An account of scientific explanation is presented according to which (1) scientific explanation consists in solving “insight” problems (Metcalfe and Wiebe 1984) and (2) understanding is the result of solving such problems. The theory is pragmatic; it draws upon van Fraassen’s (1977, 1980) insights, avoids the objections to pragmatic accounts offered by Kitcher and Salmon (1987), and relates scientific explanation directly to understanding. The theory also accommodates cases of explanatory asymmetry and intuitively legitimate rejections of explanation requests.

I argue that 'c' occurs extensionally in 'c caused e' and 'D' occurs extensionally in 'c caused e because c is D'. I claim that this has been insufficiently appreciated because the two contexts are often run together and because it has not been clear that the description D of c is among the referents of an explanatory argument. I argue as well that Hume's analysis of causation is consistent with taking causation to be a relation between single events, and (...) that even if events are eliminated as virtual entities, extensionality holds for all terms in the resulting context. (shrink)

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

Ceteris-paribus clauses are nothing to worry about; aceteris-paribus qualifier is not poisonously indeterminate in meaning. Ceteris-paribus laws teach us that a law need not be associated straightforwardly with a regularity in the manner demanded by regularity analyses of law and analyses of laws as relations among universals. This lesson enables us to understand the sense in which the laws of nature would have been no different under various counterfactual suppositions — a feature even of those laws that involve no ceteris-paribus (...) qualification and are actually associated with exceptionless regularities. Ceteris-paribus generalizations of an‘inexact science’ qualify as laws of that science in virtue of their distinctive relation to counterfactuals: they form a set that is stable for the purposes of that field. (Though an accident may possess tremendous resilience under counterfactual suppositions, the laws are sharply distinguished from the accidents in that the laws are collectively as resilient as they could logically possibly be.) The stability of an inexact science's laws may involve their remaining reliable even under certain counterfactual suppositions violating fundamental laws of physics. The ceteris-paribus laws of an inexact science may thus possess a kind of necessity lacking in the fundamental laws of physics. A nomological explanation supplied by an inexact science would then be irreducible to an explanation of the same phenomenon at the level of fundamental physics. Island biogeography is used to illustrate how a special science could be autonomous in this manner. (shrink)

Unlike explanation in science, explanation in mathematics has received relatively scant attention from philosophers. Whereas there are canonical examples of scientific explanations, there are few examples that have become widely accepted as exhibiting the distinction between mathematical proofs that explain why some mathematical theorem holds and proofs that merely prove that the theorem holds without revealing the reason why it holds. This essay offers some examples of proofs that mathematicians have considered explanatory, and it argues that these examples suggest a (...) particular account of explanation in mathematics. The essay compares its account to Steiner's and Kitcher's. Among the topics that arise are proofs that exploit symmetries, mathematical coincidences, brute-force proofs, simplicity in mathematics, merely clever proofs, and proofs that unify what other proofs treat as separate cases. (shrink)

An acceptable empiricist account of laws of nature would havesignificant implications for a number of philosophical projects. For example, such an account may vitiate argumentsthat the fundamental constants of nature are divinelydesigned so that laws produce a life permittinguniverse. On an empiricist account, laws do not produce the universe but are designed by us to systematize theevents of a universe which does in fact contain life; so any ``fine tuning'' of natural law has a naturalistic explanation.But there are problems for (...) the empiricist project. This paper develops a ``perspectival'' version of the Humean bestsystem approach and argues that this version solves the standard problems faced by the empiricist project.Furthermore, the paper argues, this version is best able to answer the proponents of divine design while leaving scientificlaw a suitably objective matter.[I]t is possible tocondense the enormous mass of results to a large extent – that is to find laws which summarize...Richard Feynman It has become fashionable in some circles to argue thatscience is ultimately a sham, that we scientists read order into nature, not out of nature, and that the laws of physicsare our laws, not nature's. I believe this is arrant nonsense. You would be hard-pressed to convince a physicist thatNewton's inverse square law of gravitation is a purely cultural concoction. The laws of physics, I submit, reallyexist in the world out there, and the job of the scientist is to uncover them, not invent them. True, at any giventime, the laws you find in the textbooks are tentative and approximate, but they mirror, albeit imperfectly, a reallyexisting order in the physical world. Of course, many scientists do not recognize that in accepting the reality of anorder in nature-the existence of laws `out there' – they are adopting a theological world view. P. C. W. Davies. (shrink)

