Copyright 1997 by the American Psychological Association, Inc. 0278-7393/97/$3.00
Journal of Experimental Psychology: Learning, Memory, and Cognition 1997, Vol. 23, No. 1, 54-70
Similar and Different: The Differentiation of Basic-Level Categories Arthur B. Markman
E d w a r d J. W i s n i e w s k i Northwestern University
Columbia University
Categories in the middle level of a taxonomic hierarchy tend to be highly differentiated in that they have both high levels of within-category similarity and low levels of between-category similarity. Research on similarity reveals a distinction between pairs of categories that are seen as dissimilar because they have few commonalities and pairs that are seen as dissimilar because they have many psychologically relevant alignable differences. The authors suggest that the low between-category similarity proposed for neighboring basic-level categories is actually a matter of having many psychologically relevant differences. In contrast, the low between-category similarity of superordinates is a result of their having few commonalities. The authors evaluate this claim in 4 experiments using a variety of natural stimuli and converging measures. The data support the importance of aliguable differences for distinguishing between pairs of basic-level categories.
People typically categorize objects at a number of levels of generality. For example, an object on top of a coffee table that has a rectangular shape, contains pages of printed text, and describes a mysterious murder can be called a murder mystery novel, a book, or reading material. The category book is more general than the category murder mystery novel because it includes other kinds of books. Likewise, the category reading material is more general than murder mystery novel or book because it contains the members of these categories as well as other objects (e.g., magazines, newspapers). In addition to this vertical structure of category hierarchies, there is also a horizontal structure. Semantically close or similar categories at the same level in the hierarchy are organized under the same parent category (e.g., books, magazines, and newspapers are types of reading material), whereas more semantically distant categories are organized under different parent categories (e.g., books are a type of reading material, but dogs are a type of animal). Hierarchically organized concepts are especially useful for drawing inferences. Knowing that an object belongs to a category allows one to plausibly infer of that object not only the properties of that category, but also those of categories higher in the taxonomy. For these and other reasons, hierarchically organized categories are important in our conceptual system.
Previous research on taxonomic hierarchies using natural and artificial stimuli has found that concepts at a middle level of abstraction are privileged in a variety of cognitive tasks, leading this level to be called the basic level (see Lassaline, Wisniewski, & Medin, 1992, for a review). Basic-level categories (e.g., book) can be contrasted with more general (i.e., superordinate) categories (e.g., reading material) and with more specific (i.e., subordinate) categories (e.g., murder mystery novel). In empirical studies, pictures of isolated objects are categorized faster at the basic level than at other levels (Jolicoeur, Gluck, & Kosslyn, 1984; Murphy & Brownell, 1985; Murphy & Wisniewski, 1989; Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976; Smith, Balzano, & Walker, 1978). People almost exclusively use basic-level names in free-naming tasks (Rosch et al., 1976). Children learn basic-level concepts sooner than other types of concepts (Anglin, 1977; Brown, 1958; Horton & Markman, 1980; Mervis & Crisafi, 1982; Rosch et al., 1976). Basic-level names are much more common in adult discourse than are names for superordinate categories (Wisniewski & Murphy, 1989). Further, different cultures tend to use the same basic-level categories, at least for living kinds (Rosch, 1974). Finally, the basic-level advantage appears to hold across a wide range of domains, including environmental categories (Tversky & Hemenway, 1984), computer programs (Adelson, 1983), personality types (Cantor & Mischel, 1979), and events (Morris & Murphy, 1990; Rifkin, 1985).
Arthur B. Markman, Department of Psychology, Columbia University; Edward J. Wisniewski, Department of Psychology, Northwestern University. We thank Dedre Gentner, Evan Heit, Tory Higgins, Mary Lassaline, Doug Medin, Greg Murphy, Kevin Sailor, Tom Ward, and Takashi Yamauchi for comments and helpful discussions during the development of this project. Special thanks to Lyman Casey, Bozena Malyscko, and Brendan Scherer for help scoring the data and to Tony Jung and Kristen Carpenter for help in running the experiments. We also thank Martin Brodeur for solid goaltending and Bob Dylan for inspiration. Correspondence concerning this article should be addressed to Arthur B. Markman, Department of Psychology, Columbia University, 406 SehearnerbornHail, New York, New York 10027. Electronic mail may be sent via Internetto
[email protected].
Similarity, Comparison, and Differentiation There are a variety of factors that contribute to the basic-level advantage. As Rosch et al. (1976) have shown, basic-level category labels are generally shorter than are labels for categories at other levels of abstraction. People may prefer to use shorter names in communication. Further, basic-level labels are often more frequent than subordinate labels. (In fact, they are often contained in subordinate labels, e.g., park bench; Murphy & Brownell, 1985.) This frequency advantage may make the basic-level term more 54
SIMILARITYAND TAXONOMY
accessible when attempting to name something. Basic-level categories also seem to be the most abstract level at which category members share parts (Tversky & Hemenway, 1984). Having a common part structure may facilitate classification of an instance at the basic level (see Biederman, 1987, for evidence). Perhaps the most compelling explanation for the basic-level advantage is based on the idea of differentiation. Compared with other categories, basic-level categories are thought to be highly differentiated (E. M. Markman, 1989; Mervis & Crisali, 1982; Morris & Murphy, 1990; Murphy & Brownell, 1985; Rosch et al., 1976). Differentiation is the result of two similarity relationships. First, the members of a basic-level category are assumed to be highly similar. This within-category similarity also holds for subordinate categories. In contrast, the members of superordinate categories are generally dissimilar. The second aspect of differentiation is that basic-level categories are thought to be dissimilar from other basic-level categories (i.e., they have low between-category similarity). As Murphy and Brownell (1985) stated, basic level categories are in general more distinctive than subordinate categories: Whereas members of a basic category tend to resemble each other, they do not resemble members of neighboring basic categories from the same superordinate. . . . By this reasoning, superordinatelevel categories are also quite distinctive. . . . In contrast, subordinate categories are not as distinctive. (p. 71) In summary, the differentiation of basic-level categories arises because they have both a high degree of withincategory similarity and a high degree of between-category dissimilarity. For example, many motorcycles have two wheels, a kickstand, an engine, and handlebars; they expose the driver to the outdoors and travel on land. Most instances of motorcycles share these features, but at the same time, these features are relatively distinctive: Members of contrasting categories (such as cars and trucks) share few of these features. Differentiation views similarity as a quantity and assumes that categories at different levels of abstraction vary in their amount of within- and between-category similarity. Basiclevel and superordinate categories have approximately equal (low) amounts of between-category similarity, but basiclevel categories have more within-category similarity than superordinates. Basic-level and subordinate categories have approximately equal (high) amounts of within-category similarity, but basic-level categories have less betweencategory similarity than do subordinates. According to the differentiation view, these similarity relationships are a matter of degree and not of kind. In this article, we refine the differentiation hypothesis using findings from research on the way that people catty out similarity comparisons between categories. Our analysis of this research suggests that the differentiation view is underspecified. In particular, there are two conceptually distinct ways in which one thing can differ from another. Thus, similarity relationships are also a matter of kind. Thus, we aim to refine the notion of "low between-category
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similarity," which is a key part of differentiation. We first turn to research on similarity to develop our hypothesis. Similarity as Structural Alignment Many studies have suggested that similarity is best viewed as an alignment of structured representations (Gentner & Markman, 1995; Goldstone, 1994a, 1994b; Goldstone & Medin, 1994; A. B. Markman & Gentner, 1993a, 1993b, 1996; Medin, Goldstone, & Gentner, 1993). The structural-alignment view is derived from research on analogy that highlights the importance of comparisons involving relations and relations' arguments in the formation of analogical correspondences (Gentner, 1983, 1989; Holyoak, 1985). According to this view, the output of the comparison process consists of commonalities between items and two kinds of differences: those related to the commonalities (called alignable differences) and those unrelated to the commonalities (called nonalignable differences; A. B. Markman & Gentner, 1993a, 1996). For example, when comparing a car with a motorcycle, the fact that both have wheels is a commonality. The fact that cars have four wheels, whereas motorcycles have two wheels, is an alignable difference that is conceptually related to the commonality of having wheels. Finally, the fact that cars have a jack in them, whereas motorcycles do not, is a nonalignable difference. In support of the psychological relation between commonalities and alignable differences, A. B. Markman and Gentner (1993a) asked participants to list the commonalities and differences of concepts that varied in their similarity. As would be expected if commonalities and alignable differences are related, there was a positive correlation between the number of commonalities and the number of alignable differences listed for a pair of concepts. In contrast, no reliable correlation was found between the number of commonalities and the number of nonalignable differences. In this study, similarity was manipulated by explicitly varying the semantic distance within a simple ontology. In this study, semantically close pairs (e.g., a robin and a bluebird) were rated as more similar than pairs of semantically distant items (e.g., a robin and a chair). Further, consistent with the predictions of structural alignment, more commonalities and alignable differences were listed for the close items than for the distant items. This analysis of similarity suggests two ways that a pair of categories can differ from each other. First, a pair of categories could have few commonalities. Second, a pair could have many alignable differences. The differentiation view does not distinguish between these possibilities, and hence it is underspecified. The previous research suggests a way to refine differentiation. This work demonstrated that the similarity between categories is correlated withsemantic distance and that the pattern of commonalities and differences that arises from a comparison is correlated with both similarity and semantic distance. At the basic level, where neighboring categories (i.e., those from the same superordinate) are semantically close, we would expect pairs to differ by having many alignable differences. Somewhat paradoxically, because
