We respond to Jack Vromen’s (this issue) critique of our discussion of the missing micro-foundations of work on routines and capabilities in economics and management research. Contrary to Vromen, we argue that (1) inter-level relations can be causal, and that inter-level causal relations may also obtain between routines and actions and interactions; (2) there are no macro-level causal mechanisms; and (3) on certain readings of the notion of routines and capabilities, these may be macro causes.

This paper argues that typical biological species are natural kinds, on a familiar realist understanding of natural kinds—classes of individuals across which certain properties cluster together, in virtue of the causal workings of the world. But the clustering is far from exceptionless. Virtually no properties, or property-combinations, characterize every last member of a typical species—unless they can also appear outside the species. This motivates some to hold that what ties together the members of a species is the ability to interbreed, (...) others that it is common descent. Yet others hold that species are scattered individuals,of which organisms are parts rather than members. But not one of these views absolves us of the need to posit a typical phenotypic profile. Vagueness is here to stay. Some seek to explain the vagueness by saying species are united by “homeostatic property clusters”; but this view collapses into the more familiar realist picture. (shrink)

The ways in which the various activities of synthetic biology connect to those of conventional biology display both a multiplicity and variety that reflect the multiplicity and variety of meanings for which the term synthetic biology has been invoked, today as in the past. Central to this variety, as well as to the connection itself, is the complex relationship between knowing and making that has prevailed in the life sciences. That relationship is the focus of this article. More specifically, my (...) aim is to explore the different assumptions about how knowing is related to making that have prevailed, implicitly or explicitly in the various activities—now or in the past—subsumed under the name synthetic biology. (shrink)

There are several different ways in which chance affects evolutionary change. That all of these processes are called “random genetic drift” is in part a due to common elements across these different processes, but is also a product of historical borrowing of models and language across different levels of organization in the biological hierarchy. A history of the concept of drift will reveal the variety of contexts in which drift has played an explanatory role in biology, and will shed light (...) on some of the philosophical controversy surrounding whether drift is a cause of evolutionary change. (shrink)

For nearly as long as the word “correlation” has been part of statistical parlance, students have been warned that correlation does not prove causation, and that only experimental studies, e.g., randomized clinical trials, can establish the existence of a causal relationship. Over the last few decades, somewhat of a consensus has emerged between statisticians, computer scientists, and philosophers on how to represent causal claims and connect them to probabilistic relations. One strand of this work studies the conditions under which evidence (...) accumulated from non-experimental (observational) studies can be used to infer a causal relationship. In this paper, I compare the typical conditions required to infer that one variable is a direct cause of another in observational and experimental studies. I argue that they are essentially the same. (shrink)

In order to motivate the thesis that there is no single concept of causation that can do justice to all of our core intuitions concerning that concept, Ned Hall has argued that there is a conflict between a counterfactual criterion of causation and the condition of causal locality. In this paper I critically examine Hall's argument within the context of a more general discussion of the role of locality constraints in a causal conception of the world. I present two strategies (...) that defenders of counterfactual accounts of causation can pursue to respond to Hall's challenge—including the adoption of a counterfactual condition that is sufficient for causal action-at-a-distance in place of Hall's ‘process’ condition—and conclude that Hall's argument against counterfactual accounts of causation is unsuccessful. (shrink)

In a recent article in this journal, Federica Russo and Jon Williamson argue that an analysis of causality in terms of probabilistic relationships does not do justice to the use of mechanistic evidence to support causal claims. I will present Ronald Giere's theory of probabilistic causation, and show that it can account for the use of mechanistic evidence (both in the health sciences—on which Russo and Williamson focus—and elsewhere). I also review some other probabilistic theories of causation (of Suppes, Eells, (...) and Humphreys) and show that they cannot account for the use of mechanistic evidence. I argue that these theories are also inferior to Giere's theory in other respects. (shrink)

It is common to defend the Homeostatic Property Cluster ( HPC ) view as a third way between conventionalism and essentialism about natural kinds ( Boyd , 1989, 1991, 1997, 1999; Griffiths , 1997, 1999; Keil , 2003; Kornblith , 1993; Wilson , 1999, 2005; Wilson , Barker , & Brigandt , forthcoming ). According to the HPC view, property clusters are not merely conventionally clustered together; the co-occurrence of properties in the cluster is sustained by a similarity generating ( (...) or homeostatic ) mechanism . I argue that conventional elements are involved partly but ineliminably in deciding which mechanisms define kinds , for deciding when two mechanisms are mechanisms of the same type, and for deciding where one particular mechanism ends and another begins. This intrusion of conventional perspective into the idea of a mechanism raises doubts as to whether the HPC view is sufficiently free of conventional elements to serve as an objective arbiter in scientific disputes about what the kinds of the special sciences should be. (shrink)

