Academic journal article Psychonomic Bulletin & Review

A Signal Detection Analysis of the Recognition Heuristic

Academic journal article Psychonomic Bulletin & Review

A Signal Detection Analysis of the Recognition Heuristic

Article excerpt

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.

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Simon (1990) observed that recognition is a natural mechanism for helping people to solve problems, such as those found in chess, medical diagnosis, or reading. Similarly, Axelrod (1985) postulated that recognition may be necessary for cooperation to be sustained in social interactions. The recent development of the recognition heuristic has added inferences to this list of indirect applications of recognition memory (Goldstein & Gigerenzer, 1999, 2002). According to the heuristic, recognition serves as a cue for making inferences about pairs of objects. The recognition heuristic can be quite accurate. These areas include, among others, making population inferences about German, U.S., and Swiss cities (Gigerenzer & Goldstein, 1996; Goldstein & Gigerenzer, 2002; Pohl, 2006), selecting stocks during a bull market (Borges, Goldstein, Ortmann, & Gigerenzer, 1999), and identifying National Hockey League players who have a high number of career points (Snook & Cullen, 2006).

Heuristics that use recognition as a predictor variable, such as the recognition heuristic, typically start with a judge's binary recognition decision (Gigerenzer & Goldstein, 1996, 1999; Goldstern & Gigerenzer, 1999, 2002). In contrast, memory research often focuses on the process that leads up to the recognition decision (Raaijmakers & Shiffrin, 2002). Research examining these memorial processes relies on laboratory experiments that have a defined learning phase in which participants study a list of items-sometimes novel, sometimes common-followed by a test phase hi which then· recognition memory is tested on the items that they learned. The results from the laboratory typically reveal that signal detection theory is useful for understanding why correct and incorrect recognition decisions are observed during memory experiments (Banks, 1970). In particular, two factors give rise to both decisions during memory experiments: (1) the ability to detect the difference between the familiarity of learned and unlearned items (sensitivity); and (2) various response factors (criterion location). Correct and incorrect recognition decisions, however, are more difficult to examine within the ecological framework of the recognition heuristic and the broader class of fast and frugal heuristics. The difficulty arises because then- ecological framework requires heuristics to be examined with a representative sample of stimuli drawn from an environment or reference class experienced outside of the laboratory (see Gigerenzer, Todd, & the ABC Research Group, 1999). Furthermore, the environment should be selected in such a way that the heuristic could sensibly be used in the environment to make inferences (see Gigerenzer et al., 1999). Consequently, the researcher does not typically know the items a respondent has or has not experienced, making it difficult-if not impossible-to identify correct and incorrect recognition decisions. …

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