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alignable differences arise from commonalities, this prediction also suggests that neighboring basic-level categories should have many commonalities. In contrast, semantically distant basic-level categories (i.e., those from different superordinates) should have few commonalities. Given these predictions, it follows that subordinate categories from the same superordinate should also have many commonalities and alignable differences (whether or not they come from the same basic-level category). Further, like basic-level categories from different superordinates, subordinates from different superordinates should also be dissimilar in not having many commonalities. Finally, to round out the predictions, pairs of superordinates are semantically distant and hence should have few commonalities. For this reason, they may not be organized into clusters of categories with a common parent (unlike subordinate and basic-level categories). If these predictions are correct then they suggest that pairs of neighboring basic-level categories and pairs of superordinates are differentiated in different ways. Specifically, neighboring basic-level categories differ from each other by virtue of having many alignable differences. These neighboring basic-level categories should also have many commonalities. In contrast, superordinates differ from each other by having few commonalities (and hence few alignable differences). This hypothesis highlights another way that the differentiation view is underspecified. It assumes that the low between-category similarity at the basic level and at the superordinate level is qualitatively the same. However, we suggest that pairs of neighboring basic-level categories and pairs of superordinates do not differ in the same way. According to the structural-alignment view, it is the comparison of similarly structured representations that yields many commonalities and alignable differences (A. B. Markman & Gentner, 1993a, 1993b; Medin et al., 1993). There are a number of ways to think about items having similar representational structure, and for the present purposes, any will do. One possibility is that pairs with similar representational structures share a common frame consisting of dimensions or "slots" that are not shared with items that have different structures (Barsalou, 1992; Minsky, 1981). A second possibility is that items with common representational structures have similar sets of relations between properties. For example, the representation for animals might contain relations that link the body parts of animals. This common structure could be matched whenever animals were compared to yield commonalities and alignable differences among physical features. Given this view of representation and comparison, we can restate our predictions more precisely. Basic-level categories differ from superordinates in that they share representational structure with neighboring categories, whereas superordihates do not. Basic-level categories differ from subordinate categories in that they share representational structure primarily with other categories that have the same parent, whereas subordinate categories share representational structure with other subordinates from the same parent (i.e., the same basic-level category) and also with subordinates from
different parents (i.e., different basic-level categories from the same superordinate). We address these predictions in two stages. First, the prediction that categories from a given superordinate share a common representational structure suggests that it should be easy to find contrasting categories for basic-level categories and for subordinate categories. For basic-level categories, the retrieved categories should generally be other basic-level categories from the same superordinate. For subordinates, the retrieved categories may be other subordinates from the same basic-level category or from different basic-level categories from the same superordinate, because all of these categories have a common representational structure. In contrast, superordinates are not expected to share much structure with other superordinates, as we have suggested that superordinates are not organized into groups of semantically close categories. Thus, finding contrasting superordinares should be difficult. We assess the retrievability of contrast categories in Experiment 1. Then, in Experiments 2 and 3, we examine the commonalities and differences that arise from comparisons of categories at different levels in hierarchies. Finally, in Experiment 4, we examine whether this refinement of differentiation helps us to understand the way basic-level and superordinate categories are used in other cognitive tasks. Experiment 1 Our refinement of the differentiation view assumes that basic-level categories share representational structure with other basic-level categories from the same superordinate. Likewise, subordinate categories from the same superordinate (both those from the same basic-level category and those from different basic-level categories from the same superordinate) should share representational structure. In contrast, superordinate categories should not have much representational structure in common with other superordihate categories. We can examine the validity of these claims by giving participants categories and asking them to generate contrasting categories. Generating a contrast category requires retrieving a category from memory (and checking to make sure that it is a contrast category). Basic-level categories should have an advantage over superordinates in this task. Because contrasting basic-level categories are expected to have similar representational structures, the elements ,of the representation of one basic-level category should be good retrieval cues to access other basic-level categories from the same superordinate. In contrast, the representations of superordinates are not expected to share representational structure. Hence, the elements of these representations should not be good retrieval cues for other superordinates. There should also be a difference in the types of contrasts listed for basic-level and subordinate targets. Basic-level categories are assumed to share representational structure with other basic-level categories from the same superordihate (i.e., the same parent category). Subordinate categories are assumed to share representational structure with both subordinates from the same basic-level category (i.e., the
SIMILARITY AND TAXONOMY same parent category) and subordinate categories from different basic-level categories (i.e., different parent categories). Thus, basic-level targets should give rise to minimal contrasts, that is, contrast categories from the same parent category as the target. 1 In contrast, subordinate categories should yield both minimal contrasts and contrasting categories from different basic-level categories from the same superordinate. To assess the degree to which participants can generate contrast categories at different levels of abstraction, we elicited contrast categories by using a methodology developed by Malt and Johnson (1992). Participants were asked to pretend that they were playing a game in which something was described to them and they had to guess what it was. Participants would then see a category and would be told that it was their first (incorrec0 guess. Participants then supplied a second guess. They saw subordinate, basic-level, and superordinate categories as target first guesses. Two analyses of the generated contrasts were carried out. First, we examined the degree to which participants produced minimal contrasts as responses to the target categories. The minimal contrast for a basic-level category is another basic-level category from the same superordinate. In analogous fashion, the minimal contrast for a subordinate category is another subordinate category from the same basic-level category. Deciding whether a response to a superordinate target is a minimal contrast is difficult because the parent category of a superordinate is difficult to determine. Therefore, t o be maximally conservative, we considered any superordinate category to be a minimal contrast to a superordinate target. In addition, we examined the contrasts listed for subordinate categories to see whether they also included subordinate categories from the same superordinate but from different basic-level categories. The structural-alignment view makes two key predictions for this task. First, we expected more minimal contrasts for basic-level targets than for superordinate targets. Second, the contrasts generated for subordinate categories should be both minimal contrasts and subordinate categories from other basic-level categories within the same superordinate, because categories from the same superordinate category share a common representational structure. These predictions contrast with those of the traditional formulation of differentiation, which does not distinguish alignable differences from nonalignable differences. This view suggests that (a) both superordinate and basic-level categories are distinct from categories at the same level of abstraction and (b) subordinates are similar to other categories at the same level. Thus, it should be difficult to find contrasts for both superordinate and basic-level contrast categories, but easy to find contrasts for subordinate targets.
Me&od Participants. The participants were 42 Northwestern University undergraduates who took part in the experiment as part of a course requirement. Materials. We constructed the stimuli by first consulting Battig and Montague's (1969) norms, which list the most common
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Table 1 Categories Used in Experiment 1 Superordinate
Basic
Subordinate
vegetable vehicle musical instrument weapon jewelry footgear exercise equipment sports equipment clothing office equipment kitchen utensil tool camping equipment animal reading material beverage entertainment food furniture plant
beans bus guitar gun necklace shoes weights ball pants paper plate saw tent dog novel milk movie potatoes table tree
green beans school bus folk guitar shotgun pearl necklace sandals Nautilus weights football jeans typing paper dinner plate chainsaw pup tent poodle mystery novel skim milk horror movie mashed potatoes kitchen table pine tree
members of general categories given by a large sample of undergraduates. We selected 20 general categories, which we assumed to be superor"dmates, and from each of these categories, we chose 1 of its 20 most common members to be a basic-level category. Cv-trtuaUyall of the members are very frequent responses given in Wisniewski's (1994) more up-to-date superordinate category norms.) We then chose from each of the 20 basic-level terms a common subcategory to be a subordinate category. A graduate student blind to the purpose of the study verified that each subordinate was a common subcategory of its basic-level category. Table 1 lists the categories. In all of the experiments that follow, superordinate, basic-level, and subordinate categories were selected in a similar manner. Our stimuli meet at least several psychological criteria for being snperordinate, basic-level, and subordinate categories. They appear to reside at the same levels of abstraction that apply to the superordinate, basic-level, and subordinate categories of typical American college undergraduates (see Rosch et al., 1976, for discussion). In general, our superordinates are perceptually diverse categories whose members cannot be identified on the basis of the average shape of their members. In contrast, it is likely that our basic-level and subordinate categories can be identified in this manner. This criterion is one used by Rosch et al. (1976) to distinguish superordinates from basic-level and subordinate categoties. Finally, at least two thirds of our superordinates and basiclevel terms have been used in previous studies examining the basic-level advantage (Murphy & Brownell, 1985; Murphy & Wisniewski, 1989; Rosch et al., 1976; Wisniewskl & Murphy, 1989). The 60 categories were randomly divided into three lists of 20 categories, with the following constraints: An approximately equal number (6 or 7) of the categories in each list were superordinates, basic-level categories, and subordinates, and only 1 category from a hierarchy appeared in a list. 1 Contrast categories have been thought of as other categories from the same parent category, but we are using the term minimal contrast to make this point explicit.
