In this paper, I sketch an argument for the view that we cannot know (or have good reasons to believe) that God exists. Some call this view “strong agnosticism” but I prefer the term “skeptheism” in order to clearly distinguish between two distinct epistemic attitudes with respect to the existence of God, namely, agnosticism and skepticism. For the skeptheist, we cannot know (or have good reasons to believe) that God exists, since there can be neither conceptual (a priori) nor empirical (...) (a posteriori) evidence for the existence of God. (shrink)

The rise of experimental philosophy has placed metaphilosophical questions, particularly those concerning concepts, at the center of philosophical attention. X-phi offers empirically rigorous methods for identifying conceptual content, but what exactly it contributes towards evaluating conceptual content remains unclear. We show how x-phi complements Rudolf Carnap’s underappreciated methodology for concept determination, explication. This clarifies and extends x-phi’s positive philosophical import, and also exhibits explication’s broad appeal. But there is a potential problem: Carnap’s account of explication was limited to empirical and (...) logical concepts, but many concepts of interest to philosophers are essentially normative. With formal epistemology as a case study, we show how x-phi assisted explication can apply to normative domains. (shrink)

Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different epistemic characters. (...) Theoretical modelling is grounded in explicit and known analogies between model and target. By contrast, inferences from model organisms are empirical extrapolations. Often such extrapolation is based on shared ancestry, sometimes in conjunction with other empirical information. One implication is that such inferences are unique to biology, whereas theoretical models are common across many disciplines. We close by discussing the diversity of uses to which model organisms are put, suggesting how these relate to our overall account. 1 Introduction2 Volterra and Theoretical Modelling3 Drosophila as a Model Organism4 Generalizing from Work on Model Organisms5 Phylogenetic Inference and Model Organisms6 Further Roles of Model Organisms6.1 Preparative experimentation6.2 Model organisms as paradigms6.3 Model organisms as theoretical models6.4 Inspiration for engineers6.5 Anchoring a research community7 Conclusion. (shrink)

The desire to minimize the number of individual new entities postulated is often referred to as quantitative parsimony. Its influence on the default hypotheses formulated by scientists seems undeniable. I argue that there is a wide class of cases for which the preference for quantitatively parsimonious hypotheses is demonstrably rational. The justification, in a nutshell, is that such hypotheses have greater explanatory power than less parsimonious alternatives. My analysis is restricted to a class of cases I shall refer to as (...) additive. Such cases involve the postulation of a collection of qualitatively identical individual objects which collectively explain some particular observed phenomenon. Especially clear examples of this sort occur in particle physics. 1 Introduction 2 Particle physics: a case study 3 Three kinds of simplicity 4 Explanatory power 5 Explanation and non-observation 6 Parsimony and scientific methodology 7 Conclusions. (shrink)

Discussions of the functions of biological traits generally take the notion of a trait for granted. Defining this notion is a non-trivial problem. Different approaches to function place different constraints on adequate accounts of the notion of a trait. Accounts of function based on engineering-style analyses allow trait boundaries to be a matter of human interest. Accounts of function based on natural selection have typically been taken to require trait boundaries that are objectively real. After canvassing problems raised by each (...) approach, I conclude with some facts that satisfactory notions of trait must respect. (shrink)

When philosophers discuss the topic of explanation, they usually have in mind the following question: given the beliefs one has and some proposition that one wishes to explain, which subset of the beliefs constitutes an explanation of the target proposition? That is, the philosophical ‘problem of explanation’ typically has bracketed the issue of how one obtains the beliefs; they are taken as given. The problem of explanation has been the problem of understanding the relation ‘x explains y’. Since Hempel did (...) so much to canonize this way of thinking about explanation, it deserves to be called ‘Hempel's problem’. (shrink)

This article discusses the role of simplicity and the notion of a best balance of simplicity and strength within the best systems account (BSA) of laws of nature. The article explores whether there is anything in scientific practice that corresponds to the notion of simplicity or to the trade-off between simplicity and strength to which the BSA appeals. Various theoretical rationales for simplicity preferences and their bearing on the identification of laws are also explored. It is concluded that there are (...) a number of issues about the role of simplicity within the BSA and its relation to strength that need to be addressed before the BSA can be regarded as an adequate account of laws. 1 Introduction2 The Best Systems Account3 The Trade-Off between Simplicity and Strength: Preliminary Considerations4 Alternative Conceptions of the Relationship between Simplicity and Strength5 Two Roles for Simplicity6 Simplicity in the Best Systems Account: Curve-Fitting7 Simplicity as a Corrective for Overfitting8 Descriptive Simplicity in the Best Systems Account?9 Simplicity as Due to Human Intellectual Limitations10 Summary11 Concluding Remarks. (shrink)

