Causation appears to present us with an interpretative difficulty. While arguably a redundant relation given fundamental physics, it is nevertheless apparently pragmatically indispensable. This chapter revisits certain arguments made previously by the author for these claims with the benefit of hindsight, starting with the role of causal models in the human sciences, and attempting to explain why it is not possible to straightforwardly ground such models in fundamental physics. This suggests that further constraints, going beyond physics, are needed to legitimate (...) such models. These supplementary constraints could be reified, but that would seem to conflict with the completeness of physics. A response is to emphasize the practical role of causal talk, and the author suggests that a fictionalist approach might be worth exploring. After clarifying fictionalism as a general approach, they carry out in some detail the project of clarifying what a fictionalist attitude to causation would involve. (shrink)

I argue that trustworthiness is an epistemic desideratum. It does not reduce to justified or reliable true belief, but figures in the reason why justified or reliable true beliefs are often valuable. Such beliefs can be precarious. If a belief's being justified requires that the evidence be just as we take it to be, then if we are off even by a little, the belief is unwarranted. Similarly for reliability. Although it satisfies the definition of knowledge, such a belief is (...) not trustworthy. We ought not use it as a basis for inference or action and ought not give others to believe it. The trustworthiness of a belief, I urge, depends on its being backed by reasons—considerations that other members of the appropriate epistemic community cannot reasonably reject. Trustworthiness is intersubjective. It both depends on and contributes to the evolving cognitive values of an epistemic community. (shrink)

This chapter offers an interpretation of Jaspers’ distinction between explaining and understanding, which relates this distinction to that between general and singular causal claims. Put briefly, I suggest that when Jaspers talks about (mere) explanation, what he has in mind are general causal claims linking types of events. Understanding, by contrast, is concerned with singular causation in the psychological domain. Furthermore, I also suggest that Jaspers thinks that only understanding makes manifest what causation between one element of a person’s mental (...) life and another ultimately consists in – that is, the particular way in which one psychic event can emerge from or arise out of another. I contrast the resulting view both with a view on causation in psychiatry recently put forward by John Campbell, and also with another view that is the target of Campbell’s attack, which is due to Donald Davidson and Daniel Dennett. (shrink)

Causalists and Evidentialists can agree about the right course of action in an (apparent) Newcomb problem, if the causal facts are not as initially they seem. If declining $1,000 causes the Predictor to have placed $1m in the opaque box, CDT agrees with EDT that one-boxing is rational. This creates a difficulty for Causalists. We explain the problem with reference to Dummett's work on backward causation and Lewis's on chance and crystal balls. We show that the possibility that the causal (...) facts might be properly judged to be non-standard in Newcomb problems leads to a dilemma for Causalism. One horn embraces a subjectivist understanding of causation, in a sense analogous to Lewis's own subjectivist conception of objective chance. In this case the analogy with chance reveals a terminological choice point, such that either (i) CDT is completely reconciled with EDT, or (ii) EDT takes precedence in the cases in which the two theories give different recommendations. The other horn of the dilemma rejects subjectivism, but now the analogy with chance suggests that it is simply mysterious why causation so construed should constrain rational action. (shrink)

In her ‘Causality and Determination’, Anscombe argues for the strong thesis that despite centuries of philosophical assumption to the contrary, the supposition that causality and necessity have something essential to do with one another is baseless. In this paper, I assess Anscombe’s arguments and endorse her conclusion. I then attempt to argue that her arguments remain highly relevant today, despite the fact that most popular general views of causation today are firmly probabilistic in orientation and thus show no trace of (...) the assumptions Anscombe hoped to undermine. My suggestion is that Anscombe's interests in causality are distinct from those which mostly animate the modern debate about the general nature of causality and that in those specialized areas of philosophy in which those concerns still dominate, one can still see the effects of the fallacies and confusions to which she alerts us. I conclude by offering two possible complementary explanations of the tendency to suppose that causation is a variety of necessitation. (shrink)