If folk science means individuals having well worked out mechanistic theories of the workings of the world, then it is not feasible. Laypeople’s explanatory understandings are remarkably coarse, full of gaps, and often full of inconsistencies. Even worse, most people overestimate their own understandings. Yet recent views suggest that formal scientists may not be so different. In spite of these limitations, science somehow works and its success offers hope for the feasibility of folk science as well. The success of science (...) arises from the ways in which scientists learn to leverage understandings in other minds and to outsource explanatory work through sophisticated methods of deference and simplification of complex systems. Three studies ask whether analogous processes might be present not only in laypeople but also in young children and thereby form a foundation for supplementing explanatory understandings almost from the start of our first attempts to make sense of the world. (shrink)

To clarify and illuminate the place of probability in science Ellery Eells and James H. Fetzer have brought together some of the most distinguished philosophers ...

Elliott Sober and his defenders think of selection, drift, mutation, and migration as distinct evolutionary forces. This paper exposes an ambiguity in Sober's account of the force of selection: sometimes he appears to equate the force of selection with variation in fitness, sometimes with ‘selection for properties’. Sober's own account of fitness as a property analogous to life-expectancy shows how the two conceptions come apart. Cases where there is selection against variance in offspring number also show that selection and drift (...) cannot be distinguished in the way Sober hopes for. These issues have significance beyond the parochial matter of the coherence of Sober's system. There is no good principled answer to the question of which features of a population should count among the contributors to fitness. This means there is no non-arbitrary account of the nature of selection. (shrink)

Denis Walsh has written a striking new defense in this journal of the statisticalist (i.e., noncausalist) position regarding the forces of evolution. I defend the causalist view against his new objections. I argue that the heart of the issue lies in the nature of nonadditive causation. Detailed consideration of that turns out to defuse Walsh’s ‘description‐dependence’ critique of causalism. Nevertheless, the critique does suggest a basis for reconciliation between the two competing views. *Received December 2009; revised December 2009. †To contact (...) the author, please write to: Department of Philosophy, 599 Lucas Hall, One University Boulevard, University of Missouri, St. Louis, MO 63121; e‐mail: [email protected]. (shrink)

John Cook Wilson (1849–1915) was Wykeham Professor of Logic at New College, Oxford and the founder of ‘Oxford Realism’, a philosophical movement that flourished at Oxford during the first decades of the 20th century. Although trained as a classicist and a mathematician, his most important contribution was to the theory of knowledge, where he argued that knowledge is factive and not definable in terms of belief, and he criticized ‘hybrid’ and ‘externalist’ accounts. He also argued for direct realism in perception, (...) criticizing both empiricism and idealism, and argued for a moderate nominalist view of universals as being in rebus and only ‘apprehended’ by their particulars. His influence helped swaying Oxford away from idealism and, through figures such as H. A. Prichard, Gilbert Ryle, or J. L. Austin, his ideas were also to some extent at the origin of ‘moral intuitionism’ and ‘ordinary language philosophy’ which defined much of Oxford philosophy until the second half of the twentieth-century. Nevertheless, his name and legacy were all but forgotten for generations after World War II. Still, his views on knowledge are with us today, being in part at work in the writings of philosophers as diverse as John McDowell, Charles Travis, and Timothy Williamson. (shrink)

Much of the philosophical literature on causation has focused on the concept of actual causation, sometimes called token causation. In particular, it is this notion of actual causation that many philosophical theories of causation have attempted to capture.2 In this paper, we address the question: what purpose does this concept serve? As we shall see in the next section, one does not need this concept for purposes of prediction or rational deliberation. What then could the purpose be? We will argue (...) that one can gain an important clue here by looking at the ways in which causal judgments are shaped by people‘s understanding of norms. (shrink)

