Some causalexplanations are non-committal in that mention of a property in the explanans conveys information about the causal origin of the explanandum even if the property in question plays no causal role for the explanandum . Programme explanations are a variety of non-committal causal (NCC) explanations. Yet their interest is very limited since, as I will argue in this paper, their range of applicability is in fact quite narrow. However there is at (...) least another variety of NCC explanations, causal orientation explanations, which offer a plausible model for many explanations in the special sciences. (shrink)
Studies exploring how students learn and understand science processes such as diffusion and natural selection typically find that students provide misconceived explanations of how the patterns of such processes arise (such as why giraffes’ necks get longer over generations, or how ink dropped into water appears to “flow”). Instead of explaining the patterns of these processes as emerging from the collective interactions of all the agents (e.g., both the water and the ink molecules), students often explain the pattern as (...) being caused by controlling agents with intentional goals, as well as express a variety of many other misconceived notions. In this article, we provide a hypothesis for what constitutes a misconceived explanation; why misconceived explanations are so prevalent, robust, and resistant to instruction; and offer one approach of how they may be overcome. In particular, we hypothesize that students misunderstand many science processes because they rely on a generalized version of narrative schemas and scripts (referred to here as a Direct-causal Schema) to interpret them. For science processes that are sequential and stage-like, such as cycles of moon, circulation of blood, stages of mitosis, and photosynthesis, a Direct-causal Schema is adequate for correct understanding. However, for science processes that are non-sequential (or emergent), such as diffusion, natural selection, osmosis, and heat flow, using a Direct Schema to understand these processes will lead to robust misconceptions. Instead, a different type of general schema may be required to interpret non-sequential processes, which we refer to as an Emergent-causal Schema. We propose that students lack this Emergent Schema and teaching it to them may help them learn and understand emergent kinds of science processes such as diffusion. Our study found that directly teaching students this Emergent Schema led to increased learning of the process of diffusion. This article presents a fine-grained characterization of each type of Schema, our instructional intervention, the successes we have achieved, and the lessons we have learned. (shrink)
The relation of teleological to causalexplanations in psychology is examined. Nagel's claim that they are logically equivalent is rejected. Two arguments for their non-equivalence are considered: (i) the impossibility of specifying initial conditions in the case of teleological explanations and (ii) the claim that different kinds of logic are involved. The view that causalexplanations provide only necessary conditions whereas teleological explanations provide sufficient conditions is rejected: causalexplanations can provide sufficient (...) conditions, typically being unable to provide necessary ones, whereas teleological explanations tend to point to necessary features. Nor is a distinction in terms of intensional and extensional logic entirely satisfactory, although there is some support for the view that teleological and causalexplanations invoke different types of explanatory framework. A key feature of teleogical explanation is the achievement of the same goal by a variety of means. Thus its main scientific function is likely to be heuristic rather than predictive. (shrink)
This paper defends my claim in earlier work that certain non-causal conditions are sufficient for the truth of some reasons explanations of actions, against the critique of this claim given by Randolph Clarke in his book, Libertarian Accounts of Free Will.
Machamer, Darden, and Craver argue (Mechanism) that causalexplanations explain effects by describing the operations of the mechanisms (systems of entities engaging in productive activities) which produce them. One of this paper’s aims is to take advantage of neglected resources of Mechanism to rethink the traditional idea (Regularism) that actual or counterfactual natural regularities are essential to the distinction between causal and non-causal co-occurrences, and that generalizations describing natural regularities are essential components of causal (...) class='Hi'>explanations. I think that causal productivity and regularity are by no means the same thing, and that the Regularists are mistaken about the roles generalizations play in causal explanation. Humean, logical empiricist, and other Regularist accounts of causal explanation have had the unfortunate effect of distracting philosophers’ from important non-explanatory scientific uses of laws and lesser generalizations which purport to describe natural regularities. My second aim is to characterize some of these uses, illustrating them with examples from neuroscientific research. (shrink)
Philosophers have proposed many alleged examples of non-causalexplanations of particular events. I discuss several well-known examples and argue that they fail to be non-causal. 1 Questions2 Preliminaries3 Explanations That Cite Causally Inert Entities4 Explanations That Merely Cite Laws I5 Stellar Collapse6 Explanations That Merely Cite Laws II7 A Final Example8 Conclusion.
