Leibniz is often cited as an authority when it comes to the formulation and answer strategy of the question “Why is there something rather than nothing?” Yet much current research assumes that Leibniz advocates an unambiguous question and strategy for the answer. In this respect, one repeatedly finds the argument in the literature that alternative explanatory approaches to this question violate Leibniz’s intention, since he derives the question from the principle of sufficient reason and also demands a causal explanation to (...) the question. In particular, the new research on non-causal explanatory strategies to the Leibniz question seems to concern this counter-argument. In this paper, however, I will argue that while Leibniz raises the question by means of the principle of sufficient reason, he even favours a non-causal explanatory strategy to the question. Thus, a more accurate Leibniz interpretation seems not only to legitimise but also to support non-causal explanations to the Leibniz question. (shrink)

An important book by the world's most eminent epistemologist. In Epistemic Explanations Sosa develops an improved virtue epistemology and uses it to explain several epistemic phenomena.

The paper discusses methodological guidelines for evaluating mechanistic explanations. According to current accounts, a satisfactory mechanistic explanation should include all of the relevant features of the mechanism, its component entities and activities, and their properties and organization, as well as exhibit productive continuity. It is not specified, however, how this kind of mechanistic completeness can be demonstrated. I argue that parameter sufficiency inferences based on mathematical model simulations provide a way of determining whether a mechanism capable of producing the (...) phenomenon of interest can be constructed from mechanistic components organized, acting, and having the properties described in the mechanistic explanation. (shrink)

Not all scientific explanations work by describing causal connections between events or the world's overall causal structure. In addition, mathematicians regard some proofs as explaining why the theorems being proved do in fact hold. This book proposes new philosophical accounts of many kinds of non-causal explanations in science and mathematics.

There is a huge philosophical literature on scientific explanation, and no one seriously denies that the sciences explain in one way or another. But what about ontology? I will argue that ontological laws and ontological theories can explain. And I will point at the differences between ontological explanations and their scientific counterparts.

A main thread of the debate over mathematical realism has come down to whether mathematics does explanatory work of its own in some of our best scientific explanations of empirical facts. Realists argue that it does; anti-realists argue that it doesn't. Part of this debate depends on how mathematics might be able to do explanatory work in an explanation. Everyone agrees that it's not enough that there merely be some mathematics in the explanation. Anti-realists claim there is nothing mathematics (...) can do to make an explanation mathematical ; realists think something can be done, but they are not clear about what that something is. I argue that many of the examples of mathematical explanations of empirical facts in the literature can be accounted for in terms of Jackson and Pettit's [1990] notion of program explanation, and that mathematical realists can use the notion of program explanation to support their realism. This is exactly what has happened in a recent thread of the debate over moral realism. I explain how the two debates are analogous and how moves that have been made in the moral realism debate can be made in the mathematical realism debate. However, I conclude that one can be a mathematical realist without having to be a moral realist. (shrink)

Recently philosophers of science have begun to pay more attention to the use of highly idealized mathematical models in scientific theorizing. An important example of this kind of highly idealized modeling is the widespread use of optimality models within evolutionary biology. One way to understand the explanations provided by these models is as a censored causal explanation: an explanation that omits certain causal factors in order to focus on a modular subset of the causal processes that led to the (...) explanandum. In this paper, I first argue that the censored causal model approach fails to establish a permanent explanatory role for optimality models in biology and mischaracterizes the explanatory virtues of biological optimality modeling. In addition, I argue that many biological optimality explanations cannot be characterized as censored causal explanations. In response, I propose an alternative approach that analyzes optimality models’ reliance on synchronically representing a system’s constraints and tradeoffs as well as their employment of various kinds of idealization in order to provide equilibrium explanations. (shrink)

If ontic dependence is the basis of explanation, there cannot be mathematical explanations. Accounting for the explanatory dependency between mathematical properties and empirical phenomena poses i...

