This paper advances the thesis of methodological mechanism, the claim that to be committed to mechanism is to adopt a certain methodological postulate, i.e. to look for causal pathways for the phenomena of interest. We argue that methodological mechanism incorporates a minimal account of understanding mechanisms, according to which a mechanism just is a causal pathway described in the language of theory. In order to argue for this position we discuss a central example of a biological mechanism, the mechanism of (...) cell death, known as apoptosis. We argue that this example shows that our philosophically deflationary account is sufficient in order to have an illuminating account of mechanisms as the concept is used in biology. (shrink)

ABSTRACT: Whereas relevance in scientific explanations is usually discussed as if it was a single problem, several criteria of relevance will be distinguished in this paper. Emphasis is laid upon the notion of intra-scientific relevance, which is illustrated using explanation of the law of areas as an example. Traditional accounts of explanation, such as the causal and unificationist accounts, are analyzed against these criteria of relevance. Particularly, it will be shown that these accounts fail to indicate which explanations fulfill the (...) condition of intra-scientific relevance. Finally, the significance of this latter criterion is emphasized, and the epistemic benefits of explanations that fulfill it are highlighted. (shrink)

Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has (...) examined Ned Hall’s distinction between two concepts of causality: production and dependence. In another recent paper, Illari examined the relatively under-explored production approach to causality, arguing that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible account of the nature of the causal link in biomarkers research, while an informational account is very promising. (shrink)

A common objection against deflationist theories of truth is that they cannot do justice to the correspondence intuition, i.e. the intuition that there is an explanatory relationship between, for instance, the truth of ‘Snow is white’ and snow's being white. We scrutinize two attempts to meet this objection and argue that both fail. We then propose a new response to the objection which, first, sheds doubt on the correctness of the correspondence intuition and, second, seeks to explain how we may (...) nonetheless have come to have that intuition. (shrink)

ABSTRACT: According to a traditional account, understanding why X occurred is equivalent to knowing that X was caused by Y. This paper defends the account against a major objection, viz., knowing-that is not sufficient for understanding-why, for understanding-why requires a kind of grasp while knowledge-that does not. I discuss two accounts of grasp in recent literature and argue that if either is true, then knowing that X was caused by Y entails at least a rudimentary understanding of why X occurred. (...) If my defense is successful, it would cast doubt on an influential account of the epistemic value of understanding. (shrink)

In this paper, I discuss Michael Moore’s and Jonathan Schaffer’s views on the ontology of omissions in context of their stances on the problem of omissive causation. First, I consider, from a general point of view, the question of the ontology of omissions, and how it relates to the problem of omissive causation. Then I describe Moore’s and Schaffer’s particular views on omissions and how they combine with their stances on the problem of omissive causation. I charge Moore and Schaffer (...) with inconsistencies and insufficiencies within their overall theories, and consider their replies. Finally, I propose my own view on the ontology of omissions and solution to the problem of omissive causation. (shrink)

Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...) for explanation, and as such which types of models can and cannot provide explanations. Explanatory monists argue that one goal will be explanatory in all contexts, while explanatory pluralists argue that the goal will vary based on pragmatic considerations. In this paper, I argue that such debates are misguided, and that both monists and pluralists are incorrect. Instead of any goal being given explanatory priority over others in a given context, the different goals are all deeply dependent on one another for their explanatory power. Any model that sacrifices some explanatory goals to attain others will always necessarily undermine its own explanatory power in the process. And so when forced to choose between individual scientific models, there can be no explanatory victors. Given that no model can satisfy all the goals typically associated with explanation, no one model in isolation can provide a good scientific explanation. Instead we must appeal to collections of models. Collections of models provide an explanation when they satisfy the web of interconnected goals that justify the explanatory power of one another. (shrink)

City College of New York The hereditarian theory of race differences in IQ was briefly revived with the appearance of The Bell Curve but then quickly dismissed. The authors attempt a defense of it here, with an eye to conceptual and logical issues of special interests to philosophers, such as alleged infirmities in the heritability concept. At the same time, some relevant post-Bell Curve empirical data are introduced.

