Scientists often make surprising claims about things that no one can observe. In physics, chemistry, and molecular biology, scientists can at least experiment on those unobservable entities, but what about researchers in fields such as paleobiology and geology who study prehistory, where no such experimentation is possible? Do scientists discover facts about the distant past or do they, in some sense, make prehistory? In this book Derek Turner argues that this problem has surprising and important consequences for the scientific realism (...) debate. His discussion covers some of the main positions in philosophy of science - realism, social constructivism, empiricism, and the natural ontological attitude - and shows how they relate to issues in paleobiology and geology. His original and thought-provoking book will be of wide interest to philosophers and scientists alike. (shrink)

David Lewis defends the thesis of the asymmetry of overdetermination: later affairs are seldom overdetermined by earlier affairs, but earlier affairs are usually overdetermined by later affairs. Recently, Carol Cleland has argued that since the distinctive methodologies of historical science and experimental science exploit different aspects of this asymmetry, the methodology of historical science is just as good, epistemically speaking, as that of experimental science. This paper shows, first, that Cleland's epistemological conclusion does not follow from the thesis of the (...) asymmetry of overdetermination, because overdetermination is compatible with epistemic underdetermination. The paper also shows, contra Cleland, that there is at least one interesting sense in which historical science is epistemically inferior to experimental science, after all, because local underdetermination problems are more widespread in historical than in experimental science. (shrink)

Philosophers of science typically associate the causal‐mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon’s account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex‐systems approach avoids certain (...) objections to Salmon’s account of causal‐mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

There is something genuinely puzzling about large-scale simplicity emerging in systems that are complex at the small scale. Consider, for example, a population of hares. Clearly, the number of hares at any given time depends on hare fertility rates, the weather, the number of predators, the health of the predators, availability of hare resources, motor vehicle traffic, individual hare locations, colour of individual hares, and so on. Indeed, given the incredibly complexity of the hares’ environment at the small-scale, it is (...) amazing that anything can be said about hare abundances. But not only can we say something about hare abundances, we can formulate equations for hare abundance as a function of time that are remarkably accurate. But most amazing of all is that such equations have very few parameters—in the simplest cases, just the growth rate and an initial population abundance. How can this be? How can we ignore all the small-scale factors when they clearly play major roles in determining abundance? Put somewhat more grandiosely: How is population ecology possible? Of course it’s not just population ecology that exhibits such small-scale complexity and large-scale simplicity. Other important systems include the weather and gases in equilibrium. The examples can easily be multiplied. The general problem is the same: How can seemingly unpredictable and complex microbehaviour of complex systems result in predictable and simple macrobehaviour? Providing an answer to this question is the central task of Michael Strevens’ excellent book Bigger than Chaos : Understanding Complexity through Probability. (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)

Experimental research is commonly held up as the paradigm of "good" science. Although experiment plays many roles in science, its classical role is testing hypotheses in controlled laboratory settings. Historical science is sometimes held to be inferior on the grounds that its hypothesis cannot be tested by controlled laboratory experiments. Using contemporary examples from diverse scientific disciplines, this paper explores differences in practice between historical and experimental research vis-à-vis the testing of hypotheses. It rejects the claim that historical research is (...) epistemically inferior. For as I argue, scientists engage in two very different patterns of evidential reasoning and, although there is overlap, one pattern predominates in historical research and the other pattern predominates in classical experimental research. I show that these different patterns of reasoning are grounded in an objective and remarkably pervasive time asymmetry of nature. (shrink)

Philosophers of neuroscience have traditionally described interfield integration using reduction models. Such models describe formal inferential relations between theories at different levels. I argue against reduction and for a mechanistic model of interfield integration. According to the mechanistic model, different fields integrate their research by adding constraints on a multilevel description of a mechanism. Mechanistic integration may occur at a given level or in the effort to build a theory that oscillates among several levels. I develop this alternative model using (...) a putative exemplar of reduction in contemporary neuroscience: the relationship between the psychological phenomena of learning and memory and the electrophysiological phenomenon known as Long-Term Potentiation. A new look at this historical episode reveals the relative virtues of the mechanistic model over reduction as an account of interfield integration. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