Though pluralism is given a lot of lip service it is not the status quo in psychiatry. In this paper I argue that following the recent Research Domain Criteria project of the National Institute of Mental Health, we run the danger of promoting a reductionist agenda that current evidence and research suggests is not the right way of tackling mental disorders. I further argue that in order to better address the needs of the patients and maintain the ethical standards required (...) in the psychiatric profession we ought to maintain a pluralistic attitude in psychiatric research as well as practice. (shrink)

Kolmogorov''s axiomatization of probability includes the familiarratio formula for conditional probability: 0).$$ " align="middle" border="0">.

Advocates of Causal Decision Theory (CDT) argue that Evidential Decision Theory (EDT) is inadequate because it gives the wrong result in Newcomb problems. Egan (2007) provides a recipe for converting Newcomb problems to counterexamples to CDT, arguing that CDT is inadequate too. Proposed by Edgington (2011), the Conditional Causal Decision Theory (CCDT) is widely taken uncritically in the recent literature as a version of CDT that conforms to the supposedly correct pre-theoretic judgments about the rationality of acts in Newcomb problems (...) and Egan cases. While the renewed attention to the debate between EDT and CDT is mostly focused on how various theories treat Egan cases, this paper scrutinizes Edgington’s treatment of Newcomb problems and argues that, despite Edgington’s promise, CCDT actually fails in Newcomb problems. This, I assume, shows that CCDT is superior neither to the classic visions of CDT nor to EDT. The paper concludes by arguing, in general, that CCDT is systematically bound to deliver the same results as does EDT in any decision problem. Despite being formulated in terms of causal notions, therefore, it collapses back into the classic EDT. (shrink)

This book defends a relational theory of the passage of time. The realist view of passage developed in this book differs from the robust, substantivalist position. According to relationism, passage is nothing over and above the succession of events, one thing coming after another. Causally related events are temporally arranged as they happen one after another along observers’ worldlines. There is no unique global passage but a multiplicity of local passages of time. After setting out this positive argument for relationism, (...) the author deals with five common objections to it: (a) triviality of deflationary passage, (b) a-directionality of passage, (c) the impossibility of experiencing passage, (d) fictionalism about passage, and (e) the incompatibility of passage with perduring objects. (shrink)

Although statistical techniques like regression analysis and path analysis are widely used in the biomedical, behavioral and social sciences to make causal inferences there has been surprisingly little philosophical discussion of the details of such techniques and of the conceptions of causation and explanation implicit in them. There also has been relatively little attempt to compare such techniques with various probabilistic models of causation and explanation in the philosophical literature.In this paper I explore, for reasons of space in a very (...) sketchy and schematic way, some issues in philosophy of science raised by regression analysis. One general conclusion I reach is that it is considerably less obvious than one might suppose that the philosophical theories alluded to above are plausibly viewed as reconstructions of regression techniques. (shrink)

This paper explores the interpretation and use of polygenic risk scores (PRSs). We argue that PRSs generally do not directly embody causal information. Nonetheless, they can assist us in tracking other causal relationships concerning genetic effects. Although their purely predictive/correlational use is important, it is this tracking feature that contributes to their potential usefulness in other applications, such as genetic dissection, and their use as controls, which allow us, indirectly, to "see" more clearly the role of environmental variables.

