Culture, category salience, and inductive reasoning

COGNITION Cognition 65 (1997) 15–32

Culture, category salience, and inductive reasoning Incheol Choi*, Richard E. Nisbett, Edward E. Smith University of Michigan, Department or Psychology, 525 East University, Ann Arbor, MI 48109, USA Received 6 May 1996; accepted 26 September 1997

Abstract The role of category salience in category-based induction was demonstrated in two ways: (i) temporarily increasing category salience facilitated category-based induction, and (ii) this effect was moderated by cultural differences that we predicted would be related to chronic category salience. Subjects for whom categories were presumed to be more accessible (Americans) were not as much influenced by manipulations to increase category salience as subjects who were presumed to have lower chronic accessibility of categories (Koreans). However, as anticipated, this pattern was reversed for inferences about behavioral properties of social categories. Due to the ‘interdependent’ nature of their culture, Koreans presumably have relatively higher chronic accessibility for social categories than do relatively ‘independent’ Americans, and hence were not influenced as much by increasing category salience.  1997 Elsevier Science B.V. Keywords: Culture; Category salience; Inductive reasoning

1. Introduction Categories promote inductive inferences about the unknown and invisible properties of an object (Smith and Medin, 1981; Gelman and Markman, 1983; Murphy and Medin, 1985). We often infer with confidence that two or more naturally-occurring objects have the same ‘hidden’ properties if they belong to the same category. For example, knowing that a bat is a mammal, we believe that it feeds its offspring, although we have not witnessed the feeding scene. The strength of such inductive inferences, however, is dependent on the property being inferred. For example, we are not likely to infer that bats and humans have the same aesthetic preferences simply because they belong to the category of mammals. At the other extreme, if we * Corresponding author. Fax: +1 313 7643520; e-mail: [email protected] 0010-0277/97/$17.00  1997 Elsevier Science B.V. All rights reserved PII S00 10-0277(97)000 34-6

16

I. Choi et al. / Cognition 65 (1997) 15–32

have little or no prior knowledge about the property and believe that the property is of a sort likely to be universal to all members of a category, we may be willing to rely on category membership in making inferences about the property. For example, given the information that dogs have an unfamiliar property (e.g., a bifold spleen), we are more likely to infer that bats have the same property than eagles simply because bats and dogs are both mammals. Such category-based induction is not restricted to natural categories. For social categories, people use category-based induction in the form of stereotypes. A person is presumed to have certain attributes if the person belongs to a group believed to be composed of members who generally have the attributes. For example, a person is presumed to have relatively little concern about money if he or she is a member of the clergy. There have been few direct attempts to manipulate the use of categories and measure their effect on inference. One way of examining the use of categories would be to make a category temporarily more available in one condition than another and compare inference outcomes in both conditions. In this study, we attempt a direct test of the role of categories in inductive inference by examining whether: (i) increased category salience increases the use of categories in induction, and (ii) groups differing in chronic accessibility of categories are differentially influenced by temporary variations in category salience. Since aspects of the similarity-coverage model of category-based induction proposed by Osherson et al. (1990) provides a framework for such tests, we will describe their model in some detail. 1.1. The similarity-coverage model of category-based induction Osherson and his colleagues found 13 empirical phenomena regarding categorybased induction by college students and proposed a model, the similarity-coverage model, to account for those phenomena. The nine phenomena that we deal with in this study are presented in Table 1. Osherson et al. (1990) use the terminology of inductive ‘arguments’ rather than inductive ‘inferences’ since inductive inference can be formalized as an inductive argument consisting of premise(s) and a conclusion. There are two types of inductive arguments, general and specific. General inductive arguments are ones in which the category in the conclusion properly includes the categories in the premises. For example, the conclusion category MAMMAL in argument (a) below includes the premise categories HIPPO and HAMSTER. (a)

Hippos have ulnar arteries. Hamsters have ulnar arteries. All mammals have ulnar arteries.