Here, I consider the recent application of phylogenetic methods in historical linguistics. After a preliminary survey of one such method, i.e. cladistic parsimony, I respond to two common criticisms of cultural phylogenies: that cultural artifacts cannot be modeled as tree-like because of borrowing across lineages, and that the mechanism of cultural change differs radically from that of biological evolution. I argue that while perhaps remains true for certain cultural artifacts, the nature of language may be such as to side-step this (...) objection. Moreover, I explore the possibility that cladistic parsimony can be justified even if is true by appealing to the inference pattern known among philosophers as ‘Inference to the Best Explanation’. (shrink)

In the past five years, there have been a series of papers in the journal Evolution debating the relative significance of two theories of evolution, a neo-Fisherian and a neo-Wrightian theory, where the neo-Fisherians make explicit appeal to parsimony. My aim in this paper is to determine how we can make sense of such an appeal. One interpretation of parsimony takes it that a theory that contains fewer entities or processes, (however we demarcate these) is more parsimonious. On the account (...) that I defend here, parsimony is a ‘local’ virtue. Scientists’ appeals to parsimony are not necessarily an appeal to a theory’s simplicity in the sense of it’s positing fewer mechanisms. Rather, parsimony may be proxy for greater probability or likelihood. I argue that the neo-Fisherians appeal is best understood on this interpretation. And indeed, if we interpret parsimony as either prior probability or likelihood, then we can make better sense of Coyne et al. argument that Wright’s three phase process operates relatively infrequently. (shrink)

In a formal theory of induction, inductive inferences are licensed by universal schemas. In a material theory of induction, inductive inferences are licensed by facts. With this change in the conception of the nature of induction, I argue that the celebrated “problem of induction” can no longer be set up and is thereby dissolved. Attempts to recreate the problem in the material theory of induction fail. They require relations of inductive support to conform to an unsustainable, hierarchical empiricism.

This article argues that a particular notion of rationality, more exactly a specific notion of legitimate inference, is presupposed by much work in the social sciences to their detriment. The author describes the notion of rationality he has in mind, explains why it is misguided, identifies where and how it affects social research, and illustrates why that research is weaker as a result. The notion of legitimate inference the author has in mind is one that believes inferences are guided by (...) principles that are formal, universal and a priori—that is, that make no substantive, domain-specific empirical assumptions about the world. The author briefly provides a variety of reasons to be skeptical about such principles. Those reasons extend from broad philosophical considerations to quasi-empirical evidence. The author then argues that this notion of inference is involved with both the practice and the content of the social sciences in various ways. In terms of practice, this notion of inference lies behind the way statistical testing is generally done in the social sciences. In terms of content, the author argues that this notion of rationality is invoked, for example, in game theory and in rational expectations macroeconomics. In all cases, use of the formal rationality notion leads social scientists to put more faith in their results than is warranted and thus is an obstacle to doing better social science. (shrink)

When two causally independent processes each have a quantity that increases monotonically (either deterministically or in probabilistic expectation), the two quantities will be correlated, thus providing a counterexample to Reichenbach's principle of the common cause. Several philosophers have denied this, but I argue that their efforts to save the principle are unsuccessful. Still, one salvage attempt does suggest a weaker principle that avoids the initial counterexample. However, even this weakened principle is mistaken, as can be seen by exploring the concepts (...) of homology and homoplasy used in evolutionary biology. I argue that the kernel of truth in the principle of the common cause is to be found by separating metaphysical and epistemological issues; as far as the epistemology is concerned, the Likelihood Principle is central. (shrink)

Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods or (...) priors per se; the virtues may be more accessible epistemically than likelihoods or priors. I then prove a ceteris paribus theorem regarding theoretical consilience, use it to correct a recent application of Reichenbach's common cause principle, and apply it to a test case of scientific reasoning. Explanation and confirmation The heuristic conception of theoretical virtues Abduction and the accessibility of explanatory power Evidential and theoretical consilience A test case: gravitational lensing Conclusion Thus natural science appears completely to lose from sight the large and general questions; but all the more splendid is the success when, groping in the thicket of special questions, we suddenly find a small opening that allows a hitherto undreamt of outlook on the whole. (L. Boltzmann, Theoretical Physics and Philosophical Problems). (shrink)

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. (shrink)