This paper is an assessment of an attempt, by James Greeno, to measure the explanatory power of statistical theories by means of the notion of transmitted information (It). It is argued that It has certain features that are inappropriate in a measure of explanatory power. In particular, given a statistical theory T with explanans variables St and explanandum variables Mj, it is argued that no plausible measure of explanatory power should depend on the probability P(Si) of occurrence of initial conditions (...) in the systems to which T applies or the magnitudes of the conditional probabilities P(Mj/Si), in the manner in which Ir does. (shrink)

This article defends the use of interventionist counterfactuals to elucidate causal and explanatory claims against criticisms advanced by James Bogen and Peter Machamer. Against Bogen, I argue that counterfactual claims concerning what would happen under interventions are meaningful and have determinate truth values, even in a deterministic world. I also argue, against both Machamer and Bogen, that we need to appeal to counterfactuals to capture the notions like causal relevance and causal mechanism. Contrary to what both authors suppose, counterfactuals are (...) not "unscientific" - a substantial tradition within statistics and the causal modelling literature makes heavy use of them. (shrink)

This essay advocates a “functional” approach to causation and causal reasoning: these are to be understood in terms of the goals and purposes of causal thinking. This approach is distinguished from accounts based on metaphysical considerations or on reconstruction of “intuitions.”.

Analytic Philosophy, Volume 62, Issue 1, Page 33-56, March 2021.

There is a systematic and suggestive analogy between grounding and causation. In my view, this analogy is no coincidence. Grounding and causation are alike because grounding is a type of causation: metaphysical causation. In this paper I defend the identification of grounding with metaphysical causation, drawing on the causation literature to explore systematic connections between grounding and metaphysical dependence counterfactuals, and I outline a non-reductive counterfactual theory of grounding along interventionist lines.

A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1974]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on Pearl ([2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were they to be transmitted only via P. Facts about such effects may (...) be gleaned from the structural equations commonly used to represent the causal relationships among variables. I contrast my analysis of the Hesslow case with those given by theorists of probabilistic causality, who mistakenly link it to issues of causal heterogeneity, token-causation and indeterminism. The reason probabilistic theories misdiagnose this case is that they pay inadequate attention to the structural relationships among variables. (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)

Darwinians are realists about the force of selection, but there has been surprisingly little discussion about what form this realism should take. Arguments about the units of selection in general and genic selectionism in particular reveal two realist assumptions: (1) for any selection process, there is a uniquely correct identification of the operative selective forces and the level at which each impinges; and (2) selective forces must satisfy the Pareto-style requirement of probabilistic causation. I argue that both assumptions are false; (...) we must temper realism about the force of selection and revise the way we think about probabilistic causation. (shrink)

The failure to recognize a correlation as spurious can lead people to adopt strategies to bring about a specific outcome that manipulate something other than a cause of the outcome. However, in a 2008 paper appearing in the journal Analysis, Bert Leuridan, Erik Weber and Maarten Van Dyck suggest that knowledge of spurious correlations can, at least sometimes, justify adopting a strategy aiming at bringing about some change. This claim is surprising and, if true, throws into question the claim of (...) Nancy Cartwright and others that knowledge of laws of association is insufficient for distinguishing effective and ineffective strategies. This paper examines the nature of spurious correlations and their value in crafting strategies for change. The conclusion of the paper is that while knowledge of a spurious correlation may have practical value, the value depends on either having knowledge of the causal structure underlying the correlation or it depends on the use of ‘causal criteria’. (shrink)

Recent articles published in this journal have highlighted the shortcomings of individualistic approaches to health promotion, and the potential contributions of relational analyses of autonomy to public health ethics. I argue that the latter helps to elucidate the former, by showing that an inadequate analysis of autonomy leads to misassignment of both forward-looking and backward-looking responsibility for health outcomes. Health promotion programmes predicated on such inadequate analyses are then ineffective, because they assign responsibility to agents whose social environment inhibits their (...) ability to act on such responsibilities; inequitable, because the social barriers to autonomous agency display a socio-economic gradient; and stigmatizing, because they license blaming of individuals for their own poor health without taking into account how reasonable it is to hold these individuals responsible, given the social barriers to autonomy they face. I further sketch how incorporating a relational understanding of autonomy could help to produce health promotion programmes that do not succumb to these difficulties, while avoiding coercive paternalism, exploring potential applications in ecological approaches to health promotion. (shrink)

