The dynamics model, which is based on L. Talmy’s (1988) theory of force dynamics, characterizes causation as a pattern of forces and a position vector. In contrast to counterfactual and probabilistic models, the dynamics model naturally distinguishes between different cause-related concepts and explains the induction of causal relationships from single observations. Support for the model is provided in experiments in which participants categorized 3-D animations of realistically rendered objects with trajectories that were wholly determined by the force vectors entered into a physics simulator. Experiments 1–3 showed that causal judgments are based on several forces, not just one. Experiment 4 demonstrated that people compute the resultant of forces using a qualitative decision rule. Experiments 5 and 6 showed that a dynamics approach extends to the representation of social causation. Implications for the relationship between causation and time are discussed.

Research suggests that causal judgment is influenced primarily by counterfactual or covariational reasoning. In contrast, the author of this article develops judgment dissociation theory (JDT), which predicts that these types of reasoning differ in function and can lead to divergent judgments. The actuality principle proposes that causal selections focus on antecedents that are sufficient to generate the actual outcome. The substitution principle proposes that ad hoc categorization plays a key role in counterfactual and covariational reasoning such that counterfactual selections focus on antecedents that would have been sufficient to prevent the outcome or something like it and covariational selections focus on antecedents that yield the largest increase in the probability of the outcome or something like it. The findings of 4 experiments support JDT but not the competing counterfactual and covariational accounts. If causation is the cement of the universe, as the philosopher David Hume (1740/1938) put it, then it is fair to say that causal knowledge is the cement that binds together each person’s representational universe. Causal reasoning—the process that generates this glue—confers many functional advantages. In virtually every sphere of human interest, our abilities to learn and categorize

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Although past theory and research have suggested that counterfactual thoughts (representations of alternatives to past outcomes) weaken the hindsight bias (after-thefact exaggeration of an outcome’s a priori likelihood), the present research shows the opposite (i.e., positive) relation. Experiment 1 demonstrated that counterfactual thinking can heighten the hindsight bias, and that the effect of counterfactuals on causal inferences can account for this relation. Experiment 2 indicated that postoutcome elaboration of the causal linkage between an antecedent and outcome is essential for thehindsightbias,and that this biasmay be redefinedto includepostoutcomecertainty regarding ‘‘what should have been’ ’ as well as what was. Experiment 3 provided more direct evidence that causal inferences mediate the facilitative effect of counterfactual thinking on the hindsight bias. © 1996 Academic Press, Inc. I just knew I should have picked door number two. L et’s Make a Deal contestant The above comment exemplifies a perception familiar perhaps not only to gameshowcontestants,but tomany ofus.Anunfortunateset of circumstances befalls us and we recognize instantly—alas, too late—that we might have This research was supported by a postdoctoral fellowship awarded to Neal Roese and a researchgrant awardedto James Olson,both fromthe SocialSciencesand HumanitiesResearch Council of Canada. We thank Dave Hamilton, Dale Miller, Mike Ross, Richard Sorrentino, Yaacov Trope, and two anonymous reviewers for providing valuable comments on various versionsof the manuscript.We are also grateful to Eileenda Pena for herassistance in runningthe first experiment. Correspondence and reprint requests should be addressed to Neal Roese,

This article describes recent research on counterfactual reasoning in causal judgment and details implications for future research on consumer and managerial decisions. Two types of counterfactual reasoning may be employed in causal judgment, one of which involves outcome contrasts, and is used to generate possible causal explanations, and the other of which involves antecedent contrasts and is used to test candidate explanations. Prior research on outcome contrasts indicates that people compare instances in which the event occurred to instances in which the event did not occur and base their causal explanations on distinctive features between these two types of occurrences. Explanations may therefore vary as a function of the instances chosen for comparison. Prior research findings suggest that consumers and managers may choose different comparison instances depending on their perspective, culture, and perceived norms. Prior research on antecedent contrasts indicates that people test possible explanations for an event by considering instances in which the candidate factor was absent and asking whether the event would have occurred anyway. Findings suggest, however, that consideration of antecedent contrasts may depend on the type of category on which the explanation is based, with less emphasis on antecedent contrasts for explanations based on categories of objects found in nature (natural kind categories) compared to categories of objects made by humans (artifactual categories). This article proposes the hypothesis that people may perceive some brands and product categories as more like natural

Research suggests that counterfactuals (i.e., thoughts of how things might have been different) play an important role in determining the perceived cause of a target outcome. Results from 3 scenario studies indicate that counterfactual content overlapped primarily with thoughts of how an outcome might have been prevented (preventability ascriptions) rather than with thoughts of how it might have been caused (causal ascriptions). Counterfactuals and preventability ascriptions focused mainly on controllable antecedents, whereas causal ascriptions focused mainly on antecedents that covaried with the target outcome over a focal set of instances. Contrary to current theorizing, causal ascriptions were unrelated to counterfactual content (Study 3). Results indicate that the primary criterion used to recruit causal ascriptions (covariation) differs from that used to recruit counterfactuals (controllability).

this paper we argue that the two phenomena are based on a single process and they can both occur with the same stimulus materials under certain situations. Before presenting our own view, the following section briefly reviews previous causal attribution theories in order to clarify our approach to this issue

Close counterfactuals are alternatives to reality that 'almost happened'. A psychological analysis of close counterfactuals offers insights into the underlying representation of causal episodes and the inherent uncertainty attributed to many causal systems. The perception and representation of causal episodes is organized around possible focal outcomes of the episode, evoking a schema of causal forces competing over time. We introduce a distinction between two kinds of assessments of outcome probability: dispositions, based on causal information available prior to the episode; and propensities, based on event cues obtained from the episode itself. The distinction is critical to the use of 'almost', which requires the attribution of a strong propensity to the counterfactual outcome. The final discussion focuses on characteristic differences between psychological and philosophical approaches to the analysis of counterfactuals, causation and probability.

human sex differences. Washington, DC:

Acknowledgement. I wish to thank Jim Woodward and the editors for their insightful comments on an earlier draft of this paper. 2 1.