Cultural disparity—the variation across cultural traits such as knowledge, skill, and belief—is a complex phenomenon, studied by a number of researchers with an expanding empirical toolkit. While there is a growing consensus as to the processes that generate cultural variation and change, general explanatory frameworks require additional tools for identifying, organising, and relating the complex causes that underpin the production of cultural disparity. Here I develop a case study in the cognitive science of religion, and demonstrate how concepts and distinctions (...) drawn from work on contrastive explanation and manipulationist accounts of causation provide such tools for distinguishing explanatory levels, organising causal narratives, and accounting for cross-cultural patterns. (shrink)

A key issue in the philosophy of biology is evolutionary contingency, the degree to which evolutionary outcomes could have been different. Contingency is typically contrasted with evolutionary convergence, where different evolutionary pathways result in the same or similar outcomes. Convergences are given as evidence against the hypothesis that evolutionary outcomes are highly contingent. But the best available treatments of contingency do not, when read closely, produce the desired contrast with convergence. Rather, they produce a picture in which any degree of (...) contingency is compatible with any degree of convergence. This is because convergence is the repeated production of a given outcome from different starting points, and contingency has been defined without reference to the size of the space of possible outcomes. In small spaces of possibilities, the production of repeated outcomes is almost assured. This paper presents a definition of contingency which includes this modal dimension in a way that does not reduce it to the binary notion of contingency found in standard modal logic. The result is a conception of contingency which properly contrasts with convergence, given some domain of possibilities and a measure defined over it. We should therefore not ask whether evolution is contingent or convergent simpliciter, but rather about the degree to which it is contingent or convergent in various domains, as measured in various ways. (shrink)

A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.

This essay discusses Elliott Sober’s Evidence and Evolution: The Logic Behind the Science. Valuable to both philosophers and biologists, Sober analyzes the testing of different kinds of evolutionary hypotheses about natural selection or phylogenetic history, including a thorough critique of intelligent design. Not at least because of a discussion of different schools of hypothesis testing (Bayesianism, likelihoodism, and frequentism), with Sober favoring a pluralism where different inference methods are appropriate in different empirical contexts, the book has lessons for philosophy of (...) science beyond its evolutionary focus. I criticize Sober for not including epistemic values and social aspects of scientific practice in his epistemological framework. (shrink)

In this paper, I argue that the ultimate argument for Scientific Realism, also known as the No-Miracles Argument (NMA), ultimately fails as an abductive defence of Epistemic Scientific Realism (ESR), where (ESR) is the thesis that successful theories of mature sciences are approximately true. The NMA is supposed to be an Inference to the Best Explanation (IBE) that purports to explain the success of science. However, the explanation offered as the best explanation for success, namely (ESR), fails to yield independently (...) testable predictions that alternative explanations for success do not yield. If this is correct, then there seems to be no good reason to prefer (ESR) over alternative explanations for success. (shrink)

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. (shrink)

Homology is a natural kind term and a precise account of what homology is has to come out of theories about the role of homologues in evolution and development. Definitions of homology are discussed with respect to the question as to whether they are able to give a non-circular account of the correspondence or sameness referred to by homology. It is argued that standard accounts tie homology to operational criteria or specific research projects, but are not yet able to offer (...) a concept of homology that does not presuppose a version of homology or a comparable notion of sameness. This is the case for phylogenetic definitions that trace structures back to the common ancestor as well as for developmental approaches such as Wagner's biological homology concept. In contrast, molecular homology is able to offer a definition of homology in genes and proteins that explicates homology by reference to more basic notions. Molecular correspondence originates by means of specific features of causal processes. It is speculated that further understanding of morphogenesis might enable biologists to give a theoretically deeper definition of homology along similar lines: an account which makes reference to the concrete mechanisms that operate in organisms. (shrink)

Philosophical discussions of biological classification have failed to recognise the central role of homology in the classification of biological parts and processes. One reason for this is a misunderstanding of the relationship between judgments of homology and the core explanatory theories of biology. The textbook characterisation of homology as identity by descent is commonly regarded as a definition. I suggest instead that it is one of several attempts to explain the phenomena of homology. Twenty years ago the ‘new experimentalist’ movement (...) in philosophy of science drew attention to the fact that many experimental phenomena have a ‘life of their own’: the conviction that they are real is not dependent on the theories used to characterise and explain them. I suggest that something similar can be true of descriptive phenomena, and that many homologies are phenomena of this kind. As a result the descriptive biology of form and function has a life of its own—a degree of epistemological independence from the theories that explain form and function. I also suggest that the two major ‘homology concepts’ in contemporary biology, usually seen as two competing definitions, are in reality complementary elements of the biological explanation of homology. (shrink)

ABSTRACT ‘Modus Darwin’ is the name given by Elliott Sober to a form of argument that he attributes to Darwin in the Origin of Species, and to subsequent evolutionary biologists who have reasoned in the same way. In short, the argument form goes: similarity, ergo common ancestry. In this article, I review and critique Sober’s analysis of Darwin’s reasoning. I argue that modus Darwin has serious limitations that make the argument form unsuitable for supporting Darwin’s conclusions, and that Darwin did (...) not reason in this way. (shrink)

In a recent article I compared the problem of theory choice, in which scientists must choose between competing theories, with the problem of social choice, in which society must choose between competing social alternatives. I argued that the formal machinery of social choice theory can be used to shed light on the problem of theory choice in science, an argument that has been criticized by Michael Morreau and Jacob Stegenga. This article replies to Morreau’s and Stegenga’s criticisms.