The most compelling extant accounts of explanation casts all explanations as causal. Yet there are sciences, theoretical population biology in particular, that explain their phenomena by appeal to statistical, non-causal properties of ensembles. I develop a generalised account of explanation. An explanation serves two functions: metaphysical and cognitive. The metaphysical function is discharged by identifying a counterfactually robust invariance relation between explanans event and explanandum. The cognitive function is discharged by providing an appropriate description of this relation. I offer examples (...) of explanations from portfolio theory and population genetics that meet this characterisation. In each case the invariance relation holds between a statistical property of an ensemble and a change in structure of the ensemble. In neither case, however, does the statistical property cause the outcome it explains. There are genuine statistical, non-causal scientific explanations. (shrink)

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)

Psychiatry is a discipline that deals with both the physical and the mental lives of individuals and though it is true that, largely because of this characteristic, different models are used for different disorders, there is still a remnant tendency towards reductionist views in the field. In this paper I argue that the available empirical evidence from psychiatry gives us reasons to question biological reductionism and that in its place we should adopt a pluralistic explanatory model that is more suited (...) to the needs of the discipline and to the needs of the patients it is meant to help. This will allow us to retain psychiatry as an autonomous science that can productively co-exist with neuroscience while also giving patients the kind of attention they need. I further argue that this same evidence supports a view of the mind that is anti-reductive and that allows that causation can be both bottom-up and top-down and that such a view is available in emergentism coupled with an interventionist model of causation. (shrink)

Causal eliminativists maintain that all causal talk is false. The prospects for such a view seem to be stymied by an indispensability argument, charging that any agent must distinguish between effective and ineffective strategies, and that such a distinction must commit that agent to causal notions. However, this argument has been under-explored. The contributions of this paper are twofold: first, I provide a thorough explication of the indispensability argument and the various ways it might be defended. Second, I point to (...) an important limitation in the argument and suggest that it does not give us sufficient reason to reject eliminativism. In support of this last claim, I show that the distinction between effective and ineffective strategies could perfectly well be grounded in a counterfactual rather than a causal decision theory and argue that there are fully adequate explanations of how we could come to make the requisite counterfactual judgments that need not invoke causal concepts. (shrink)

In the philosophy of causation, manipulationist literature is broadly divided into agency and interventionist accounts. The division between these accounts is partially due to a dispute regarding the meaning of “manipulation”, which specifically questions, “Must one analyse manipulation by appealing to human agency?” This paper attempts to clarify the notion of manipulation and defends the thesis that agency theorists and interventionists analyse manipulation by appealing to human agency. However, following Collingwood's work, I argue that there are two ways to interpret (...) “human agency”. With an extended notion of agency in place, I reveal a pathway towards a consensus between the agency and interventionist accounts. Further, I highlight the alleged discrepancies between agency and interventionist accounts, including the issues of scope and objectivity, and suggest additional pathways towards a consensus. (shrink)

The investigation of probabilistic causality has been plagued by a variety of misconceptions and misunderstandings. One has been the thought that the aim of the probabilistic account of causality is the reduction of causal claims to probabilistic claims. Nancy Cartwright (1979) has clearly rebutted that idea. Another ill-conceived idea continues to haunt the debate, namely the idea that contextual unanimity can do the work of objective homogeneity. It cannot. We argue that only objective homogeneity in combination with a causal interpretation (...) of Bayesian networks can provide the desired criterion of probabilistic causality. (shrink)

In a recent essay, Deery and Nahmias :1255–1276, 2017) utilize interventionism about causation to develop an account of causal sourcehood in order to defend compatibilism about free will and moral responsibility from manipulation arguments. In this paper, we criticize Deery and Nahmias’s analysis of sourcehood by drawing a distinction between two forms of causal invariance that can come into conflict on their account. We conclude that any attempt to resolve this conflict will either result in counterintuitive attributions of moral responsibility (...) or will undermine their response to manipulation arguments. (shrink)