According to conceptual reductive accounts, if properties of one domain can be conceptually reduced to properties of another domain, then the former properties are ontologically reduced to the latter properties. I will argue that conceptual reductive accounts face problems: either they do not recognise that many higher-level properties are correlated with multiple physical properties, or they do not clarify how we can discover new truthmakers of sentences about a higher-level property. Still, there is another way to motivate ontological reduction, the (...) truthmaker reductive explanations (TRE). TRE can be given by using resources from John Heil’s truthmaker theory and the a priori entailment view or the a posteriori entailment view. I will argue that we can give these truthmaker reductive explanations if there are various less-than-perfectly similar physical properties that can be the truthmakers of sentences about higher-level properties and the physical similarity between them can explain why an irreducible higher-level property is not needed. (shrink)

The present paper analyzes the self‐generated explanations (from talk‐aloud protocols) that “Good” and “Poor” students produce while studying worked‐out examples of mechanics problems, and their subsequent reliance on examples during problem solving. We find that “Good” students learn with understanding: They generate many explanations which refine and expand the conditions for the action parts of the example solutions, and relate these actions to principles in the text. These self‐explanations are guided by accurate monitoring of their own understanding (...) and misunderstanding. Such learning results in example‐independent knowledge and in a better understanding of the principles presented in the text. “Poor” students do not generate sufficient self‐explanations, monitor their learning inaccurately, and subsequently rely heavily on examples. We then discuss the role of self‐explanations in facilitating problem solving, as well as the adequacy of current AI models of explanation‐based learning to account for these psychological findings. (shrink)

This article discusses minimal model explanations, which we argue are distinct from various causal, mechanical, difference-making, and so on, strategies prominent in the philosophical literature. We contend that what accounts for the explanatory power of these models is not that they have certain features in common with real systems. Rather, the models are explanatory because of a story about why a class of systems will all display the same large-scale behavior because the details that distinguish them are irrelevant. This (...) story explains patterns across extremely diverse systems and shows how minimal models can be used to understand real systems. (shrink)

Shapiro and Sober claim that Walsh, Ariew, Lewens, and Matthen give a mistaken, a priori defense of natural selection and drift as epiphenomenal. Contrary to Shapiro and Sober’s claims, we first argue that WALM’s explanatory doctrine does not require a defense of epiphenomenalism. We then defend WALM’s explanatory doctrine by arguing that the explanations provided by the modern genetical theory of natural selection are ‘autonomous-statistical explanations’ analogous to Galton’s explanation of reversion to mediocrity and an explanation of the (...) diffusion ofgases. We then argue that whereas Sober’s theory of forces is an adequate description of Darwin’s theory, WALM’s explanatory doctrine is required to understand how themodern genetical theory of natural selection explains large-scale statistical regularities. 1 Introduction2 Shapiro and Sober’s ‘Epiphenomenalism Do’s and Don’ts’3 WALM’s Explanatory Doctrine4 Galton’s Autonomous-Statistical Explanation5 A Second Example: The Statistical Explanation of the Diffusion of Gases6 Distinguishing Two Theories of Evolution by Natural Selection7 A Possible Objection: Are Statistical Laws Sufficient for Explanation?8 Conclusion. (shrink)

This article focuses on a case that expert practitioners count as an explanation: a mathematical account of Plateau’s laws for soap films. I argue that this example falls into a class of explanations that I call abstract explanations.explanations involve an appeal to a more abstract entity than the state of affairs being explained. I show that the abstract entity need not be causally relevant to the explanandum for its features to be explanatorily relevant. However, it remains unclear (...) how to unify abstract and causal explanations as instances of a single sort of thing. I conclude by examining the implications of the claim that explanations require objective dependence relations. If this claim is accepted, then there are several kinds of objective dependence relations. 1 Introduction2 A Case3 Abstract and Causal Explanations4 Recent Work on Mathematical Explanation5 Explanation and Dependence6 Conclusion. (shrink)