Most discussions of causalexplanations of behavior focus on the problem of whether it makes sense to regard reasons as causes of human behavior, whether there can be laws connecting reasons with behavior, and the like. This essay discusses explanations of human behavior that do not appeal to reasons. Such explanations can be found in several areas of the social sciences. Moreover, these explanations are both causal and non-reductionist. Historical linguists, for example, offer (...) class='Hi'>causalexplanations of changes in how words are pronouncedand linguistic change in generalwithout appealing to human intentions. I use examples from linguistics, anthropology, and evolutionary psychology to discuss the importance of this sort of explanation and to examine its compatibility with recent philosophical accounts of causation. (shrink)
We report two Experiments to compare counterfactual thoughts about how an outcome could have been different and causalexplanations about why the outcome occurred. Experiment 1 showed that people generate counterfactual thoughts more often about controllable than uncontrollable events, whereas they generate causalexplanations more often about unexpected than expected events. Counterfactual thoughts focus on specific factors, whereas causalexplanations focus on both general and specific factors. Experiment 2 showed that in their spontaneous counterfactual (...) thoughts, people focus on normal events just as often as exceptional events, unlike in directed counterfactual thoughts. The findings are consistent with the suggestion that counterfactual thoughts tend to focus on how a specific unwanted outcome could have been prevented, whereas causalexplanations tend to provide more general causal information that enables future understanding, prediction, and intervention in a wide range of situations. (shrink)
The mechanistic and causal accounts of explanation are often conflated to yield a ‘causal-mechanical’ account. This paper prizes them apart and asks: if the mechanistic account is correct, how can causalexplanations be explanatory? The answer to this question varies according to how causality itself is understood. It is argued that difference-making, mechanistic, dualist and inferentialist accounts of causality all struggle to yield explanatory causalexplanations, but that an epistemic account of causality is more (...) promising in this regard. (shrink)
Singular causalexplanations cite explicitly, or may be paraphrased to cite explicitly, a particular factor as the cause of another particular factor. During recent years there has emerged a consensus account of the nature of an important feature of such explanations, the distinction between a factor regarded correctly in a given context of inquiry as ‘the cause’ of a given result and those other causally relevant factors, sometimes called ‘mere conditions’, which are not regarded correctly in that (...) context of inquiry as the cause of that result. In this paper that consensus account is characterized and developed. The developed version is then used to illuminate some recent discussions of singular causalexplanations. (shrink)
The prevention, treatment and management of disease are closely linked to how the causes of a particular disease are explained. For multi-factorial conditions, the causalexplanations are inevitably complex and competing models may exist to explain the same condition. Selecting one particular causal explanation over another will carry practical and ethical consequences that are acutely relevant for health policy. In this paper our focus is two-fold; (i) the different models of causal explanation that are put forward (...) within current scientific literature for the high and rising prevalence of the common complex conditions of coronary artery disease (CAD) and type 2 diabetes mellitus (T2D); and (ii) how these explanations are taken up (or not) within national health policy guidelines. We examine the causalexplanations for these two conditions through a systematic database search of current scientific literature. By identifying different causalexplanations we propose a three-tier taxonomy of the most prominent models of explanations: (i) evolutionary, (ii) lifecourse, and (iii) lifestyle and environment. We elaborate this taxonomy with a micro-level thematic analysis to illustrate how some explanations are semantically and rhetorically foregrounded over others. We then investigate the uptake of the scientific causalexplanations in health policy documents with regard to the prevention and management recommendations of current National Service Frameworks for CAD and T2D. Our findings indicate a lack of congruence between the complexity and frequent overlap of causalexplanations evident in the scientific literature and the predominant focus on lifestyle recommendations found in the mainstream health policy documents. (shrink)
