Gavanski I, Hui C
Department of Psychology, Indiana University, Bloomington 47405.
J Pers Soc Psychol. 1992 Nov;63(5):766-80. doi: 10.1037//0022-3514.63.5.766.
This article proposes a novel framework for understanding judgments of probability. Both accurate and inaccurate judgments are conceptualized in terms of the sets of information, or sample spaces, on which they are based. When appropriate sample spaces are easily accessed from memory (e.g., when they correspond to natural cognitive categories), people will make relatively accurate judgments; otherwise, people may substitute more accessible but inappropriate sample spaces and make judgment errors. In 3 experiments, the sample space framework was applied to account for the base rate fallacy. Results showed that (a) people spontaneously access sample spaces that correspond to natural categories, (b) reliance on inappropriate sample spaces produces the base rate fallacy, and (c) highlighting appropriate sample spaces improves the sensitivity of people's judgments to base rates. Discussion extends the framework to explain accuracy and error in other judgment domains.
本文提出了一个理解概率判断的新颖框架。准确和不准确的判断都是根据它们所基于的信息集或样本空间来概念化的。当合适的样本空间能够轻易地从记忆中获取时（例如，当它们对应于自然认知类别时），人们会做出相对准确的判断；否则，人们可能会用更容易获取但不适当的样本空间来替代，并出现判断错误。在3个实验中，样本空间框架被用于解释基率谬误。结果表明：（a）人们会自发地获取与自然类别相对应的样本空间；（b）依赖不适当的样本空间会产生基率谬误；（c）突出合适的样本空间会提高人们的判断对基率的敏感性。讨论将该框架扩展到解释其他判断领域中的准确性和错误。