Specific inductive arguments are ones in which any category that properly includes a premise or conclusion category also properly includes all other premise or conclusion categories (roughly, the conclusion and premise categories are all the

I. Choi et al. / Cognition 65 (1997) 15–32

17

Table 1 Summary of nine inductive phenomena in Osherson et al. (1990) Phenomenon

Description and example

Specific arguments Similarity

Diversity Monotonicity (number) Non-monotonicity (heterogeneity)

General arguments Typicality Diversity

Monotonicity (number) Non-monotonicity (heterogeneity)

Conclusion-specificity

The more similar the premise(s) to the conclusion, the stronger the argument: ROBIN/SPARROW>PENGUIN/ SPARROW The more diverse the premises, the stronger the argument: LION, GIRAFFE/RABBIT>LION, TIGER/RABBIT The more premises, the stronger the argument: FOX, PIG, WOLF/GORILLA>PIG, WOLF/GORILLA An argument gets weaker if a premise from a different category is added: FLY/BEE>FLY, ORANGUTAN/BEE

The more typical the premise(s), the stronger the argument: ROBIN/BIRD>PENGUIN/BIRD The more diverse the premises, the stronger the argument: HIPPO, HAMSTER/MAMMAL>HIPPO, RHINO/ MAMMAL The more premises, the stronger the argument: HAWK, SPARROW, EAGLE/BIRD>SPARROW, EAGLE/BIRD An argument gets weaker if a premise from a different category is added: CROW, PEACOCK/BIRD>CROW, PEACOCK, RABBIT/BIRD The more specific the conclusion, the stronger the argument: BLUEJAY, FALCON/BIRD>BLUEJAY, FALCON/ ANIMAL

same level). For example, argument (b) below is a specific argument because the conclusion category DOG and the premise categories HIPPO and HAMSTER are all included in MAMMAL. (b)

Hippos have ulnar arteries. Hamsters have ulnar arteries. Dogs have ulnar arteries.

An argument is strong to the extent that belief in the premises causes people to believe the conclusion. Osherson et al. (1990) used blank properties in their study in order to eliminate or minimize the role of properties in induction and instead to maximize the role of categories. Blank properties refer to properties of which lay people do not have substantial prior knowledge (for example, having ulnar arteries). If people have prior knowledge about properties, then the strength of an inductive argument is determined both by category and property (Smith et al., 1993). Osherson et al. (1990) proposed that the strength of categorical arguments depends on (i) the degree of similarity between premise categories and conclusion category, the similarity component, and (ii) the degree to which premise categories ‘cover’ the inclusive category, where the latter is the lowest-level category that includes both

18

I. Choi et al. / Cognition 65 (1997) 15–32

premise and conclusion categories as proper member, the coverage component. The following example will demonstrate the role of the two components in categorybased induction. (a)

Lions have BCC in their blood. Giraffes have BCC in their blood. Rabbits have BCC in their blood.

(b)

Lions have BCC in their blood. Tigers have BCC in their blood. Rabbits have BCC in their blood.

In order to choose the stronger argument of the above two, a typical American presumably would compute the similarity between the premise categories and the conclusion category of each argument, the similarity component. Her reasoning continues in line with the coverage component as if she were thinking: Lions and giraffes are more different from each other than lions and tigers and therefore cover the mammal category better. So it is more likely that all mammals have BCC in argument (a) than in argument (b). Rabbits are mammals. Therefore, it is more likely that rabbits have BCC in their blood in argument (a) than in argument (b). After calculating both similarity and coverage, she would combine these two components additively and come to the conclusion that argument (a) is stronger since premise-conclusion similarity is thought to be the same for both arguments but coverage is greater for argument (a) (see Osherson et al. (1990) for more details about these two components and the way of combining them). In what follows, we use aspects of the similarity-coverage model (SCM) to analyze cultural differences in category-based induction. In doing this, we do not presuppose the correctness of the model in all its details. Rather, our analysis hinges on one critical assumption of the model: when drawing a category-based inference, one makes a computation involving the premise categories and a more general or inclusive category, and if that inclusive category is not explicitly provided as the conclusion category (or in specific arguments), it must be generated. Our cultural analyses hinge on this generation process. To the extent our analyses are successful, they add support to a category-based model like the SCM in comparison to competing models of the same inductive domain, like those advanced by Sloman (1993) and McDonald et al. (1996). 1.2. Differential category salience of general and specific arguments Deciding between the strength of two general arguments should be easier than choosing between two specific arguments. This is because, according to the similarity-coverage model, judging the strength of a specific argument requires subjects to generate the inclusive category in order to calculate the degree of coverage. Generating the inclusive category is a prerequisite for showing the phenomena in specific arguments predicted by the similarity-coverage model. However, this is not the case for general arguments. Since the conclusion category itself is the inclusive category in general arguments, subjects do not have to generate it. The inclusive

I. Choi et al. / Cognition 65 (1997) 15–32

19

category is already salient. Therefore, we expect that a given phenomenon (for example, diversity) is less likely to occur for specific arguments than general arguments. However, there exists an exception to this claim. In the case of non-monotonicity (that is, heterogeneity) (Table 1) in specific arguments, we propose that the inclusive category is salient although it is not present in the conclusion. For example, consider the following pair of arguments. (a)

Flies have X. Bees have X.