Bayesian methods have become among the most popular methods in phylogenetics, but theoretical opposition to this methodology remains. After providing an introduction to Bayesian theory in this context, I attempt to tackle the problem mentioned most often in the literature: the “problem of the priors”—how to assign prior probabilities to tree hypotheses. I first argue that a recent objection—that an appropriate assignment of priors is impossible—is based on a misunderstanding of what ignorance and bias are. I then consider different methods (...) of assigning prior probabilities to trees. I argue that priors need to be derived from an understanding of how distinct taxa have evolved and that the appropriate evolutionary model is captured by the Yule birth–death process. This process leads to a well-known statistical distribution over trees. Though further modifications may be necessary to model more complex aspects of the branching process, they must be modifications to parameters in an underlying Yule model. Ignoring these Yule priors commits a fallacy leading to mistaken inferences both about the trees themselves and about macroevolutionary processes more generally. (shrink)

Our epistemic access to the past is infamously patchy: historical information degrades and disappears and bygone eras are often beyond the reach of repeatable experiments. However, historical scientists have been remarkably successful at uncovering and explaining the past. I argue that part of this success is explained by the exploitation of dependencies between historical events, entities, and processes. For instance, if sauropod dinosaurs were hot blooded, they must have been gluttons; the high-energy demands of endothermy restrict sauropod grazing strategies. Understanding (...) such dependencies extends our reach into the past in spite of incomplete data. In addition, this serves as a counterexample to two accounts of method in the historical sciences. By one, historical science proceeds by identifying ‘smoking guns’: traces that discriminate between live hypotheses. By the other, historical hypotheses are supported by consilience: the convergence of independent lines of evidence. However, testing for ‘coherency’ between past hypotheses also plays a critical role in historical confirmation. Just as historical scientists exploit dependencies between past entities and present entities to infer what the past was like, they also exploit dependencies between past entities themselves. I do not suggest that archetypical historical science proceeds in this manner. Rather, the lesson I draw is that historical methodology cannot be characterized as archetypically relying on one method or another. Historical science is at base opportunistic, and is resistant to unitary analyses. 1 Introduction2 Snowballs and Explosions: The Basic Idea3 Were Sauropods Endothermic?4 Dependent Entities and Interdependent Explanations5 Smoking Guns and Consilience. (shrink)

From the 1960s, mathematical and computational tools have been developed to arrive at human population trees from various kinds of serological and molecular data. Focusing on the work of the Italian-born population geneticist Luigi Luca Cavalli-Sforza, I follow the practices of tree-building and mapping from the early blood-group studies to the current genetic admixture research. I argue that the visual language of the tree is paralleled in the narrative of the human diasporas, and I show how the tree was actually (...) mapped onto the surface of the earth. This visual and textual structure is mirrored in the liberal discourse of unity in diversity that has been criticized as running counter to the socio-political effects of human population genetics. From this perspective, one may ask how far the phylogenetic diagram in its various forms is a manifestation of the physics of power that according to Michel Foucault consists in mechanisms that analyse distributions, movements, series, combinations, and that uses instruments to render visible, to register, to differentiate and to compare. It is one among other disciplinary technologies that ensure the ordering of human diversity. In the case of intra-human phylogenetic trees, population samples and labels are one issue. Another is that the separated branches seem to show groups of people, who have in reality been interacting and converging, as isolated. Often based on so-called isolated peoples, molecular tree diagrams freeze a hierarchical kinship system that is meant to represent a state before the great historical population movements. (shrink)