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The three lists were each given to 14 participants. Half of the participants (7) saw the list in one random order, and half saw the list in the reverse order. Procedure. Participants read the following instructions: Imagine that you have heard a description of a thing and you are trying to guess what that thing is. You make a guess, but it turns out to be wrong. You now have to make a second guess. For example, suppose you heard the description, "thin, has a pointy end, used for writing." Suppose your first guess was "pencil." This guess turned out to be wrong. Your next guess might be "pen." On the next page you will see a list of "first guesses." (You will not see any descriptions of things.) Your task is to generate a second guess. Participants simply wrote their second guesses to the right of the first guess, in the blank provided. The task took about 10 min to complete.
Results We examined the prediction that of all target categories, basic-level targets would be most likely to yield minimal contrasts (i.e., contrast categories that are at the same level of abstraction as the target and come from the same parent category as the target). We counted the number of minimal contrasts listed for basic, subordinate, and superordinate targets (where superordinate minimal contrasts were any superordinate categories listed for a superordinate target). A one-way analysis of variance (ANOVA) revealed that there were reliable differences in the number of minimal contrasts as a function of level of abstraction, F(1, 57) = 6.97, MSE = 13.55, p < .005. As expected, more minimal contrasts were listed for basic-level targets (M = 9.70) than for either superordinate targets ( M = 5.15) or subordinate targets (M = 6.80), both p < .05 by Tukey's honestly significant difference (HSD). (The difference between superordinates and subordinates was not significant.) Whereas many contrasts listed for subordinate targets were minimal contrasts, there were also a number of contrasts listed for subordinates that came from other basic categories from the same superordinate. A count of the contrasts listed for subordinate targets that came from the
same superordinate shows that on average, the number of targets that came from the same superordinate (M = 8.95) was just about the same as the number obtained for basic-level targets (M = 9.70). This finding suggests that categories from the same superordinate have a common representational structure. In a final analysis, we examined the consistency of the contrast categories generated for categories at different levels of abstraction. We counted the number of unique responses out of the 14 total for each category. A high number of unique responses would indicate low consistency between subjects, whereas a low number would indicate high consistency between subjects. A one-way ANOVA on these data revealed significant differences between conditions, F(2, 57) = 4.80, MSE = 6.33, p < .05. Significantly fewer unique categories were listed at the basic level (M = 7.80) than at the superordinate level (M = 10.25),p < .01 by Tukey's HSD. The number of unique categories listed for subordinates (M = 9.25) was intermediate between that of basic-level and superordinate categories but did not differ significantly from either. To illustrate this pattern of data, Table 2 presents the contrast categories listed for a superordinate term (furniture), one of its basic-level categories (table), and a subordinate of that basic-level term (kitchen table). For this example, participants listed many different categories as contrasts for the superordinate. Fewer distinct categories were listed for the basic-level and subordinate categories. Further, there was a high level of agreement among participants at the basic level, with 7 out of 14 (50%) of the participants listing desk as a contrast for table. For the subordinate and superordinate categories, no more than 4 participants listed the same contrast category.
Discussion Participants were most likely to list minimal contrasts for basic-level target categories. This finding suggests that basic-level categories share representational structure with other basic-level categories from the same superordinate. The number of minimal contrasts listed for basic-level
Table 2
Sample Contrast Category Listings in Experiment I Superordinate (furniture)
Basic (table)
Subordinate (kitchen table)
Listed contrast
Number
Listed contrast
Number
Listed contrast
Number
floor clothes futon paintings trash can artwork bed car carpeting luggage table tree stump
3 1 1 1 1 1 1 1 1 1 1 1
desk chair dresser nightstand place mat
7 4 1 1 1
dining room table family room table counter desk bed grill living room furniture tray chair
4 2 2 1 1 1 1 1 1
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SIMILARITYAND TAXONOMY targets was approximately the same as the number of contrasts listed for subordinate targets that come from the same superordinate category. This finding suggests that all categories that come from a given superordinate have a similar representational structure. In contrast to participants' success at listing contrasts for basic and subordinate targets, participants had great difficulty listing superordinate contrasts for superordinate targets. This finding implies that superordinate categories do not share representational structure with other superordinates. Not only were minimal contrasts produced most often at the basic level, but agreement among participants was also higher at this level. Across participants, many fewer different categories were listed when the initial category was at the basic level than when it was at the superordinate or subordinate level. Thus, it appears that participants not only called to mind basic-level categories as potential contrasts but also tended to focus on a smaller set of categories at the basic level. Further, this result is consistent with the fact that contrasts at the basic level are focused on other categories from the same parent, whereas contrasts at the subordinate level draw both from categories from the same parent (i.e., subordinates from the same basic-level category) and from categories from different parents (i.e., subordinates from other basic-level categories from the same superordinate). One objection to these results is that they may simply reflect differences in word or object co-occurrence frequency. In particular, perhaps basic-level categories from the same superordinate are more associated with each other than are superordinates with other superordinates or subordinates with other subordinates. For example, we may be more likely to hear basic-level terms together because they are more frequent than superordinate or subordinate terms, or we may be more likely to see members of contrasting basic-level categories together (e.g., dog and cat are more likely to be seen together than are German shepard and dalmation). These factors, rather than comparability, may have caused the pattern of findings. To address these alternative explanations, we examined word-association norms for basic-level terms. If our results were primarily due to word or object co-occurrence frequency between basic-level categories from the same superordinate, then frequently produced word associations with basic-level terms should be other basic-level terms from the same superordinate. We examined the three most frequently produced responses to 15 basic-level terms that we randomly selected from Palermo and Jenkins's (1964) wordassociation norms for college students. 2 Associations with a basic-level term fell into six categories: the superordinate (13%), a basic-level term from the same superordinate (20%), a thematic relation, such as sleep for bed (29%), a thematically related object not from the same superordinate, such as pillow for bed (20%), an attribute of the basic-level category (13%), and a synonym (4%). In this analysis then, most (80%) of the common words associated with basiclevel terms were not other basic-level terms from the same superordinate. Two examples from the data of Experiment 1 should make the pattern of data clear. For the target table, the most frequent response given by participants was desk
(given by 7 participants) rather than the highly associated chair (which was given by only 4 participants). Similarly, for the target potatoes, the responses included minimal contrasts like beets, carrots, onions, and yams. Highly associated but more distant contrasts like steak were not listed. Therefore, it seems unlikely that our results were primarily due to word or object co-occurrence frequency. The results of this experiment imply that basic-level categories share representational structure with other basiclevel categories from the same superordinate. These findings clear the way to examine the commonalities and differences that arise from comparisons. In the introduction, we hypothesized that comparisons of pairs of categories from the same superordinate should yield many commonalities and many alignable differences, whereas comparisons of superordinates (and comparisons of basic-level categories from different superordinates) should yield few commonalities and few alignable differences. These predictions were tested in Experiment 2 with the commonality- and differencelisting methodology used by A. B. Markman and Gentner (1993a, 1996). Experiment 2
Participants listed the cornmonalities and differences of three types of category pairs:pairs of basic-levelcategories from different superordinates (basic/basic-rift),pairs of basic-level categories from the same superordinate (basic/ basic-same), and pairs of superordinates (super/super).3 This design specificallyseparatespairsof basic-levelcategories into those from the.same supcrordinate and those from differentsuperordinatcs.In contrast,pairs of superordinates were constructed by random selection.Analogous to the pairing of basic-level categories, an alternative strategy would have been to determine pairs of superordinates from the same and different high-level categories (i.e.,"supersuperordinate categories").However, participantsin Experiment 1 had great difficultylistingcontrast categories given superordinate targets, suggesting that these categories are not organized into higher levelcategories. In this experiment, we predicted that basic-levelcategories from the same superordinate would have both many commonalities and many alignable differences.This pattern of data differs from what would be expected given the traditionalformulation of differentiation,which would assume that contrasting basic-level categories are dissimilar 2 We could not directly compare the responses to our items with the word associations to those items because there was little overlap between our stimuli and those used by palermo and Jenkins (1964). 3 We also tested comparisons that crossed category levels (i.e., those consisting of a basic-level concept and either its superordinate or another superordinate). These pairs were included to round out the design but had no theoretical significance. Indeed, it is quite difficult to list properties, particularly differences, for the comparison of a basic-level concept and its superordinate (e.g., chairfurniture). Participants may view difference listings for these pairs as a violation of Gricean principles. We do not report the results from these comparisons.