(b)

Flies have X. Orangutans have X. Bees have X.

When given these two arguments, subjects would likely notice that flies and orangutans belong to quite different categories, that is INSECT and MAMMAL. In this case, the salience of a higher-level category is great because of the obvious contrast between categories in the premises. Hence, salience of a higher-level category is achieved without mentioning that category in the conclusion. This argument is further supported by a contrast between the monotonicity (that is, number) and the non-monotonicity phenomenon (Table 1). An argument with a larger number of premises is stronger when the premise categories all belong to the same higher-level category (monotonicity or number). However, an argument is weaker when the premise categories belong to different higher-level categories (non-monotonicity or heterogeneity). If people do not recognize that these premise categories belong to different higher-level categories, they should show the monotonicity phenomenon rather than the non-monotonicity phenomenon. For example, people should judge argument (b) stronger than argument (a) in the above example if they do not realize that FLY and ORANGUTAN are members of different higher-level categories. However, they show the opposite. This supports our contention that in the case of non-monotonicity people are aware that the premises belong to different higherlevel categories. Therefore, whenever the non-monotonicity phenomenon occurs, we may assume that the lowest-level category that subsumes the premise categories is psychologically salient. Table 2 presents the classification of nine phenomena in terms of category salience (Table 2). This classification will provide an opportunity to investigate the role of category salience in induction. We regard similarity in specific arguments as a control case because it presumably makes no use of categories. Simple pairwise similarity judgments are sufficient to explain the similarity phenomenon in specific arguments. 1.3. Differential level of chronic accessibility of categories for Americans and Koreans We expected that greater category salience would enhance the above phenomena. That is, the more salient a higher-level category, the more likely it is used in the inductive process, and consequently the stronger should be the phenomena that rest on such category use. However, if a category is chronically salient to someone, her

20

I. Choi et al. / Cognition 65 (1997) 15–32

Table 2 Classification of the phenomena Category salient All general arguments Typicality Diversity Monotonicity (number) Non-monotonicity (heterogeneity) Conclusion-specificity Specific argument Non-monotonicity (heterogeneity) Category non-salient Specific arguments Diversity Monotonicity (number) Control condition Specific argument Similarity

inductions will not be much influenced by manipulations of category salience. She may not have much difficulty in generating the lowest-level categories necessary for the occurrence of diversity and monotonicity/non-monotonicity phenomena with specific arguments. There are two other studies suggesting that there are group differences in chronic accessibility of categories although the authors did not interpret their findings in those terms. Lopez et al. (1992) find that developmentally different groups showed different patterns of category-based induction. Unlike college students, second-grade children failed to show the diversity and the monotonicity phenomena for specific arguments. We suggest that this might be because categories become more elaborated and accessible as development proceeds. This differs from the computational-load interpretation offered by Lopez et al. but of course both computational capacity and category salience can plausibly be assumed to increase with development. Atran (1993) compared American subjects with Maya subjects in category-based induction and found that Maya subjects also failed to show the diversity phenomenon. Maya subjects might have a lower level of accessibility of categories than do Western college students and be less accustomed to using categories in inductive inference. Atran (1993) and Medin et al. (1997) also found evidence for another factor that might result in lesser reliance on categories, namely substantial knowledge that serves to produce causal interpretations of information contained in the premises. This does not conflict with our view. Greater knowledge about specific animals and their relation to the ecology might well reduce reliance on categories for purposes of inductive reasoning. We think that East Asians may have lower chronic accessibility of categories than Westerners and consequently East Asians’ performance in the category-based induction task should be different from that of Westerners. In the section following we present some evidence for this claim.

