Account Of Scientific Explanation Research Articles

How to Reconcile a Unified Account of Explanation with Explanatory Diversity

The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma (Pincock in: Reutlinger A, Saatsi J (eds) Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). Either there is nothing that unifies all instances of scientific explanation that makes them count as explanations, or there is some set of unifying features, which seems incompatible with explanatory pluralism. Different philosophers have adopted different horns of this dilemma. Some argue that no unified account of explanation is possible (Morrison in Reconstructing reality, Oxford University Press, Oxford, 2015). Others suggest that there is a set of necessary features that can unify all explanations under a single account (Potochnik in Idealization and the aims of science, Chicago University Press, Chicago, 2017; Reutlinger in Reutlinger A, Saatsi J (eds) Explanation beyond causation, Oxford University Press, Oxford, pp 74–95, 2018; Strevens in Depth: an account of scientific explanation, Harvard University Press, Cambridge, 2008). In this paper, we argue that none of the features identified by existing accounts of explanation are necessary for all explanations. However, we argue that a unified account can still be provided that accommodates pluralism. This can be accomplished, we argue, by reconceiving of scientific explanation as a cluster concept: there are multiple subsets of features that are sufficient for providing an explanation, but no single feature is necessary for all explanations. Reconceiving of explanation as a cluster concept not only accounts for the diversity of kinds of explanations, but also accounts for the widespread disagreement in the explanation literature and enables explanatory pluralism to avoid Pincock’s dilemma.

Possibilist Explanation: Explaining How-Possibly Through Laws

‘Possibilist Explanation’ is a promising account of scientific explanation which avoids the familiar problems of “how-possibly explanations”. It explains an event by showing how-actually it was epistemically possible, instead of why it was epistemically necessary. Its explanandum is the epistemic possibility of an actual event previously considered epistemically impossible. To define PE, two new concepts are introduced: ‘permissive condition’ and ‘possibilist law’. A permissive condition for an event is something that does not entail the event itself, but a necessary condition for it. A ‘Possibilist Law’ is a kind of scientific law that predicts that in the absence of a necessary condition N, the event E is not possible. Both PE and PL are legitimate and neglected parts of scientific knowledge and are especially suitable for human sciences.

Explanatory schema and the process of model building

In this paper, we argue that rather than exclusively focusing on trying to determine if an idealized model fits a particular account of scientific explanation, philosophers of science should also work on directly analyzing various explanatory schemas that reveal the steps and justification involved in scientists’ use of highly idealized models to formulate explanations. We develop our alternative methodology by analyzing historically important cases of idealized statistical modeling that use a three-step explanatory schema involving idealization, mathematical operation, and explanatory interpretation.

The Pythagorean table of opposites, symbolic classification, and Aristotle.

At Metaphysics A 5 986a22-b2, Aristotle refers to a Pythagorean table, with two columns of paired opposites. I argue that 1) although Burkert and Zhmud have argued otherwise, there is sufficient textual evidence to indicate that the table, or one much like it, is indeed of Pythagorean origin; 2) research in structural anthropology indicates that the tables are a formalization of arrays of "symbolic classification" which express a pre-scientific world view with social and ethical implications, according to which the presence of a principle on one column of the table will carry with it another principle within the same column; 3) a close analysis of Aristotle's arguments shows that he thought that the table expresses real causal relationships; and 4) Aristotle faults the table of opposites with positing its principles as having universal application and with not distinguishing between those principles that are causally prior and those that are posterior. Aristotle's account of scientific explanation and his own explanations that he developed in accordance with this account are in part the result of his critical encounter with this prescientific Pythagorean table.

Collaborative explanation and biological mechanisms

This paper motivates and outlines a new account of scientific explanation, which I term ‘collaborative explanation.’ My approach is pluralist: I do not claim that all scientific explanations are collaborative, but only that some important scientific explanations are—notably those of complex organic processes like development. Collaborative explanation is closely related to what philosophers of biology term ‘mechanistic explanation’ (e.g., Machamer et al., Craver, 2007). I begin with minimal conditions for mechanisms: complexity, causality, and multilevel structure. Different accounts of mechanistic explanation interpret and prioritize these conditions in different ways. This framework reveals two distinct varieties of mechanistic explanation: causal and constitutive. The two have heretofore been conflated, with philosophical discussion focusing on the former. This paper addresses the imbalance, using a case study of modeling practices in Systems Biology to reveals key features of constitutive mechanistic explanation. I then propose an analysis of this variety of mechanistic explanation, in terms of collaborative concepts, and sketch the outlines of a general theory of collaborative explanation. I conclude with some reflections on the connection between this variety of explanation and social aspects of scientific practice.

