Elliott Sober

In 'Two Dogmas of Empiricism', Quine attacks the analytic/synthetic distinction and defends a doctrine that I call epistemological holism. Now, almost fifty years after the article's appearance, what are we to make of these ideas? I suggest that the philosophical naturalism that Quine did so much to promote should lead us to reject Quine's brief against the analytic/synthetic distinction; I also argue that Quine misunderstood Carnap's views on analyticity. As for epistemological holism, I claim that this thesis does not follow from the logical point that Duhem and Quine made about the role of auxiliary assumptions in hypothesis testing, and that the thesis should be rejected. \\\ [Peter Hylton] Section I of this essay discusses Quine's views about reference, contrasting them with those of Russell. For the latter, our language and thought succeed in being about the world because of our acquaintance with objects; the relation of reference-roughly, the relation between a name and its bearer-is thus fundamental. For Quine, by contrast, the fundamental relation by which our language comes to be about the world, and to have empirical content, is that between a sentence and stimulations of our sensory surfaces; reference, while important, is a derivative notion. Section II shows how this view of reference as derivative makes possible the notorious Quinean doctrine of ontological relativity. Section III raises the issue of realism. It argues that somewhat different notions of realism are in play for Quine and for Russell-for Russell, objects, and our knowledge of objects, play the fundamental role, while for quine objectivity and truth are fundamental, with ontology being derivative.

Adaptationism is a doctrine that has meant different things to different people. In this essay, I want to isolate and discuss a reading of adaptationism that makes it a non-trivial empirical thesis about the history of life. I'll take adaptationism to be the following claim: natural selection has been the only important cause of most of the phenotypic traits found in most species. I won't try to determine whether adaptationism, so defined, is true. Rather, my task will be one of clarification. What does this statement mean, and how is it related to various remarks that biologists have made about adaptationism, pro and con?

The argument from design is best understood as a likelihood inference. Its Achilles heel is our lack of knowledge concerning the aims and abilities that the putative designer would have; in consequence, it is impossible to determine whether the observations are more probable under the design hypothesis than they are under the hypothesis of chance. Hypotheses about the role played by natural selection in the history of life also can be evaluated within a likelihood framework, and here too there are auxiliary assumptions that need to be in place if the likelihoods of selection and chance are to be compared. I describe some problems that arise in connection with the project of obtaining independent evidence concerning those auxiliary assumptions.

We argue elsewhere that explanatoriness is evidentially irrelevant . Let H be some hypothesis, O some observation, and E the proposition that H would explain O if H and O were true. Then O screens-off E from H: Pr = Pr. This thesis, hereafter “SOT” , is defended by appeal to a representative case. The case concerns smoking and lung cancer. McCain and Poston grant that SOT holds in cases, like our case concerning smoking and lung cancer, that involve frequency data. However, McCain and Poston contend that there is a wider sense of evidential relevance—wider than the sense at play in SOT—on which explanatoriness is evidentially relevant even in cases involving frequency data. This is their main point, but they also contend that SOT does not hold in certain cases not involving frequency data. We reply to each of these points and conclude with some general remarks on screening-off as a test of evidential relevance

In this paper I want to clarify what biologists are talking about when they talk about the evolution of altruism. I'll begin by saying something about the common sense concept. This familiar idea I'll call 'vernacular altruism.' One point of doing this is to make it devastatingly obvious that the common sense concept is very different from the concept as it's used in evolutionary theory. After that preliminary, I'll describe some features of the evolutionary concept. Then I'll conclude by briefly considering what explanatory relation might obtain between vernacular altruism and evolutionary altruism.

This book consists of four essays on Darwin’s theory of evolution and three postscripts on contemporary evolutionary theory. The main questions that the chapters address are: How are common ancestry and natural selection related to each other in Darwin’s theory? What were Darwin’s views about group selection and the evolution of altruism? Why did Darwin change his mind about sex ratio, and how are his ideas related to the creationism that preceded him and the evolutionary biology that followed? Do Darwin’s theory and modern evolutionary theory obey the principle of methodological naturalism and ought they to do so?The book is philosophical because it focuses on the logic of arguments. I attend closely to Darwin’s texts, but I sometimes use tools that Darwin did not have available. These include ideas from contemporary biology and from probability theory. I see merit in this approach because it helps elucidate Darwin’s theory. Darwin pointed to the need for this sort of ..

