Elliott Sober

A distinction is drawn between property causation and token causation. According to the former, a positive causal factor in a population raises the probability of its effects within "background contexts". The latter, which concerns "actual physical connections" between token events, is not explicated here although its distinctness from the first concept and its importance are discussed. The applicability of both is illustrated by two currently controversial issues in evolutionary theory -- the units of selection controversy and the use of parsimony as an inference rule in phylogenetic reconstruction.

Writers like Attneave [I960], Fodor [I968], and Dennett [1978] have argued that explanations of a mental capacity can only avoid the emptiness of Moliere's dormative virtue by decomposing the capacity into a set of components which are more rudimentary. But What is wrong with smart homunculi? I argue that smart homunculi may explain token events, such as why I now see the page in front of me, but they do not explain what seeing is. It is the importance of the latter explanatory problem which explains why homunculi must be so stupid.

According to information processing models of cognition, such as Chomsky's, the set of well-formed formulae of any natural language must be recursively enumerable (RE), otherwise, human learning language is impossible. I argue that there is nothing unlearnable about languages that are not RE. Insofar as natural languages turn out to be RE, this is to be accounted for on grounds of simplicity and not by appeal to the mistaken claim that nonRE languages are ruled out a priori. A consequence of this position is that grammars will be somewhat depsychologized, and the acquisition of competence will come to be seen as a matter of degree - perhaps admitting of refinement and improvement without end.

Although the justification for using cladistic parsimony to infer phylogenetic trees has been extensively discussed, much less attention has been paid to the use of cladistic parsimony to reconstruct the character states of the ancestral species postulated by an inferred phylogenetic tree. These two problems differ in terms of both their inputs and their outputs, as shown in the following table. In the former, one begins with data on the character states of extant species and tries to find the best supported phylogenetic tree. In the latter, one begins with the tree that is most firmly supported by characteristics C1, C2,... Cn-1; one then takes some new characteristic Cn and records the character states of Cn that attach to the tree’s interior nodes, which represent common ancestors. In both cases, cladistic parsimony solves the problem by finding the hypothesis that requires the fewest changes in character state that are needed to explain the observations.

Ernst Mayr has argued that Darwinian theory discredited essentialist modes of thought and replaced them with what he has called "population thinking". In this paper, I characterize essentialism as embodying a certain conception of how variation in nature is to be explained, and show how this conception was undermined by evolutionary theory. The Darwinian doctrine of evolutionary gradualism makes it impossible to say exactly where one species ends and another begins; such line-drawing problems are often taken to be the decisive reason for thinking that essentialism is untenable. However, according to the view of essentialism I suggest, this familiar objection is not fatal to essentialism. It is rather the essentialist's use of what I call the natural state model for explaining variation which clashes with evolutionary theory. This model implemented the essentialist's requirement that properties of populations be defined in terms of properties of member organisms. Requiring such constituent definitions is reductionistic in spirit; additionally, evolutionary theory shows that such definitions are not available, and, moreover, that they are not needed to legitimize population-level concepts. Population thinking involves the thesis that population concepts may be legitimized by showing their connections with each other, even when they are not reducible to concepts applying at lower levels of organization. In the paper, I develop these points by describing Aristotle's ideas on the origins of biological variation; they are a classic formulation of the natural state model. I also describe how the development of statistical ideas in the 19th century involved an abandoning of the natural state model

Sober [2011] argues that some causal statements are a priori true and that a priori causal truths are central to explanations in the theory of natural selection. Lange and Rosenberg [2011] criticize Sober's argument. They concede that there are a priori causal truths, but maintain that those truths are only ‘minimally causal’. They also argue that explanations that are built around a priori causal truths are not causal explanations, properly speaking. Here we criticize both of Lange and Rosenberg's claims.

To evaluate Hume's thesis that causal claims are always empirical, I consider three kinds of causal statement: ?e1 caused e2 ?, ?e1 promoted e2 ?, and ?e1 would promote e2 ?. Restricting my attention to cases in which ?e1 occurred? and ?e2 occurred? are both empirical, I argue that Hume was right about the first two, but wrong about the third. Standard causal models of natural selection that have this third form are a priori mathematical truths. Some are obvious, others less so. Empirical work on natural selection takes the form of defending causal claims of the first two types. I provide biological examples that illustrate differences among these three kinds of causal claim