We show how an epistemology informed by cognitive science promises to shed light on an ancient problem in the philosophy of mathematics: the problem of exactness. The problem of exactness arises because geometrical knowledge is thought to concern perfect geometrical forms, whereas the embodiment of such forms in the natural world may be imperfect. There thus arises an apparent mismatch between mathematical concepts and physical reality. We propose that the problem can be solved by emphasizing the ways in which the (...) brain can transform and organize its perceptual intake. It is not necessary for a geometrical form to be perfectly instantiated in order for perception of such a form to be the basis of a geometrical concept. (shrink)

Why do we represent the world around us using causal generalizations, rather than, say, purely statistical generalizations? Do causal representations contain useful additional information, or are they merely more efficient for inferential purposes? This paper considers the second kind of answer: it investigates some ways in which causal cognition might aid us not because of its expressive power, but because of its organizational power. Three styles of explanation are considered. The first, building on the work of Reichenbach in "The Direction (...) of Time", points to causal representation as especially efficient for predictive purposes in a world containing certain pervasive patterns of conditional independence. The second, inspired by work of Woodward and others, finds causal representation to be an excellent vehicle for representing all-important relations of manipulability. The third, based in part on my own work, locates the importance of causal cognition in the special role it reserves for information about underlying mechanisms. All three varieties of explanation show promise, but particular emphasis is placed on the third. (shrink)

An overview of how mechanisms work in explanations.

In evolutionary biology changes in population structure are explained by citing trait fitness distribution. I distinguish three interpretations of fitness explanations—the Two‐Factor Model, the Single‐Factor Model, and the Statistical Interpretation—and argue for the last of these. These interpretations differ in their degrees of causal commitment. The first two hold that trait fitness distribution causes population change. Trait fitness explanations, according to these interpretations, are causal explanations. The last maintains that trait fitness distribution correlates with population change but does not cause (...) it. My defense of the Statistical Interpretation relies on a distinctive feature of causation. Causes conform to the Sure Thing Principle. Trait fitness distributions, I argue, do not. *Received July 2009; revised October 2009. †To contact the author, please write to: Department of Philosophy/Institute for the History, Philosophy of Science and Technology, University of Toronto, Victoria College, 91 Charles Street West, Toronto, ON M5S 1K7, Canada; e‐mail: [email protected]. (shrink)

Today, mechanisms and mechanistic explanation are very popular in philosophy of science and are deemed a welcome alternative to laws of nature and deductive‐nomological explanation. Starting from Mitchell's pragmatic notion of laws, I cast doubt on their status as a genuine alternative. I argue that (1) all complex‐systems mechanisms ontologically must rely on stable regularities, while (2) the reverse need not hold. Analogously, (3) models of mechanisms must incorporate pragmatic laws, while (4) such laws themselves need not always refer to (...) underlying mechanisms. Finally, I show that Mitchell's account is more encompassing than the mechanistic account *Received August 2008; revised January 2010. †To contact the author, please write to: Centre for Logic and Philosophy of Science, Ghent University, Blandijnberg 2, B‐9000 Belgium; e‐mail: [email protected]. (shrink)

What conception of causation is at work in the law? I argue that the law implicitly relies on a contrastive conception. In a liability case where the defendant's breach of duty must be shown to have caused the plaintiff's damages, it is not enough to consider what would have happened if the cause had not occurredthe law requires us to look to a specific replacement for the effect, which in this case is the hypothetical outcome in which the plaintiff came (...) off better. In place of I suggest the more explicit An explicitly contrastive approach can thus potentially help the lawyer phrase her causal question in a more explicit way, while shedding light on our conception of causation. (shrink)

A common argument against explanatory reductionism is that higher‐level explanations are sometimes or always preferable because they are more general than reductive explanations. Here I challenge two basic assumptions that are needed for that argument to succeed. It cannot be assumed that higher‐level explanations are more general than their lower‐level alternatives or that higher‐level explanations are general in the right way to be explanatory. I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at different (...) levels are preferable in different circumstances because they offer different types of generality, which are appropriate in different circumstances of explanation. (shrink)

Much of the modern philosophy of causation has been governed by two ideas: (i) causes make their effects inevitable; (ii) a cause is something that makes a difference to whether its effect occurs. I focus on explaining the origin of idea (ii) and its connection to (i). On my view, the frequent attempts to turn (ii) into an analysis of causation are wrongheaded. Patterns of difference-making aren't what makes causal claims true. They merely provide a useful test for causal claims. (...) Moreover, what justifies us in using them as a test is idea (i). That's how (i) and (ii) are connected. (shrink)