Is it accurate to label Darwin's theory "the theory of evolution by natural selection," given that the concept of common ancestry is at least as central to Darwin's theory? Did Darwin reject the idea that group selection causes characteristics to evolve that are good for the group though bad for the individual? How does Darwin's discussion of God in The Origin of Species square with the common view that he is the champion of methodological naturalism? These are just some of the intriguing questions raised in this volume of interconnected philosophical essays on Darwin. The author's approach is informed by modern issues in evolutionary biology, but is sensitive to the ways in which Darwin's outlook differed from that of many biologists today. The main topics that are the focus of the book--common ancestry, group selection, sex ratio, and naturalism--have rarely been discussed in their connection with Darwin in such penetrating detail.

Darwin claims in the Origin that similarity is evidence for common ancestry, but that adaptive similarities are ‘almost valueless’ as evidence. This second claim seems reasonable for some adaptive similarities but not for others. Here we clarify and evaluate these and related matters by using the law of likelihood as an analytic tool and by considering mathematical models of three evolutionary processes: directional selection, stabilizing selection, and drift. Our results apply both to Darwin’s theory of evolution and to modern evolutionary biology. 1 Introduction2 The Likelihood Framework3 A Sufficient Condition for a Similarity to Favour Common Ancestry over Separate Ancestry4 The 1/p Criterion and Its Limitations5 Directional Selection versus Drift6 Stabilizing Selection versus Drift7 Going beyond Two Taxa8 ConclusionsAppendix.

In what follows, I propose to evaluate Giere's analysis by applying it to a causal process considered in evolutionary theory, namely, natural selection. To say that there is selection for a given trait is to say that possessing that trait causes differential reproductive success. If there is selection for a trait and if no other evolutionary forces impinge and there is no "sampling error" due to random drift, individuals with the trait will on average have more offspring than individuals without it. But sampling error can't be discounted for finite populations; so the combined effect of selection and drift will be a probability distribution of numbers of offspring. In this event, selection for a trait will imply that the mean value of the distribution associated with the individuals possessing the trait exceeds the mean value for individuals without the trait. Evolutionary theory assigns a probability distribution of possible reproductive outputs to each organism and, thereby, views organisms as stochastic systems. This implies no commitment to indeterminacy at the microlevel, of course.

Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike [1973], which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light on the theoretical virtues of parsimoniousness, unification, and non ad hocness, on the dispute about Bayesianism, and on empiricism and scientific realism. * Both of us gratefully acknowledge support from the Graduate School at the University of Wisconsin-Madison, and NSF grant DIR-8822278 (M.F.) and NSF grant SBE-9212294 (E.S.). Special thanks go to A. W. F. Edwards.William Harper. Martin Leckey. Brian Skyrms, and especially Peter Turney for helpful comments on an earlier draft.

In a recent article, Kim Sterelny and Philip Kitcher5 defend a version of genic selectionism and attempt to refute the criticisms I made of that doctrine. Their defense has two components. First, they find fault with the account I gave of the units-of-selection controversy-an account which uses the idea of probabilistic causality as a tool of explication. Second, they provide a positive account of their own of what that controversy concerns, one which they think allows genic selectionism to emerge as a successful thesis. I believe that the position they sketch is mistaken, both in its general orientation and in its details. I believe that the Sterelny/ Kitcher position misunderstands what the biological question of the units of selection is about and that their criticisms of my own proposal are mistaken as well.

If a parsimony criterion may be used to choose between theories that make different predictions, may the same criterion be used to choose between theories that are predictively equivalent? The work of the statistician H. Akaike (1973) is discussed in connection with this question. The results are applied to two examples in which parsimony has been invoked to choose between philosophical theories-Shoemaker's (1969) discussion of the possibility of time without change and the discussion by Smart (1959) and Brandt and Kim (1967) of mind/body dualism and the identity theory.

We argue against some of Reichenbach's claims about causal forks are incorrect. We do not see why the Second Law of Thermodynamics rules out the existence of conjunctive forks open to the past. In addition, we argue that a common effect rarely forms a conjunctive fork with its joint causes, but it sometimes does. Nevertheless, we think there is something to be said for Reichenbach's idea that forks of various kinds are relevant to explaining why we know more about the past than about the future. And entropy turns out to play a role in the explanation, though not the determining role that Reichenbach envisions.

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.

This paper proposes a game-theoretic solution of the surprise examination problem. It is argued that the game of “matching pennies” provides a useful model for the interaction of a teacher who wants her exam to be surprising and students who want to avoid being surprised. A distinction is drawn between prudential and evidential versions of the problem. In both, the teacher should not assign a probability of zero to giving the exam on the last day. This representation of the problem provides a diagnosis of where the backwards induction argument, which “proves” that no surprise exam is possible, is mistaken.

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.

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.

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.

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.

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.

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

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.