What thesis is Hume trying to establish in his essay “On Miracles” and does he succeed? John Earman’s answer to the latter question is clearly conveyed by the title of his new book. Earman uses a Bayesian representation of the problem to make his case. For Earman, this mode of analysis is both perspicuous and nonanachronistic, in that probability reasoning was central to the 18th century debate about miracles in particular and testimony in general. Indeed, one of Hume’s most interesting antagonists, Richard Price, was the person to whom Thomas Bayes entrusted his now-famous essay for posthumous publication. For Earman, Price is the proper Bayesian, while Hume’s essay provides only “rhetoric and schein geld”. Earman’s tone is consistently prosecutorial and sometimes snide; he says that his animus is not so much against Hume himself as against those who smugly invoke Hume’s essay as definitively settling the matter. This tone should not deter potential readers who are convinced that Hume’s essay contains something of value. Earman’s book is interesting and provocative in multiple ways—it places Hume’s essay in its historical setting, it offers an insightful close reading of the text, and it shows how the resources of Bayesianism can be powerfully put to work. Besides Earman’s own essay, the volume also contains Hume’s essay and relevant work by others, including Locke, Spinoza, Samuel Clarke, Price, Laplace, and Babbage. The book would be an excellent choice for an advanced undergraduate or graduate seminar.

The examples and concepts that Shoemaker cites are rather heterogeneous. Some distinctions need to be drawn. An optimality thesis involves not just an ordering of options, but a value judgment about them. So let us begin by distinguishing minimality from optimality. And the concept of minimality can play a variety of roles, among which I distinguish between extremum descriptions, statements hypothesizing an optimizing process, and methodological recommendations. Finally, I consider how the three categories relate to Shoemaker’s question that “Who is optimizing: the scientist or nature?”

In our essay ‘What’s Historical About Historical Materialism?’, we drew two contrasts between the Darwinian theory of evolution (ET) and the Marxist theory of historical materialism (HM).1 We described the former as a ‘micro-theory’ and the latter as a ‘macro-theory’. We also argued that, in Darwinian theory, evolution is driven by exogenous forces, specifically, by natural selection induced by environmental factors; whereas historical materialism sees the transformation of a society from feudalism to capitalism and then to socialism as a consequence of an endogenous process, involving ‘contradictions’ between forces and relations of production and class struggle. Nolan has taken issue with both of these contrasts; his view is that the two theories are more similar than our account allows.

Akaike's framework for thinking about model selection in terms of the goal of predictive accuracy and his criterion for model selection have important philosophical implications. Scientists often test models whose truth values they already know, and they often decline to reject models that they know full well are false. Instrumentalism helps explain this pervasive feature of scientific practice, and Akaike's framework helps provide instrumentalism with the epistemology it needs. Akaike's criterion for model selection also throws light on the role of parsimony considerations in hypothesis evaluation. I explain the basic ideas behind Akaike's framework and criterion; several biological examples, including the use of maximum likelihood methods in phylogenetic inference, are considered.

John Beatty (1995) and Alexander Rosenberg (1994) have argued against the claim that there are laws in biology. Beatty's main reason is that evolution is a process full of contingency, but he also takes the existence of relative significance controversies in biology and the popularity of pluralistic approaches to a variety of evolutionary questions to be evidence for biology's lawlessness. Rosenberg's main argument appeals to the idea that biological properties supervene on large numbers of physical properties, but he also develops case studies of biological controversies to defend his thesis that biology is best understood as an instrumental discipline. The present paper assesses their arguments.

Several evolutionary biologists have used a parsimony argument to argue that the single gene is the unit of selection. Since all evolution by natural selection can be represented in terms of selection coefficients attaching to single genes, it is, they say, "more parsimonious" to think that all selection is selection for or against single genes. We examine the limitations of this genic point of view, and then relate our criticisms to a broader view of the role of causal concepts and the dangers of reification in science

Altruism has both an evolutionary and a psychological meaning. As the term is used in evolutionary theory, a trait is deemed altruistic if it reduces the fitness of the actor and enhances the fitness of someone else. In its psychological sense, the thesis that we have altruistic ultimate motives asserts that we care about the welfare of others, not just as a means of enhancing our own well-being, but as an end in itself. In Unto Others (hereafter UO), we consider both evolutionary altruism (Part I) and psychological altruism (Part II) from an evolutionary perspective. We propose a multilevel selection theory to explain how altruism can evolve from group selection, based on Darwin’s solution to the problem. Our presentation of multilevel selection theory expands the range of topics beyond altruism in other respects as well. In Part I1 of UO, we evaluate the arguments, both conceptual and empirical, that philosophers and psychologists have advanced in an attempt to choose between psychological egoism and motivational pluralism. We conclude that these arguments are inconclusive.

