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Perceptual and Conceptual Cues in Classification and Inference Tasks

Perceptual and Conceptual Cues in Classification and Inference Tasks Clare E. Sims (clare.holtpatrick@colorado.edu) Department of Psychology and Neuroscience, 345 UCB Boulder, CO 80309-0345 USA Eliana Colunga (eliana.colunga@colorado.edu) Department of Psychology and Neuroscience, 345 UCB Boulder, CO 80309-0345 USA Abstract the contributions of both perceptual and conceptual information to several types of category learning and use. In the current work we explore the contributions of perceptual and conceptual information to categorization, and particularly how each type of information is weighed in different kinds of categorization tasks. We do this in the domain of animacy in order to take advantage of a well- known characteristic of animacy categories. We are able to use many types of information available in the environment when categorizing or making inferences. This research explores how two types of information—perceptual and conceptual—may be used to different extents in different tasks. The method takes advantage of the distinction between animate and artifact categories. In two experiments, adult participants were given perceptual and conceptual information about the animacy of novel categories, and then were tested on three tasks. Participants categorized items by classifying with a given novel name, with a given fact, or by inferring untrained facts about the items. Results showed that participants used different sources of information depending on the task. These results are discussed in terms of how they could add to an account of the mechanisms of categorization. Animate and Artifact Categories Animacy is an apt domain for the exploration of the uses of different sources of information because people exhibit distinct patterns of categorization for animates versus artifacts. One way to characterize these different patterns is that artifact categories tend to be broader and more inclusive whereas animate categories tend to be narrower and more conservative. These distinctive patterns have been shown in both developmental and adult studies. Developmental studies have examined how children categorize animates and artifacts with novel name generalization tasks. In such tasks, a child is trained on a novel exemplar with a novel label. The child is then presented with various other novel test items that match the original in specific dimensions such as shape, size, and/or texture, while varying in other dimensions. When asked which of the test items would be labeled with the same name, children show distinct generalization patterns depending on whether the exemplar was presented as an artifact or as an animate. By three years of age children use shape as the only critical feature in categorizing novel artifact-like objects, but they use a more stringent criteria of both shape and texture for novel objects presented as animates (Jones, Smith, & Landau, 1991). The pattern of categorizing animates by multiple similarities, making for more restrictive categories, and categorizing artifacts by fewer similarities develops early in life and endures into adulthood. One study found that adults tended to classify items with more feature variability as artifacts, and only classified highly consistent items as animates (Freeman & Sera, 1996). Another explored the structural nature of animacy categories and found that artifact categories tend to be more flexible and spread out in similarity space whereas natural kinds, including animates, are more tightly clustered by similarities (Malt, Sloman, Gennari, Shi, & Wang, 1999). Keywords: Categorization; classification; inference; animacy; perceptual and conceptual information. Introduction A fundamental question of cognitive psychology centers on how we use the information available to us in the environment to accomplish cognitive tasks such as categorization. An intuitive view is that categorization is based on similarity information (Shepard, 1987). For example, objects that have perceptual features in common are often categorized together; cup-shaped objects tend to be grouped with other cup-shaped objects. More abstract commonalities, such as functional attributes, can also be involved in categorization (Rosch & Mervis, 1975). For example, the category of vehicles is well characterized by the functional attribute of being used for transportation. Categorization is highly complex and based on multiple types and sources of information. In this paper we focus on two specific types of information that contribute to categorization: perceptual and conceptual. Perceptual information refers to directly perceptible features of items we encounter, such as size and shape. Conceptual information refers to more abstract facts about these items, such as internal characteristics and function that may not be directly observable. The dichotomy between perceptual and conceptual information is at the heart of a lively debate in the developmental literature in which proponents of either side argue that category learning is a top-down, conceptually driven process (e.g., Booth & Waxman, 2008) or that it is a bottom-up, associative process (e.g., Colunga & Smith, 2008). The research with adults in this paper contributes by offering a method of comparing