The Causal Structure of Utility Conditionals

The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ‘‘if p then q’’ statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This article introduces a new parameter in this analysis, the underlying causal structure of the conditional. Four experiments showed that causal structure moderated utility‐informed conditional reasoning. These inferences were strongly invited when the underlying structure of the conditional was causal, and significantly less so when the underlying structure of the conditional was diagnostic. This asymmetry was only observed for conditionals in which the utility of q was clear, and disappeared when the utility of q was unclear. Thus, an adequate account of utility‐informed inferences conditional reasoning requires three components: utility, probability, and causal structure.     

The Causal Structure of Evolutionary Theory

One contentious debate in the philosophy of biology is that between the statisticalists and causalists. The former understand core evolutionary concepts like fitness and selection to be mere statistical summaries of underlying causal processes. In this view, evolutionary changes cannot be causally explained by selection or fitness. The causalist side, on the other hand, holds that populations can change in response to selection—one can cite fitness differences or driftability in causal explanations of evolutionary change. But, on the causalist side, it is often not clear how, precisely, one should understand these causes. Thus, much more could be said about what sort of causes fitness and driftability are. In this paper, I borrow Dretske's distinction between structuring and triggering causes and I suggest that fitness and driftability are structuring causes of evolution.     

The Structure of Causal Evidence Based on Eliminative Induction

It is argued that in deterministic contexts evidence for causal relations states whether a boundary condition makes a difference or not to a phenomenon. In order to substantiate the analysis, I show that this difference/indifference making is the basic type of evidence required for eliminative induction in the tradition of Francis Bacon and John Stuart Mill. To this purpose, an account of eliminative induction is proposed with two distinguishing features: it includes a method to establish the causal irrelevance of boundary conditions by means of indifference making, which is called strict method of agreement, and it introduces the notion of a background against which causal statements are evaluated. Causal statements thus become three-place-relations postulating the relevance or irrelevance of a circumstance C to the examined phenomenon P with respect to a background B of further conditions. To underline the importance of evidence in terms of difference/indifference making, I sketch two areas, in which eliminative induction is extensively used in natural and engineering sciences. One concerns exploratory experiments, the other engineering design methods. Given that a method is discussed that has been used for centuries, I make no claims to novelty in this paper, but hope that the combined discussion of several topics that are still somewhat underrepresented in the philosophy of science literature is of some merit.     

The Units Of Selection And The Causal Structure Of The World

Genic selectionism holds that all selection can be understood as operating on particular genes. Critics (and conventional biological wisdom) insist that this misrepresents the actual causal structure of selective phenomena at higher levels of biological organization, but cannot convincingly defend this intuition. I argue that the real failing of genic selectionism is pragmatic – it prevents us from adopting the most efficient corpus of causal laws for predicting and intervening in the course of affairs – and I offer a Pragmatic account of causation itself which ultimately bears out the claim that genic selectionism misrepresents the causal structure of selective contexts.     

TETRAD: Discovering Causal Structure

We describe multilevel modeling of cognitive function in subjects with schizophrenia, their healthy first degree relatives and controls. The purpose of the study was to compare mean cognitive performance between the three groups after adjusting for various covariates, as well as to investigate differences in the variances. Multilevel models were required because subjects were nested within families and some of the measures were repeated several times on the same subject. The following four methodological issues that arose during the analysis of the data are discussed. First, when the random effects distribution was not normal, non-parametric maximum likelihood (NPML) was employed, leading to a different conclusion than the conventional multilevel model regarding one of the main study hypotheses. Second, the between-subject (within-family) variance was allowed to differ between the three groups. This corresponded to the variance at level 1 or level 2 depending on whether repeated measures were analyzed. Third, a positively skewed response was analyzed using a number of different generalized linear mixed models. Finally, penalized quasilikelihood (PQL) estimates for a binomial response were compared with estimates obtained using Gaussian quadrature. A small simulation study was carried out to assess the accuracy of the latter.     

Effects of Causal Structure on Decisions About Where to Intervene on Causal Systems

We investigated how people design interventions to affect the outcomes of causal systems. We propose that the abstract structural properties of a causal system, in addition to people's content and mechanism knowledge, influence decisions about how to intervene. In Experiment 1, participants preferred to intervene at specific locations (immediate causes, root causes) in a causal chain regardless of which content variables occupied those positions. In Experiment 2, participants were more likely to intervene on root causes versus immediate causes when they were presented with a long‐term goal versus a short‐term goal. These results show that the structural properties of a causal system can guide the design of interventions.     