In place of earlier instrumentalist and phenomenalist interpretations of science both Quine and Sellars have developed highly influential realist positions centering around the doctrine that accepting a theory as explanatory and irreducible rationally entails accepting the entities posited by the theory. A growing reaction against this realism is partially based on perceived inadequacies in the doctrines of Quine and Sellars, but even more on reconstructions of scientific explanations which do not involve such ontic commitments. Three types of anti-realistic positions are (...) considered and criticized. Hesse's neo-Duhemian position couples a statistical theory of inference to a downgrading of purely theoretical statements. Sneed uses the method of axiomatrization through set-theoretic predicates to supply a reconstruction of Kuhn's account of scientific development. Here Ramsey-reduction sentences serve to eliminate purely theoretical terms. The longest section deals with van Fraassen's semantic model based on a state-space representation of scientific theories and the use of this model in interpreting quantum mechanics. It is argued that the model is valuable, but that the anti-realist interpretation accorded it is not justified and entails serious inconsistencies. (shrink)

John Stuart Mill regards economics as an inexact and separate science which employs a deductive method. This paper analyzes and restates Mill's views and considers whether they help one to understand philosophical peculiarities of contemporary microeconomic theory. The author concludes that it is philosophically enlightening to interpret microeconomics as an inexact and separate science, but that Mill's notion of a deductive method has only a little to contribute.

In the general problem of verisimilitude, we try to define the distance of a statement from a target, which is an informative truth about some domain of investigation. For example, the target can be a state description, a structure description, or a constituent of a first-order language. In the problem of legisimilitude, the target is a deterministic or universal law, which can be expressed by a nomic constituent or a quantitative function involving the operators of physical necessity and possibility. The (...) special case of legisimilitude, where the target is a probabilistic law, has been discussed by Roger Rosenkrantz and Ilkka Niiniluoto. Their basic proposal is to measure the distance between two probabilistic laws by the Kullback–Leibler notion of divergence, which is a semimetric on the space of probability measures. This idea can be applied to probabilistic laws of coexistence and laws of succession, and the examples may involve discrete or continuous state spaces. In this paper, these earlier studies are elaborated in four directions. First, even though deterministic laws are limiting cases of probabilistic laws, the target-sensitivity of truthlikeness measures implies that the legisimilitude of probabilistic laws is not easily reducible to the deterministic case. Secondly, the Jensen-Shannon divergence is applied to mixed probabilistic laws which entail some universal laws. Thirdly, a new class of distance measures between probability distributions is proposed, so that their horizontal differences are taken into account in addition to vertical ones. Fourthly, a solution is given for the epistemic problem of estimating degrees of probabilistic legisimilitude on the basis of empirical evidence. (shrink)

Three competing ‘methods’ have been endorsed for inferring phylogenetic hypotheses: parsimony, likelihood, and Bayesianism. The latter two have been claimed superior because they take into account rates of sequence substitution. Can rates of substitution be justified on its own accord in inferences of explanatory hypotheses? Answering this question requires addressing four issues: (1) the aim of scientific inquiry, (2) the nature of why-questions, (3) explanatory hypotheses as answers to why-questions, and (4) acknowledging that neither parsimony, likelihood, nor Bayesianism are inferential (...) actions leading to explanatory hypotheses. The aim of scientific inquiry is to acquire causal understanding of effects. Observation statements of organismal characters lead to implicit or explicit why-questions. Those questions, conveyed in data matrices, assume the truth of observation statements, which is contrary to subsequently invoking substitution rates within inferences to phylogenetic hypotheses. Inferences of explanatory hypotheses are abductive in form, such that some version of an evolutionary theory(ies) is/are included or implied. If rates of sequence evolution are to be considered, it must be done prior to, rather than within abduction, which requires renaming those putatively-shared nucleotides subject to substitution rates. There are, however, no epistemic grounds for renaming characters to accommodate rates, calling into question the legitimacy of causally accounting for sequence data. (shrink)