Makes a Difference

Michael Strevens has produced an ambitious and comprehensive new account of scientific explanation. This review discusses its main themes, focusing on regularity explanation and a number of methodological concerns.

Michael Strevens. Depth: An Account of Scientific Explanation

Michael Strevens’ Depth: An Account of Scientific Explanation is an impressive recent contribution to the philosophical literature on explanation. While clearly influenced by several of the leading theories of the later twentieth century, Strevens’ account of explanation is firmly rooted in the causal tradition. His most notable intellectual debts in this regard owe to David Lewis, Wesley Salmon and James Woodward. Still, Strevens sees the work of these theorists as flawed in important respects, and his “kairetic account” of explanation is meant to provide answers to problems his predecessors left unresolved (or poorly resolved, as the case may be). Before examining Strevens’ account in detail we should identify the more significant of these problems and briefly survey the contexts in which they arose.

Depth: an account of scientific explanation

* List of Figures* and Table** * Preface * Part I. The Causal Approach to Explanation *1. Approaches to Explanation *1.1 Causal Explanation and Explanatory Relevance *1.2 Preliminaries *1.3 Accounts of the Explanatory Relation *1.4 The Causal Element in Explanation *1.5 The Pursuit of Explanation *2. Causal and Explanatory Relevance *2.1 The Minimal Causal Account of Event Explanation *2.2 The Problem of Relevance *2.3 The Probabilistic Solution *2.4 The Counterfactual Solution *2.5 The Manipulationist Solution * Part II. The Kairetic Account of Explanation *3. The Kairetic Account of Difference-Making *3.1 Overview of the Kairetic Account *3.2 Causal Models *3.3 States of Affairs *3.4 The Eliminative Procedure *3.5 Abstraction and Optimizing *3.6 Cohesion *3.7 The Optimizing Procedure *3.8 Rival Accounts of Difference-Making Reconsidered *4. The Kairetic Account of Explanation *4.1 Standalone Explanation *4.2 Difference-Making and Transitivity in Compound Explanations *4.3 Comparing Standalone Explanations *4.4 Laplacean Blindness *5. Extending the Kairetic Account *5.1 Quantifying Explanatory Relevance *5.2 Trading Off Accuracy for Generality *5.3 The Explanatory Framework *5.4 Black Boxes, Functional Properties, and Multiple Realizability *5.5 Aggregative Explanation *5.6 Contrastive Explanation *5.7 Beyond Causal Explanation *6. Event Explanation and Causal Claims *6.1 Background Conditions versus Causes *6.2 Preemption *6.3 Nonevents as Difference-Makers *6.4 Nonevents as Explananda *6.5 Transitivity *6.6 Three Kinds of Causation * Part III. Explanation of Laws and Regularities *7. Regularity Explanation *7.1 Approaches to Regularity Explanation *7.2 Explaining Laws with Mechanisms *7.3 Basing Generalizations *7.4 Property Laws *7.5 Other Laws *7.6 The Metaphysics of High and Low *8. Abstraction in Regularity Explanation *8.1 Problems of Abstraction in Regularity Explanation *8.2 Explaining Boyle's Law *8.3 A Theory of Idealization *8.4 Mathematically Driven Explanation * Part IV. Probabilistic Explanation *9. Approaches to Probabilistic Explanation *9.1 Explanatory Questions *9.2 Varieties of Probabilistic Explanation: Examples *9.3 Varieties of Probabilistic Explanation: Commentary *9.4 Accounts of Probabilistic Explanation *9.5 Elitism versus Egalitarianism *9.6 Probability and Determinism *9.7 Formal Elements of the Kairetic Approach *10. Kairetic Explanation of Frequencies *10.1 Probabilistic Explanation in Deterministic Systems *10.2 Explanation with Complex Probability *10.3 Explanation with Quasiprobability *10.4 Elitism versus Egalitarianism the Kairetic Way *10.5 Regularity Explanation and Probabilistic Metaphysics *11. Kairetic Explanation of Single Outcomes *11.1 Single Outcome Explanation *11.2 Robustness *11.3 Nonexplanatory Probability-Raisers *11.4 Nonexplanatory Critical Events *11.5 Elitism and Egalitarianism Revisited * Part V. Valediction *12. Looking Outward *12.1 Biology: Probabilistic Explanation *12.2 Psychology: Content and Explanation *12.3 Economics: Abstraction *12.4 Explanatory Autonomy *13. Looking Inward * Notes * References * Index ** Figures *2.1 The counterfactual and manipulationist tests for difference-making contrasted *3.1 A compound causal model for a window's breaking *4.1 A compound standalone explanation *4.2 Intensification: inserting an intermediate setup *4.3 The structure of a hybrid causal model *6.1 A single event as both a backup cause and an actual cause *7.1 A bridge diagram for interlevel explanation *9.1 Examples of probabilistic causal models *10.1 An evolution function for a simple wheel of fortune *10.2 A probability density function over initial conditions *10.3 The frequency produced by a microconstant evolution function is equal to the strike ratio, provided that the initial-condition density is macroperiodic *10.4 A nonmacroperiodic initial-condition density over a microconstant evolution function may produce a frequency that differs from the strike ratio *10.5 An evolution function with imperfect microconstancy *11.1 A probabilistic model for a bombing death expanded to show all probabilistic outcomes *11.2 An alternative expanded probabilistic model for a bomb-related death *11.3 A typical microconstant explanation of a long-run frequency expanded to show the probabilistic derivation's route through the macroperiodicity of the actual initial-condition distribution *** Table *9.1 Positions in the elitism/egalitarianism debate