What is it for history to matter? Stephen Gould argued that unpredictability is part of the answer. For example, the “fact“ that repeated replays of the history of life would end differently every time is a sign that history matters to the course of evolution. But there is a problem here: if a particular point in the past leaves open alternative possible futures, then in what sense does that point in the past matter with regard to which of the outcomes (...) occurs? We argue that unpredictability is central to the importance of history. However, it is not the unpredictability of the future, but rather the unpredictability of the past itself that is the key. History matters when a particular future depends on a particular past that was not bound to happen, but did. (shrink)

How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...) operation within a mechanism, and highlights the role that various kinds of regularity play in scientific explanation. I defend this regularity requirement in terms of regularity’s role in individuating mechanisms against a background of other causal processes, and by prioritizing mechanisms’ ability to serve as a model of scientific explanation, rather than as a metaphysical account of causation. It is because mechanisms are regular, in the expanded sense described here, that they are capable of supporting the kinds of generalizations that figure prominently in scientific explanations. (shrink)

How do historians, comparative linguists, biblical and textual critics and evolutionary biologists establish beliefs about the past? How do they know the past? This book presents a philosophical analysis of the disciplines that offer scientific knowledge of the past. Using the analytic tools of contemporary epistemology and philosophy of science the book covers such topics as evidence, theory, methodology, explanation, determination and underdetermination, coincidence, contingency and counterfactuals in historiography. Aviezer Tucker's central claim is that historiography as a scientific discipline should (...) be thought of as an effort to explain the evidence of past events. He also emphasizes the similarity between historiographic methodology to Darwinian evolutionary biology. This is an important, fresh approach to historiography and will be read by philosophers, historians and social scientists interested in the methodological foundations of their disciplines. (shrink)

The official model of explanation proposed by the logical empiricists, the covering law model, is subject to familiar objections. The goal of the present paper is to explore an unofficial view of explanation which logical empiricists have sometimes suggested, the view of explanation as unification. I try to show that this view can be developed so as to provide insight into major episodes in the history of science, and that it can overcome some of the most serious difficulties besetting the (...) covering law model. (shrink)

This paper presents a counterfactual account of what a mechanism is. Mechanisms consist of parts, the behavior of which conforms to generalizations that are invariant under interventions, and which are modular in the sense that it is possible in principle to change the behavior of one part independently of the others. Each of these features can be captured by the truth of certain counterfactuals.

This paper presents a counterfactual account of what a mechanism is. Mechanisms consist of parts, the behavior of which conforms to generalizations that are invariant under interventions, and which are modular in the sense that it is possible in principle to change the behavior of one part independently of the others. Each of these features can be captured by the truth of certain counterfactuals.

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.

The paper explicates unique events and investigates their epistemology. Explications of unique events as individuated, different, and emergent are philosophically uninteresting. Unique events are topics of why-questions that radically underdetermine all their potential explanations. Uniqueness that is relative to a level of scientific development is differentiated from absolute uniqueness. Science eliminates relative uniqueness by discovery of recurrence of events and properties, falsification of assumptions of why-questions, and methodological simplification e.g. by explanatory methodological reduction. Finally, an overview of contemporary philosophical disputes (...) that hinge on issues of uniqueness emphasizes its philosophical significance. (shrink)

In this book, Michael Strevens aims to explain how simplicity can coexist with, indeed be caused by, the tangled interconnections between a complex system's ...

The ontological dependence of one domain on another is compatible with the explanatory autonomy of the less basic domain. That autonomy results from the fact that the relationship between two domains can be very complex. In this paper I distinguish two different types of complexity, two ways the relationship between domains can fail to be transparent, both of which are relevant to evolutionary biology. Sometimes high level explanations preserve a certain type of causal or counterfactual information which would be lost (...) at the lower level; I argue that this is central to the proper understanding of the adaptationist program. Sometimes high level kinds are multiply realised by lower level kinds: I argue that this is central to the understanding of macroevolution. (shrink)

The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...) argument for scientific realism akin to the argument that convinced twentieth-century physical scientists of the existence of atoms and molecules. To do justice to such notions as irreducibly statistical laws and statistical explanation, he offers a novel account of physical randomness. The transition from the "reviewed view" of scientific explanation to the causal/mechanical model requires fundamental rethinking of basic explanatory concepts. (shrink)

Hilary Putnam, who may have been the first philosopher to advance the notion that the computer is an apt model for the mind, takes a radically new view of his...