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and hence should have few commonalities. We further assumed that pairs o f superordinates and pairs o f basic-level categories from different superordinates have different representational structures and hence should have few commonalities and alignable differences. If the data follow these predictions, then we would also show that the basic level is the most abstract level at which contrasting categories exhibit many commonalities and differences. Method Participants. The participants were 80 Northwestern undergraduates who took part in the commonality- and difference-listing task as part of a course requirement. Design and materials. The stimuli were 16 superordinate categories and two common basic-level categories from each superordinate. Table 3 shows the superordinates and their basiclevel categories. Two groups of stimuli were constructed in the following manner. The first group was created by randomly pairing the 16 superordinares to produce eight super/super pairs (e.g., disease vegetable). The superordinates were then randomly divided into two sets of 8. Two members of each superordinate from one set formed the basic/basic-same pairs (e.g., bed couch from the superordinate furniture). Finally, 1 randomly selected member from each of the 16 superordinates was paired to produce eight basic/basic--diff pairs. For example, one pair was fork newspaper, with fork selected from the superordinate kitchen utensil and newspaper selected from reading material. This process resulted in 24 category pairs: 8 pairs of each of the three stimulus types described above. In addition, 16 pairs that matched superordinate categories with basic-level categories were generated, but as mentioned in footnote 1, we do not discuss the data from these pairs. A second set was created by repeating this process. Each stimulus group was further divided in half, and each participant was given one of the resulting groups of 20 word pairs. Each participant saw 4 pairs of each type. Booklets were constructed to present the stimuli to participants. In each booklet, one pair was placed at the top of each page along with instructions to list the commonalities or differences of the pair in the remaining space. Half of the pairs in each booklet were
Table 3 Superordinates and Their Basic-Level Categories (Experiment 2)
Superordinate
Basic-level categories
clothing musical instrument
tie-scarf trumpet-saxophone
weapon vehicle furniture reading material
sword-spear bus--truck bed-couch
kitchen utensil human dwelling tool beverage fruit vegetable animal insect bird disease
magazine--newspaper spoon-fork apartment-hotel screwdriver-drill coffee-tea apple-pear onion-radish horse--cow
ant-termite robin-canary measles--chicken pox
commonality pairs, and half were difference pairs. Thus, 2 participants were required to obtain a complete commonality and difference listing for each set. The order of pages was determined randomly for each booklet. Each booklet was given to 10 participants. Procedure. Participants in the commonality- and differencelisting task read the following instructions: In this study, we are interested in the commonalities and differences you can find for various word pairs. At the top of each page in this booklet is a pair of words preceded by the instructions 'Commonalities of' or 'Differences between.' Follow the instructions for each pair by listing either the commonalities or the differences of the pair in the space provided. Take as much time as you need on each pair. If you run out of room for a pair, continue listing the commonalities or differences on the back of the sheet. When you have finished listing properties for a pair, go on to the next page. Do not go back and add any properties once you have gone on. Please list only commonalities or differences of the concepts labeled by the terms. Do not compare properties of the physical words (e.g., 'Both start with vowels') or their grammatical categories (e.g., 'Both are nouns'). If you do not know the meaning of one (or both) of the words in a pair circle the word(s) you do not know and go on to the next pair. If you have any questions, please ask the experimenter now. Otherwise, you may turn to the next page and begin. Participants proceeded through the booklet at their own pace. The study took approximately 1 hr to complete. Scoring. The data were scored using a modified version of the procedure adopted by A. B. Markman and Gentner (1993a). Two naive raters were used. Each rater scored the data for half of the word pairs. Scoring of the commonality listings was straightforward. One commonality was counted for each item that participants listed as true of both objects. Each utterance beginning with "Both [items] are x" or "Both [items] are not x" was scored as commonalities. In contrast, commonalities (and differences) in the surface form of the stimulus words or of their grammatical category were not counted as commonalities. Finally, associations between the objects were not counted as commonalities. The difference listings required some method for distinguishing alignable and nonalignable differences. For a response to count as an alignable difference, participants had to make explicit or implicit mention of a different value along some property or dimension for both objects. Thus, a statement like A watch is worn on the wrist, and a necklace is worn on the neck is an explicit mention, whereas a statement like A watch and a necklace are worn on different parts of the body is an implicit mention. Either of these descriptions would be counted as an alignable difference. All other differences were considered nonalignable differences. For example, saying A watch has a face, but a necklace does not is a nonaiignable difference. The total number of differences for a pair was simply the sum of the alignable and nonalignable differences. As a check on the accuracy and consistency of the raters, one of the authors also scored a representative subset of the differencelisting data. (The commonality data were not examined in this regard because scoring these data was just a matter of counting the number of features that participants listed.) Two of the eight category pairs from each condition were selected for this analysis. There was 85% agreement between the raters' scoring, with a Cohen's kappa of 0.73. Results We report analyses for the super/super, basic/basic-same, and basic/basic-diff pairs. Table 4 lists the mean number o f
SIMILARITYAND TAXONOMY
61
Table 4 Mean Number of Commonalities, Alignable Differences, and Nonalignable Differences, as Well as the Proportion of Alignable Differences Listed by Participants in Experiment 2 Mean Mean proportion Mean Mean alignable nonalignable of alignable Condition commonalities differences differences differences Basic/basic-cliff 2.86 2.55 2.68 .48 Basic/basic-same 6.68 3.07 0.78 .81 Super/super 3.13 2.06 2.14 .50 Note. Basic/basic-diff = pairs of basic-level concepts from different superordinates; basic/basicsame = pairs of basic-level concepts from the same superordinate; super/super = pairs of superordinates. |
listed commonalities, alignable differences, and nonalignable differences for all pairs in each condition. The mean proportion of differences that were alignable differences is also reported. Item analyses were done rather than subject analyses, as each participant did not see all of the words. One-way ANOVAs performed on each of these variables indicated significant differences in these variables as a function of comparison type. We report post hoc comparisons between conditions, in which significant differences are reliable at p < .05 by Tukey's HSD. For each analysis, we also present the model mean square error used as the basis of the mean comparisons. Consistent with our hypothesis, participants listed significantly more commonalities for basic/basic-same pairs (M = 6.68; model MSE = 1.87) than for either the basic/ basic-diff pairs (M = 2.86) or the super/super pairs (M = 3.13), which did not differ significantly from each other. The pattern of listed alignable differences also conformed to our hypotheses. As predicted, participants listed significantly more alignable differences for basic/basic-same pairs (M = 3.08; model MSE = 0.80) than for super/super pairs (M = 2.06). The number of alignable differences for basic/ basic-diff pairs (M = 2.55) was not reliably lower than that for basic/basic-same pairs. A very different pattern of property listings was obtained for nonalignable differences. Significantly more nonalignable differences were listed for basic/basic-diff (M = 2.68; model MSE = 0.87) and super/super pairs (M = 2.14) than for basic/basic-same pairs (M = 0.78). The difference in the number of nonalignable differences listed for basic/basicdiff and super/super pairs was not significant. In opposition to the pattern for alignable differences, more nonalignable differences were listed for pairs of superordinates and basic-level categories from different superordinates than for pairs of basic-level categories from the same superordinate. It is somewhat surprising that the number of alignable differences listed for basic-level categories from the same superordinate is not reliably higher than the number of alignable differences listed for basic-level categories from different superordinates. However, the difference between these comparisons becomes much clearer when considering the proportion of listed differences that were alignable differences. This analysis reveals that as expected, a significantly higher proportion of listed differences were atignable
differences for basic/basic-same pairs (M = 0.81; model MSE = 0.02) than for either basic/basic-diff (M = 0.48) or super/super (M = 0.50) pairs (which did not differ significantly). Finally, to ensure that the data did not differ systematically from those of previous studies, we examined the relationships among commonalities, alignable differences, and nonalignable differences. Previous work on the comparison process suggests that there is a positive relationship between the number of commonalities and the number of alignable differences listed for pairs. (As noted in the introduction, finding commonalities between concepts leads to finding their differences.) Consistent with this prediction, there was a significant positive correlation between the number of commonalities and the number of alignable differences listed for each pair, r(46) = .37, p < .05. 4 In contrast, there was a negative correlation between the number of commonalities and the number of nonalignable differences listed for each pair, r(46) = -.58, p < .01. Thus, there is no reason to believe that these data deviate from those of previous studies of commonalities and differences.