Philosophers have used the probabilistic relation of ’screening-off‘ to explicate concepts in the theories of causation and explanation. Brandon has used screening-off relations in an attempt to reconstruct an argument of Mayr and Gould that natural selection acts at the level of the organism. I argue that Brandon‘s reconstruction is unsuccessful.

In recent years, there has been a philosophical cottage industry producing arguments that our concept of causation is not univocal: that there are in fact two concepts of causation, corresponding to distinct species of causal relation. Papers written in this tradition have borne titles like “Two Concepts of Cause” and “Two Concepts of Causation”. With due apologies to Charles Dickens, I hereby make my own contribution to this genre.

Antecedent-strengthening, a trivially valid inference of classical logic of the form: P → Q ⊨ → Q, has a counterpart in everyday reasoning that often fails. A plausible solution to the problem involves assuming an implicit ceteris paribus qualifier that can be explicated as an additional conjunct in the antecedent of the premise. The qualifier can be explicated as ‘everything else relevant remains unchanged’ or alternatively as ‘nothing interferes’. The qualifier appears most prominently in the context of the discussion of (...) laws in the sciences, where these laws are often expressed with a CP qualifier. From an analysis of the qualifier’s role in the problem of antecedent-strengthening, we can learn more about CP qualifiers in general and in their application to the laws used in the sciences. (shrink)

The following article treats the 'applicational turn' of modern fluid dynamics as it set in at the beginning of the 20th century with Ludwig Prandtl's concept of the boundary layer. It seeks to show that there is much more to applying a theory in a highly mathematical field like fluid dynamics than deriving a special case from a general explanatory theory under particular antecedent conditions. In Prandtl's case, the decisive move was to introduce a model that provided a physical/causal conception (...) of viscous flow at high Reynolds numbers. It facilitated an approximate solution to the Navier-Stokes equations, which in turn gave rise to many special applications. After a detailed account of Prandtl's achievement, the article discusses the role of the physical model and its experimental and mathematical significance. It is shown that the mathematical simplification provided by the physical model greatly expanded the explanatory capacity of the theory which the Navier-Stokes equations alone could not provide. (shrink)

In my 1984 book on The Foundations of Psychoanalysis, I addressed two main questions: Are the analyst’s observations in the clinical setting reliable as ‘data,’ and if so, can they actually support the major hypotheses of the theory of repression or psychic conflict, which is the cornerstone of the psychoanalytic edifice, as we know? In the book, I argued for giving a negative answer to both of these questions. Clearly, if the evidence from the couch is unreliable from the outset, (...) then this defect alone suffices to jeopardize the very foundations of the clinical theory. But, as I strongly emphasized, even if clinical data were not contaminated by the analyst’s influence, the inability of the psychoanalytic method of clinical investigation by free association to warrant the required sort of causal inferences leaves the major pillars of the theory of psychic conflict ill-supported. Thus, I see a two-fold threat to the psychoanalytic case-study method as a means of scientific inquiry.It is an immediate corollary of my challenge that it applies not only to Freud’s own original hypotheses, but also to any and all post-Freudian versions of psychoanalysis that rely on his clinical methods of validating causal inferences, though the specific content of their theories of psychic conflict is different. After all, the alteration in the content of the hypotheses hardly makes their validation more secure. Therefore, as Morris Eagle documented in a recent publication, those analysts who have objected to my critique as anachronistic have simply not come to grips with it. For example, such inadequate engagement is present, in my view, in the recent Freud Anniversary Lecture ‘Psychoanalysis as a Science: A Response to the New Challenges,’ given by Robert Wallerstein, the current president of the International Psychoanalytical Association. As he tells us, ‘The Freud Anniversary Lecture was intended primarily as a response to Grünbaum.’ Yet he does not come to grips at all with the gravamen of my challenge: Even if clinical data could be taken at face value as being uncontaminated epistemically, the inability of the psychoanalytic method of clinical investigation by free association to warrant causal inferences leaves the major pillars of the clinical theory of repression ill-supported. (shrink)