Bayesianism and likelihoodism are two of the most important frameworks philosophers of science use to analyse scientific methodology. However, both frameworks face a serious objection: much scientific inquiry takes place in highly idealized frameworks where all the hypotheses are known to be false. Yet, both Bayesianism and likelihoodism seem to be based on the assumption that the goal of scientific inquiry is always truth rather than closeness to the truth. Here, I argue in favour of a verisimilitude framework for inductive (...) inference. In the verisimilitude framework, scientific inquiry is conceived of, in part, as a process where inference methods ought to be calibrated to appropriate measures of closeness to the truth. To illustrate the verisimilitude framework, I offer a reconstruction of parsimony evaluations of scientific theories, and I give a reconstruction and extended analysis of the use of parsimony inference in phylogenetics. By recasting phylogenetic inference in the verisimilitude framework, it becomes possible to both raise and address objections to phylogenetic methods that rely on parsimony. 1Introduction2Problems with the Law of Likelihood3Introducing Verisimilitude-Based Inference4Examples of Verisimilitude-Based Inference Procedures4.1Parsimony inference over theories4.2Parsimony inference in phylogenetics5Conclusion. (shrink)

We discuss the scientific task of historical reconstruction and the problem of epistemic access. We argue that strong epistemic support for historical claims consists in the consilience of multiple independent lines of evidence, and analyze the impact hypothesis for the End-Cretaceous mass extinction to illustrate the accrual of epistemic support. Although there are elements of the impact hypothesis that enjoy strong epistemic support, the general conditions for this are strict, and help to clarify the difficulties associated with reconstructing the deep (...) past. (shrink)

In earlier work ( Cleland [2001] , [2002]), I sketched an account of the structure and justification of ‘prototypical’ historical natural science that distinguishes it from ‘classical’ experimental science. This article expands upon this work, focusing upon the close connection between explanation and justification in the historical natural sciences. I argue that confirmation and disconfirmation in these fields depends primarily upon the explanatory (versus predictive or retrodictive) success or failure of hypotheses vis-à-vis empirical evidence. The account of historical explanation that (...) I develop is a version of common cause explanation. Common cause explanation has long been vindicated by appealing to the principle of the common cause. Many philosophers of science (e.g., Sober and Tucker) find this principle problematic, however, because they believe that it is either purely methodological or strictly metaphysical. I defend a third possibility: the principle of the common cause derives its justification from a physically pervasive time asymmetry of causation (a.k.a. the asymmetry of overdetermination). I argue that explicating the principle of the common cause in terms of the asymmetry of overdetermination illuminates some otherwise puzzling features of the practices of historical natural scientists. (shrink)

An empirical procedure is suggested for testing a model that postulates variables that intervene between observed causes and abserved effects against a model that includes no such postulate. The procedure is applied to two experiments in psychology. One involves a conditioning regimen that leads to response generalization; the other concerns the question of whether chimpanzees have a theory of mind.

Morgan’s Canon is a very widely endorsed methodological principle in animal psychology, believed to be vital for a rigorous, scientific approach to the study of animal cognition. In contrast I argue that Morgan’s Canon is unjustified, pernicious and unnecessary. I identify two main versions of the Canon and show that they both suffer from very serious problems. I then suggest an alternative methodological principle that captures all of the genuine methodological benefits that Morgan’s Canon can bring but suffers from none (...) of its problems. (shrink)

A naturalistic account of the strengths and limitations of cladistic practice is offered. The success of cladistics is claimed to be largely rooted in the parsimony-implementing congruence test. Cladists may use the congruence test to iteratively refine assessments of homology, and thereby increase the odds of reliable phylogenetic inference under parsimony. This explanation challenges alternative views which tend to ignore the effects of parsimony on the process of character individuation in systematics. In a related theme, the concept of homeostatic property (...) cluster natural kinds is used to explain why cladistics is well suited to provide a traditional, verbal reference system for the evolutionary properties of species and clades. The advantages of more explicitly probabilistic approaches to phylogenetic inference appear to manifest themselves in situations where evolutionary homeostasis has for the most part broken down, and predictive classifications are no longer possible. (shrink)

In my dissertation I define historical disciplines as disciplines that aim to give a historical interpretation of the evidence. Phylogenetic systematics is a historical discipline and therefore in my definition phylogenies should be thought of as historical interpretations of relationships between taxa.

This paper examines the strengths and weaknesses of one of science's most pervasive and flexible metaprinciples;optimalityis used to explain utility maximization in economics, least effort principles in physics, entropy in chemistry, and survival of the fittest in biology. Fermat's principle of least time involves both teleological and causal considerations, two distinct modes of explanation resting on poorly understood psychological primitives. The rationality heuristic in economics provides an example from social science of the potential biases arising from the extreme flexibility of (...) optimality considerations, including selective search for confirming vidence, ex post rationalization, and the confusion of prediction with explanation. Commentators are asked to reflect on the extent to which optimality is an organizing principle of nature, a set of relatively unconnected techniques of science, a normative principle for rational choice and social organization, a metaphysical way of looking at the world, or something else still. (shrink)