It is widely thought that there is an important argument to be made that starts with premises taken from the science of physics and ends with the conclusion of physicalism. The standard view is that this argument takes the form of a causal argument for physicalism. Roughly, physics tells us that the physical realm is causally complete, and so minds (among other entities) must be physical if they are to interact with the world as we think they do. In what (...) follows, I raise problems for this view. After an initial review of the causal argument, I begin my case by showing that the totality of physical truths do not deductively entail the causal completeness of the physical realm, using a double-prevention scenario and causation by omission to show that nonphysical causes of physical effects would not need to violate physical conservation laws. I then move on to raise problems for an inductive argument for causal completeness by drawing on the neo-Russellian view that there is no causation in fundamental physics, and so causation must itself be a realized or derived entity. I conclude by suggesting that the underlying problem is that the causal argument has fallen out of touch with the sophisticated understanding that philosophers have developed of the role of causation within physics. (shrink)

Explanatory realism is the position that all explanations give information about whatever metaphysically determines the explanandum. This view is popular and plays a central role in metaphysics, but in this paper I argue that explanatory realism is false. In Sect. 1 I introduce explanatory realism in its weak and strong versions, and discuss the argumentative work that explanatory realism is used for in contemporary metaphysics. In Sect. 2 I present a series of problem cases for explanatory realism, including explanation by (...) analogy, explanations involving rules, reduction ad absurdum explanations and certain statistical explanations. In Sect. 3 I consider and reject two modified versions of explanatory realism: the position that explanatory realism is true only of explanation in metaphysics, and the position that determinative explanation is the most complete form of explanation. In conclusion I consider explanatory antirealism and explanatory pluralism as alternatives to explanatory realism. (shrink)

Kerry et al. criticize our discussion of causal knowledge in evidence-based medicine (EBM) and our assessment of the relevance of their dispositionalist ontology for EBM. Three issues need to be addressed in response: (1) problems concerning transfer of causal knowledge across heterogeneous contexts; (2) how predictions about the effects of individual treatments based on population-level evidence from RCTs are fallible; and (3) the relevance of ontological theories like dispositionalism for EBM.

Reasons transmit. If one has a reason to attain an end, then one has a reason to effect means for that end: reasons are transmitted from end to means. I argue that the likelihood ratio (LR) is a compelling measure of reason transmission from ends to means. The LR measure is superior to other measures, can be used to construct a condition specifying precisely when reasons transmit, and satisfies intuitions regarding end-means reason transmission in a broad array of cases.

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. (shrink)

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. 1 Introduction2 Biological Population, Broad and Narrow3 Difficulties with Narrow Biological Population Conditions3.1 Against the genealogical condition3.2 Against the conspecificity condition3.3 Against the proximity condition3.4 Against the typology condition4 Causal Connectivity5 Massively Multidimensional Population Constructs6 Population Uniqueness and Natural Selection6.1 Statisticalism and its discontents6.2 Price at what price?7 Conclusion. (shrink)

In this paper two accounts of Reichenbachian common cause systems are compared. Examples are provided which show that Hofer-Szabó and Rédei account and Hofer-Szabó et al. account is compatible, with but not equivalent, to Mazzola’s. Moreover, the difference of the two accounts with respect to their explanatory adequacy is discussed, in the light of Salmon’s statistical-relevance approach to statistical explanation.

Evidence hierarchies are widely used to assess evidence in systematic reviews of medical studies. I give several arguments against the use of evidence hierarchies. The problems with evidence hierarchies are numerous, and include methodological shortcomings, philosophical problems, and formal constraints. I argue that medical science should not employ evidence hierarchies, including even the latest and most-sophisticated of such hierarchies.