Reduction: the Cheshire cat problem and a return to roots

In this paper, I propose two theses, and then examine what the consequences of those theses are for discussions of reduction and emergence. The first thesis is that what have traditionally been seen as robust, reductions of one theory or one branch of science by another more fundamental one are a largely a myth. Although there are such reductions in the physical sciences, they are quite rare, and depend on special requirements. In the biological sciences, these prima facie sweeping reductions fade away, like the body of the famous Cheshire cat, leaving only a smile. ... The second thesis is that the “smiles” are fragmentary patchy explanations, and though patchy and fragmentary, they are very important, potentially Nobel-prize winning advances. To get the best grasp of these “smiles,” I want to argue that, we need to return to the roots of discussions and analyses of scientific explanation more generally, and not focus mainly on reduction models, though three conditions based on earlier reduction models are retained in the present analysis. I briefly review the scientific explanation literature as it relates to reduction, and then offer my account of explanation. The account of scientific explanation I present is one I have discussed before, but in this paper I try to simplify it, and characterize it as involving field elements (FE) and a preferred causal model system (PCMS) abbreviated as FE and PCMS. In an important sense, this FE and PCMS analysis locates an “explanation” in a typical scientific research article. This FE and PCMS account is illustrated using a recent set of neurogenetic papers on two kinds of worm foraging behaviors: solitary and social feeding. One of the preferred model systems from a 2002 Nature article in this set is used to exemplify the FE and PCMS analysis, which is shown to have both reductive and nonreductive aspects. The paper closes with a brief discussion of how this FE and PCMS approach differs from and is congruent with Bickle’s “ruthless reductionism” and the recently revived mechanistic philosophy of science of Machamer, Darden, and Craver.

Comment on Professor Jeffner's Paper

By far the most common term in Professor Jeffner's paper is ‘understanding’, and it is clearly with understanding that he is primarily concerned. However, at the beginning of his paper he talks of understanding and explanation, and at least in the case of his third kind of reality he clearly sees understanding and explanation as intimately related. In this he is surely right. I myself would say that understanding is cognizing a manifold as a single whole in all its internal relationships, and this ties up with what Jeffner has to say about Gestalts on pp. 220–221. And explanation, as I hope to show, depends upon or presupposes the understanding that flows from the possession of a Gestalt. However, Jeffner adopts Hempel and Oppenheim's deductivist account of scientific explanation, and I believe this account to be fundamentally mistaken, and to have serious consequences for his argument. One does not achieve explanation merely by finding a set of empirically true premises from which a proposition expressing the explanandum can be deduced – if that were so one would explain Socrates' mortality by pointing out that everything snub-nosed is mortal, and that Socrates was snub-nosed. It is interesting, in this respect, to compare Hempel's account of explanation with that of Aristotle. There are substantial similarities between the two accounts, but there is one fundamental difference. Hempel insists that there can be no explanation unless events are connected in some way, and so rejects, for example, a mere sequential narrative as constituting an explanation.

Toulmin on Ideals of Natural Order

In this paper I criticize Toulmin's concept of ‘Ideals of Natural Order’ and his account of the role these ‘Ideals’ play in scientific explanation as given in his book, Foresight and Understanding. I argue that Toulmin's account of ‘Ideals of Natural Order’ as those theories taken to be self evident by scientists at a given time introduces an undesirable subjectivism into his account of scientific explanation. I argue also that the history of science, especially the recent history of microphysics, does not support Toulmin's contentions about the supposed self-evidence of the basic explanatory theories in science.