Causation,causal perception,and conservation laws

We investigated the perception of causation via the ability to detect conservation violations in simple events. We showed that observers were sensitive to energy conservation violations in free-fall events. Furthermore, observers were sensitive to gradually perturbed energy dynamics in such events. However, they were more sensitive to the effect of decreasing gravity than to that of increasing gravity. Displays with decreasing gravity were the only displays in which the energy profile was dominated by (apparent) potential energy, leading to an asymmetric trajectory.     

Inductive reasoning and judgment interference: experiments on Simpson's paradox

In a series of experiments on inductive reasoning, participants assessed the relationship between gender, success, and a covariate in a situation akin to Simpson's paradox: Although women were less successful then men according to overall statistics, they actually fared better then men at either of two universities. Understanding trivariate relationships of this kind requires cognitive routines similar to analysis of covariance. Across the first five experiments, however, participants generalized the disadvantage of women at the aggregate level to judgments referring to the different levels of the covariate, even when motivation was high and appropriate mental models were activated. The remaining three experiments demonstrated that Simpson's paradox could be mastered when the salience of the covariate was increased and when the salience of gender was decreased by the inclusion of temporal cues that disambiguate the causal status of the covariate.     

A priori causal laws

Sober and Elgin defend the claim that there are a priori causal laws in biology. Lange and Rosenberg take issue with this on Humean grounds, among others. I will argue that Sober and Elgin don’t go far enough – there are a priori causal laws in many sciences. Furthermore, I will argue that this thesis is compatible with a Humean metaphysics and an empiricist epistemology.     

A generalized probabilistic theory of causal relevance

I advance a new theory of causal relevance, according to which causal claims convey information about conditional probability functions. This theory is motivated by the problem of disjunctive factors, which haunts existing probabilistic theories of causation. After some introductory remarks, I present in Section 3 a sketch of Eells's (1991) probabilistic theory of causation, which provides the framework for much of the discussion. Section 4 explains how the problem of disjunctive factors arises within this framework. After rejecting three proposed solutions, I offer in Section 6 a new approach to causation that avoids the problem. Decision-theoretic considerations also support the new approach. Section 8 develops the consequences of the new theory for causal explanation. The resulting theory of causal explanation incorporates the new insights while respecting important work on scientific explanation by Salmon (1971), Railton (1981), and Humphreys (1989). My conclusions are enumerated in Section 9.I would like to thank Nuel Belnap, John Earman, Richard Gale, Paul Humphreys, Satish Iyengar, Wes Salmon, and two anonymous referees for comments and discussion. I am also indebted to the members of an audience at the Center for Philosophy of Science at the University of Pittsburgh, where some of the ideas contained in this paper were presented.     

A probabilistic contrast model of causal induction

Deviations from the predictions of covariational models of causal attribution have often been reported in the literature. These include a bias against using consensus information, a bias toward attributing effects to a person, and a tendency to make a variety of unpredicted conjunctive attributions. It is contended that these deviations, rather than representing irrational biases, could be due to (a) unspecified information over which causal inferences are computed and (b) the questionable normativeness of the models against which these deviations have been measured. A probabilistic extension of Kelley's analysis-of-variance analogy is proposed. An experiment was performed to assess the above biases and evaluate the proposed model against competing ones. The results indicate that the inference process is unbiased.     

Betting on transitivity in probabilistic causal chains

Causal reasoning is crucial to people’s decision making in probabilistic environments. It may rely directly on data about covariation between variables (correspondence) or on inferences based on reasonable constraints if larger causal models are constructed based on local relations (coherence). For causal chains an often assumed constraint is transitivity. For probabilistic causal relations, mismatches between such transitive inferences and direct empirical evidence may lead to distortions of empirical evidence. Previous work has shown that people may use the generative local causal relations A → B and B → C to infer a positive indirect relation between events A and C, despite data showing that these events are actually independent (von Sydow et al. in Proceedings of the thirty-first annual conference of the cognitive science society. Cognitive Science Society, Austin, 2009, Proceedings of the 32nd annual conference of the cognitive science society. Cognitive Science Society, Austin, 2010, Mem Cogn 44(3):469–487, 2016). Here we used a sequential learning scenario to investigate how transitive reasoning in intransitive situations with negatively related distal events may relate to betting behavior. In three experiments participants bet as if they were influenced by a transitivity assumption, even when the data strongly contradicted transitivity.     

A new consequence of Simpson's paradox: stable cooperation in one-shot prisoner's dilemma from populations of individualistic learners

Theories of choice in economics typically assume that interacting agents act individualistically and maximize their own utility. Specifically, game theory proposes that rational players should defect in one-shot prisoners' dilemmas (PD). Defection also appears to be the inevitable outcome for agents who learn by reinforcement of past choices, because whatever the other player does, defection leads to greater reinforcement on each trial. In a computer simulation and 4 experiments, the authors show that, apparently paradoxically, when players' choices are correlated by an exogenous factor (here, the cooperativeness of the specific PD chosen), people obtain greater average reinforcement for cooperating, which can sustain cooperation. This effect arises from a well-known statistical paradox, Simpson's paradox. The authors speculate that this effect may be relevant to aspects of real-world human cooperative behavior.     