I. Choi et al. / Cognition 65 (1997) 15–32

21

Some ethnographers, philosophers, and historians of science have proposed that there are differences in reasoning style between Westerners and East Asians of a very broad nature that include a different emphasis on the role of categories in thought (e.g., Needham, 1962; Nagashima, 1973; Liu, 1974; Hsu, 1981; Munro, 1985; Nakamura, 1985; Lloyd, 1990). These proposals include claims both about ontology and epistemology. Western thought is held to be analytic. The focus of attention is on objects (both physical and social objects) and their attributes, with the attributes being used to place the objects into categories. The categories are the basis for rules that allow for predictions and explanations about the behavior of the objects. Formal logic plays a role in at least the thought of philosophers and scientists, if not of laypeople. East Asian (Chinese, Japanese, and Korean; and some scholars would add Southeast Asian and even South Asian) thought is held to be holistic, including the field in the focus of attention and predicting and explaining the behavior of objects with respect to the interaction of field and object rather than with respect to universal laws pertaining to object categories. Formal logic plays little or no role in Eastern philosophy or history of science (Liu, 1974). There are several interesting facts that fit with these claims. The Chinese discovered the principle of action at a distance 1500 years before Galileo, presumably because of their attention to the field, which played little role either in Aristotelian or Medieval science (Lloyd, 1990). And ancient Chinese notions of matter were always wave-based whereas ancient notions of matter in the West were mostly particlebased (Needham, 1962). More recent psychological evidence supports these cultural claims as well. The so-called fundamental attribution error, that is, the tendency to attribute people’s behavior to their fixed attributes rather than to the situation they find themselves in, is less common among Asians than Americans. Asians tend to attribute behavior much more to the situation and context (Miller, 1984; Morris et al., 1993; Morris and Peng, 1994; Lee et al., 1996; Choi and Nisbett, 1997; Norenzayan and Nisbett, unpublished data). These attribution differences hold even for attributions about the actions of animals and for the behavior of inanimate objects. Americans see the behavior of an individual fish moving in various ways in relation to a group of fish as being due to internal properties of the individual fish; Chinese are more likely to see the behavior of the individual fish as a reaction to the behavior of the group (Morris et al., 1993; Morris and Peng, 1994). And while Americans tend to see hydrodynamic and aerodynamic events as being the consequence of internal properties of objects, Chinese are more likely to see them as due to the field or an interaction between field and object properties (Peng and Nisbett, 1997b). Consistent with this tendency to focus on the environment, Peng and Nisbett (1997a) found that Chinese subjects were more accurate in detecting the degree of covariation between arbitrary stimulus events presented on a computer screen than were their American subjects. Evidence also exists with respect to category usage. Chiu (1972) reported that Chinese children were more likely to group pictures together in a relational-contextual manner (‘mothers take care of babies and go together’), whereas American children grouped according to common category memberships and shared features (‘adults go together’ or ‘these all have a motor’). Norenzayan et al. (unpublished

22

I. Choi et al. / Cognition 65 (1997) 15–32

data) found that East Asians have more difficulty in learning a category when analytic or rule-based processing is required, but that the cultures are equivalent when holistic or exemplar-based processing is required. If use of categories is more common for Westerners than for East Asians, our American subjects should be less influenced by the salience of categories than our Asian subjects. Categories should be more accessible to Americans than to Asians, hence manipulations of salience should make relatively little difference to them. There is an exception to the above prediction. A great deal of ethnographic evidence, and an increasing amount of psychological evidence, indicates that East Asian societies are more ‘collectivist’ or ‘interdependent’, that is, concerned with human roles and relationships, than are Western societies, which are more ‘individualist’ or ‘independent’ (e.g., Hofstede, 1980; Hsu, 1981; Bond, 1986; Markus and Kitayama, 1991; Triandis, 1995). For example, when asked to describe a person, self or other, Japanese (Cousins, 1989), Chinese (Triandis et al., 1990), Indians (Shweder and Bourne, 1984), and Koreans (Rhee et al., 1995) made more reference to their social roles, group memberships, and status than their American counterparts did. East Asians prefer to categorize people with respect to social-relational terms rather than individual-personal terms. Thus we would expect that the accessibility of social categories such as age, status, and occupations may actually be greater for Asians than for Westerners, and consequently the cultural differences in category-based induction should be less than for non-social categories. Unlike most previous studies of category-based induction in which only animal categories (e.g., mammals, birds) and blank biological properties (e.g., having BCC in their blood, having ulnar arteries) were used, the current study also included social categories (i.e., occupations) and meaningful behavioral properties (i.e., preferences). This allows us both to examine the similarity-coverage model for a wider range of categories and properties and to test the interaction between culture and category type we propose. 1.4. Hypotheses First, we hypothesized that the basic phenomena associated with the similaritycoverage model would be confirmed by more varied subjects, namely Asian as well as American subjects, by more varied categories, namely human categories as well as animal categories, and by more varied properties, namely behavioral properties as well as biological properties (see Heit and Rubinstein (1994) for the use of properties other than biological ones). Second, we hypothesized that subjects would show the above phenomena more when categories are salient than when categories are not salient. Third, we hypothesized that American and Asian subjects would show differential sensitivity to category salience. Because American subjects are presumed to have a high level of chronic accessibility of categories, any attempt to increase category salience should have little effect on their inductive reasoning. Asian subjects, for whom categories are less salient, should be more affected by attempts to increase category salience than American subjects.