The Causal Principle

There is a charge sometimes made in metaphysics that particular commitments are ‘hypothetical’, ‘dubious’ or ‘suspicious’. There have been two analyses given of what this consists in—due to Crisp (2007) and Cameron (2011). The aim of this paper is to reject both analyses and thereby show that there is no obvious way to press the objection against said commitments that they are ‘dubious’ and objectionable. Later in the paper I consider another account of what it might be to be ‘dubious’, and argue that this too fails. I use Bigelow's (1996) Lucretian properties as a vehicle for the discussions of dubiousness that follow. As a consequence, the paper ends up offering a partial defense of Lucretianism.     

Sufficiency and Necessity Assumptions in Causal Structure Induction

Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when deciding between alternative causal structures. In three experiments, we requested subjects to choose which of two observable variables was the cause and which the effect. We found strong evidence that learners have interindividually variable but intraindividually stable priors about causal parameters that express a preference for causal determinism (sufficiency or necessity; Experiment 1). These priors predict which structure subjects preferentially select. The priors can be manipulated experimentally (Experiment 2) and appear to be domain‐general (Experiment 3). Heuristic strategies of structure induction are suggested that can be viewed as simplified implementations of the priors.     

非良基集合的域和分类

本文介绍正则互模拟理论并比较了正则互模拟的外延性大小,通过对非良基公理之间不相容的条件的讨论,我们进一步比较了由正则互模拟决定的非良基集合域的大小,最后对非良基集合论FAFA、SAFA和AFA中的非良基集合进行了分类。     

The Causal Exclusion Argument

Jaegwon Kim’s causal exclusion argument says that if all physical effects have sufficient physical causes, and no physical effects are caused twice over by distinct physical and mental causes, there cannot be any irreducible mental causes. In addition, Kim has argued that the nonreductive physicalist must give up completeness, and embrace the possibility of downward causation. This paper argues first that this extra argument relies on a principle of property individuation, which the nonreductive physicalist need not accept, and second that once we get clear on overdetermination, there is a way to reject the exclusion principle upon which the causal exclusion argument depends, but third that this should not lead to the belief that mental causation is easily accounted for in terms of counterfactual dependencies.     

The Causal Exclusion Puzzle

The article is divided into two parts. The first part offers a careful reconstruction and detailed discussion of the argument of causal exclusion, as well as of the implications it has for physicalism. In its second part the article examines two important objections to the causal exclusion argument: the generalization objection, which holds that the argument is unacceptable since it confers causal efficacy only to ultimate basic properties, which arguably might not exist; and Yablo's objection, according to which underlying the argument of causal exclusion there is a principle of causal parsimony which leads to strong counterintuitive results and should therefore be abandoned. The article offers grounds for rejecting both objections as well as a new diagnosis of the problem for mental causation generated by the causal exclusion argument.     

The Causal Chain Problem

This paper addresses a problem that arises when it comes to inferring deterministic causal chains from pertinent empirical data. It will be shown that to every deterministic chain there exists an empirically equivalent common cause structure. Thus, our overall conviction that deterministic chains are one of the most ubiquitous (macroscopic) causal structures is underdetermined by empirical data. It will be argued that even though the chain and its associated common cause model are empirically equivalent there exists an important asymmetry between the two models with respect to model expansions. This asymmetry might constitute a basis on which to disambiguate corresponding causal inferences on non-empirical grounds.

The Metaphysics of Causal Models

This paper presents an attempt to integrate theories of causal processes—of the kind developed by Wesley Salmon and Phil Dowe—into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are rendered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques suffice to explain cases of late pre?mption and other cases that have proved problematic for causal models.

The Reduction of Causal Processes

The principle that causes always render their effects more likely is fundamental to the enterprise of reducing facts of causation to facts about (objective) chances. This reductionist enterprise faces famous difficulties in accommodating common-sense intuitions about causal processes, if it insists on cashing out causal processes in terms of streams of events in which every event that belongs to the stream is a cause of the adjoining event downstream of it. I shall propose modifications to this way of cashing out causal processes, still well within the reductionist faith. These modifications will allow the reductionist to handle processes successfully, on the assumption that the reductionist proposal is itself otherwise satisfactory. I shall then argue that the reductionist enterprise lies squarely behind the Theory of Relativity, and so has all the confirmatory weight of Relativity behind it. However this is not all good news for reductionists. For throughout I shall simply assume that the reductionist proposal, to the effect that causes are just chance-raisers, is correct. AndI shall sidestep problems with that proposal as such. And so I shall show that, if in the end we find the reductionist proposal unsatisfactory, it cannot be on grounds of its treatment of causal processes as such. Thus, while I shall argue that causal processes pose no extra trouble for redutionists, I shall be making a case that all the action between reductionists and their opponents should be focused upon the proposal to reduce the two-term causal relation itself to relations amongst probabilities.