The paper explores how, in economics and biology, theoretical models are used as explanatory devices. It focuses on a modelling strategy by which, instead of starting with an unexplained regularity in the world, the modeller begins by creating a credible model world. The model world exhibits a regularity, induced by a mechanism in that world. The modeller concludes that there may be a part of the real world in which a similar regularity occurs and that, were that the case, the (...) model would offer an explanation. Little concrete guidance is given about where such a regularity might be found. Three modelling exercises in evolutionary game theory—one from economics and two from biology—are used as case studies. Two of these (one from each discipline) exemplify ‘explanation in search of observation’. The third goes a step further, analysing a regularity in a model world and treating it as informative about the real world, but without saying anything about real phenomena. The paper argues that if the relation between the model and real worlds is understood in terms of similarity, and if modelling is understood as an ongoing discovery process rather than as the demonstration of empirical truths, there can be value in creating explanations before finding the regularities that are to be explained. (shrink)

In both cognitive science and philosophy, many theorists have recently appealed to a predictive processing framework to offer explanations of why certain individuals form delusional beliefs. One aim of this essay will be to illustrate how one could plausibly develop a predictive processing account in different ways to account for the onset of different kinds of delusions. However, the second aim of this essay will be to discuss two significant limitations of the predictive processing framework. First, I shall draw (...) on the structure of explanatory why-questions to argue that predictive processing theories can only partially explain the formation of delusional beliefs. Second, I shall argue that predictive processing theories cannot explain how implausible delusional hypotheses are generated. Yet understanding why an agent even generates a delusional hypothesis is a crucial step to understanding why she eventually comes to believe it. The final section of the essay presents three alternative ways the process of hypothesis generation might be functionally divergent in cases of delusional cognition. (shrink)

Nozick analyzes fundamental issues, such as the identity of the self, knowledge and skepticism, free will, the foundations of ethics, and the meaning of life.

The very idea of narrative explanation invites two objections: a methodological objection, stating that narrative structure is too far from the form of a scientific explanation to count as an explanation, and a metaphysical objection, stating that narrative structure situates historical practice too close to the writing of fiction. Both of these objections, however, are illfounded. The methodological objection and the dispute regarding the status of historical explanation can be disposed of by revealing their motivating presupposition: the plausibility of an (...) exclusivist explication of explanation which appeals either to the unity-of-method thesis or some implicit notion of analytic equivalence, both problematic philosophical doctrines. The metaphysical objection fails with the rejection of the idea, in Mink's phrase, of an "untold story." The argument against history as an "untold story" develops from Danto's image of an Ideal Chronicler recording ideal events. A consequence of rejecting this view is that it no longer makes sense to speak of historical narratives as true or false. However, this failure engenders no special problem for assessing the objectivity or explanatory utility of narratives qua explanations. (shrink)

Existing definitions of relevance relations are essentially ambiguous outside the binary case. Hence definitions of probabilistic causality based on relevance relations, as well as probability values based on maximal specificity conditions and homogeneous reference classes are also not uniquely specified. A 'neutral state' account of explanations is provided to avoid the problem, based on an earlier account of aleatory explanations by the author. Further reasons in support of this model are given, focusing on the dynamics of explanation. It (...) is shown that truth in explanation need not entail maximal specificity and that probabilistic explanations should not contain a specification of probability values. (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)

Strong reciprocity has recently been subject to heated debate. In this debate, the “West camp” :231–262, 2011), which is critical of the case for SR, and the “Laland camp” :1512–1516, 2011, Biol Philos 28:719–745, 2013), which is sympathetic to the case of SR, seem to take diametrically opposed positions. The West camp criticizes advocates of SR for conflating proximate and ultimate causation. SR is said to be a proximate mechanism that is put forward by its advocates as an ultimate explanation (...) of human cooperation. The West camp thus accuses advocates of SR for not heeding Mayr’s original distinction between ultimate and proximate causation. The Laland camp praises advocates of SR for revising Mayr’s distinction. Advocates of SR are said to replace Mayr’s uni-directional view on the relation between ultimate and proximate causes by the bi-directional one of reciprocal causation. The paper argues that both the West camp and the Laland camp misrepresent what advocates of SR are up to. The West camp is right that SR is a proximate cause of human cooperation. But rather than putting forward SR as an ultimate explanation, as the West camp argues, advocates of SR believe that SR itself is in need of ultimate explanation. Advocates of SR tend to take gene-culture co-evolutionary theory as the correct meta-theoretical framework for advancing ultimate explanations of SR. Appearances notwithstanding, gene-culture coevolutionary theory does not imply Laland et al.’s notion of reciprocal causation. “Reciprocal causation” suggests that proximate and ultimate causes interact simultaneously, while advocates of SR assume that they interact sequentially. I end by arguing that the best way to understand the debate is by disambiguating Mayr’s ultimate-proximate distinction. I propose to reserve “ultimate” and “proximate” for different sorts of explanations, and to use other terms for distinguishing different kinds of causes and different parts of the total causal chain producing behavior. (shrink)

