Knowledge,Cause, and Abstract Objects: Causal Objections to Platonism

Book Information Knowledge, Cause, and Abstract Objects: Causal Objections to Platonism. Knowledge, Cause, and Abstract Objects: Causal Objections to Platonism Colin Cheyne, Dordrecht: Kluwer Academic Publishers, 2001, xvi + 236, £55 (cloth) By Colin Cheyne. Dordrecht: Kluwer Academic Publishers. Pp. xvi + 236. £55,     

Causal Exclusion and Causal Autonomism

The causal exclusion problem is often considered as one of the major difficulties for which non-reductive physicalists have no easy solution to offer. Some non-reductive physicalists address this problem by arguing that mental properties are to some extent causally autonomous. If this is the case, then mental properties will not be causally excluded by their physical realizers because causation, in general, is a relation between properties of the same level. In this paper, I argue that the response from causal autonomy cannot be successful for two reasons. First, it does not offer a satisfactory explanation for how mental particulars can have causal efficacy in a non-reductive physicalist framework. Second, the causal considerations underpinning this response do not really support the conclusion that mental properties are causally autonomous.     

Nosology and Causal Necessity; The Relation BetweenDefining a Disease and Discovering its Necessary Cause

The problem of disease definition is related to theproblem of proving that a certain agent is thenecessary cause of a certain disease. Natural kindterms like rheumatoid arthritis and AIDS refer toessences which are discoverable rather thanpredeterminate. No statement about such diseases isa priori necessarily true. Because theories onnecessary causes involve natural kind semantics,Koch's postulates cannot be used to falsify or verifysuch theories. Instead of proving that agent A is thenecessary cause of disease D, we include A in atheoretical definition of D, take this to representthe real meaning of D, and discard thepretheoretical definition. This is illustrated byKoch's own attempt to prove he had discovered thenecessary cause of tuberculosis. Methodologicalarguments about disease causation require a clear viewof our use of diagnostic terms. Medical lexicographersshould do more to provide such a view.     

Causal Exclusion and Causal Bayes Nets

In this paper I reconstruct and evaluate the validity of two versions of causal exclusion arguments within the theory of causal Bayes nets. I argue that supervenience relations formally behave like causal relations. If this is correct, then it turns out that both versions of the exclusion argument are valid when assuming the causal Markov condition and the causal minimality condition. I also investigate some consequences for the recent discussion of causal exclusion arguments in the light of an interventionist theory of causation such as Woodward's ( 2003 ) and discuss a possible objection to my causal Bayes net reconstruction.     

灾难性事件对幸福感的“积极”影响

灾难性事件在造成人员和财产巨大损失的同时, 对个人的幸福感可能还存在一个重新建构的积极影响模型。灾难性事件本身不可能引发幸福感, 但灾难性事件却可能会使个人从认知、需要和情绪三个方面, 重新建构幸福感的结构性成分, 进而改变促发幸福感的条件。灾后, 幸福感可能比灾前更容易产生。除此之外, 未受灾的个人, 也可能在与受灾当事人的比较中, 产生立即性的幸福感体验。     

Age Bias in the Workplace: The Impact of Ageism and Causal Attributions1

This study considers the roles of managerial ageism and causal attributions in the age bias process. Specifically, we predicted that employee age and manager ageism would interact in predicting the severity of recommendations made about an employee's performance errors, such that ageist managers would be more likely to engage in age bias. Second, we proposed that age bias is caused partially by differential attributions made about the performance errors of older vs. younger workers. Results indicated that older employees received more severe recommendations for poor performance than did their younger counterparts. Also, some ageist attitudes moderated the relationship between age and performance recommendations. Stability attributions mediated the relationship of employee age on endorsement of the more punitive recommendations.     

Finding the Cause: Verbal Framing Helps Children Extract Causal Evidence Embedded in a Complex Scene

In making causal inferences, children must both identify a causal problem and selectively attend to meaningful evidence. Four experiments demonstrate that verbally framing an event (“Which animals make Lion laugh?”) helps 4-year-olds extract evidence from a complex scene to make accurate causal inferences. Whereas framing was unnecessary when evidence was isolated, children required it to extract and reason about evidence embedded in a more complex scene. Subtler framing stating the causal problem, but not highlighting the relevant variables, was equally effective. Simply making the causal relationship more perceptually obvious did facilitate children's inferences, but not to the level of verbal framing. These results illustrate how children's causal reasoning relies on scaffolding from adults.     

Causal Closure,Causal Exclusion,and Supervenience Physicalism

This article considers the recent defense of the supervenience approach to physicalism due to Jaegwon Kim. Kim argues that supervenience supports physical causal closure, and that causal closure supports physicalism – indeed, a kind of reductive physicalism – and thus that supervenience suffices for physicalism. After laying out Kim's argument, I ask whether its success would truly vindicate the role of supervenience in defining physicalist positions. I argue that it would not, and that insofar as Kim's defense of supervenience physicalism succeeds, it does so by showing that supervenience physicalism is not a unique, nonredundant way to be a physicalist.     