The consensus among evolutionists seems to be that the morphological complexity of organisms increases in evolution, although almost no empirical evidence for such a trend exists. Most studies of complexity have been theoretical, and the few empirical studies have not, with the exception of certain recent ones, been especially rigorous; reviews are presented of both the theoretical and empirical literature. The paucity of evidence raises the question of what sustains the consensus, and a number of suggestions are offered, including the (...) possibility that certain cultural and/or perceptual biases are at work. In addition, a shift in emphasis from theoretical to empirical inquiry is recommended for the study of complexity, and guidelines for future empirical studies are proposed. (shrink)

This paper is about mechanisms and models, and how they interact. In part, it is a response to recent discussion in philosophy of biology regarding whether natural selection is a mechanism. We suggest that this debate is indicative of a more general problem that occurs when scientists produce mechanistic models of populations and their behaviour. We can make sense of claims that there are mechanisms that drive population-level phenomena such as macroeconomics, natural selection, ecology, and epidemiology. But talk of mechanisms (...) and mechanistic explanation evokes objects with well-defined and localisable parts which interact in discrete ways, while models of populations include parts and interactions that are neither local nor discrete in any actual populations. This apparent tension can be resolved by carefully distinguishing between the properties of a model and those of the system it represents. To this end, we provide an analysis that recognises the flexible relationship between a mechanistic model and its target system. In turn, this reveals a surprising feature of mechanistic representation and explanation: it can occur even when there is a mismatch between the mechanism of the model and that of its target. Our analysis reframes the debate, providing an alternative way to interpret scientists’ mechanism-talk , which initially motivated the issue. We suggest that the relevant question is not whether any population-level phenomenon such as natural selection is a mechanism, but whether it can be usefully modelled as though it were a particular type of mechanism. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

Proponents of mechanistic explanation all acknowledge the importance of organization. But they have also tended to emphasize specificity with respect to parts and operations in mechanisms. We argue that in understanding one important mode of organization—patterns of causal connectivity—a successful explanatory strategy abstracts from the specifics of the mechanism and invokes tools such as those of graph theory to explain how mechanisms with a particular mode of connectivity will behave. We discuss the connection between organization, abstraction, and mechanistic explanation and (...) illustrate our claims by looking at an example from recent research on so-called network motifs. (shrink)

During the last three decades, reflections on the growth of scientific knowledge have inspired historians, sociologists, and some philosophers to contend that scientific objectivity is a myth. In this book, Kitcher attempts to resurrect the notions of objectivity and progress in science by identifying both the limitations of idealized treatments of growth of knowledge and the overreactions to philosophical idealizations. Recognizing that science is done not by logically omniscient subjects working in isolation, but by people with a variety of personal (...) and social interests, who cooperate and compete with one another, he argues that, nonetheless, we may conceive the growth of science as a process in which both our vision of nature and our ways of learning more about nature improve. Offering a detailed picture of the advancement of science, he sets a new agenda for the philosophy of science and for other "science studies" disciplines. (shrink)

The historical sciences, such as geology, evolutionary biology, and archaeology, appear to have no means to test hypotheses. However, on closer examination, reasoning in the historical sciences relies upon regularities, regularities that can be tested. I outline the role of regularities in the historical sciences, and in the process, blur the distinction between the historical sciences and the experimental sciences: all sciences deploy theories about the world in their investigations.

Many of the things that we try to explain, in both our common sense and our scientific engagement with the world, are capable of being explained more or less finely: that is, with greater or lesser attention to the detail of the producing mechanism. A natural assumption, pervasive if not always explicit, is that other things being equal, the more finegrained an explanation, the better. Thus, Jon Elster, who also thinks there are instrumental reasons for wanting a more fine-grained explanation, (...) assumes that in any case the mere fact of getting nearer the detail of production makes such an explanation intrinsically superior: “a more detailed explanation is also an end in itself”. Michael Taylor agrees: “A good explanation should be, amongst other things, as fine-grained as possible.”. (shrink)

Abstract Starting with Ben-Menahem's definition of historical contingency as sensitivity to variations in initial conditions, we suggest that historical events and processes can be thought of as forming a complex landscape of contingency and necessity. We suggest three different ways of extending and elaborating Ben-Menahem's concepts: (1) By supplementing them with a notion of historical disturbance; (2) by pointing out that contingency and necessity are subject to scaling effects; (3) by showing how degrees of contingency/necessity can change over time. We (...) also argue that further development of Sterelny's notion of conditional inevitability leads to our conclusion that the topography of historical contingency is something that can change over time. (shrink)