Laws in the special sciences are usually regarded to be non-universal. A theory of laws in the special sciences faces two challenges. (I) According to Lange's dilemma, laws in the special sciences are either false or trivially true. (II) They have to meet the ?requirement of relevance?, which is a way to require the non-accidentality of special science laws. I argue that both challenges can be met if one distinguishes four dimensions of (non-) universality. The upshot is that I argue (...) for the following explication of special science laws: L is a special science law just if (1) L is a system law, (2) L is quasi-Newtonian, and (3) L is minimally invariant. (shrink)

It has often been suggested that people’s ordinary capacities for understanding the world make use of much the same methods one might find in a formal scientific investigation. A series of recent experimental results offer a challenge to this widely-held view, suggesting that people’s moral judgments can actually influence the intuitions they hold both in folk psychology and in causal cognition. The present target article distinguishes two basic approaches to explaining such effects. One approach would be to say that the (...) relevant competencies are entirely non-moral but that some additional factor (conversational pragmatics, performance error, etc.) then interferes and allows people’s moral judgments to affect their intuitions. Another approach would be to say that moral considerations truly do figure in workings of the competencies themselves. It is argued that the data available now favor the second of these approaches over the first. (shrink)

The main focus of this paper is the question as to what it is for an individual to think of her environment in terms of a concept of causation, or causal concepts, in contrast to some more primitive ways in which an individual might pick out or register what are in fact causal phenomena. I show how versions of this question arise in the context of two strands of work on causation, represented by Elizabeth Anscombe and Christopher Hitchcock, respectively. I (...) then describe a central type of reasoning that, I suggest, a subject has to be able to engage in, if we are to credit her with causal concepts. I also point out that this type of reasoning turns on the idea of a physical connection between cause and effect, as articulated in recent singularist approaches of causation. (shrink)

Moral philosophers are, among other things, in the business of constructing moral theories. And moral theories are, among other things, supposed to explain moral phenomena. Consequently, one’s views about the nature of moral explanation will influence the kinds of moral theories one is willing to countenance. Many moral philosophers are (explicitly or implicitly) committed to a deductive model of explanation. As I see it, this commitment lies at the heart of the current debate between moral particularists and moral generalists. In (...) this paper I argue that we have good reasons to give up this commitment. In fact, I show that an examination of the literature on scientific explanation reveals that we are used to, and comfortable with, non-deductive explanations in almost all areas of inquiry. As a result, I argue that we have reason to believe that moral explanations need not be grounded in exceptionless moral principles. (shrink)

The notion of ‘causal web’ emerged in the epidemiological literature in the early Sixties and had to wait until the Nineties for a thorough critical appraisal. Famously, Nancy Krieger argued that such a notion isn’t helpful unless we specify what kind of spiders create the webs. This means, according to Krieger, (i) that the role of the spiders is to provide an explanation of the yarns of the web and (ii) that the sought spiders have to be biological and social. (...) This paper contributes to the development of the notion of causal web, elaborating on the two following points: (i) to catch the spiders we need multi-fold evidence—specifically, mechanistic and difference-making—and (ii) for the eco-social to be explanatory, the web has to be mechanistic in a sense to be specified. (shrink)

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in contradiction. The second variety offers (...) a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations. (shrink)

The first part of this paper presents an argument showing that the currently most highly acclaimed interventionist theory of causation, i.e. the one advanced by Woodward, excludes supervening macro properties from having a causal influence on effects of their micro supervenience bases. Moreover, this interventionist exclusion argument is demonstrated to rest on weaker premises than classical exclusion arguments. The second part then discusses a weakening of interventionism that Woodward suggests. This weakened version of interventionism turns out either to be inapplicable (...) to cases of downward causation involving supervening macro properties or to render corresponding causal claims meaningless. In sum, the paper argues that, contrary to what many non-reductive physicalists claim, interventionism does not render non-reductive physicalism immune to the problem of causal exclusion. (shrink)

