Recognition-based judgments and decisions: Introduction to the special issue (II)
Journal Title: Judgment and Decision Making - Year 2011, Vol 6, Issue 1
Abstract
We are pleased to present Part II of this Special Issue of Judgment and Decision Making on recognition processes in inferential decision making. In addition, it is our pleasure to announce that there will be a third part, providing, among other contents, comments on the articles published in Parts I and II as well as on the broader scholarly debates reflected by these articles (Table 1). We have therefore decided to keep this introduction to Part II short. Part II contains 7 articles, featuring a range of new experimental tests of Goldstein and Gigerenzer’s (1999, 2002; Gigerenzer & Goldstein, 1996) recognition heuristic, which is the model of recognition-based judgments and decisions that is central to almost all articles published in the parts of this special issue (Table 2). In addition, Part II presents very early but thus far unpublished experiments on this heuristic, and a discussion of past and future research on recognition-based judgments and decisions as well as an outline of challenges for future recognition heuristic research. Let us provide a short overview of the articles’ contents. Gigerenzer and Goldstein (1996) proposed the recognition heuristic as a model for situations in which a decision maker has to retrieve all available information from memory—a decision task they dubbed inferences from memory.1 Following the recognition heuristic, decisions can be based solely on a person’s recognition judgments, that is, on a sense of prior encounter with an alternative’s name (e.g., a car brand’s name). Yet, thus far comparatively little research has focused on how the decision processes assumed by the recognition heuristic tie into memory processes; for instance into those that determine whether an alternative’s name is judged as recognized or not. Erdfelder, Küpper-Tetzel, and Mattern (2011) aim to fill this gap (see also, e.g., Pleskac, 2007; Schooler & Hertwig, 2005) by studying the recognition heuristic from the perspective of a two-high-threshold model of recognition memory (Bredenkamp & Erdfelder, 1996; Snodgrass & Corwin, 1988) that belongs to the class of multinomial processing tree models (Batchelder & Riefer, 1990; Erdfelder et al., 2009). Following this two-high-threshold model, Erdfelder et al. (2011) assume that recognition judgments can arise from two types of cognitive states: (i) certainty states in which recognition judgments are strongly correlated with memory strength (including certainty for recognition with high memory strength as well as certainty for non-recognition with low memory strength) and (ii) uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. Erdfelder et al. (2011) report an experiment designed to test the prediction that the recognition heuristic applies to certainty states only. Based on their results, they argue that memory states influence people’s reliance on recognition in binary decisions. Erdfelder et al.’s (2011) article thus not only contributes to the recognition heuristic literature, but also to the broader field of recognition memory research and two-high-threshold models in particular (e.g., Bröder & Schütz, 2009; Erdfelder & Buchner, 1998; Erdfelder, Cüpper, Auer, & Undorf, 2007).
Authors and Affiliations
Julian N. Marewski, Rüdiger F. Pohl and Oliver Vitouch
Keywords
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