STRUCTURAL ALIGNMENT IN COMPARISON:

Abstract— Theories of similarity generally agree that the similarity of a pair increases with its commonalities and decreases with its differences. Recent research suggests that this comparison process involves an alignment of structured representations yielding commonalities, differences related to the commonalities, and differences unrelated to the commonalities. One counterintuitive prediction of this view is that it should be easier to find the differences between pairs of similar items than to find the differences between pairs of dissimilar items. This prediction is particularly strong for differences that are related to the commonalities. We tested this prediction in two experiments in which subjects listed a single difference for each of a number of word pairs. The results are consistent with the predictions of structural alignment. In light of these findings, we discuss the potential role of structural alignment in other cognitive processes that involve comparisons.     

Affective Impact of Close Counterfactuals: Implications of Possible Futures for Possible Pasts

Close outcomes have been shown to influence counterfactual thoughts and affective reactions. Not quite achieving a goal can be particularly disheartening, and just making it can be particularly uplifting. Prior research (Medvec, Madey, & Gilovich, 1995; Medvec & Savitsky, 1997) has demonstrated a satisfaction reversal: People who just miss a better outcome (e.g., losing by 1 point) actually feel worse than those who were not as close (e.g., losing by 10 points). It was hypothesized that this effect should depend critically on whether there are future possibilities. In Study 1, analyses of newspaper articles showed that reactions to a close game depended on whether it was the first or last game of a series. Study 2 demonstrated a new type of satisfaction reversal: At halftime, people felt better when their team was down by 1 point than if their team was up by 1 point. It is suggested that finality evokes contrast effects and that future possibilities evoke assimilation.     

Perceptions of women and men as entrepreneurs: evidence for differential effects of attributional augmenting

It was hypothesized that perceptions of women who become entrepreneurs are enhanced by attributional augmenting because they adopt this role despite major obstacles to doing so. In contrast, attributional augmenting was expected to operate to a lesser degree for men who become entrepreneurs because they presumably face weaker obstacles. Three studies offered support for these hypotheses; all of these investigations used between-subjects designs in which women and men shown in standard-format photos were described to different groups of raters as being either entrepreneurs or managers. As predicted, raters assigned significantly higher scores to women, but not to men, when they were described as entrepreneurs.     

How do indirect measures of evaluation work? Evaluating the inference of prejudice in the Implicit Association Test.

There has been significant interest in indirect measures of attitudes like the Implicit Association Test (IAT), presumably because of the possibility of uncovering implicit prejudices. The authors derived a set of qualitative predictions for people's performance in the IAT on the basis of random walk models. These were supported in 3 experiments comparing clearly positive or negative categories to nonwords. They also provided evidence that participants shift their response criterion when doing the IAT. Because of these criterion shifts, a response pattern in the IAT can have multiple causes. Thus, it is not possible to infer a single cause (such as prejudice) from IAT results. A surprising additional result was that nonwords were treated as though they were evaluated more negatively than obviously negative items like insects, suggesting that low familiarity items may generate the pattern of data previously interpreted as evidence for implicit prejudice.     

Self-construal and the processing of covariation information in causal reasoning

Causal induction provides a nice test domain for examining the influence of individual-difference factors on cognition. The phenomena of both conditionalization and discounting reflect attention to multiple potential causes when people infer what caused an effect. We explored the hypothesis that individuals with an independent self-construal are relatively less sensitive to context (other causes) than are individuals with an interdependent self-construal in this domain. We found greater levels of conditionalization and data consistent with discounting for participants in whom we primed an interdependent self-construal than for participants in whom we primed an independent self-construal.     

Preference and the specificity of goals

In this study, the authors examined (a) the effect of changes in the need to eat on expressed preferences for foods that are appropriate for different times of day and (b) whether that need is directed toward food in general or foods contextually appropriate to the time of day. Previous findings suggest that, when the goal is active relative to when it is inactive, items relevant to satisfying a goal increase in value but items unrelated to that goal decrease in value. The authors observed that, when people needed to eat, they sought foods that are contextually appropriate to the time of day of the study. Hence, the goal they sought to fulfill was narrower than seeking foods in general.     

Priming interdependence affects processing of context information in causal inference—But not how you might think

Cultural mindset is related to performance on a variety of cognitive tasks. In particular, studies of both chronic and situationally-primed mindsets show that individuals with a relatively interdependent mindset (i.e., an emphasis on relationships and connections among individuals) are more sensitive to background contextual information than individuals with a more independent mindset. Two experiments tested whether priming cultural mindset would affect sensitivity to background causes in a contingency learning and causal inference task. Participants were primed (either independent or interdependent), and then saw complete contingency information on each of 12 trials for two cover stories in Experiment 1 (hiking causing skin rashes, severed brakes causing wrecked cars) and two additional cover stories in Experiment 2 (school deadlines causing stress, fertilizers causing plant growth). We expected that relative to independent-primed participants, those interdependent-primed would give more weight to the explicitly-presented data indicative of hidden alternative background causes, but they did not do so. In Experiment 1, interdependents gave less weight to the data indicative of hidden background causes for the car accident cover story and showed a decreased sensitivity to the contingencies for that story. In Experiment 2, interdependents placed less weight on the observable data for cover stories that supported more extra-experimental causes, while independents' sensitivity did not vary with these extra-experimental causes. Thus, interdependents were more sensitive to background causes not explicitly presented in the experiment, but this sensitivity hurt rather than improved their acquisition of the explicitly-presented contingency information.     

The influence of the number of relevant causes on the processing of covariation information in causal reasoning

Research on causal reasoning has focused on the influence of covariation between candidate causes and effects on causal judgments. We suggest that the type of covariation information to which people attend is affected by the task being performed. For this, we manipulated the test questions for the evaluation of contingency information and observed its influence on both contingency learning and subsequent causal selections. When people select one cause related to an effect, they focus on conditional contingencies assuming the absence of alternative causes. When people select two causes related to an effect, they focus on conditional contingencies assuming the presence of alternative causes. We demonstrated this use of contingency information in four experiments.