Reprint of the original, first published in 1869.

A leading scholar in the psychology of thinking and reasoning argues that the counterfactual imagination—the creation of "if only" alternatives to ...

Studies causation both as a concept and as it is 'in the objects.' Offers new accounts of the logic of singular causal statements, the form of causal regularities, the detection of causal relationships, the asymmetry of cause and effect, and necessary connection, and it relates causation to functional and statistical laws and to teleology.

The mental model theory of naive causal understanding and reasoning (Goldvarg & Johnson‐Laird, 2001, Cognitive Science, 25, 565–610) claims that people distinguish between causes and enabling conditions on the basis of sets of models that represent possible causal situations. In the tasks used to test this hypothesis, however, the proposed set of models was confounded with linguistic cues that frame which event to assume as given (the enabling condition) and which to consider as responsible for the effect under this assumption (...) (the cause). By disentangling these two factors, we were able to show that when identifying causes and enabling conditions in these tasks, people rely strongly on the linguistic cues but not on the proposed set of models and that this set of models does not even reflect people's typical interpretation of the tasks. We propose an alternative explanation that integrates syntactic and causal considerations. (shrink)

A normative framework for modeling causal and counterfactual reasoning has been proposed by Spirtes, Glymour, and Scheines. The framework takes as fundamental that reasoning from observation and intervention differ. Intervention includes actual manipulation as well as counterfactual manipulation of a model via thought. To represent intervention, Pearl employed the do operator that simplifies the structure of a causal model by disconnecting an intervened-on variable from its normal causes. Construing the do operator as a psychological function affords predictions about how people (...) reason when asked counterfactual questions about causal relations that we refer to as undoing, a family of effects that derive from the claim that intervened-on variables become independent of their normal causes. Six studies support the prediction for causal arguments but not consistently for parallel conditional ones. Two of the studies show that effects are treated as diagnostic when their values are observed but nondiagnostic when they are intervened on. These results cannot be explained by theories that do not distinguish interventions from other sorts of events. (shrink)

It is human nature to wonder how things might have turned out differently--either for the better or for the worse. For the past two decades psychologists have been intrigued by this phenomenon, which they call counterfactual thinking. Specifically, researchers have sought to answer the "big" questions: Why do people have such a strong propensity to generate counterfactuals, and what functions does counterfactual thinking serve? What are the determinants of counterfactual thinking, and what are its adaptive and psychological consequences? This important (...) work brings together a collection of thought-provoking papers by social and cognitive psychologists who have made important theoretical and empirical contributions to our understanding of this topic. The essays in this volume contain novel theoretical insights, and, in many cases descriptions of previously unpublished empirical studies. The Psychology of Counterfactual Thinking provides an excellent overview of this fascinating topic for researchers, as well as advanced undergraduates and graduates in psychology--particularly those with an interest in social cognition, social judgment, decision judgment, decision making, thinking and reasoning. (shrink)

Three experiments investigated reasoners' beliefs about causal powers; that is, their beliefs about the capacity of a putative cause to produce a given effect. Covariation-based theories (e.g., Cheng, 1997; Kelley, 1973; Novick & Cheng, 2004) posit that beliefs in causal power are represented in terms of the degree of covariation between the cause and its effect; covariation is defined in terms of the degree to which the effect occurs in the presence of the cause, and fails tooccur in the absence (...) of the cause. To test the degree to which beliefs incausal power are reflected in beliefs about covariation information, participants in three experiments rated their beliefs that putative causes have the capacity to produce a given effect (i.e., possess the causal power to produce an effect) as well as their beliefs regarding the degree to which the putative cause and effectcovary. A strong positive correlation was discovered between participants' beliefs in causal power and their beliefs that the effect occurs in the presence of the cause. However, no direct relationship was found between participants' beliefs in causal power and their belief that the effect will fail tooccur in the absence of the cause. These findings were replicated using bothwithin- (Experiments 1 and 3) and between-subject designs (Experiment 2). In Experiment 3, we extended these analyses to measures of familiarity, imageability, and detailedness of the representation. We found that participants' beliefs in causal power were strongly associated with familiarity, and imageability, but not the perceived detailedness of the cause and effect relationship. These data provide support for a multidimensional account of causal knowledge whereby people's representations of causation include, but are not limited to, the covariation, familiarity, and imageability of cause and effect relationships. (shrink)

Although the developmental and adult literatures on causal understanding appear at first glance to have little in common, in fact this appearance is illusory, and the idea of two theories helps to bring the two literatures in contact with each other.

Good explanations are not only true or probably true, but are also relevant to a causal question. Current models of causal explanation either only address the question of the truth of an explanation, or do not distinguish the probability of an explanation from its relevance. The tasks of scenario construction and conversational explanation are distinguished, which in turn shows how scenarios can interact with conversational principles to determine the truth and relevance of explanations. The proposed model distinguishes causal discounting from (...) causal backgrounding , and makes predictions concerning the differential effects of contextual information about alternative explanations on: (a) the kind of mental models constructed; (b) belief revision about probable cause; and (c) the perceived quality of a focal explanation. Four experiments are reported that test these predictions. The significance of the notion of explanatory relevance for research on causal explanation is then discussed. (shrink)

An updated and extended second edition supporting the findings of its well-known predecessor which claimed that courts employ common-sense notions of causation in determining legal responsibility.

Cross-cultural differences in cognition are often related to one single cultural dimension. Whether this suffices even for simple tasks is examined in the context of causal attribution. Culture-specific attribution biases are well-established for the social domain, but under dispute for the physical domain. In order to identify and assess possible impacts on assigning physical causation, we conducted a cross-cultural experiment with participants from Germany, China and Tonga. Participants were required to identify which of two entities is the ultimate cause for (...) a physical interaction that was varied with regard to linguistic cues and content. Our data reveal overall cultural differences in attribution tendencies analogous to those in the social domain, but also an impact of linguistic cues and of the task-specific content. (shrink)

In order to resolve the controversial discussion regarding content effects in deductive reasoning, we propose distinguishing between two inferential sources—an argument's form , and additional relations people associate with the argument's content —and analysing their interplay. Both sources are equally necessary in order to understand the role content plays in deductive reasoning. People make valid deductions from the content relations ( content competence ), but in thematic reasoning tasks, these deductions lead to the intriguing phenomenon known as content effects . (...) Focusing on the interplay of both sources of inferences, the dual source distinction enables a novel class of predictions to be made, namely the correct mastery of the logical connectors ( form competence ) in tasks that require the individual to think about an argument's form in relation to its content. To illustrate the dual source approach and its implications, the selection task paradigm of conditional reasoning with a point of view is used in combination with two content domains: conditional promises with cheating and non-cheating perspectives and technical systems with causal perspectives. Experimental findings corroborate all three phenomena: content competence, content effects, and form competence. The dual source distinction is discussed with regard to current theories of reasoning. (shrink)