No abstract

No abstract

No abstract

No abstract

Three experiments tested the hypothesis that people's overconfidence in the quality of their intuitive judgment strategies contributes to their reluctance to use helpful actuarial judgment aids. Participants engaged in a judgment task that required them to use five cues to decide whether a prospective juror favored physician-assisted suicide. Participants had the opportunity to examine the judgments of a statistical equation that correctly classified 77% of the prospective jurors. In all experiments, participants infrequently examined the equation, performed worse than the equation, and were highly overconfident. In Experiments 1 and 2, outcome feedback and calibration feedback failed to reduce overconfidence. In Experiment 3, enhanced calibration feedback reduced overconfidence and increased reliance on the equation, thus leading to improved judgment performance.

Recency effects (REs) have been well established in memory and probability learning paradigms but have received little attention in category earning research. Extant categorization models predict REs to be unaffected by learning, whereas a functional interpretation of REs, suggested by results in other domains, predicts that people are able to learn sequential dependencies and incorporate this information into their responses. These contrasting predictions were tested in 2 experiments involving a classification task in which outcome sequences were autocorrelated. Experiment 1 showed that reliance on recent outcomes adapts to the structure of the task, in contrast to models' predictions. Experiment 2 provided constraints on how sequential information is learned and suggested possible extensions to current models to account for this learning.

Exemplar and connectionist models were compared on their ability to predict overconfidence effects in category learning data. In the standard task, participants learned to classify hypothetical patients with particular symptom patterns into disease categories and reported confidence judgments in the form of probabilities. The connectionist model asserts that classifications and confidence are based on the strength of learned associations between symptoms and diseases. The exemplar retrieval model (ERM) proposes that people learn by storing examples and that their judgments are often based on the first example they happen to retrieve. Experiments 1 and 2 established that overconfidence increases when the classification step of the process is bypassed. Experiments 2 and 3 showed that a direct instruction to retrieve many exemplars reduces overconfidence. Only the ERM predicted the major qualitative phenomena exhibited in these experiments.

Three studies examined cultural variations in indecisiveness among Chinese, Japanese, and Americans. In Study 1, validated self-report, comprehensive measures of indecisiveness indicated large cultural differences, with Japanese participants exhibiting substantially more indecisiveness than Chinese or Americans. Study 2 provided evidence that such cultural variations correspond to variations in people’s positive versus negative values for decisive behaviors, suggesting that such values are plausibly an important means for motivating and sustaining cultural differences in indecisiveness. Study 3 provided direct behavioral instances of the differences in indecisiveness implicated in Studies 1 and 2. It also suggested that thoroughness might be an important cognitive mechanism whereby cultural differences in indecision actually occur, with thoroughness being especially prominent among Japanese decision makers. Suggestions for theory concerning the nature and foundations of indecisiveness and its cultural variations are developed and discussed, along with plausible implications for real-life practical issues, for example, in politics and management.