I. Choi et al. / Cognition 65 (1997) 15–32

23

Fourth, since Asian subjects are more sensitive to social categories, and inferences about behavioral properties are more common and more important for social categories, we expected that, for the case of behavioral properties concerning social categories, Asian subjects would be little influenced by increased category salience, perhaps even less than American subjects.

2. Method 2.1. Subjects Fifty-three undergraduate students in an introductory psychology class at the University of Michigan participated in the experiment for extra credit. Fifty-four undergraduate students in an introductory psychology class at Pusan National University in Korea participated in the experiment. 2.2. Procedure About half of the subjects in each culture were randomly assigned to the ‘biological property’ condition and another half of the subjects were randomly assigned to the ‘behavioral property’ condition. Subjects were given a booklet containing a series of pairs of inductive arguments about biological or behavioral properties of animal and social categories. The animal categories and biological properties were the same sort as those used by Osherson et al. (1990). Social categories were occupations. Behavioral properties were preferences of various sorts, for example, ‘prefer cold food to hot food’ and ‘prefer jazz to classical music’. The first page of the booklet contained instructions, and the following pages contained the pairs of arguments. The instructions were as follows: We are interested in how people evaluate arguments. On each page of your booklet there will be pairs of two arguments labeled ‘A’ and ‘B’. Each argument will contain one, two, or three statements separated from a conclusion by a line. Assume that the statements above the line are true even if they seem unlikely to you. Then please choose the argument that you think supports the conclusion better. These are subjective judgments; there are no right or wrong answers. We examined four phenomena concerning specific arguments (similarity, diversity, monotonicity (number), and non-monotonicity (heterogeneity)) and five phenomena concerning general arguments (typicality, diversity, monotonicity (number), non-monotonicity (heterogeneity), and conclusion-specificity) and two kinds of categories (animal and social categories). There were thus 18 combinations of phenomenon with category-type. Two pairs of inductive arguments per each combination were presented to the subjects. Therefore, subjects in both biological-property condition and in the behavioral-property condition were given 36 pairs of inductive arguments in total. Some examples of specific arguments are

24

I. Choi et al. / Cognition 65 (1997) 15–32

Table 3 Some examples of categories and properties Examples of category Animal category

Social category

Similarity Diversity

Horse/zebra versus pig/zebra Hawk, chicken/sparrow versus hawk, eagle/sparrow

Monotonicity

Mouse, dog, horse/cat versus mouse, dog/cat Elephant, cow/giraffe versus sparrow, elephant, cow/giraffe

Dentist/physician versus CPA/physician Psychoanalyst, engineer/criminologist versus psychoanalyst, physician/ criminologist Physician, engineer, CPA/professor versus physician, CPA/professor Professor, pharmacologist/dentist versus cab driver, professor, pharmacologist/dentist

Non-monotonicity

Examples of property

Biological

Animal category

Social category

Have ulnar arteries

Rely more on left visual field than right visual field Have larger frontal lobes than average More brain activity at night than in the morning Prefer mystery story to romance story Prefer Picasso to Matisse Prefer baroque arts to rococo arts

Have sesamoid bones Have BCC Behavioral

Prefer oat to wheat Prefer butter to cheese Prefer peanut to almond

illustrated in Table 3. General arguments were produced by replacing the conclusion category in specific arguments by the lowest-level category that includes the premise categories. We presented subjects with specific arguments first and then general arguments in both conditions to prevent them from being primed to use categories by mention of the categories’ names. After completing the inductive reasoning task, subjects were asked to judge the typicality of the items used to study the typicality phenomenon and to judge the similarity between the pairs of items used to study the similarity and diversity phenomena. We translated the material into Korean and backtranslated the Korean version into English. There was no substantial difficulty in translation. American subjects were tested in groups of 4–8 while Korean subjects were tested in a class.