Recently, there have been several attempts to generalize the counterfactual theory of causal explanations to mathematical explanations. The central idea of these attempts is to use conditionals whose antecedents express a mathematical impossibility. Such countermathematical conditionals are plugged into the explanatory scheme of the counterfactual theory and—so is the hope—capture mathematical explanations. Here, I dash the hope that countermathematical explanations simply parallel counterfactual explanations. In particular, I show that explanations based on countermathematicals are susceptible (...) to three problems counterfactual explanations do not face. These problems seriously challenge the prospects for a counterfactual theory of explanation that is meant to cover mathematical explanations. (shrink)

This paper discusses the constitution relation within the framework of the mechanistic approach to neurobiological explanation. It develops a regularity theory of constitution as an alternative to the manipulationist theory of constitution advocated by some of the proponents of the mechanistic approach. After the main problems of the manipulationist account of constitution have been reviewed, the regularity account is developed based on the notion of a minimal type relevance theory. A minimal type relevance theory expresses a minimally necessary condition of (...) a given type that consists of a disjunction of minimally sufficient conditions of that type. Afterwards, the attained definition is successfully applied in an analysis of the logical structure of the explanation of spatial learning and memory in rats as a paradigm neurobiological explanation. The overall result is a more robust and more precise version of the mechanistic approach to neurobiological explanations. (shrink)

Humean accounts of natural law have long been charged with being unable to account for the laws’ explanatory power in science. One form of this objection is to charge Humean accounts with explanatory circularity: a fact in the Humean mosaic helps to explain why some regularity is a law (first premise), but that law, in turn, helps to explain why that mosaic fact holds (second premise). To this objection, Humeans have replied that the explanation in the first premise is metaphysical (...) whereas the explanation in the second premise is scientific, so (since these two varieties of explanation operate very differently) the two explanations cannot be chained together to yield explanatory circularity. This paper presents a new circularity argument that avoids this objection because both explanations in the premises are metaphysical. The new circularity argument also avoids the objection that the contrasts at the point where the two explanations are chained together fail to line up properly. The upshot is to leave the Humean account of law with two unattractive options: to regard scientific explanation under natural law as not constituting genuine explanation at all or to regard the Humean account as involving a vicious explanatory circularity. (shrink)

To suppose X means to pretend to change one's belief for the sake of the argument to include X. How to do so is a decision problem: of the many ways to modify one's beliefs to include X, one should choose the one that best fits with one's epistemic goals. I examine the role of suppositional reasoning in the evaluation of purported scientific explanations of various sorts, based on Hempel and Oppenheim's deductive-nomological and inductive-statistical explanations. First, I present (...) for each type of explanation the suppositional reasoning conditions it must satisfy. For example, the dipping of blue litmus paper in acid explains why it turned red only if, when one supposes that the litmus paper was not dipped in acid, one must also give up the belief that it turned red. Second, I argue that a specific decision making method should be used to determine how one is to change one's beliefs for the sake of the argument in each case. Third, I evaluate in detail whether purported explanations, both intuitively explanatory and intuitively non-explanatory satisfy these conditions. Fourth, I show that the suppositional reasoning conditions for explanations, when evaluated correctly, systematically solve the many counterexamples to the original Hempel-Oppenheim model. (shrink)