This paper considers the problem of causal explanation in classical and statistical thermodynamics. It is argued that the irreversibility of macroscopic processes is explained in both formulations of thermodynamics in a teleological way that appeals to entropic or probabilistic consequences rather than to efficient-causal, antecedental conditions. This explanatory structure of thermodynamics is not taken to imply a teleological orientation to macroscopic processes themselves, but to reflect simply the epistemological limitations of this science, wherein consequences of heat-work asymmetries are (...) either macroscopically measurable (entropy) or calculable (probabilities), while efficient-causal relationships are obscure or indeterminable. (shrink)
How are scientific explanations possible in ecology, given that there do not appear to be many—if any—ecological laws? To answer this question, I present and defend an account of scientific causal explanation in which ecological generalizations are explanatory if they are invariant rather than lawlike. An invariant generalization continues to hold or be valid under a special change—called an intervention—that changes the value of its variables. According to this account, causes are difference-makers that can be intervened upon to (...) manipulate or control their effects. I apply the account to ecological generalizations to show that invariance under interventions as a criterion of explanatory relevance provides interesting interpretations for the explanatory status of many ecological generalizations. Thus, I argue that there could be causalexplanations in ecology by generalizations that are not, in a strict sense, laws. I also address the issue of mechanistic explanations in ecology by arguing that invariance and modularity constitute such explanations. (shrink)
forthcoming in New Essays on the Explanation of Action Abstract Philosophers influenced by Wittgenstein rejected the idea that the explanatory power of our ordinary interpretive practices is to be found in law-governed, causal relations between items to which our everyday mental terms allegedly refer. Wittgenstein and those he inspired pointed to differences between the explanations provided by the ordinary employment of mental expressions and the style of causal explanation characteristic of the hard sciences. I believe, however, that (...) the particular non-causalism espoused by the Wittgensteinians is today ill- understood. The position does not, for example, find its place on a map that charts the territory disputed by mental realists and their irrealist opponents. In this paper, I take a few steps toward reintroducing this ill-understood position by sketching my own understanding of it and explaining why it fits so uncomfortably within the contemporary metaphysical landscape. (shrink)
In the literature on scientific explanation two types of pluralism are very common. The first concerns the distinction between explanations of singular facts and explanations of laws: there is a consensus that they have a different structure. The second concerns the distinction between causalexplanations and uni.cation explanations: most people agree that both are useful and that their structure is different. In this article we argue for pluralism within the area of causalexplanations: (...) we claim that the structure of a causal explanation depends on the causal structure of the relevant fragment of the world and on the interests of the explainer. (shrink)
Renormalization group (RG) methods are an established strategy to explain how it is possible that microscopically different systems exhibit virtually the same macro behavior when undergoing phase-transitions. I argue – in agreement with Robert Batterman – that RG explanations are non-causalexplanations. However, Batterman misidentifies the reason why RG explanations are non-causal: it is not the case that an explanation is non- causal if it ignores causal details. I propose an alternative argument, according (...) to which RG explanations are non-causalexplanations because their explanatory power is due to the application mathematical operations, which do not serve the purpose of representing causal relations. (shrink)
Frank Jackson and Philip Pettit have defended a non-reductive account of causal relevance known as the ‘program explanation account’. Allegedly, irreducible mental properties can be causally relevant in virtue of figuring in non-redundant program explanations which convey information not conveyed by explanations in terms of the physical properties that actually do the ‘causal work’. I argue that none of the possible ways to spell out the intuitively plausible idea of a program explanation serves its purpose, viz., (...) defends non-reductive physicalism against Jaegwon Kim’s Causal Exclusion Argument according to which non-reductive physicalism is committed to epiphenomenalism because irreducible mental properties are ‘screened off’ from causal relevance by their physical realizers. Jackson and Pettit’s most promising explication of a program explanation appeals to the idea of invariance of effect under variation of realization , but I show that invariance of effect under variation of realization is neither necessary nor sufficient for causal relevance. (shrink)