3. Results 3.1. Similarity and typicality ratings It is important to establish that any observed cultural difference in the induction task reflects true difference in category usage, not differences in similarity and

25

I. Choi et al. / Cognition 65 (1997) 15–32

typicality. Consider one specific example. An argument consisting of Lion, Tiger/ Cow should be judged weaker than an argument of Lion, Cat/Cow because of the greater coverage of the premise categories in the second argument. In other words, Lion and Cat are more diverse than Lion and Tiger. It should be the case that this similarity difference between the two pairs is comparable in the two cultures. In fact, we found remarkable convergence between the two cultures in this matter: there was only one case out of 48 (40 for similarity ratings and eight for typicality ratings) in which subjects from the two cultures disagreed. American subjects rated EngineerSystem Analyst as significantly more similar than Psychoanalyst-System Analyst, while Korean subjects did not show any difference between the two pairs. This might have been due to relative unfamiliarity with the psychoanalyst occupation for Korean subjects. This result is consistent with the finding by Atran (1995) that the basic distance among natural categories was almost identical for both Americans and Maya people. Therefore, observed cultural differences in the present study cannot be attributed to differences in judged similarity and typicality. 3.2. The generality of the Osherson et al. (1990) phenomena To test the first hypothesis that the Osherson et al. (1990) phenomena can be obtained with a different population (Korean subjects), different categories (human professional categories) and different properties (behavioral preferences), we combined the data across cultures, properties, and categories. Since each subject Table 4 The generality of the similarity-coverage model USA + Korea USA (n = 107) (n = 53)

Korea (n = 54)

Control condition Similarity

3.47***

3.57***

3.37***

Category non-salient Diversity – specific Monotonicity (number) – specific Mean

2.26* 2.83*** 2.54***

2.17 3.15*** 2.66***

2.35* 2.52*** 2.43***

Category salient Typicality Diversity – general Monotonicity (number) – general Non-monotonicity (heterogeneity) – general and specific Conclusion – specificity Mean

3.29*** 2.65*** 3.74*** 2.87*** 3.50*** 3.05***

3.00*** 2.42* 3.83*** 2.57*** 3.23*** 2.84***

3.19*** 2.89*** 3.65*** 3.17*** 3.76*** 3.26***

Each number represents the average number of items that subjects chose that accord with the prediction of the similarity-coverage model. Since there are four items per each phenomenon, 4 represents complete responsiveness to categories and 2 represents ignoring categories completely. *P , 0.05, **P , 0.01, ***P , 0.001.

26

I. Choi et al. / Cognition 65 (1997) 15–32

received four items per each phenomenon (because we combined animal categories with social categories), the expected score is 2 if they were ignoring category membership in making their inference and 4 if they attended to it for every problem they were presented. We conducted t-tests against this expected score. Table 4 lists the results of t-tests (Table 4). As seen in the left-most column of Table 4, all phenomena obtained by Osherson et al. (1990) were found in the present study. Also like Osherson et al. (1990), we found that diversity in specific arguments was the weakest phenomenon: American subjects in fact failed to show it. This is consistent with the finding that recognition of the importance of diversity occurs late in development (Lopez et al., 1992), and with the finding that Maya subjects did not show the diversity phenomenon even for general arguments (Atran, 1993). 3.3. The effect of category salience To test the second hypothesis, we compared subjects’ responses when categories were not salient with those when categories were salient. As predicted, subjects showed the relevant phenomena more when categories were salient than when they were not salient (mean = 2.54 for non-salient, mean = 3.05 for salient), F(1,105) = 24.60, P , 0.0011. The effect of category salience was significant separately just for the two directly parallel phenomena of diversity and monotonicity. Subjects showed greater diversity effects, F(1,105) = 6.25, P , 0.05, and monotonicity effects, F(1,105) = 72.00, P , 0.001, when categories were salient (mean = 2.65 for diversity, mean = 3.74 for monotonicity) than when they were not salient (mean = 2.26 for diversity, mean = 2.83 for monotonicity). 3.4. The effect of chronic accessibility of categories We anticipated that Korean subjects would be more affected by category salience than American subjects. This was the case. The interaction between culture and category salience was significant, F(1,105) = 10.04, P , 0.0052 as may be seen in Table 4. The difference between the category non-salient condition and the category salient condition was larger for Korean subjects (2.43 vs. 3.26) than for American subjects (2.66 vs. 2.84). Fig. 1 shows detailed patterns of the difference between category-salient and category-non-salient arguments3. For biological properties for both animal and social categories and for behavioral properties for animal categories, Korean subjects were more influenced by category salience than American subjects. The interaction was significant for the combination of biological property with social category, F(1,50) = 15.29, P , 0.001, and for the combination of beha1 The effect of category salience was still significant when we excluded the heterogeneity in specific arguments from the category salient condition, F(1,105) = 44.12, P , 0.001. 2 The interaction was still significant when we excluded the heterogeneity in specific arguments from the category salient condition, F(1,105) = 8.57, P , 0.005. 3 The appearance of Fig. 1 did not change, nor did the significance levels of the interactions, when we excluded the heterogeneity in specific arguments from the category salient condition.