Among philosophers, controversy over the notion of drift in population genetics is ongoing. This is at least partly because the notion of drift has an ambiguous usage among population geneticists. My goal in this paper is to explicate the causal dimension of drift, to say what causal influences are responsible for the stochasticity in population genetics models. It is commonplace for population genetics to oppose the influence of selection to that of drift, and to consider how the dynamics of populations (...) are altered when each has greater or lesser influence. I define the causes that are referred to as drift when researchers speak this way. Introduction Populations and Variant Types The Cause–Effect Ambiguity of Drift Non-directional Factors in Population Genetics How N ev Is Used in Population Genetics Causal Conceptions of Drift 6.1 The Millstein/Beatty conception of drift 6.2 Rosenberg and Bouchard: Drift as initial conditions NINPICs 7.1 Why drift is instituted by NINPICs 7.2 How NINPICS work 7.3 NINPICs and random sampling 7.4 Independent sampling and effective population size 7.5 Variance in progeny number 7.6 Population effects of NINPICs NINPICs and the Stochastic Character of Selection Theory Conclusion Appendix CiteULike Connotea Del.icio.us What's this? (shrink)

This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...) David Lewis’ notion of “influence” and also with the extent to which a causal relation approximates to the ideal of one cause–one effect. Interrelations among these notions and their possible biological significance are also discussed. (shrink)

Identity theories are those that hold that 'sensations are brain processes'. In particular, they hold that mental/psychological state kinds are identical to brain/neuroscientific state kinds. In this paper, I isolate and explain some of the key features of contemporary identity theories. They are then contrasted with the main live alternatives by means of considering the two most important lines of objection to identity theories.

We have argued elsewhere that: (A) Natural selection is not a cause of evolution. (B) A resolution-of-forces (or vector addition) model does not provide us with a proper understanding of how natural selection combines with other evolutionary influences. These propositions have come in for criticism recently, and here we clarify and defend them. We do so within the broad framework of our own “hierarchical realization model” of how evolutionary influences combine.

Scientific models invariably involve some degree of idealization, abstraction, or nationalization of their target system. Nonetheless, I argue that there are circumstances under which such false models can offer genuine scientific explanations. After reviewing three different proposals in the literature for how models can explain, I shall introduce a more general account of what I call model explanations, which specify the conditions under which models can be counted as explanatory. I shall illustrate this new framework by applying it to the (...) case of Bohr's model of the atom, and conclude by drawing some distinctions between phenomenological models, explanatory models, and fictional models. (shrink)

We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) “neuron” and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial system state since state changes are relevant, but (...) most current accounts ignore state changes through time; (5) more generally, there is no reason to think that philosophical judgements about these sorts of cases are normative; but (6) there is a dearth of relevant psychological research that bears on whether various philosophical accounts are descriptive. Our skepticism is not directed towards the possibility of a correct account of actual causation; rather, we argue that standard methods will not lead to such an account. A different approach is required. Once upon a time a hungry wanderer came into a village. He filled an iron cauldron with water, built a fire under it, and dropped a stone into the water. “I do like a tasty stone soup” he announced. Soon a villager added a cabbage to the pot, another added some salt and others added potatoes, onions, carrots, mushrooms, and so on, until there was a meal for all. (shrink)

Community ecology entered the 1970s with the belief that niche theory would supply a general theory of community structure. The lack of wide-spread empirical support for niche theory led to a focus on models specific to classes of communities such as lakes, intertidal communities, and forests. Today, the needs of conservation biology for metrics of “ecological health” that can be applied across types of communities prompts a renewed interest in the possibility of general theory for community ecology. Disputes about the (...) existence of general patterns in community structure trace at least to the 1920s and continue today almost unchanged in concept, although now expressed through mathematical modeling. Yet, a new framework emerged in the 1980s from findings that community composition and structure depend as much on the processes that bring species to the boundaries of a community as by processes internal to a community, such as species interactions and co-evolution. This perspective, termed “supply-side ecology”, argued that community ecology was to be viewed as an “organic earth science” more than as a biological science. The absence of a general theory of the earth would then imply a corresponding absence of any general theory for the communities on the earth, and imply that the logical structure of theoretical community ecology would consist of an atlas of models special to place and geologic time. Nonetheless, a general theory of community ecology is possible similar in form to the general theory for evolution if the processes that bring species to the boundary of a community are analogized to mutation, and the processes that act on the species that arrive at a community are analogized to selection. All communities then share some version of this common narrative, permitting general theorems to be developed pertaining to all ecological communities. Still, the desirability of a general theory of community ecology is debatable because the existence of a general theory suppresses diversity of thought even as it allows generalizations to be derived. The pros and cons of a general theory need further discussion. (shrink)

