizations as statistical generalizations about correlations. Earman and Roberts claim that these statistical generalizations are not qualified by ceteris paribus (henceforth, cp) conditions. I present two challenges to the statistical account. According to the first challenge, the statistical account does not get rid of so-called "non-lazy" cp-conditions. This result undermines one of the alleged advantages of the statistical account. The second challenge is that the statistical account, qua general theory of special science laws, is weakened by the fact that idealized law statements resist a purely statistical interpretation

Ceteris Paribus Laws

Laws of nature take center stage in philosophy of science. Laws are usually believed to stand in a tight conceptual relation to many important key concepts such as causation, explanation, confirmation, determinism, counterfactuals etc. Traditionally, philosophers of science have focused on physical laws, which were taken to be at least true, universal statements that support counterfactual claims. But, although this claim about laws might be true with respect to physics, laws in the special sciences (such as biology, psychology, economics etc.) appear to have—maybe not surprisingly—different features than the laws of physics. Special science laws—for instance, the economic law “Under the condition of perfect competition, an increase of demand of a commodity leads to an increase of price, given that the quantity of the supplied commodity remains constant” and, in biology, Mendel's Laws—are usually taken to “have exceptions”, to be “non-universal” or “to be ceteris paribus laws”. How and whether the laws of physics and the laws of the special sciences differ is one of the crucial questions motivating the debate on ceteris paribus laws. Another major, controversial question concerns the determination of the precise meaning of “ceteris paribus”. Philosophers have attempted to explicate the meaning of ceteris paribus clauses in different ways. The question of meaning is connected to the problem of empirical content, i.e., the question whether ceteris paribus laws have non-trivial and empirically testable content. Since many philosophers have argued that ceteris paribus laws lack empirically testable content, this problem constitutes a major challenge to a theory of ceteris paribus laws