Pleskac Timothy J
University of Basel, Basel, Switzerland.
Psychon Bull Rev. 2007 Jun;14(3):379-91. doi: 10.3758/bf03194081.
The recognition heuristic uses a recognition decision to make an inference about an unknown variable in the world. Theories of recognition memory typically use a signal detection framework to predict this binary recognition decision. In this article, I integrate the recognition heuristic with signal detection theory to formally investigate how judges use their recognition memory to make inferences. The analysis reveals that false alarms and misses systematically influence the performance of the recognition heuristic. Furthermore, judges should adjust their recognition response criterion according to their experience with the environment to exploit the structure of information in it. Finally, the less-is-more effect is found to depend on the distribution of cue knowledge and judges' sensitivity to the difference between experienced and novel items. Theoretical implications of this bridge between the recognition heuristic and models of recognition memory are discussed.
再认启发式利用再认决策对世界中的未知变量进行推断。再认记忆理论通常使用信号检测框架来预测这种二元再认决策。在本文中，我将再认启发式与信号检测理论相结合，以正式研究判断者如何利用他们的再认记忆进行推断。分析表明，误报和漏报会系统性地影响再认启发式的表现。此外，判断者应根据他们对环境的经验调整其再认反应标准，以利用其中的信息结构。最后，发现少即是多效应取决于线索知识的分布以及判断者对熟悉项目和新异项目之间差异的敏感度。本文还讨论了再认启发式与再认记忆模型之间这一桥梁的理论意义。