Explanation is usually taken to be a relation between certain entities. The aim of this paper is to discuss what entities are suitable as explanatory relata of singular causalexplanations, i.e., explanations concerning singular causality relating particular events or other appropriate entities. I outline three different positions. The purely causal approach stipulates that the same entities that are related in the singular causal relation are also linked by the explanatory relation. This position, however, has a (...) problem to distinguish between causation and explanation, two distinct relations allegedly obtaining between the same entities. The linguistic approach states that explanatory relata are linguistic entities of some sort, e.g., statements, propositions, etc. There are various versions of this position. I deal with two of them and try to show that they are unsatisfactory because they transform explanation into some other type of relation. On the first version, explanation is very close to interpretation or clarification of intension and on the second version it seems to be indistinguishable from an evidential relation or justification. I consider these transformations in understanding explanation unnecessary, and consequently reject linguistic views of explanatory relata. The most promising proposal concerning explanatory relata seems to be the mixed view, according to which propositions explain events or other fitting extra-linguistic entities. (shrink)
This essay will defend a causal conception of action explanations in terms of an agent’s reasons by delineating a metaphysical and epistemic framework that allows us to view folk psychology as providing us with causal and autonomous explanatory strategies of accounting for individual agency. At the same time, I will calm philosophical concerns about the issue of causal deviance that have been at the center of the recent debates between causalist and noncausalist interpretations of action (...) class='Hi'>explanations. For that purpose, it is important to realize that the domain of folk-psychological action explanation is also the domain of skillful and goal-directed bodily movements, a domain to which we have independent epistemic access. (shrink)
I argue that psychologists interested in human causal judgment should understand and adopt a representation of causal mechanisms by directed graphs that encode conditional independence (screening off) relations. I illustrate the benefits of that representation, now widely used in computer science and increasingly in statistics, by (i) showing that a dispute in psychology between ‘mechanist’ and ‘associationist’ psychological theories of causation rests on a false and confused dichotomy; (ii) showing that a recent, much-cited experiment, purporting to show that (...) human subjects, incorrectly let large causes ‘overshadow’ small causes, misrepresents the most likely, and warranted, causal explanation available to the subjects, in the light of which their responses were normative; (iii) showing how a recent psychological theory (due to P. Cheng) of human judgment of causal power can be considerably generalized: and (iv) suggesting a range of possible experiments comparing human and computer abilities to extract causal information from associations. (shrink)
Little Johnny: “Can we be punished for something we have not done?” Mother: “Of course not!” Johnny: “Good—because I didn’t turn off the gas…” At this point Johnny smiles and thinks he got away with it. Unfortunately, his mother is smarter than he expected. “I said we cannot be punished for something we have not done”, she says, “but certainly we can be punished for not having done something”.
Causalists about explanation claim that to explain an event is to provide information about the causal history of that event. Some causalists also endorse a proportionality claim, namely that one explanation is better than another insofar as it provides a greater amount of causal information. In this chapter I consider various challenges to these causalist claims. There is a common and influential formulation of the causalist requirement – the ‘Causal Process Requirement’ – that does appear vulnerable to (...) these anti-causalist challenges, but I argue that they do not give us reason to reject causalism entirely. Instead, these challenges lead us to articulate the causalist requirement in an alternative way. This alternative articulation incorporates some of the important anti-causalist insights without abandoning the explanatory necessity of causal information. For example, proponents of the ‘equilibrium challenge’ argue that the best available explanations of the behaviour of certain dynamical systems do not appear to provide any causal information. I respond that, contrary to appearances, these equilibrium explanations are fundamentally causal, and I provide a formulation of the causalist thesis that is immune to the equilibrium challenge. I then show how this formulation is also immune to the ‘epistemic challenge’ – thus vindicating (a properly formulated version of) the causalist thesis. (shrink)
By "an infinite series of contingent beings" is meant a beginningless succession of modally contingent beings, such that the succession of beings occupies an infinite number of equal-lengthened temporal intervals (e.g. an aleph-zero number of past years).