Discussion These data support the predictions of the structuralalignment extension to differentiation. The key finding is that comparisons of contrasting basic-level categories yielded many commonalities and many alignable differences. In contrast, pairs of superordinates and pairs of basic-level categories from different superordinates yielded few commonalities and few alignable differences. These data suggest that pairs of basic-level categories from the same superordinate differ by virtue of having many aligoable differences, whereas pairs of superordinates (and pairs of basic-level categories from different superordinates) differ by virtue of having few commonalities and many nonalignable differences. 5 4 This correlation is significantly positive, though smaller than has been observod in other studies. One possible explanation for the size of this correlation is simply that the range of listed alignable differences in this experiment is rather small relative to the range in other studies in which more extreme variations in semantic distance of pairs were used. s Nonalignable differences do not appear to be central to the
62
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~
AND WlSNIEWSKI
One objection to our results is that they may be due to differences in the availability of properties at different category levels. In this experiment and others (e.g., Rosch et ai., 1976), participants have typically listed more properties for basic-level terms than for superordinate terms. Thus, pairs of basic-level categories may generally have more properties available for listing than pairs of superordinates do. Therefore, the observed differences between pairs of basic-level categories from the same superordinate and pairs of superordinates may reflect differences in property availability rather than differences in comparability. However, two other findings argue against this alternative interpretation. First, these differences were also observed between basic-level categories from the same superordinate and basic-level categories from different superordinates. Second, the proportion of listed alignable differences was also higher for pairs of basic-level categories from the ~ m e superordinate than for other pairs. If these findings had only resulted from the relative availability of properties, then there should not have been any systematic difference in the proportion of listed differences that were alignable differences. Experiment 3 extended Experiment 2 in two ways. First, we expanded the stimulus set to include subordinates, as well as basic-level categories and superordinates. Because different subordinates from the same superordinate should also share representational structure, pairs of subordinates from the same basic-level category and pairs of subordinates from different basic-level categories from the same superordinate should give rise to many commonalities and alignable differences. Further, if subordinate categories from different supemrdinates do not share representational structure, then comparisons of these items should yield few commonalities or alignable differences. Second, we extended Experiment 2 by performing a content analysis on the properties listed, which may provide insight into the kinds of information stored at different levels of a hierarchy. Experiment 3 The stimulus set for this experiment included superordinate, basic-level, and subordinate categories. Participants listed commonalities and differences for six types of comparisons. As in the first study, there were pairs of superordinates (super/super), pairs of basic-level concepts from different superordinates (basic/basic-diff), and pairs of basic-level concepts from the same superordinate (basic/basic-same). In addition, there were three kinds of pairs involving subordinates: subordinates from different superordinates (sub/sub-cliff super), subordinates from different basic-level categories but the same superordinate (sub/sub-cliff basic), and pairs of subordinates from the same basic-level category (sub/sub-same basic). Our predictions for the basic-level and superordinate concepts mirror those for Experiment 2. Comparisons of superordinates should yield few commonalities and alignable differences. Participants should list more commonalioutput of comparison as commonalities or alignable differences (Genmer & Markman, 1994; A. B. Markman & Genmer, 1996).
ties and alignable differences for pairs of basic-level categories from the same superordinate than for pairs of basic-level categories from different superordinates. Because subordinate categories from the same superordinate should have similar representational structures, many commonalities and alignable differences should be listed both for pairs of subordinates from the same basic-level category and pairs of subordinates from different basic-level categories from the same superordinate. Finally, few commonalities and alignable differences should be listed for pairs of subordinates from different superordinates, which should not share representational structure.
Method Participants. The l~a'ticipants were 23 Northwestern undergraduates who took part in the experiment as part of a course requirement. Materials. Twenty hierarchies were used to construct pairs of categories at three levels of abstraction (i.e., the superordinate, basic, and subordinate levels). Ten hierarchies consisted of one superordinate category, three basic-level categories, two subordinate categories from each of two of these basic-level categories, and one subordinate category from the remaining basic-level category. For ease of exposition, we refer to these hierarchies as Group 1 hierarchies. Ten other hierarchies consisted of one superordinate, one basic-level category, and one subordinate of this basic category. We refer to these as the Group 2 hierarchies. Six types of category pairs were constructed by pairing the categories from a Group 1 hierarchy with those of a Group 2 hierarchy. Table 5 shows examples of the six types, which were constructed by using all of the categories from the Group 1 hierarchy headed by the superordinate vehicle and from the Group 2 hierarchy headed by the superordinate reading material.
Table 5
Examples of Categories and Their Pairings (Experiment 3) Superordinate vehicle
Basic level bus truck
reading material
car novel
Subordinate school bus city bus fire truck semitrailer truck limousine mystery novel
Pairing Category
Example vehicle-reading material bus--truck car-novel school bus-city bus fire truck-limousine semitrailer truck-mystery novel
Super/super Basic/basic-same Basic/basic-diff Sub/sub-same basic Sub/sub--diffbasic Sub/sub-diff super Note. Super/super = pairs of superordinates; basic/basic-same = pairs of basic-level concepts from the same superordiuate; basic/ basic-diff = pairs of basic-level concepts from different superordinares; sub/sub-same basic = pairs of subordinates from the same basic-level categories; sub/sub--diff basic = pairs of subordinates from different basic-level categories but the same superordinate; sub/sub-diff super = subordinates from different superordinates.
SIMILARITYAND TAXONOMY As shown in Table 5, a super/super pair was created by randomly pairing a Group 1 and a Group 2 superordinate. A basic/basic-same pair was created by randomly selecting two of the three basic-level categories from the Group 1 set. A basic/basic--diff pair was created by pairing the remaining basic-level category of the Group 1 set with the basic-level category of the Group 2 set. A sub/sub-same basic pair was created by pairing the two subordinates from one of the basic-level categories of the Group 1 set. A sub/sub--diff basic pair was created by pairing subordinates of the other two basiclevel categories from the Group 1 set, resulting in a pair of subordinates nested in different basic-level categories but the same superordinate. Finally, a sub/sub--diff super pair was created by pairing the remaining subordinate from the Group 1 set with the subordinate from the Group 2 set, yielding subordinates from different superordinates. Pairing the categories of 10 Group 1 sets and 10 Group 2 sets resulted in 10 examples of each of the six types of category pairs. Design. Two lists of the category pairs were created. In one list, half of the examples (5)of each of the types of the 6 category pairs were randomly designated as pairs for which participants would list differences, and half were randomly designated as pairs for which participants would list commonaiities. This process resulted in a list of 30 pairs for which participants listed differences and 30 pairs for which they listed commonalities. In the other list, these designations were reversed (i.e., pairs for which participants were to list differences were now pairs for which they were to list commonalities and vice versa). Approximately half (11) of the participants saw the first list, and half (12) saw the second list. Each participant saw the category pairs in a different random order. Procedure. Participants were told that the study investigated the way that people compared concepts. Participants saw pairs of words at the top of a computer screen along with instructions to list the commonalities of a pair or the differences of a pair. Participants typed all the commonalities (or differences) that they could. Participants were instructed to type one commonality (or difference) on each line and to hit the return key at the end of each line to go on to the next line. If they reached the bottom of the screen, it automatically scrolled up. When participants typed all the commonaiities (or differences) that they could think of, they hit the tab key to go on to the next pair. Participants also were asked to list commonalities or differences of the concepts indicated by the words, rather than the physical words themselves (like the number of letters). The instructions also stated that participants should take their time, as the experimenter was interested in what a participant
63
could think of rather than how fast the participant could think of it. Finally, participants were told to type, I don't know what the [word] is, if they did not know the meaning of one of the words in a pair. The task took about 1 hr and 30 rain to complete. Scoring. The data were scored with the same procedure as in Experiment 2. One of the authors scored the d~ta for all of the word pairs. Again, scoring of commonality listings was straightforward. One commonality was counted for each item that participants listed as true of both objects. For the difference listings, statements were classified as alignable differences if a participant made an explicit or implicit mention of a different value along some property or dimension for both objects. All other differences were classified as nonalignable differences. Once again, associations between the objects and properties of the words were not counted. To check the accuracy and consistency of the rater, a naive rater scored 2 of the 10 category pairs from each condition. There was 90% agreement between the raters, with a Cohen's kappa of 0.80.
Results Table 6 presents the mean number of commonalities, alignable differences, and nonalignable differences listed by participants for each type o f comparison. The proportion of differences that were alignable differences was also determined. As for Experiment 2, item analyses were performed, with one-way ANOVAs done on each response variable. Just as we found in Experiment 2, these ANOVAs revealed significant differences between conditions for each variable. We present the results o f post hoc comparisons, in which all significant differences were obtained by Tukey's HSD. Again, the model mean square errors that formed the basis of the mean comparisons are presented. First, we discuss the mean number of commonalities listed by participants. As expected, significantly more commortalities were listed for pairs with the same parent category (basic/basic-same pairs, M = 4.91, model MSE = 1.04; and sub/sub-same basic pairs, M = 5.38) than for pairs with different parent categories (super/super pairs, M = 3.15; basic/basic-diff pairs, M = 2.67; and sub/subdiff super pairs, M = 2.51). In addition, participants listed significantly more commonalities for the sub/sub-same
Table 6
Mean Commonalities, Alignable Differences, Nonalignable Differences, and Proportion of Alignable Differences Listed by Participants in Each Comparison Condition.of Experiment 3 Condition
Mean commonalities
Mean alignable differences
Mean nonalignable differences
Mean proportion of alignable differences
Sub/sub-same basic Sub/sub--diff basic Sub/sub--diff super Basic/basic-same super Basic/basic-diff super Super/super
5.38 3.94 2.51 4.91 2.67 3.15
2.67 2.53 2.00 2.62 1.94 1.76
1.35 1.95 2.67 1.43 2.62 1.62
.66 .56 .44 .66 .43 .54
Note. Sub/sub-same basic = pairs of subordinates from the same basic level category; sub/sub-diff basic = subordinates from different basic-level categories but the same superordinate; sub/sub--rift super = subordinates from different superordinates; basic/basic-same super --- pairs of basic-level concepts from the same superordinate; basic/basic--diff super = pairs of basic-level concepts from different superordinates; super/super = pairs of superordinates.