I. Choi et al. / Cognition 65 (1997) 15–32

27

Fig. 1. The differential effect of category salience on preference for arguments for subjects from two cultures.

vioral property with animal category, F(1,50) = 22.45, P , 0. 001. As anticipated, there was a striking exception to the overall trend: in the case of social categories combined with behavioral properties, American subjects were actually more influenced by category salience than Korean subjects, F(1,50) = 4.47, P , 0. 05. Figs. 2 and 3 show how category salience affected the diversity and the monotonicity phenomena for the two cultures. Fig. 2 shows that in the case of diversity Korean subjects were more affected by category salience for biological properties of social categories and behavioral properties of animal categories. However, as expected, American subjects were more affected for behavioral properties of social categories. Fig. 3 shows that in the case of monotonicity Korean subjects were more affected by category salience for both properties of animal categories. However, as expected, American subjects were more affected for behavioral properties of social categories. In sum, the predicted interactions were in the expected direction for seven of the eight comparisons, significant for six, and non-significantly reversed for one.

4. Discussion We have shown that the phenomena predicted by the similarity-coverage model are rather general, extending to social categories and behavioral properties. Moreover, the results show that the role played by categories in induction is affected by both temporary and chronic salience of categories. Temporarily increasing category salience facilitated category usage in induction. However, this effect was qualified

28

I. Choi et al. / Cognition 65 (1997) 15–32

Fig. 2. The effect of category salience on preference for arguments with greater diversity of premises.

by chronic salience associated with culture. American subjects were less influenced by category salience than Korean subjects when induction tasks were about animal categories, or about the biological properties of social categories. Since Americans presumably have higher chronic accessibility of such categories, their inductions

Fig. 3. The effect of category salience on preference for arguments with larger number of premises.

I. Choi et al. / Cognition 65 (1997) 15–32

29

were little influenced by temporary variations in salience. However, this pattern was reversed when the induction concerned behavioral properties of social categories. Since presumably Koreans are more concerned with social events, Koreans were less influenced by increasing category salience than were Americans. This cultural difference might be explained away by arguing that the two cultures have different hierarchies of categories. Korean subjects might have generated different superordinate categories because they have different taxonomies. Though this is possible and should be studied, the work of Atran (1995) and Lopez et al. (1997) tends to speak against this possibility. Lopez et al. (1997) found that Maya Indians have taxonomies that are highly similar to those of American college students. Atran (1995) and Lopez et al. (1997) have argued that, in fact, basic taxonomic forms are universal. Thus, cultural differences in this study are not likely to be due to the two cultures having different taxonomies. Instead, we believe that the present results are due to people in European cultures in fact making more use of categories spontaneously than do people in Asian cultures. This study does not imply that Asians do not use categories at all. Rather it suggests that they use categories less spontaneously. Social categories are an exception to this generalization, though: the importance of events of a given kind can force the creation and use of categories even though categorization is in general not a common habit among Asian cultures. And for East Asians and members of other relatively interdependent societies, social events are sufficiently important to prompt greater likelihood of generation and salience of social categories than for relatively individualistic societies. We believe that the exception to our generalizations about culture and category usage may be understood in terms of the theory that has been offered by some scholars to account for why differences should exist for category usage at all. As the psychologist L.-H. Chiu (1972) put it: ‘Chinese are situation-centered. They are obliged to be sensitive to their environment. Americans are individual-centered. They expect their environment to be sensitive to them’ (p. 236). ‘[The American] orientation may inhibit the development of a tendency to perceive objects in the environmental context in terms of relationships or interdependence. On the other hand, the Chinese child learns very early to view the world as based on a network of relationships; he is socio-oriented, or situation-centered’ (p. 241). This view is endorsed by such other scholars as Hsu (1981), Nakamura (1985), Triandis (1995) and Witkin and Berry (1975). Note that in this view the cognitive differences are derived from the social differences. The outward focus means attention to the field and to relationships, hence attribution to context; the focus on self and object means an attempt to categorize the object and derive rules about its behavior based on its category memberships. The origin of cultural differences of the sort the present study reports is far from clear. Nonetheless, it seems likely that the differences between East and West in social systems are related to differences in cognitive processes. Further research is needed to deepen our understanding of how culture shapes cognition. Apart from its implications for category-based induction in different cultures, the present study raises an important question about the SCM itself. The model requires