The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more probable when it was linked to evidence by a causal chain than when both variables shared a common cause; (b) predictive chains in which evidence is (...) a cause of the hypothesis gave rise to higher judgments than diagnostic chains in which evidence is an effect of the hypothesis; and (c) direct chains gave rise to higher judgments than indirect chains. A Bayesian learning model was applied to our data but failed to explain them. An explanation-based hypothesis stating that statistical information will affect judgments only to the extent that it changes beliefs about causal structure is consistent with the results. (shrink)
The invariance under interventions –account of causal explanation imposes a modularity constraint on causal systems: a local intervention on a part of the system should not change other causal relations in that system. This constraint has generated criticism against the account, since many ordinary causal systems seem to break this condition. This paper answers to this criticism by noting that explanatory models are always models of specific causal structures, not causal systems as a whole, (...) and that models of causal structures can have different modularity properties which determine what can and what cannot be explained with the model. (shrink)
From 1959 until 1969, Heidegger lectured to psychiatrists and psychiatry students at the University of Zurich Psychiatric Clinic and in Zollikon. The transcriptions of these lectures were published as the Zollikon Seminars. In these seminars Heidegger is highly critical of psychoanalysis, because of its causal and objectifying approach to the human being. In general, Heidegger considers it an objectification or even an elimination of the human being to approach a patient from a causal perspective. In our view Heidegger (...) has overlooked the peculiar nature and complexity of psychotherapy and psychiatry, namely that psychiatry is not just a discipline that combines a hermeneutical approach and a natural science approach on a theoretical level, but it also deals with psychopathology in practice. We argue, also referring to Strawson and Gadamer, that in psychiatric practice causal explanation and hermeneutic understanding are no mutually exclusive approaches. We conclude that the encounter of philosophy and psychiatry in matters of causality and motivation could be particularly fruitful when the practical situation is addressed, recognizing the special character of psychopathology. (shrink)
The analyses of explanation and causal beliefs are heavily dependent on using probability functions as models of epistemic states. There are, however, several aspects of beliefs that are not captured by such a representation and which affect the outcome of the analyses. One dimension that has been neglected in this article is the temporal aspect of the beliefs. The description of a single event naturally involves the time it occurred. Some analyses of causation postulate that the cause must not (...) occur later than the effect. If we want this kind of causality it is easy to add the appropriate clause to ( CAUS ). An alternative is not to rule out backwards causation or causal loops a priori , but expect that ( CAUS ), via the properties of the contraction P C - , will result in the desired temporal relation between C and E . One way of ensuring this is to postulate that when the probability function P is contracted to P C - , the probabilities of all events that occurred before C remain the same in P C - as in P . This means that all beliefs about the history of events up to C are left unaltered in the construction of the hypothetical state of belief P C - . In conclusion, I hope to have shown that, in spite of these limitations, ( EXP ) and ( CAUS ) provide viable analyses of explanation and causality between single events for the case when epistemic states can be described by probability functions. I have also shown that the two analyses can be used to explicate the close connections between the two notions. These analyses reduce the problems of explanation and causality, hopefully in a non-circular way, to the problem of identifying contractions of states of belief. (shrink)
It has been argued that psychoanalytic and biological theories cannot be integrated because they rely on different epistemological grounds, namely on hermeneutic versus causalexplanations, that are inconsistent with each other. Such inconsistency would seriously question the general possibility of neuropsychanalytic research. Here, I review three important arguments that have been raised in favour of this inconsistency: First, that psychoanalytic attempts to overcome repression aim to go beyond causal relationships; second, that hermeneutic explanations are retrospective and (...) context-dependent and therefore follow a different logic than causalexplanations; and third, that only causal hypotheses are falsifiable, while the introspective reasons for one’s own behaviour are not. I present arguments against each of these statements and show that actually, causal and hermeneutic explanations are, at least in principle, consistent with each other. The challenge for neuropsychoanalytic research remains to find indeed empirical examples of theories which are causal and hermeneutic at the same time. (shrink)
Pluralism with respect to the structure of explanations of facts is not uncommon. Wesley Salmon, for instance, distinguished two types of explanation: causalexplanations (which provide insight in the causes of the fact we want to explain) and unification explanations (which fit the explanandum into a unified world view). The pluralism which Salmon and others have defended is compatible with several positions about the exact relation between these two types of explanations. We distinguish four such (...) positions, and argue in favour of one of them. We also compare our results with the views of some authors who have recently written on this subject. (shrink)