Philosophers of science have developed an account of causal-mechanical explanation that captures regularity, but this account neglects variation. In this article I amend the philosophy of mechanisms to capture variation. The task is to explicate the relationship between regular causal mechanisms responsible for individual development and causes of variation responsible for variation in populations. As it turns out, disputes over this relationship have rested at the heart of the nature–nurture debate. Thus, an explication of the relationship between regular causal mechanisms (...) and causes of variation and between individual development and variation offers both the necessary amendment to the philosophy of mechanisms and the resources to mediate the dispute. (shrink)

Jaegwon Kim’s supervenience/exclusion argument attempts to show that non-reductive physicalism is incompatible with mental causation. This influential argument can be seen as relying on the following principle, which I call “the piggyback principle”: If, with respect to an effect, E, an instance of a supervenient property, A, has no causal powers over and above, or in addition to, those had by its supervenience base, B, then the instance of A does not cause E (unless A is identical with B). In (...) their “Epiphenomenalism: The Dos and the Don’ts,” Larry Shapiro and Elliott Sober employ a novel empirical approach to challenge the piggyback principle. Their empirical approach pulls from the experiments of August Weismann regarding the inheritance of acquired characteristics. Through an examination of Weismann’s experiments, Shapiro and Sober extract lessons in reasoning about the epiphenomenalism of a property. And according to these empirically drawn lessons, the piggyback principle is a don’t. My primary aim in this paper is to defend the piggyback principle against Shapiro and Sober’s empirical approach. (shrink)

All univocal analyses of causation face counterexamples. An attractive response to this situation is to become a pluralist about causal relationships. "Causal pluralism" is itself, however, a pluralistic notion. In this article, I argue in favor of pluralism about concepts of cause in the social sciences. The article will show that evidence for, inference from, and the purpose of causal claims are very closely linked. Key Words: causation • pluralism • evidence • methodology.

Causal claims are context sensitive. According to the old orthodoxy (Mackie 1974, Lewis 1986, inter alia), the context sensitivity of causal claims is all due to conversational pragmatics. According to the new contextualists (Hitchcock 1996, Woodward 2003, Maslen 2004, Menzies 2004, Schaffer 2005, and Hall ms), at least some of the context sensitivity of causal claims is semantic in nature. I want to discuss the prospects for causal contextualism, by asking why causal claims are context sensitive, what they are sensitive (...) to, and where they are sensitive to it. (shrink)

Throughout the 1990s, Jaegwon Kim developed a line of argument that what purport to be nonreductive forms of physicalism are ultimately untenable, since they cannot accommodate the causal efficacy of mental states. His argument has received a great deal of discussion, much of it critical. We believe that, while the argument needs some tweaking, its basic thrust is sound. In what follows, we will lay out our preferred version of the argument and highlight its essential dependence on a causal-powers metaphysic, (...) a dependence that Kim does not acknowledge in his official presentations of the argument.i We then discuss two recent physicalist strategies for preserving the causal efficacy of the mental in the face of this sort of challenge, strategies that (ostensibly) endorse a causal powers metaphysics of properties while offering distinctive accounts of the physical realization of mental properties. We argue that neither picture can be satisfactorily worked out, and that seeing why they fail strongly suggests that nonreductive physicalism and a causal powers metaphysic are not compatible, as our original argument contends. Since we also believe that robust realism concerning mental causation should not be abandoned, we take the argument of this paper to strongly motivate an account on which the mental is unrealized by and ontologically emergent from the physical. In a final section, we sketch what an ontologically emergentist account of the mental might look like. (shrink)

, whereby some causes are deemed more important than others, are ubiquitous in historical studies. Drawing from influential recent work on causation, I develop a definition of causal-explanatory strength. This makes clear exactly which aspects of explanatory weighting are subjective and which objective. It also sheds new light on several traditional issues, showing for instance that: underlying causes need not be more important than proximate ones; several different causes can each be responsible for most of an effect; small causes need (...) not be less important than big ones; and non-additive interactive effects between causes present no particular difficulty. Key Words: causation • explanation • history • interaction • proximate • underlying. (shrink)