It is often claimed that artificial society simulations contribute to the explanation of social phenomena. At the hand of a particular example, this paper argues that artificial societies often cannot provide full explanations, because their models are not or cannot be validated. Despite that, many feel that such simulations somehow contribute to our understanding. This paper tries to clarify this intuition by investigating whether artificial societies provide potential explanations. It is shown that these potential explanations, if they contribute to our (...) understanding, considerably differ from potential causal explanations. Instead of possible causal histories, simulations offer possible functional analyses of the explanandum . The paper discusses how these two kinds explanatory strategies differ, and how potential functional explanations can be appraised. (shrink)

This paper argues for several related theses. First, the epistemological position that knowledge requires safe belief can be motivated by views in the philosophy of science, according to which good explanations show that their explananda are robust. This motivation goes via the idea—recently defended on both conceptual and empirical grounds—that knowledge attributions play a crucial role in explaining successful action. Second, motivating the safety requirement in this way creates a choice point—depending on how we understand robustness, we'll end up with (...) different conceptions of safety in epistemology. Lastly, and most controversially, there's an attractive choice at this point that will not vindicate some of the most influential applications of the safety-theoretic framework in epistemology, e.g., Williamson's arguments against the KK principle, and luminosity. (shrink)

We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...) construct new causal maps and that their learning is consistent with the Bayes net formalism. (shrink)

Why should a citizen vote? There are two ways to interpret this question: in a prudential sense, and in a moral sense. Under the first interpretation, the question asks why—or under what circumstances—it is in a citizen's self-interest to vote. Under the second interpretation, it asks what moral reasons citizens have for voting. I shall mainly try to answer the moral version of the question, but my answer may also, in some circumstances, bear on the prudential question. Before proceeding to (...) my own approach, let me briefly survey alternatives in the field. (shrink)

An influential tradition in the philosophy of causation has it that all token causal facts are, or are reducible to, facts about difference-making. Challenges to this tradition have typically focused on pre-emption cases, in which a cause apparently fails to make a difference to its effect. However, a novel challenge to the difference-making approach has recently been issued by Alyssa Ney. Ney defends causal foundationalism, which she characterizes as the thesis that facts about difference-making depend upon facts about physical causation. (...) She takes this to imply that causation is not fundamentally a matter of difference-making. In this paper, I defend the difference-making approach against Ney’s argument. I also offer some positive reasons for thinking, pace Ney, that causation is fundamentally a matter of difference-making. (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)

Recent papers by a number of philosophers have been concerned with the question of whether natural selection is a causal process, and if it is, whether the causes of selection are properties of individuals or properties of populations. I shall argue that much confusion in this debate arises because of a failure to distinguish between causal productivity and causal relevance. Causal productivity is a relation that holds between events connected via continuous causal processes, while causal relevance is a relationship that (...) can hold between a variety of different kinds of facts and the events that counterfactually depend upon them. I shall argue that the productive character of natural selection derives from the aggregation of individual processes in which organisms live, reproduce and die. At the same time, a causal explanation of the distribution of traits will necessarily appeal both to causally relevant properties of individuals and to causally relevant properties that exist only at the level of the population. (shrink)

In this paper I offer an analysis of causation based upon a theory of mechanisms-complex systems whose internal parts interact to produce a system's external behavior. I argue that all but the fundamental laws of physics can be explained by reference to mechanisms. Mechanisms provide an epistemologically unproblematic way to explain the necessity which is often taken to distinguish laws from other generalizations. This account of necessity leads to a theory of causation according to which events are causally related when (...) there is a mechanism that connects them. I present reasons why the lack of an account of fundamental physical causation does not undermine the mechanical account. (shrink)