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basic pairs than for sub/sub-diff basic pairs (M = 3.95). The difference between basic/basic-same pairs and sub/sub--cliff basic pairs was not significant. This result seems reasonable, as both comparisons involved categories from the same superordinate. The only other significant difference obtained was that as expected, more commonalities were listed for sub/sub-cliff basic pairs than for sub/sub--diff super pairs. The pattern of property listings for alignable differences is also consistent with our hypotheses. Participants listed significantly more alignable differences for sub/sub-same basic pairs (M = 2.67; model MSE = 0.46) than for super/ super pairs (M = 1.76). In addition, participants marginally significantly listed more alignable differences for basic/basicsame pairs (M = 2.62) than for super/super pairs, p = .065 by Tukey's HSD. No other differences between conditions were significant. As in Experiment 1, the number of alignable differences listed for basic/basic-diff pairs (M = 1.94) was intermediate between the number of alignable differences listed for basic/basic-same pairs and super/ super pairs. The pattern of property listings for nonalignable differences was different than that obtained for alignable differences. As expected, significantly more nonalignabte differences were listed for comparisons involving categories with different parents (i.e., sub/sub-diff super pairs, M = 2.67, model MSE = 0.61; and basic/basic--4iff pairs, M = 2.62) than for super/super pairs (M = 1.62), basic/basic-same pairs (M = 1.43), or sub/subsame basic pairs (M = 1.35; this latter difference was only marginally significant, p = .06 by Tukey's HSD). Although the number of nonalignable differences listed for basic/basic-same pairs was less than the number for super/super pairs, it did not reach statistical reliability.6 No other differences between conditions were significant. Once again, we determined the proportion of differences that were alignable differences. Participants listed a higher proportion of alignable differences for basic/basic-same pairs (M = 0.66, model MSE = 0.02) and for sub/sub-same basic pairs (M = 0.66) than for basic/basic-diff pairs (M = 0.43) and sub/sub-diff super pairs (M = 0.44). As for Experiment 1, the proportion of alignable differences was higher for basic/basic-same pairs than for super/super pairs (M = 0.54), though the difference was not statistically significant, p > .10 by Tukey's HSD. No other differences between conditions were significant. As we did for Experiment 2, we checked the consistency of these data with those of previous studies through correlational analyses. Again, a significant positive correlation was obtained between the number of commonalities listed for pairs and the number of alignable differences listed for pairs, r(58) = .44, p < .01. In contrast, a negative correlation was obtained between the number of commonalities and the number of nonalignable differences listed for pairs, r(58) = -.53, p < .01. This finding suggests that pairs with many commonalities have many alignable differences, whereas pairs with few commonalities have few alignable differences. That is, the same pairs can be seen as both similar and different.
Types of Listed Properties Many kinds of content analyses could be performed on commonality- and difference-listing data. Previous research using commonality and difference listings has found that a narrower range of properties is listed consistently by participants for dissimilar pairs than for similar pairs. For example, Gentner and Markman (1994) asked participants to list one difference for pairs that were either of high similarity or of low similarity. For the dissimilar pairs, the two most frequently listed types of differences (function and category) accounted for 65% of the listed differences. In contrast, for the similar pairs, the seven most frequently listed types of differences (parts, function, size, location, power source, age, and temperature) accounted for only 62% of the listed differences. We examined the content of the commonality and difference listings in this study to see whether a wider range of properties was again listed for similar pairs than for dissimilar pairs. For this analysis, we used a rater who did not know the hypothesis under study. Problems classifying items were resolved by discussion with one of the authors, but these difficulties were rare. Table 7 presents the properties that were listed by a mean of 2 or more participants per item for the six types of comparisons in this study. The data in this table are subdivided by kinds of properties listed as commonalities and kinds of properties listed as differences. It is interesting to consider just those pairs listed on average by at least 4 participants per item (approximately one third of the participants listing commonalities or differences). For pairs coming from different superordinates, only function reached this criterion as a listed commonality or difference. For contrasting basic-level categories, function, parts, and category all reached this criterion. For subordinate categories from the same superordinate, function, parts, category, and location all exceeded this criterion. Thus, a wider range of properties was available with some consistency for categories that shared a common structure than for categories that did not. Further, the basic-level was the most abstract level at which comparisons promoted access to a range of properties.
Discussion Taken together, the results of the first three experiments suggest that neighboring basic-level categories have many commonalities and many alignable differences. This pattern was also observed for pairs of subordinates from the same superordinate. In contrast, pairs of superordinates and pairs of more specific categories from different superordinates did not exhibit this pattern. This finding is consistent with the claim that basic-level and subordinate categories from a given superordinate have comparable representational struc-
6 No strong predictions were made for the number of nonalignable differences that would be listed for a pair. Often nonalignable differences seem to have been listed when no other differences were available or when information about the items did not need to be stored in working memory (Markman & Gentner, 1996).
SIMILARITYAND TAXONOMY
65
Table 7
Classes of Properties Listed as Commonalities and Differences in Experiment 3 Super/super
M
Basic/basic-same
M
Basie/basic-diff
function commodity owner
4.7 2.2 2.1
function category part material location cost
10.2 6.6 4.2 3.3 2.5 2.1
function
11.5 3.3
function parts
13.3 4.6 2.5 2.0
function category animacy parts size naturalness material
M
Sub/sub-same basic
Commonalities 3.0 function category parts location when used owner
M
Sub/sub-diff basic M
9.7 8.4 8.4 3.0 2.4 2.1
category function location parts
7.3 5.9 4.4 2.1
7.3 3.6 2.7 2.4 2.1
function parts location size when used category
6.5 5.1 4.2 2.5 2.5 2.4
Sub/sub-diff super
M
owner
2.1
Differences function animacy
function 13.8 category 3. I cost 2.9 size parts 3.0 requires care 2.2 category size 3.0 location 2.7 material 2.6 animacy 2.5 naturalness 2.3 shape 2.2 cost 2.1 Note. Only properties listed by an average of 2 participants per item are included here. Super/super = pairs of superordinates; basie/hasic-same = pairs of basic-level concepts from the same superordinate; basic/basic--diff = pairs of basic-level concepts from different superordinates; sub/sub-same basic = pairs of subordinates from the same basic-level category; sub/sub--tiff basic = subordinates from different basic-level categories but the same superordinate; sub/sub--diff super = subordinates from different superordinates.
tures. Finally, a simple content analysis of the property listings in Experiment 3 suggests that a wider range of properties emerge consistently from comparisons of categories with a common structure than for categories that do not have a common structure. Experiment 4 Up to this point, our experiments have used instructional manipulations to bias participants toward a comparison of mental representations. In Experiments 2 and 3, we explicitly asked participants to compare mental representations. In Experiment 1, our instructions to generate a contrasting category may have created this bias as well. However, if comparability is a psychologically important factor for distinguishing superordinate and basic-level categories, then we should see evidence for its importance in everyday tasks in which participants are not directly instructed to make comparisons. In this experiment, we examined another task that is thought to involve comparison: the interpretation of novel combinations of concepts (see also Downing, 1977; Hampton, 1988, 1991; Medin & Shoben, 1988; Murphy, 1988; Wisniewski & Gentner, 1991; Wisniewski, 1996). Novel combinations are an important language construction. People create novel combinations to specify referents of discourse contexts and to extend the vocabulary of their language (Downing, 1977; Gerrig & Murphy, 1992). In many languages (such as English), their use is ubiquitous. In this experiment, participants interpreted novel noun phrases composed of either two superordinate categories, two basic-level categories from the same superordinate, or two basic-level categories from different superordinates.
13.0 3.0 2.9 2.7 2.4 2.3 2.2
parts function color cost weight
The aim of this experiment was to demonstrate that there is a qualitative difference in the way that noun phrases are interpreted depending on whether the nouns have overlapping, comparable structure. To make more specific predictions, we must first review some recent findings in conceptual combination. Wisniewski (1996) suggested that there are three basic strategies for combining concepts. In relation linking, people link the constituents of a combination by a relation, as in snake that EATS robins; for robin snake. In property mapping, they assert that one or more properties of the modifier concept apply to the head concept, as in snake with a RED underbelly, for robin snake. In an extreme form of property mapping, called hybridization, people map so many properties of the modifier concept to the head concept that the combination is a hybrid of its constituents (e.g., robin canary is a bird that is a cross between a robin and a canary). Wisniewski and his colleagues (Wisniewski, 1996; Wisniewski & Gentner, 1991; Wisniewski & Markman, 1993) have suggested that property mapping involves a comparison process in which conceptual structures are aligned. They have shown that highly comparable representations yield more property mapping. In one study, highly comparable noun-noun pairs were almost exclusively interpreted in this manner (Wisniewski, 1996). For example, people often interpreted goose duck as either a duck with a long neck or a bird that was a cross between a goose and a duck. In contrast, when the constituents of the pair were less comparable, people more often interpreted it by relation linking (e.g., apple duck was often interpreted as a duck that eats apples).