Several writers have argued for the implausibility of there being naturalistic explanations of mystical experience. These writers recognize that the evidential significance of mystical experiences for theism depends upon whether explanations that exclude supernatural agency can be discounted; but they seem unaware of some of the best scientific work done in this area. Part I of the present paper introduces the theory of I. M. Lewis, an anthropologist, and tests it against the case of St Teresa. I use (...) Teresa because of her prominence, and because we have considerable biographical data for her. I conclude that Lewis's approach, suitably supplemented, is strikingly successful in explaining this case. (shrink)

Pseudo‐mechanistic explanations in psychology and cognitive neuroscienceThis paper focuses on the level of systems/cognitive neuroscience. It argues that the great majority of explanations in psychology and cognitive neuroscience is “pseudo‐mechanistic.” On the basis of various case studies, Hommel argues that cognitive neuroscience should move beyond what he calls an “Aristotelian phase” to become a mature “Galilean” science seeking to discover actual mechanisms of cognitive phenomena.

There is a long tradition in philosophy and the social sciences that emphasizes the meaningfulness of human action. This tradition doubts or even negates the possibility of causal explanations of human action precisely on the basis that human actions have meaning. This article provides an argument in favor of methodological naturalism in the social sciences. It grants the main argument of the Interpretivists, that is, that human actions are meaningful, but it shows how a transformation of a "nexus of (...) meaning" into a "causal nexus" can take place, proposing the "successful transformation argument.". (shrink)

A conservation law in physics can be either a constraint on the kinds of interaction there could be or a coincidence of the kinds of interactions there actually are. This is an important, unjustly neglected distinction. Only if a conservation law constrains the possible kinds of interaction can a derivation from it constitute a scientific explanation despite failing to describe the causal/mechanical details behind the result derived. This conception of the relation between “bottom-up” scientific explanations and one kind of (...) “top-down” scientific explanation is motivated by several examples from classical and modern physics. (shrink)

There are lots of arguments for, or justifications of, mathematical theorems that make use of principles from physics. Do any of these constitute explanations? On the one hand, physical principles do not seem like they should be explanatorily relevant; on the other, some particular examples of physical justifications do look explanatory. In this article, I defend the idea that physical justifications can and do explain mathematical facts. 1 Physical Arguments for Mathematical Truths2 Preview3 Mathematical Facts4 Purity5 Doubts about Purity: (...) I6 Doubts about Purity: II7 How Physical Arguments Might Explain: I8 How Physical Arguments Might Explain: II9 Conclusion. (shrink)

It is widely thought that there are limits to how things can perceptually appear to us. For instance, nothing can appear both square and circular, or both pure red and pure blue. Adam Pautz has dubbed such constraints “laws of appearance.” But if the laws of appearance obtain, then what explains them? Here I examine the prospects for an empirical explanation of the laws of appearance. First, I challenge extant empirical explanations that appeal purely to the format of perceptual (...) representation. I then develop a hybrid approach, on which the laws are explained not merely by format, but by two further factors: ecological constraints imposed by our environments, and computational constraints embodied by our perceptual systems. While the hybrid approach implies that the laws of appearance are contingent, I argue that this implication is empirically defensible, since even some of the most intuitively compelling laws have real-world counterexamples. (shrink)

Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the (...) discussion by proposing the etiological stance as a comprehensive approach to identify modifiable causes of illness. (shrink)

Batterman and Rice offer an account of “minimal model explanations” and argue against “common features accounts” of those explanations. This paper offers some objections to their proposals and arguments. It argues that their proposal cannot account for the apparent explanatory asymmetry of minimal model explanations. It argues that their account threatens ultimately to collapse into a “common features account.” Finally, it argues against their motivation for thinking that an explanation appealing to “common features” would have to explain (...) the common features’ own prevalence. (shrink)

Really statistical explanation is a hitherto neglected form of noncausal scientific explanation. Explanations in population biology that appeal to drift are RS explanations. An RS explanation supplies a kind of understanding that a causal explanation of the same result cannot supply. Roughly speaking, an RS explanation shows the result to be mere statistical fallout.