Stable Causal Relationships Are Better Causal Relationships

We report three experiments investigating whether people's judgments about causal relationships are sensitive to the robustness or stability of such relationships across a range of background circumstances. In Experiment 1, we demonstrate that people are more willing to endorse causal and explanatory claims based on stable (as opposed to unstable) relationships, even when the overall causal strength of the relationship is held constant. In Experiment 2, we show that this effect is not driven by a causal generalization's actual scope of application. In Experiment 3, we offer evidence that stable causal relationships may be seen as better guides to action. Collectively, these experiments document a previously underappreciated factor that shapes people's causal reasoning: the stability of the causal relationship.     

Laws and Causal Relations

How are causal relations between particular states of affairs related to causal laws? There appear to be three main answers to this question, and the choice among those three alternatives would seem to be crucial for any account of causation. In spite of this fact, the question of which view is correct has been all but totally neglected in present-day discussions. Indeed, since the time of Hume, one answer has more or less dominated philosophical thinking about causation. In this paper I shall attempt to show that the view in question is exposed to decisive objections.     

Causal reasoning and backtracking

I argue that one central aspect of the epistemology of causation, the use of causes as evidence for their effects, is largely independent of the metaphysics of causation. In particular, I use the formalism of Bayesian causal graphs to factor the incremental evidential impact of a cause for its effect into a direct cause-to-effect component and a backtracking component. While the “backtracking” evidence that causes provide about earlier events often obscures things, once we our restrict attention to the cause-to-effect component it is true to say promoting (inhibiting) causes raise (lower) the probabilities of their effects. This factoring assumes the same form whether causation is given an interventionist, counterfactual or probabilistic interpretation. Whether we think about causation in terms of interventions and causal graphs, counterfactuals and imaging functions, or probability raising against the background of causally homogenous partitions, if we describe the essential features of a situation correctly then the incremental evidence that a cause provides for its effect in virtue of being its cause will be the same.     

Interventionism and Causal Exclusion

A number of writers, myself included, have recently argued that an “interventionist” treatment of causation of the sort defended in Woodward, 2003 can be used to cast light on so‐called “causal exclusion” arguments. This interventionist treatment of causal exclusion has in turn been criticized by other philosophers. This paper responds to these criticisms. It describes an interventionist framework for thinking about causal relationships when supervenience relations are present. I contend that this framework helps us to see that standard arguments for causal exclusion involve mistaken assumptions about what it is appropriate to control for or hold fixed in assessing causal claims. The framework also provides a natural way of capturing the idea that properties that supervene on but that are not identical with realizing properties can be causally efficacious.     

Co-responsibility and Causal Involvement

In discussions of moral responsibility for collectively produced effects, it is not uncommon to assume that we have to abandon the view that causal involvement is a necessary condition for individual co-responsibility. In general, considerations of cases where there is “a mismatch between the wrong a group commits and the apparent causal contributions for which we can hold individuals responsible” motivate this move. According to Brian Lawson, “solving this problem requires an approach that deemphasizes the importance of causal contributions”. Christopher Kutz’s theory of complicitious accountability in Complicity from 2000 is probably the most well-known approach of that kind. Standard examples are supposed to illustrate mismatches of three different kinds: an agent may be morally co-responsible for an event to a high degree even if her causal contribution to that event is a) very small, b) imperceptible, or c) non-existent (in overdetermination cases). From such examples, Kutz and others conclude that principles of complicitious accountability cannot include a condition of causal involvement. In the present paper, I defend the causal involvement condition for co-responsibility. These are my lines of argument: First, overdetermination cases can be accommodated within a theory of coresponsibility without giving up the causality condition. Kutz and others oversimplify the relation between counterfactual dependence and causation, and they overlook the possibility that causal relations other than marginal contribution could be morally relevant. Second, harmful effects are sometimes overdetermined by non-collective sets of acts. Over-farming, or the greenhouse effect, might be cases of that kind. In such cases, there need not be any formal organization, any unifying intentions, or any other noncausal criterion of membership available. If we give up the causal condition for coresponsibility it will be impossible to delimit the morally relevant set of acts related to those harms. Since we sometimes find it fair to blame people for such harms, we must question the argument from overdetermination. Third, although problems about imperceptible effects or aggregation of very small effects are morally important, e.g. when we consider degrees of blameworthiness or epistemic limitations in reasoning about how to assign responsibility for specific harms, they are irrelevant to the issue of whether causal involvement is necessary for complicity. Fourth, the costs of rejecting the causality condition for complicity are high. Causation is an explicit and essential element in most doctrines of legal liability and it is central in common sense views of moral responsibility. Giving up this condition could have radical and unwanted consequences for legal security and predictability. However, it is not only for pragmatic reasons and because it is a default position that we should require stronger arguments (than conflicting intuitions about “mismatches”) before giving up the causality condition. An essential element in holding someone to account for an event is the assumption that her actions and intentions are part of the explanation of why that event occurred. If we give up that element, it is difficult to see which important function responsibility assignments could have.     

Counterfactuals and Causal Explanation

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.