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Other findings suggest that alignable differences between concepts form the basis of many property-mapping interpretations. Wisniewski and Markman (1993) compared propertymapping and relation-linking interpretations of noun pairs to commonality and difference listings of the same pairs obtained from other participants. They found that propertymapping interpretations often corresponded to alignable differences from the commonality and difference listings. For example, in comparing a motorcycle with a car, people often said that a motorcycle has two wheels, whereas a car has four wheels. In like fashion, people often interpreted motorcycle car as a car with two wheels. No such relation was found between properties-listed and relation-linking interpretations. These results suggest that structural alignment is involved in property mapping, but not in relation linking. Because combinations involving categories with comparable representations give rise to more property-mapping interpretations than those with noncomparable representations, combinations involving basic-level concepts from the same superordinate should result in more property mapping than combinations involving superordinate categories. In contrast, because combinations involving categories with noncomparable representations give rise to more relationlinking interpretations than those with comparable representations, combinations involving superordinate categories and basic-level categories from different superordinates should result in more relation-linking interpretations than those involving basic-level categories from the same superordinate. These findings would provide evidence that cognitive processes operating on basic-level categories from the same superordinate yield access to the many commonalities and alignable differences of the pair, whereas cognitive processes operating on superordinates and on distant basiclevel categories do not make use of the commonalities and differences of the pair.
Method Participants. The participants were 48 Northwestern University undergraduates who took part in the experiment as part of a course requirement. Materials. The 20 superordinates and their three basic-level categories (shown in Table 8) were used to construct the concept combinations. Participants saw three types of combinations: Super/ super phrases were created by randomly pairing one superordinate with another (e.g., animal food, entertainment sports equipment, and beverage jewelry). Basic~basic-same phrases were created by randomly pairing two of the basic categories of a superordinate (e.g., the basic-level categories onion and pepper from the superordinate vegetable were randomly paired to produce the phrase onion pepper). Basic~basic-rift phrases were created by randomly pairing a basic-level category of a superordinate with that of another superordinate (e.g,, the basic-level category dog from the superordiuate animal was randomly paired with skates from footgear to produce dog skates). Six lists of 30 unique noun phrases were constructed. A list consisted of 10 super/super pairs, 10 basic/basic-same pairs, and 10 basie/basic--diff pairs. Eight participants saw each of the six lists. A list was constructed in the following manner. First, the 20 superordinates were paired to produce the 10 super/super pairs.
Table 8
Categories Used in Conceptual Combination Experiment (Experiment 4) Superordinate
Basic-level categories
jewelry sports equipment beverage musical instrument clothing animal exercise equipment furniture vehicle office equipment plant vegetable tool food weapon kitchen utensil entertainment footgear reading material
necklace, ring, watch ball, racquet, net milk, soda, alcohol guitar, piano, drum pants, shirt, underwear dog, fish, mouse weights, bicycle, pool chair, table, lamp bus, truck, car paper, pencil, pen tree, fern, flower beans, pepper, onion saw, screwdriver, hammer potato, cereal, bread gun, knife, bomb plate, spoon, cup movie, TV show, museum shoes, boots, skates novel, magazine, reference
Then, 2 basic-level categories were taken from each of 10 superordinates to produce the 10 basic/basic-same pairs. The third basic-level category from each of these superordinates was paired with a basic-level category from the remaining 10 superordinates to produce the 10 basic/basic--diff pairs. Pairing and selection of categories were random and subject to two constraints. First, across the lists, there were equal numbers of basic/basic-same and basic/basic--diff pairs corresponding to each superordinate. That is, for each superordinate, half (three) of the lists contained a basic/basic-same pair that had two of its basic-level categories, and half contained a basic/basic--diff pair that had one of its basic-level categories. Second, every basic-level category appeared as a noun in at least 1 basic/basic-same pair and 1 basic/basic--diff pair. Booklets of noun phrases were constructed by randomly ordering a list of phrases, typing them onto six pages with five phrases per page and several lines of blank space in which to write an interpretation. The pages were rotated so that each page appeared about equally often in the first through sixth positions of the booklet. Procedure. Participants read the following instructions: Thank you very much for participating in this study. This experiment investigates how people interpret novel noun phrases, such as earthquake school, tiger cheese, and snake fish. In contrast, familiar noun phrases include dog sled, river boat, shoe store, and winter coat. In this study, you will be presented with many phrases which are novel--you may have never seen or heard them before. Your task is to read each phrase and think of a likely meaning for it. Pretend that you have just heard the phrase in a conversation. What would be the meaning of the phrase that seems most natural to you? Write down the meaning of the phrase in the space provided. Please write clearly (we want to read them later) and avoid vague interpretations. For some of the phrases, it will be difficult to come up with a meaning. Just do the best that you can. Participants wrote meanings for the phrases at their own pace. The task took approximately 20 min to complete. Scoring. The interpretations were classified into one of three categories: relation linking, property mapping, and other. An
SIMILARITYAND TAXONOMY interpretation was classified as relation linking if it involved a relation between two objects, either those named by the constituents or typically derived in some way from a constituent. Examples of the former include paper that is used to clean a guitar for guitar paper, when it rains and you are camping you have to put your firewood in the tent for tent firewood, and boring documentary on different famous museums for museum movie. An example of relation linking that involved an object derived from a constituent was a rack to hold shoes in a closet for shoe chair. This interpretation does not involve a relation between shoe and chair, but rather involves a relation between shoe and something that appears to be derived from the function of chair (i.e., a rack). An interpretation was classified as property mopping if one or more properties of a constituent were asserted as the referent of the combination as in high-top shoe for boot shoe, a type of spicy bean for pepper bean, and very plain car for bread car. Finally, an interpretation was scored as other if it did not fit into one of the other two categories. For these interpretations, participants typicaily gave vague meanings (e.g., special Mexican sauce for burritos for bean onion) or interpreted nouns as adjectives (e.g., someone interpreted light TV movie as a funny, not serious TV show). The data were scored by two raters. A naive rater scored two thirds of the data. One of the authors scored the remaining data. As a check for accuracy and consistency, another naive rater scored a subset of the data scored by each of the first two raters. The first and third raters agreed 81% of the time with a Cohen's kappa of 0.67. The second and third raters agreed 85% of the time with a Cohen's kappa of 0.73.
Results and Discussion
Table 9 shows the proportion of relation-linking, propertymapping, and other interpretations given by participants. Because we are interested primarily in the proportion of property-mapping interpretations, a one-way ANOVA on the proportion of property-mapping interpretations given for each item revealed significant differences as a function of the type of pair, F(2, 177) = 7.75, M S E = 0.09, p < .005. Planned comparisons with Tukey's HSD revealed that there was a significantly higher proportion of property-mapping interpretations for basic-level terms from the same superordinate (M = 0.55) than for either basic-level categories from different superordinates (M = 0.36) or pairs of superordinates (M = 0.37).
Table 9 Proportion o f Interpretations Classified as Slot Filling, Property Mapping, and Other by Category Pair in Experiment 4 Definition class Pair type
Relation linking
Basic/basic-same Basie/basic-diff Super/super
.44 .50 .55
Property mapping Other .50 .38 .37
.06 .12 .08
Note. Basic/basic-same = pairs of basic-level concepts from the same superordinate; basic/basic--diff = pairs of basic-level concepts from different superordinates; super/super = pairs of superordinates.
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The prediction that basic-level categories from the same superordinate would yield property-mapping interpretations was based on the belief that property mapping involves carrying over an alignable difference from the modifier noun of the phrase to the head noun (Wisniewski & Markman, 1993). For example, 1 participant defined dog mouse as a mouse that barks. In this case, the characteristic sound of dogs (barking) was carried over to mice (which are generally assumed to squeak). In general, a single property was carried over in a property-mapping interpretation. For example, potato bread was defined as bread made in the shape o f a potato. Here the shape of potatoes is the only property brought over. In the case of highly similar items, many properties were sometimes carried over, leading to hybridization. For example, 6 of the 8 participants defining the novel combination pencil pen created a hybrid like a writing implement that contains both lead and ink. In contrast, for combinations made up of more distant pairs like flower plate, participants generally found it easier to posit a relation between the head noun and the modifier noun, such as a plate used under a flower pot to collect excess water and dead leaves. These data provide a glimpse of the power of the alignment of structured representations. Comparisons of contrasting items allowed easy access to the properties of the items, which were then used to define terms. Comparisons of more distantly related items did not yield access to commonalities and differences and hence focused participants on potential associations and relationships between the items. Thus, the degree of comparability of a pair of categories was important not only for situations in which the categories were obviously being compared, but also for other cognitive processes that may make use of comparisons. General Discussion Similarity plays a fundamental role in understanding the basic level of categorization. As discussed here, the differentiation view assumes that the basic level is marked by high within-category similarity and low between-category similarity. However, in light of current research on the process of similarity comparison, the proposal that basic-level categories have low between-category similarity is underspecified. One possibility is that low between-category similarity at the basic level means that pairs of basic-level categories from the same superordinate have few commonalities, and hence few psychologically important differences. A second possibility is that pairs of basic-level categories from the same superordinate have many alignable differences. Our findings provide evidence for this latter view of low betweencategory similarity. Overall, the results suggest that basic-level categories from the same superordinate have comparable representational structures, whereas pairs of superordinates and pairs of more distant basic-level categories do not. First, as would be expected in this view, participants were most easily able to find contrasts within a given superordinate category (and minimal contrasts for basic-level categories). Second, participants were able to list many commonalities and many
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alignable differences for pairs of basic-level categories from the same superordinate, as well as for pairs of subordinate categories from the same superordinate. These findings contrast with the pattern observed for pairs of superordinates and pairs of more specific categories from different superordinates. For these categories, participants listed fewer commonalities and alignable differences but more nonalignable differences. This pattern suggests that these pairs of categories are different because they are not comparable. Our findings also refine the differentiation view that both basic-level and superordinate categories exhibit (the same kind of) low between-category similarity. Because pairs of neighboring basic-level categories are comparable, they are both similar and different, where similar is defined as "having commonalities," and different is defined as "having alignable differences." On the other hand, superordinates are different where different is defined as "having few commonalities and alignable differences." Thus, contrary to the traditional formulation of differentiation, pairs of contrasting basic-level categories and pairs of superordinates are dissimilar in different ways.