I apply James Woodward’s interventionist theory of causation to organic chemistry, modelling three different ways that chemists are able to manipulate the reaction conditions in order to control the outcome of a reaction. These consist in manipulations to the reaction kinetics, thermodynamics, and whether the kinetics or thermodynamics predominates. It is possible to construct interventionist causal models of all of these kinds of manipulation, and therefore to account for them using Woodward’s theory. However, I show that there is an alternate, (...) more illuminating way of thinking about the third kind of reaction control, according to which chemists are thought of as manipulating which causal system is instantiated. I show that our ability to manipulate which system is instantiated is an important part of our ability to control the world, as is therefore especially relevant to interventionism. Thus, considering examples from organic chemistry leads to the identification of an important extension to Woodward’s theory. Finally, this investigation into reaction control in organic chemistry also has a more general implication: it suggests that interventionism results in a version of pragmatism about causation. (shrink)

Data from medical research are typically summarized with various types of outcome measures. We present three arguments in favor of absolute over relative outcome measures. The first argument is from cognitive bias: relative measures promote the reference class fallacy and the overestimation of treatment effectiveness. The second argument is decision-theoretic: absolute measures are superior to relative measures for making a decision between interventions. The third argument is causal: interpreted as measures of causal strength, absolute measures satisfy a set of desirable (...) properties, but relative measures do not. Absolute outcome measures outperform relative measures on all counts. (shrink)

This paper develops axiomatic foundations for a probabilistic-interventionist theory of causal strength. Transferring methods from Bayesian confirmation theory, I proceed in three steps: I develop a framework for defining and comparing measures of causal strength; I argue that no single measure can satisfy all natural constraints; I prove two representation theorems for popular measures of causal strength: Pearl's causal effect measure and Eells' difference measure. In other words, I demonstrate these two measures can be derived from a set of plausible (...) adequacy conditions. The paper concludes by sketching future research avenues. (shrink)

This is one of a pair of discussion notes comparing some features of the account of causation in Wolfgang Spohn’s Laws of Belief with the “interventionist” account in James Woodward’s Making Things Happen. This note locates the core difference of the accounts in the fact that Woodward’s account follows an epistemological order, while Spohn’s follows a conceptual order. This unfolds in five further differences: type- versus token-level causation, reference to time, actual/counterfactual intervention versus epistemic/suppositional wiggling, a circular versus a circle-free (...) conception of the circumstances of a direct causal relation, and absolute versus model-relative causation. (shrink)

The paper builds on the basically Humean idea that A is a cause of B iff A and B both occur, A precedes B, and A raises the metaphysical or epistemic status of B given the obtaining circumstances. It argues that in pursuit of a theory of deterministic causation this ‘status raising’ is best explicated not in regularity or counterfactual terms, but in terms of ranking functions. On this basis, it constructs a rigorous theory of deterministic causation that successfully deals (...) with cases of overdetermination and pre-emption. It finally indicates how the account's profound epistemic relativization induced by ranking theory can be undone. Introduction Variables, propositions, time Induction first Causation Redundant causation Objectivization. (shrink)

In this paper I want to clarify what biologists are talking about when they talk about the evolution of altruism. I’ll begin by saying something about the common sense concept. This familiar idea I’ll call ‘vernacular altruism.’ One point of doing this is to make it devastatingly obvious that the common sense concept is very different from the concept as it’s used in evolutionary theory. After that preliminary, I’ll describe some features of the evolutionary concept. Then I’ll conclude by briefly (...) considering what explanatory relation might obtain between vernacular altruism and evolutionary altruism. Although the points I’ll make are rather elementary ones, their interest is not restricted to those who have never heard of the evolutionary problem. The reason for this is that there is some amount of confusion about evolutionary altruism among evolutionary biologists themselves. (shrink)

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

In a recent article (Sober 1982), I criticized an account of causation proposed by Giere (1979, 1980) by describing a series of examples concerning natural selection. Collier (1983) has criticized my criticisms, saying that I misapplied Giere's proposal and misconstrued the biology. More recently, Giere (1984) has defended his theory against my criticisms. Here I argue that my criticisms still stand.