One of the central functions of categorization is to support reasoning. Having categorized some entity as a bird, one may predict with reasonable confidence that it builds a nest, sings, and can fly, though none of these inferences is certain. In addition, between-category relations may guide reasoning. For example, from the knowledge that robins have some enzyme in their blood, one is likely to be more confident that sparrows also have this enzyme than that raccoons have this enzyme. The basis for this confidence may be that robins are more similar to sparrows than to raccoons or that robins and sparrows share a lower rank superordinate category (birds) than do robins and raccoons (vertebrates).Recently, researchers have developed specific models for category-based reasoning and generated a range of distinctive reasoning phenomena (see Heit, 2000, for a review). These phenomena are quite robust when American college students are the research participants, but at least some of them do not generalize well to other populations. To address these limitations, we will offer not so much a specific model but rather a framework theory organized around the principle of relevance. This theory is more abstract than many of its predecessors, and one might imagine a number of implementations consistent with the relevance framework. Nonetheless, we will see that the relevance theory has testable implications.The rest of the paper is organized as follows. First, we briefly review two of the most influential models for induction: the Osherson, Smith, Wilkie, López, and Shafir (1990) category-based induction model, and Sloman's (1993) feature-based induction model. Next, we turn to the question of the generality of reasoning phenomena and describe two, more abstract, approaches that may be able to address the question of generality. Then we offer a theory at an intermediate level of abstraction, the "relevance theory," and describe some tests of its implications. Finally, we summarize and argue that there are benefits from approaching induction from a number of levels of analysis.The similarity-coverage model (SCM A framework theory, organized around the principle of relevance,is proposed for category-basedreasoning. According to the relevance principle, people assume that premises are informative with respect to conclusions. This idea leads to the prediction that people will use causal scenarios and property reinforcement strategiesin inductive reasoning. These predictions are contrasted with both existing models and normative logic. Judgments of argument strength were gathered in three different countries, and the results showed the importance of both causal scenarios and property reinforcement in categorybased inferences. The relation between the relevance framework and existing models of category-based inductive reasoning is discussed in the light of these findings. THEORETICAL AND REVIEW ARTICLES
This study examined 2-year-old children's ability to make category-based inferences. Subjects were asked a series of questions that they could answer based on category membership, appearances, or both. In one condition, all pictures were named; in a second condition, none were named. Children performed well on prototypical pictures regardless of whether they were named; on atypical pictures, they performed better when category labels were provided. A control study demonstrated that children ignored the label when it named a transient property rather than a stable category. Contrary to standard views of young children, these results indicate an early-emerging capacity to overlook salient appearances. However, one important development still to take place is the ability to use subtle perceptual cues to determine category membership in the absence of language. Are young children's categories based on appearances alone, or are children aware that categories can reflect deeper commonalities? Many years of developmental research and theory have suggested that children cannot look beyond the obvious (Wellman & Gelman, 1988). Children are highly attentive to perceptual similarities on a range of important tasks (e.g, Fenson, Cameron, & Kennedy, 1988; Gentner, 1988; L. B. Smith, 1989). At the same time, growing evidence suggests that surface similarity alone cannot adequately describe adult concepts and that theories play an important role in the organization of knowledge for adults (Murphy & Medin, 1985). Accordingly, a number of researchers have suggested that conceptual development reflects a shift from categories based on perceptual similarity to categories based on theories that reflect deeper underlying commonalities among category members (e.g., Neisser, 1987, p. 6). Recently, the notion of a developmental shift has been challenged by studies demonstrating that preschool children can overlook misleading perceptual information when reasoning about categories (S. A. Gelman & Markman, 1986). The impetus for this work was the assumption that categories function to extend knowledge beyond what is obvious or already known. If we learn certain facts about one category member, we are likely to infer that they are true of other category members as well. For example, if we learn that one dog has leukocytes inside it, we are likely to infer that other dogs also have leukocytes inside
Recent research shows that preschool children are skilled classifiers, using categories both to organize information efficiently and to extend knowledge beyond what is already known. Moreover, by 2 1/2 years of age, children are sensitive to nonobvious properties of categories and assume that category members share underlying similarities. Why do children expect categories to have this rich structure, and how do children appropriately limit this expectation to certain domains (i.e., animals vs. artifacts)? The present studies explore the role of maternal input, providing one of the first detailed looks at how mothers convey information about category structure during naturalistic interactions. Forty-six mothers and their 20- or 35-month-old children read picture books together. Sessions were videotaped, and the resulting transcripts were coded for explicit and implicit discussion of animal and artifact categories. Sequences of gestures toward pictures were also examined in order to reveal the focus of attention and implicit links. drawn between items. Results indicate that mothers provided a rich array of information beyond simple labeling routines. Taxonomic categories were stressed in subtle and indirect ways, in both speech and gesture, especially for animals. Statements and gestures that linked two pictures were more frequent for taxonomically related animal pictures than for other picture pairs. Mothers also generalized category information using generic noun phrases, again more for animals than for artifacts. However, mothers provided little explicit discussion of nonobvious similarities, underlying properties, or inductive potential among category members. These data suggest possible mechanisms by which a notion of kind is conveyed in the absence of detailed information about category essences.
The authors present evidence that seemingly unrelated biological misconceptions may share common conceptual origins arising from underlying systems of intuitive biological reasoning, or “cognitive construals.” The findings presented raise the intriguing possibility that university-level biology education may reify construal-based thinking and related misconceptions.
The authors examined inductive reasoning among experts in a domain. Three types of tree experts (landscapers, taxonomists, and parks maintenance personnel) completed 3 reasoning tasks. In Experiment 1, participants inferred which of 2 novel diseases would affect "more other kinds of trees" and provided justifications for their choices. In Experiment 2, the authors used modified instructions and asked which disease would be more likely to affect "all trees." In Experiment 3, the conclusion category was eliminated altogether, and participants were asked to generate a list of other affected trees. Among these populations, typicality and diversity effects were weak to nonexistent. Instead, experts' reasoning was influenced by "local" coverage (extension of the property to members of the same folk family) and causal-ecological factors. The authors concluded that domain knowledge leads to the use of a variety of reasoning strategies not captured by current models of category-based induction.Cognitive psychologists are increasingly interested in conceptual functions beyond categorization (e.g., Barsalou & Hale, 1992;Markman, Yamauchi, & Makin, 1997;Pazzani, 1991;Ross, 1996Ross, , 1997Wisniewski, 1995). Particularly, they have focused on the use of categories in reasoning and have proposed a number of formal models of category-based reasoning (e.g., Heit, 1998;McDonald, Samuels, & Rispoli, 1996; Osherson, Smith, Wilkie, L6pez, & Shaf'tr, 1990;Sloman, 1993;Smith, Shafir, & Osherson, 1993). The observation of some interesting regularities in reasoning patterns (see Osherson et al., 1990;Rips, 1975) has had a strong influence on the development of such models. In this article, we are particularly interested in the effect of extensive domain knowledge on reasoning. To explore this issue, we examine expert reasoning on inductive tasks and evaluate the ability of existing models to account for experts' reasoning behavior.In general, category-based induction requires that information about one set of categories be used to make inferences about another category. A set of premises establishes that one or more categories possess a certain property. The premises are followed by an assertion (the conclusion) that a target category also pos-
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