How two causes are different from one: The use of (un)conditional information in Simpson's paradox

In a causally complex world, two (or more) factors may simultaneously be potential causes of an effect. To evaluate the causal efficacy of a factor, the alternative factors must be controlled for (or conditionalized on). Subjects judged the causal strength of two potential causes of an effect that covaried with each other, thereby setting up a Simpson's paradox--a situation in which causal judgments should vary widely depending on whether or not they are conditionalized on the alternative potential cause. In Experiments 1 (table format) and 2 (trial-by-trial format), the subjects did conditionalize their judgments for one causal factor on a known alternative cause. The subjects also demonstrated that they knew what information was needed to properly make causal judgments when two potential causes are available. In Experiment 3 (trial-by-trial), those subjects who were not told about the causal mechanism by which the alternative cause operated were less likely to conditionalize on it. However, the more a subject recognized the covariation between the alternative cause and the effect, the more the subject conditionalized on it. Such behavior may arise from the interaction between bottom-up and top-down processing.     

Partitions and Conditionals

The literature on conditionals is rife with alternate formulations of the abstract semantics of conditional logic. Each formulation has its own advantages in terms of applications and generalizations; nevertheless, they are for the most part equivalent, in the sense that they underwrite the same range of logical systems. The purpose of the present note is to bring under this umbrella the partition semantics introduced by Brian Skyrms in (Skyrms, 1984).     

Notes on selective influence, probabilistic causality, and probabilistic dimensionality

The paper provides conceptual clarifications for the issues related to the dependence of jointly distributed systems of random entities on external factors. This includes the theory of selective influence as proposed in Dzhafarov [(2003a). Selective influence through conditional independence. Psychometrika, 68, 7-26] and generalized versions of the notions of probabilistic causality [Suppes, P., & Zanotti, M. (1981). When are probabilistic explanations possible? Synthese, 48, 191-199] and dimensionality in the latent variable models [Levine, M. V. (2003). Dimension in latent variable models. Journal of Mathematical Psychology, 47, 450-466]. One of the basic observations is that any system of random entities whose joint distribution depends on a factor set can be represented by functions of two arguments: a single factor-independent source of randomness and the factor set itself. In the case of random variables (i.e., real-valued random entities endowed with Borel sigma-algebras) the single source of randomness can be chosen to be any random variable with a continuous distribution (e.g., uniformly distributed between 0 and 1).     

Continuum,name and paradox

The article deals with Cantor’s argument for the non-denumerability of reals somewhat in the spirit of Lakatos’ logic of mathematical discovery. At the outset Cantor’s proof is compared with some other famous proofs such as Dedekind’s recursion theorem, showing that rather than usual proofs they are resolutions to do things differently. Based on this I argue that there are “ontologically” safer ways of developing the diagonal argument into a full-fledged theory of continuum, concluding eventually that famous semantic paradoxes based on diagonal construction are caused by superficial understanding of what a name is.     

Judgments of voluntary and physical causes in causal chains: probabilistic and social functionalist criteria for attributions

Four experiments investigated judgments about voluntary human actions and physical causes that were embedded in causal chains ending in negative outcomes (e.g., a forest fire). Causes were judged for their explanatory quality, their effect on the probability of the outcome, and the extent to which they could be socially controlled. Results supported legal theorists' claim that voluntary actions are judged better explanations than physical causes. Indices derived from theories of probability change generally failed to predict the preference for voluntary actions. In contrast, this preference was mediated by the perceived extent to which voluntary versus physical causes may be brought under social control. These results suggest that causal explanation, at least within causal chains, is not driven solely by changes in the probability of an outcome when a cause is added, and that observers recognize the potential social function of explanations in drawing attention to socially controllable causes. Copyright © 2006 John Wiley & Sons, Ltd.     

A causal ontology of objects,causal relations,and various kinds of action

Synthese - The explanatory/pragmatic-trial distinction enjoys a burgeoning philosophical and medical literature and a significant contingent of support among philosophers and healthcare...     

Individualism,causal powers,and explanation

Versions of this paper were presented at the 17th Annual Meeting of the Society for Philosophy and Psychology in June 1991, at Cornell University in October 1991, and at Queen's University in January 1992; I thank Terence Horgan and Carl Ginet, respectively, for their comments on the first two of these occasions. I would also like to thank Terence Irwin, Sydney Shoemaker, Bob Stalnaker, Ed Stein, and J. D. Trout for comments on earlier versions of the paper, and Joe Moore, Dave Robb and Sergio Sismondo for useful discussion.