This book examines the philosophical conception of abductive reasoning as developed by Charles S. Peirce, the founder of American pragmatism. It explores the historical and systematic connections of Peirce's original ideas and debates about their interpretations. Abduction is understood in a broad sense which covers the discovery and pursuit of hypotheses and inference to the best explanation. The analysis presents fresh insights into this notion of reasoning, which derives from effects to causes or from surprising observations to explanatory theories. The (...) author outlines some logical and AI approaches to abduction as well as studies various kinds of inverse problems in astronomy, physics, medicine, biology, and human sciences to provide examples of retroductions and abductions. The discussion covers also everyday examples with the implication of this notion in detective stories, one of Peirce’s own favorite themes. The author uses Bayesian probabilities to argue that explanatory abduction is a method of confirmation. He uses his own account of truth approximation to reformulate abduction as inference which leads to the truthlikeness of its conclusion. This allows a powerful abductive defense of scientific realism. This up-to-date survey and defense of the Peircean view of abduction may very well help researchers, students, and philosophers better understand the logic of truth-seeking. (shrink)

This paper attempts to clarify the meaning and significance of "qualitative confirmation". The need to do so is related to the fact that, without such a conceptualization, a large portion of the human sciences are relegated to a less than scientific status. Accordingly, "qualitative confirmation" is viewed as a proper subset of traditional confirmation theory. To establish such a case, a general Hempelian framework is utilized, but it is supplemented with two additional levels of confirmation. It is concluded that the (...) final test for adequacy of such confirmation must rest on a subjective probability notion. (shrink)

The question of whether or not to partition data for the purposes of inferring phylogenetic hypotheses remains controversial. Opinions have been especially divided since Kluge's (1989, Systematic Zoology 38, 7–25) claim that data partitioning violates the requirement of total evidence (RTE). Unfortunately, advocacy for or against the RTE has not been based on accurate portrayals of the requirement. The RTE is a basic maxim for non-deductive inference, stipulating that evidence must be considered if it has relevance to an inference. Evidence (...) is relevant if it has a positive or negative effect on a given conclusion. In the case of ℈partitioned’ phylogenetic inferences, the RTE is violated, and the basis for rational belief in any conclusion is compromised, unless it is shown that the partitions are evidentially irrelevant to one another. The goal of phylogenetic systematics is to hypothesize past causal conditions to account for observed shared similarities among two or more species. Such inferences are non-deductive, necessitating consideration of the RTE. Some phylogeneticists claim the parsimony criterion as justification for the RTE. There is no relation between the two – parsimony is a relation between a hypothesis and causal question(s). Parsimony does not dictate the content of premises prior to an inference. ℈Taxonomic congruence,’ ℈supertrees,’ and ℈conditional combination’ methods violate the RTE. Taxonomic congruence and supertree methods also fail to achieve the intended goal of phylogenetic inference, such that ℈consensus trees’ and ℈supertrees’ lack an empirical basis. ℈Conditional combination’ is problematic because hypotheses derived from partitioned data cannot be compared – a causal hypothesis inferred to account for a set of effects only has relevance to those effects, not any comparative relevance to other causal hypotheses. A similar problem arises in the comparisons of hypotheses derived from different causal theories. (shrink)

Attention is drawn to two closely related functions served by scientific theory which are of fundamental importance in physical science but as yet little discussed in philosophy. As indicated by their names, they constitute the theoretical basis of physical measurements. After analysing some historically important examples and sketching the historical development of these ideas, this paper examines the similarities and differences between the estimate functions of theory and such well-known functions as prediction and explanation. The pervasiveness of the estimative functions (...) even when theory is but poorly developed is noted; and some of the problems raised by the physical equivalence of the measuring instrument to the object measured are discussed. The relations of estimation to ‘reductive logic’ are also considered. We then apply this understanding of estimative functioning to distinguishing experimental errors from those genuine anomalies which result in discovery. It is also shown that there can be no facts established nor any verification of predictions except on the basis of valid estimates derived, in turn, from antecedently accepted theories. (shrink)

Here we enrich Paul Weirich’s thesis holding that a simulation model can create knowledge in the form of causal explanations. We sustain the validity of exporting results from the model to the modelized world in virtue of the similarity between model and world, which is analyzable in terms of partial identity of structure, eliminating the superficial similarity that repeats empirical results by adjusting data via calibration. The structure of relations rescues from the world critical results to analyze such similarity, as (...) so certain properties which condition the kind of relations held between the elements of the model representing entities of the world. (shrink)

Logic and philosophy of science share a long history, though contacts have gone through ups and downs. This paper is a brief survey of some major themes in logical studies of empirical theories, including links to computer science and current studies of rational agency. The survey has no new results: we just try to make some things into common knowledge.