Most philosophical accounts of causation take causal relations to obtain between individuals and events in virtue of nomological relations between properties of these individuals and events. Such views fail to take into account the consequences of the fact that in general the properties of individuals and events will depend upon mechanisms that realize those properties. In this paper I attempt to rectify this failure, and in so doing to provide an account of the causal relevance of higher-level properties. I do (...) this by critiquing one prominent model of higher-level properties—Kim’s functional model of reduction—and contrasting it with a mechanistic approach to higher-level properties and causation. (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)

I argue that transference is, ultimately, identity over time, and that identity over time can't possibly be causation. Transference, then, fails as an analysis of causation.

The paper argues for a pragmatic account of genetic explanation. This is to say that when a disease or other trait is termed genetic, the reasons for singling out genes as causes over other, also necessary, genetic and nongenetic conditions are not wholly theoretical but include pragmatic dimensions. Whether the explanation is the presence of a trait in an individual or differences in a trait among individuals, genetic explanations are context-dependent in three ways: they are relative to a causal background (...) of genetic and nongenetic factors; they are relative to a population; and they are relative to the present state of knowledge. Criteria like causal priority, nonstandardness, and causal efficacy that purport to distinguish objectively between genetic causes and nongenetic conditions either incorporate pragmatic elements or fail for other reasons. When the pragmatic dimensions of genetic explanations are recognized, we come to understand the current phenomenon of geneticization to be a reflection of increased technological capacities to manipulate genes in the laboratory, and potentially the clinic, rather than theoretical progress in understanding how diseases and other traits arise. This calls into question the value of the search for theoretical definitions of designations like genetic disease or genetic susceptibility as directives for action. (shrink)

I provide a theory of causation within the causal modeling framework. In contrast to most of its predecessors, this theory is model-invariant in the following sense: if the theory says that C caused (didn't cause) E in a causal model, M, then it will continue to say that C caused (didn't cause) E once we've removed an inessential variable from M. I suggest that, if this theory is true, then we should understand a cause as something which transmits deviant or (...) non-inertial behavior to its effect. (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)

Framing systematics as a field consistent with scientific inquiry entails that inferences of phylogenetic hypotheses have the goal of producing accounts of past causal events that explain differentially shared characters among organisms. Linking observations of characters to inferences occurs by way of why-questions implied by data matrices. Because of their form, why-questions require the use of common-cause theories. Such theories in phylogenetic inferences include natural selection and genetic drift. Selection or drift can explain ‘morphological’ characters but selection cannot be causally (...) applied to sequences since fitness differences cannot be directly associated with individual nucleotides or amino acids. The relation of selection to sequence data is by way of downward or top-down causation from those phenotypes upon which selection occurs. The application of phylogenetic inference to explain sequence data is thus restricted to instances where drift is the relevant theory; those nucleotides or amino acids that can be explained via downward causation are precluded from inclusion in the data matrix. The restrictions on the inclusion of sequence data in phylogenetic inferences equally apply to species hypotheses, precluding the more restrictive approach known as DNA barcoding. Not being able to discern drift and selection as relevant causal mechanisms can severely constrain the inclusion and explanations of sequence data. Implications of such exclusion are discussed in relation to the requirement of total evidence. (shrink)

ABSTRACT Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of ‘actual cause’. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation. 1Introduction 2Preemption 3Structural Equation Models 4The Halpern and Pearl Definition of ‘Actual Cause’ 5Preemption Again 6The Probabilistic Case 7Probabilistic Causal Models 8A Proposed Probabilistic Extension of Halpern and Pearl’s Definition 9Twardy and Korb’s Account 10Probabilistic (...) Fizzling 11Conclusion. (shrink)