Differentiation and the Basic-Level Advantage As discussed in the introduction, differentiation is one of many factors that converge at the basic level that may contribute to its advantage over other levels of categorization. The particular manifestation of low between-category similarity at the basic level is advantageous. Previous research has found that alignable differences are more focal in similarity comparisons than nonalignable differences (A. B. Markman & Gentner, 1996). Further, alignable differences are more likely to be used in other cognitive processes that involve comparisons, such as decision making (A. B. Markman & Medin, 1995), conceptual combination (Wisniewski, 1996; Wisniewski & Markman, 1993), and concept formation (Wisniewski & Markman, 1996). Thus, it seems appropriate that the level of categorization that has an advantage in a variety of cognitive tasks is marked by the presence of differences that are also privileged in a variety of tasks. Of course, just because comparisons of basic-level categories yield many commonalities and alignable differences does not mean that other factors that contribute to the basic-level advantage are unimportant. For example, we do not dispute that basic-level categories have high withincategory similarity. In fact, our results actually support this view: Pairs of subordinates from the same basic-level category had many commonalities, as would be expected if there is high within-category similarity at the basic level. By this criterion, however, one could argue that members of superordinate categories also have more within-category similarity than is generally acknowledged, as comparisons of basic-level categories from the same superordinate also had many commonalities. The high degree of commonality and alignable difference of pairs of basic-level categories from the same superordinate can explain the finding that objects are often named at the basic level. Basic-level names provide information about
a common structure shared by the item named as well as by other items from the same superordinate. At the same time, basic-level names make psychologically relevant differences available to these contrasting categories. In contrast, superordinate names do not provide information about the way that category contrasts with other categories. Further, subordinates share structure both with contrasting subordinates from the same basic-level category and with subordinates from other basic-level categories from the same superordinate, as all of these categories have a common representational structure. Thus, subordinates do not provide a category for which all categories from the same parent and only those categories share representational structure. This pattern may be helpful in communication. When establishing reference to an object, it is helpful to use similar labels for similar items. However, it is also important to be able to distinguish between objects with the same label to permit reference to.unique individuals (A. B. Markman, Yamauchi, & Makin, in press). This simultaneous attention to commonality and difference suggests the same attention to commonalities and alignable differences that was observed in comparisons of basic-level categories from the same superordinate. Other behavioral advantages of the basic level may be well explained by a combination of factors. A good case in point is object recognition. On the one hand, the pattern of commonalities and alignable differences arising from comparisons may facilitate object recognition. For example, if a small animal is mistakenly classified as a dog, the actual category is more likely to be a minimally contrasting category (e.g., a cat or a wolf) than a nonminimally contrasting category (e.g., a chair or a car). At the subordinate level, a mistaken classification may reflect a confusion with a minimally contrasting subordinate, but it may also reflect a confusion with a more distant subordinate. On the other hand, our findings alone would predict that people are less likely to mistakenly classify something at the superordinate level than at other levels (because superordinates have noncomparable structure and thus are less confusable). However, other factors such as the high shape similarity of different members of basic-level categories also facilitate recognition of objects at the basic level compared with the superordinate level (Rosch et al., 1976). Consistent with this proposal, part commonalities were listed by more than 4 participants per item only for subordinate categories from the same basic-level category (assuming that part similarities reflect within-category shape similarity at the basic level). A combination of factors is also likely to explain why children often learn basic-level categories first (Anglin, 1977; Brown, 1958; Horton & Markman, 1980; Mervis & Crisafi, 1982; Rosch et al., 1976). Because categories are learned in a social situation, the high frequency of basiclevel names and the shortness of those names facilitate the acquisition of basic-level categories. Further, the withincategory shape similarity that assists in object recognition also eases category acquisition. However, basic-level category acquisition also seems to involve acquisition of a representational structure common to contrasting categories.
SIMILARITYAND TAXONOMY For example, Mandler and Bauer (1988) found that children's early categories are overgeneralized relative to the adult basic-level categories, in that they include other members of the same superordinate. Whereas some of this difficulty may involve shape similarities, it is also suggests that children are learning both a representational structure common to members of superordinates and alignable differences based on that structure that separates neighboring categories. As these examples demonstrate, the basic-level advantage is the result of a convergence of many factors. Comparability and Cognitive Processing Experiment 4 demonstrated how differences in comparability may affect cognitive processing more generally. In this study, we focused on conceptual combination and found that relation linking (which involves finding a relationship between categories) was most prevalent for phrases involving superordinates and dissimilar basic-level categories. In contrast, property mapping (which involves transfer of one or more properties from one concept to another) was most prevalent for noun phrases involving neighboring basiclevel categories. This study suggests that when a pair of categories is comparable, people generate novel interpretations of combinations of these categories by using the commonalities and alignable differences that result from comparing them. Other findings also support the conclusion that degree of comparability affects the cognitive strategies brought to bear on a task. We use decision making as an illustration. Johnson (1988, 1989) has studied choices between sets of comparable items (e.g., toasters) and noncomparable items (e.g., a toaster and a smoke alarm). For decisions between comparable items, participants made use of specific properties (generally alignable differences) of the items. For example, when deciding between two toasters, the number of heat settings or the number of slots of the toasters may have been relevant. In contrast, for decisions between pairs of noncomparable items, participants either resorted to holistic evaluations of the products (e.g., "I need a toaster more than a smoke alarm"), or they created more abstract attributes of the products that were alignable (e.g., "This smoke alarm appears to be better constructed than this toaster"). Johnson (1989) also performed one study that can be interpreted as a manipulation of category level. Some participants were presented with choices between sets of items from different general categories (e.g., two toasters and two smoke alarms). In these studies, participants generally used a two-stage choice process. In these the first stage, they selected between the higher order categories (e.g., toasters and smoke alarms) by using holistic strategies that are relevant to noncomparable items. After selecting a general category (e.g., toasters), they used a feature-based strategy for deciding between the comparable items. One way to think about this process is that participants used very abstract properties when trying to choose between products from different superordinates, because comparisons of these items did not provide access to specific properties. In contrast, choices between options from the same category
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involved many more specific properties, because more commonalities and differences were available from the comparison of these items. This pattern is just the one that would be expected in a structural-alignment view. Conclusions The differentiation view of the basic-level advantage has traditionally assumed that basic-level categories have both high within-category similarity (which they share with subordinates) and low between-category similarity (which they share with superordinates). First, it does not acknowledge that a pair of categories can be dissimilar either because it has few commonalities or because it has many psychologically relevant differences. Second, it assumes that the low between-category similarity of superordinates and basiclevel categories is of the same type. The present data resolve both problems. Contrasting basic-level categories differ by virtue of having a common structure that gives rise to many alignable differences. Further, superordinates differ from each other by virtue of lacking a common structure, and thus differences between superordinates are not alignable. As a result, there is a qualitative difference in the output of comparisons of contrasting basic-level categories and comparisons of superordinates. Finally, we showed that the ready access of alignable differences for contrasting basiclevel categories affected one cognitive task (i.e., conceptual combination) that does not obviously require comparison. Access to alignable differences may also be an important component in many other tasks that have demonstrated a basic-level advantage, including object recognition, naming, and ease of acquisition. References Anglin, J. M. (1977). Word, object and conceptual development. New York: Norton. Barsalou, L. W. (1992). Frames, concepts, and conceptual fields. In A. Lehrer & E. E Kittay (Eds.), Frames, fields and contrasts: New essays in semantic and lexical organization (pp. 21-74). HiUsdale, NJ: Erlbanm. Battig, W. E, & Montague, W. E. (1969). Category norms for verbal items in 56 categories: A replication and extension of the Connecticut category norms. Journal of Experimental Psychology, 80 (Monograph Supplement 3, Part 2). Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychological Review, 94, 115147. Brown, R. (1958). How shall a thing be called? Psychological Review, 65, 14-21. Cantor, N., & Mischel, W. (1979). Prototypes in person perception. In L. Berkowitz (E,d.),Advances in experimental social psychology (pp. 3-52). New York: Academic Press. Downing, P. (1977). On the creation and use of English compound nouns. Language, 53, 810-842. Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7, 155-170. Gentner, D. (1989). The mechanisms of analogical learning. In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning (pp. 199-241). Cambridge, England- Cambridge University Press.
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