Starting with Ben-Menahem’s definition of historical contingency as sensitivity to variations in initial conditions, we suggest that historical events and processes can be thought of as forming a complex landscape of contingency and necessity. We suggest three different ways of extending and elaborating Ben-Menahem’s concepts: By supplementing them with a notion of historical disturbance; by pointing out that contingency and necessity are subject to scaling effects; by showing how degrees of contingency/necessity can change over time. We also argue that further (...) development of Sterelny’s notion of conditional inevitability leads to our conclusion that the topography of historical contingency is something that can change over time. (shrink)

Extreme variation in the meaning of the term “species” throughout the history of biology has often frustrated attempts of historians, philosophers and biologists to communicate with one another about the transition in biological thinking from the static species concept to the modern notion of evolving species. The most important change which has underlain all the other fluctuations in the meaning of the word “species” is the change from it denoting such metaphysical entities as essences, Forms or Natures to denoting classes (...) of individual organisms. Several authors have taken notice of the role of metaphysics in the work of particular biologists. An attempt will be made in this paper to present a systematic investigation of the role which metaphysics has played in the work of representative biologists throughout the history of biology, especially as it relates to their species concepts. (shrink)

Extreme variation in the meaning of the term “species” throughout the history of biology has often frustrated attempts of historians, philosophers and biologists to communicate with one another about the transition in biological thinking from the static species concept to the modern notion of evolving species. The most important change which has underlain all the other fluctuations in the meaning of the word “species” is the change from it denoting such metaphysical entities as essences, Forms or Natures to denoting classes (...) of individual organisms. Several authors have taken notice of the role of metaphysics in the work of particular biologists. An attempt will be made in this paper to present a systematic investigation of the role which metaphysics has played in the work of representative biologists throughout the history of biology, especially as it relates to their species concepts. (shrink)

A central subject is the main strand around which the fabric of an historical narrative is woven. Such a subject must possess both spatial and temporal continuity. It is integrated into an historical entity through the relationship between those properties which make it an individual, and their interaction with the historical event. Scientific theory is useful in the reconstruction of past events and the definition of the central subject. Ideas used as central subjects present the problem of finding internal principles (...) of integration which will make the idea continuous over time. The purpose of narratives is to explain an event by integrating it into an organized whole. (shrink)

This paper is a defense of "explanatory pluralism" (i.e., the view that some events can be correctly explained in two distinct ways). To defend pluralism, I identify two distinct (but compatible) styles of explanation in paleobiology. The first approach ("actual sequence explanation") traces out the particular forces that affect each species. The second approach treats the trend as "passive" or "random" diffusion away from a boundary in morphological space. I argue that while these strategies are distinct, some trends are correctly (...) explained in both ways. Further, since neither strategy can be reduced or eliminated from paleobiology, we should accept that both strategies can provide correct explanations for a single trend. (shrink)

Non-actual model systems discussed in scientific theories are compared to fictions in literature. This comparison may help with the understanding of similarity relations between models and real-world target systems. The ontological problems surrounding fictions in science may be particularly difficult, however. A comparison is also made to ontological problems that arise in the philosophy of mathematics.

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

While much of the recent literature on mechanisms has emphasized the superiority of mechanisms and mechanistic explanation over laws and nomological explanation, paradigmatic mechanisms—e.g., clocks or synapses—actually exhibit a great deal of stability in their behavior. And while mechanisms of this kind are certainly of great importance, there are many events that do not occur as a consequence of the operation of stable mechanisms. Events of natural and human history are often the consequence of causal processes that are ephemeral and (...) capricious. In this paper I shall argue that, notwithstanding their ephemeral nature, these processes deserve to be called mechanisms. Ephemeral mechanisms share important characteristics with their more stable cousins, and these shared characteristics will help us to understand connections between scientific and historical explanation. (shrink)

How should the concept of evidence be understood? And how does the concept of evidence apply to the controversy about creationism as well as to work in evolutionary biology about natural selection and common ancestry? In this rich and wide-ranging book, Elliott Sober investigates general questions about probability and evidence and shows how the answers he develops to those questions apply to the specifics of evolutionary biology. Drawing on a set of fascinating examples, he analyzes whether claims about intelligent design (...) are untestable; whether they are discredited by the fact that many adaptations are imperfect; how evidence bears on whether present species trace back to common ancestors; how hypotheses about natural selection can be tested, and many other issues. His book will interest all readers who want to understand philosophical questions about evidence and evolution, as they arise both in Darwin's work and in contemporary biological research. (shrink)

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. (shrink)