The hypothesis of group selection fell victim to a seemingly devastating critique in 1960s evolutionary biology. In Unto Others (1998), we argue to the contrary, that group selection is a conceptually coherent and empirically well documented cause of evolution. We suggest, in addition, that it has been especially important in human evolution. In the second part of Unto Others, we consider the issue of psychological egoism and altruism -- do human beings have ultimate motives concerning the well-being of others? We argue that previous psychological and philosophical work on this question has been inconclusive. We propose an evolutionary argument for the claim that human beings have altruistic ultimate motives.

Developing a definition of group selection, and applying that definition to the dispute in the social sciences between methodological holists and methodological individualists, are the two goals of this paper. The definition proposed distinguishes between changes in groups that are due to group selection and changes in groups that are artefacts of selection processes occurring at lower levels of organization. It also explains why the existence of group selection is not implied by the mere fact that fitness values of organisms are sensitive to the composition of groups. And, lastly, the definition explains why group selection need not involve selection for altruism. Group selection is thereby seen as an evolutionary force which is objectively distinct from other evolutionary forces. Applying the distinction between group and individual selection to the holism/individualism dispute has the desirable result that the dispute is not decidable a priori. This way of looking at the dispute yields a conception of individualism which is untainted by atomism and a conception of holism which is unspoiled by hypostatis.

How could the fundamental mental operations which facilitate scientific theorizing be the product of natural selection, since it appears that such theoretical methods were neither used nor useful "in the cave"-i.e., in the sequence of environments in which selection took place? And if these wired-in information processing techniques were not selected for, how can we view rationality as an adaptation? It will be the purpose of this paper to address such questions as these, and in the process to sketch some of the considerations that an evolutionary account of rationality may involve. By describing the broad framework within which the evolution of rationality may eventually be understood, I hope to undermine the idea that evolutionary theory is somehow incapable of dealing with this characteristic and requires supplementation by some novel principle. A more modest ambition of the paper is to try to provoke those who think that there are special problems involved in this evolutionary inquiry to say what these problems are.

Parsimony arguments are advanced in both science and philosophy. How are they related? This question is a test case for Naturalismp, which is the thesis that philosophical theories and scientific theories should be evaluated by the same criteria. In this paper, I describe the justifications that attach to two types of parsimony argument in science. In the first, parsimony is a surrogate for likelihood. In the second, parsimony is relevant to estimating how accurately a model will predict new data when fitted to old. I then consider how these two justifications apply to parsimony arguments in philosophy concerning theism and atheism, the mind/body problem, ethical realism, the question of whether mental properties are causally efficacious, and nominalism versus Platonism about numbers

Charles Stein discovered a paradox in 1955 that many statisticians think is of fundamental importance. Here we explore its philosophical implications. We outline the nature of Stein’s result and of subsequent work on shrinkage estimators; then we describe how these results are related to Bayesianism and to model selection criteria like AIC. We also discuss their bearing on scientific realism and instrumentalism. We argue that results concerning shrinkage estimators underwrite a surprising form of holistic pragmatism.

Russell (1948), Reichenbach (1956), and Salmon (1975, 1979) have argued that a fundamental principle of science and common sense is that "matching" events should not be chalked up to coincidence, but should be explained by postulating a common cause. Reichenbach and Salmon provided this intuitive idea with a probabilistic formulation, which Salmon used to argue for a version of scientific realism. Van Fraassen (1980, 1982) showed that the principle, so construed, runs afoul of certain results in quantum mechanics. In this paper a new formulation of the principle is offered that emerges from its use in evolutionary theory. This characterization identifies fairly general conditions in which postulating common causes will be more explanatory than postulating separate causes

Reconstructing the Past seeks to clarify and help resolve the vexing methodological issues that arise when biologists try to answer such questions as whether human beings are more closely related to chimps than they are to gorillas. It explores the case for considering the philosophical idea of simplicity/parsimony as a useful principle for evaluating taxonomic theories of evolutionary relationships. For the past two decades, evolutionists have been vigorously debating the appropriate methods that should be used in systematics, the field that aims at reconstructing phylogenetic relationships among species. This debate over phylogenetic inference, Elliott Sober observes, raises broader questions of hypothesis testing and theory evaluation that run head on into long standing issues concerning simplicity/parsimony in the philosophy of science. Sober treats the problem of phylogenetic inference as a detailed case study in which the philosophical idea of simplicity/parsimony can be tested as a principle of theory evaluation. Bringing together philosophy and biology, as well as statistics, Sober builds a general framework for understanding the circumstances in which parsimony makes sense as a tool of phylogenetic inference. Along the way he provides a detailed critique of parsimony in the biological literature, exploring the strengths and limitations of both statistical and nonstatistical cladistic arguments.