Abstract

Previous research has shown that the judged probability of an event depends on whether its description mentions examples (“What is the probability that a randomly chosen Italian businessman will travel during the next month to Warsaw, Budapest, Prague or some other European city?”) or does not mention examples (“What is the probability that a randomly chosen Italian businessman will travel during the next month to a European city?”). Here, we examined descriptions that mention examples and manipulated whether these are relatively similar (e.g., Warsaw, Budapest, Prague) or diverse (e.g., Warsaw, Marseilles, Helsinki). Four experiments (N = 1112) revealed a diversity effect: Overall, descriptions with diverse examples received higher probability judgments than descriptions with similar examples. We discuss several possible mechanisms for this effect, such as that descriptions with diverse examples prompt fuller representations of the target category or that the effect is driven by a representativeness or proximity heuristic.

摘要

先前的研究表明，判断一个事件的概率取决于它的描述是否提到了例子（“随机选择的意大利商人在下个月前往华沙、布达佩斯、布拉格或其他欧洲城市的概率是多少？”）或者没有提及示例（“随机选择的意大利商人在下个月前往欧洲城市的概率是多少？”）。在这里，我们检查了提及示例的描述并处理了这些示例是相对相似的（例如，华沙、布达佩斯、布拉格）还是不同的（例如，华沙、马赛、赫尔辛基）。四次实验（N = 1112）揭示了多样性效应：总体而言，具有不同示例的描述比具有相似示例的描述获得更高的概率判断。我们讨论了这种效应的几种可能机制，例如具有不同示例的描述会促使目标类别的更全面表示，或者该效应是由代表性或邻近启发式驱动的。