This paper investigates the relationship between structural explanation and the New Mechanistic account of explanation. The aim of this paper is twofold: firstly, to argue that some phenomena in the domain of fundamental physics, although mechanically brute, are structurally explained; and secondly, by elaborating on the contrast between SE and mechanistic explanation to better clarify some features of SE. Finally, this paper will argue that, notwithstanding their apparently antithetical character, SE and ME can be reconciled within a unified account of (...) general scientific explanation. (shrink)

This essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step involving making (...) counterfactual statements about the model itself and the second step involving making hypothetical statements transferring over claims derived from the model onto the target. To illustrate how this two-step activity proceeds, an agent-based simulation model is discussed. (shrink)

Although scientific realism is the default position in the life sciences, philosophical accounts of realism are geared towards physics and run into trouble when applied to fields such as biology or neuroscience. In this paper, I formulate a new robustness-based version of entity realism, and show that it provides a plausible account of realism for the life sciences that is also continuous with scientific practice. It is based on the idea that if there are several independent ways of measuring, detecting (...) or deriving something, then we are justified in believing that it is real. I also consider several possible objections to robustness-based entity realism, discuss its relationship to ontic structural realism, and show how it has the potential to provide a novel response to the pessimistic induction argument. (shrink)

Philosophical accounts of scientific explanation are broadly divided into ontic and epistemic views. This paper explores the idea that the lexical ambiguity of the verb to explain and its nominalisation supports an ontic conception of explanation (Salmon 1989; Craver 2007). I analyse one argument which challenges this strategy by criticising the claim that explanatory talk is lexically ambiguous (Wright, European Journal of Philosophy of Science 2(3), 375–394, 2012). I propose that the linguistic mechanism of transfer of meaning (Nunberg, Journal of (...) Semantics 12(2), 109–132, 1995) provides a better account of the lexical alternations that figure in the systematic polysemy of explanatory talk, and evaluate the implications of this proposal for the debate between ontic and epistemic conceptions of scientific explanation. (shrink)

A “contrastive explanation” explains not only why some event A occurred, but why A occurred as opposed to some alternative event B. Some philosophers argue that agents could only be morally responsible for their choices if those choices have contrastive explanations, since they would otherwise be “luck infested”. Assuming that contrastive explanations cannot be offered for causally undetermined events, this requirement entails that no one could be held responsible for a causally undetermined choice. Such arguments challenge incompatibilism, since they entail (...) that causal determinism is a prerequisite for moral responsibility. However, I argue that for a significant class of choices, even if we stipulate that they are determined, we will be unable to provide a relevant contrastive explanation. Hence causal determinism is no remedy for luck infestation, and compatibilists do not fare much better than incompatibilists in the face of this requirement. This should serve to weaken its philosophical appeal. (shrink)

During the past decades several philosophers of science and social scientists have been interested in the problems of causation. Recently attention has been given to probabilistic causation in dichotomous causal systems. The paper uses the basic features of probabilistic causation to argue that the causal modeling approaches developed by such researchers as Blalock and Duncan can provide, when an additional assumption is added, adequate qualitative measures of one variableś causal influence upon another. Finally, some of the difficulties and issues involved (...) in developing adequate quantitative measures are discussed, and it is concluded that the causal modeling measures cannot provide adequate quantitative measures. (shrink)

The complexity and heterogeneity of causes influencing ecology’s domain challenge its capacity to generate a general theory without exceptions, raising the question of whether ecology is capable, even in principle, of achieving the sort of theoretical success enjoyed by physics. Weber has argued that competition theory built around the Competitive Exclusion Principle (especially Tilman’s resource-competition model) offers an example of ecology identifying a law-like causal regularity. However, I suggest that as Weber presents it, the CEP is not yet a causal (...) regularity. Instead, I argue that the scientific understanding in Tilman’s theory takes a different form. The theory explains through a structure I call “channeling explanation” which does not depend on deduction from general laws, but rather builds on constraints and trade-offs represented in state-space. Recognizing this structure supports the more general point that ecology and other so-called special sciences can reveal novel theoretical approaches to philosophy of science when approached with openness to their uniqueness. (shrink)