It is widely believed that many of the competing accounts of scientific explanation have ramifications which are relevant to the scientific realism debate. I claim that the two issues are orthogonal. For definiteness, I consider Cartwright's argument that causalexplanations secure belief in theoretical entities. In Section I, van Fraassen's anti-realism is reviewed; I argue that this anti-realism is, prima facie, consistent with a causal account of explanation. Section II reviews Cartwright's arguments. In Section III, it is (...) argued that causalexplanations do not license the sort of inferences to theoretical entities that would embarass the anti-realist. Section IV examines the epistemic commitments involved in accepting a causal explanation. Section V presents my conclusions: contra Cartwright, the anti-realist may incorporate a causal account of explanation into his vision of science in an entirely natural way. (shrink)
To give a causal explanation is to give information about causal history. But a vast amount of causal history lies behind anything that happens, far too much to be included in any intelligible explanation. This is the Problem of Limitation for explanatory information. To cope with this problem, explanations must select for what is relevant to and adequate for answering particular inquiries. In the present paper this idea is used in order to distinguish two kinds of (...)causal explanation, on the grounds of systematic differences in their conditions of relevance and adequacy. It is further argued that these two forms of causal explanation are interdependent and their interaction provides an instrument through which causal knowledge is acquired and enhanced. What we understand causation in the world to be is neither unconditioned regularity, nor counterfactual dependence, but the sum of correct answers to explanatory inquiries of these two interdependent kinds. (shrink)
It is observed that in ordinary everyday causalexplanations often just one causal factor is mentioned. One causal factor carries the explanatory burden, even if there are several causal factors that are responsible for the event to be explained. This paper deals with the question of how to account for this explanatory selection. I argue for a pragmatic stance towards explanation, that we must attend to the question–answer situation as a whole and the context of (...) the explanation. The context of an explanation includes the inquirer's and the explainer's beliefs and presuppositions relevant for the explanation-seeking question, and these are encoded in a reference class. Furthermore I argue that the explanation-giving answer contains an implicit counterfactual claim, the explanation-giving counterfactual. The solution to the problem of explanatory selection is to be found in the presuppositions encoded by the reference class and the eg-counterfactual. In short we select as explanatory that factor which, together with the presupposition encoded in the reference class we believe will make the eg-counterfactual true. (shrink)
Semantic properties are not commonly held to be part of the basic ontological furniture of the world. Consequently, we confront a problem: how to 'naturalize' semantics so as to reveal these properties in their true ontological colors? Dominant naturalistic theories address semantic properties as properties of some other (more primitive, less problematic) kind. The reductionistic flavor is unmistakable. The following quote from Fodor's Psychosemantics is probably the contemporary locus classicus of this trend. Fodor is commendably unapologetic: "I suppose that sooner (...) or later the physicists will complete the catalogue they've been compiling of the ultimate and irreducible properties of things. When they do, the likes of spin, charm, and charge will perhaps appear upon their list. But aboutness surely won't; intentionality simply doesn't go that deep. It's hard to see, in the face of this consideration, how one can be a Realist about intentionality without also being, to some extent or other, a Reductionist. If the semantic and the intentional are real properties of things, it must be in virtue of their identity with (or maybe of their supervenience on?) properties that are themselves neither intentional nor semantic. If aboutness is real, it must be really something else." (Fodor 1987, 97) Notice the shape of this explanatory project. Intentional properties will count as real in virtue of their identity with, or supervenience on, some set of lower-level physical properties. Fodor thus assumes, in effect (as do many others engaged in naturalization projects for semantics), that the program of naturalization demands a higher-to-lower, top-to-bottom, kind of explanatory strategy. This paper addresses precisely that assumption, namely, that the non-semantic properties on which semantic properties depend, belong to what are intuitively lower levels of description than the intentional level itself. It also questions the higher-to-lower explanatory scheme associated with that assumption. My discussion of this topic draws on Robert Brandom's recent work (Brandom 1994) and can be considered an analysis of Brandom's stance and its implications. The discussion should help to explain the general lack of progress in the project of naturalizing content. It should also help show why attempts to eliminate the normative vocabulary employed in specifying the practices that guide the use of a language are unlikely to succeed. I shall start by displaying the general order of explanation that characterizes typical naturalization projects, showing that even when a full reduction to physics is avoided, some important assumptions inherited from the explanatory model of physics remain. These include the demand for an array of causalexplanations couched in terms of ultimate properties of the world, and the idea that such non-semantic properties should be constitutive (in a narrow or individualistic sense to be explained below) of whatever semantic properties are in question. Extending Brandom's idea that the normativity of content is not reducible to physics, I shall argue that even such residual demands are inappropriate. More positively, I suggest that, despite the deep irreducibility of the normative dimension of content, we need not consider that dimension either primitive or inexplicable. Instead, such normative aspects can be unpacked by invoking a different, lower-to-higher, explanatory scheme in which the explanans includes higher level features such as skilled know-how and social frames of action. (shrink)