The goal of this paper is to encourage a reconfiguration of the discussion about typology in biology away from the metaphysics of essentialism and toward the epistemology of classifying natural phenomena for the purposes of empirical inquiry. First, I briefly review arguments concerning ‘typological thinking’, essentialism, species, and natural kinds, highlighting their predominantly metaphysical nature. Second, I use a distinction between the aims, strategies, and tactics of science to suggest how a shift from metaphysics to epistemology might be accomplished. Typological (...) thinking can be understood as a scientific tactic that involves representing natural phenomena using idealizations and approximations, which facilitates explanation, investigation, and theorizing via abstraction and generalization. Third, a variety of typologies from different areas of biology are introduced to emphasize the diversity of this representational reasoning. One particular example is used to examine how there can be epistemological conflict between typology and evolutionary analysis. This demonstrates that alternative strategies of typological thinking arise due to the divergent explanatory goals of researchers working in different disciplines with disparate methodologies. I conclude with several research questions that emerge from an epistemological reconfiguration of typology. (shrink)

Bionic technologies connecting biological nervous systems to computer or robotic devices for therapeutic purposes have been recently claimed to provide novel experimental tools for the investigation of biological mechanisms. This claim is examined here by means of a methodological analysis of bionics-supported experimental inquiries on adaptive sensory-motor behaviours. Two broad classes of bionic systems (regarded here as hybrid simulations of the target biological system) are identified, which differ from each other according to whether a component of the biological target system (...) is replaced by an artificial component, or else a component of an artificial system is replaced by a biological component. The role of these hybrid systems in the modelling of adaptive sensory-motor biological behaviours is discussed with reference to bionics-supported experiments on the mechanisms of body stabilization in lampreys. Methodological problems emerging from these case studies often arise in computer-based and biorobotic simulations of biological behaviours too. Accordingly, the present analysis contributes to identifying a more general regulative methodological framework for the machine-based modelling of biological systems. (shrink)

The generalizations found in biology, psychology, sociology, and other high-level sciences are typically physically contingent. You might conclude that they play only a limited role in scientific investigation, on the grounds that physically contingent generalizations offer no or only feeble counterfactual support. But the link between contingency and counterfactual support is more complex than is commonly supposed. A certain class of physically contingent generalizations, comprising many, perhaps the vast majority, of those in the high-level sciences, provides strong counterfactual support of (...) just the sort that appears to be scientifically important. This paper explains why. (shrink)

An influential line of thought in metaphysics holds that where common sense discerns a tree or a dog or a baseball there may be just many microparticles. Provided the microparticles are arranged in the right way—are “treewise” or “dogwise” or “baseballwise” arranged—our sensory experiences will be just the same as if a tree or dog or baseball were really there. Thereforewhetherthere really are such familiar objects in the world can be decided only by determining whatmoreis needed for microparticles dogwise arranged (...) actually tocomposea dog. This paper argues that this line of thought sets up the wrong agenda. Composition is trivial; dogwise (etc.) arrangement is tricky. Dogwise arrangement will obtain in the wrong regions unless we stipulate that there are dogs, and that dogwise arrangement obtains only within their borders. The bearers of dogwise arrangement, moreover, will have to be dogs themselves, not their microparticles. Thus allowing that dogwise arrangement obtains at all is allowing that there are dogs. (shrink)

The use of unrealistic assumptions in Economics is usually defended not only for pragmatic reasons, but also because of the intrinsic difficulties in determining the degree of realism of assumptions. Additionally, the criterion used for evaluating economic models is associated with their ability to provide accurate predictions. This mode of thought involves –at least implicitly– a commitment to the existence of unvarying invariant factors or regularities. Contrary to this, the present paper presents a critique to the use of invariant knowledge (...) in economics. One reason for this analysis lies in the fact that economic phenomena are not compatible with the logic of invariance, but with the logic of "possibility trees" or "open-ended results". The other reason is that the use of invariant knowledge may entail both external validity problems and negative exposures to a "black swan". Alternatively, an approach where models are understood as possible scenarios is proposed. It is argued that the realism of assumptions is crucial here, since it helps to ascertain the degree of resemblance between the different models and the target system. (shrink)

The dominant view among macroeconomists is that macroeconomics reduces to microeconomics, both in the sense that all macroeconomic phenomena arise out of microeconomic phenomena and in the sense that macroeconomic theory—to the extent that it is correct—can be derived from microeconomic theory. More than that, the dominant view believes that macroeconomics should in practice use the reduced microeconomic theory: this is the program of microfoundations for macroeconomics to which the vast majority of macroeconomists adhere. The "microfoundational" models that they actually (...) employ are, however, characterized by another feature: they are highly idealized, even when they are applied as direct characterizations of actual data, which itself consists of macroeconomic aggregates. This paper explores the interrelationship between reductionism and idealization in the microfoundational program and the role of idealization in empirical modeling. (shrink)