30

I. Choi et al. / Cognition 65 (1997) 15–32

the same computation of category-coverage in arguments manifesting the diversity phenomenon and in arguments manifesting the typicality phenomenon; i.e., for the diversity phenomenon to occur, people should calculate the average similarity of the premise categories to all instances in the conclusion category, and this same centraltendency calculation is necessary for typicality to occur. However, as Table 4 indicates, subjects from both cultures were more sensitive to typicality than diversity even for the general arguments. This discrepancy suggests that different computations may underlie the typicality and the diversity phenomena. It may be that subjects always make two computations about coverage, one the central-tendency computation assumed by the SCM, and the other a determination of the similarity between the premise categories and the prototype/ideal of the conclusion or inclusive category4. For arguments manifesting the typicality phenomenon, the prototype/ideal computation will suffice to favor the argument with more typical premise categories; hence, the typicality phenomenon should occur even if subjects have difficulty computing central tendency. In contrast, for arguments manifesting other phenomena, like diversity, the typicality computation is of no help in choosing the stronger of two arguments because the arguments were constructed so as not to vary in typicality. For arguments manifesting diversity, then, the subjects must rely exclusively on the central-tendency computation, and difficulties in making the computation would lead to less sensitivity to diversity. The upshot is that the diversity phenomenon should be weaker than the typicality phenomenon. The finding by Lopez et al. (1992) that the typicality phenomenon developmentally precedes the diversity phenomenon is consistent with this reasoning. Acknowledgements This study was supported by a Summer Research Fellowship from the Department of Psychology at the University of Michigan to Incheol Choi, National Science Foundation Grant SBR-9319798 to Edward Smith, and a grant for the study of Culture and Cognition from the Office of Vice-President for Research of the University of Michigan to Richard Nisbett. We are grateful to Dan Sperber, Kaiping Peng, and Ara Norenzayan for their thoughtful comments on this study, We also thank Carolyn Nguyen and Shin-Ho Ahn for their assistance in data collection. References Atran, S., 1993. Core domains versus scientific theories: evidence from systematics and Itza-Maya folkbiology. In: Hirschfeld, L., Gelman, S. (Eds.), Domain Specificity in Cognition and Culture. Cambridge University Press, New York. Atran, S., 1995. Classifying nature across cultures. In: Osherson, D., Smith, E.E. (Eds.), Thinking. The MIT Press. Bond, M.H., 1986. The Psychology of Chinese People. Oxford University Press, New York. Chiu, L.-H., 1972. A cross-cultural comparison of cognitive styles in Chinese and American children. International Journal of Psychology, 7, 235–242. 4

We thank an anonymous reviewer for making this point.

I. Choi et al. / Cognition 65 (1997) 15–32

31

Choi, I., Nisbett, R.E., 1997. Situational salience and cultural differences in the correspondence bias and actor- observer bias. Personality and Social Psychology Bulletin (in press). Cousins, S.D., 1989. Culture and self-perception in Japan and the United States. Journal of Personality and Social Psychology, 56, 124–131. Gelman, S.A., Markman, E.M., 1983. Natural kind terms and children’s ability to draw inferences. Paper presented at the meeting of the Western Psychological Association, San Francisco. Heit, E., Rubinstein, J., 1994. Similarity and property effects in inductive reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20 (2), 411–422. Hofstede, G., 1980. Culture’s Consequences: International Differences in Work-Related Values. Sage, Beverly Hills, CA. Hsu, F.L.K., 1981. American and Chinese: Passage to Differences, third ed. University of Hawaii Press, Honolulu. Lee, F., Hallahan, M., Herzog, T., 1996. Explaining real life events: how culture and domain shape attributions. Personality and Social Psychology Bulletin, 22, 732–741. Liu, S.H., 1974. The use of analogy and symbolism in traditional Chinese philosophy. Journal of Chinese Philosophy, 1, 313–338. Lloyd, G.E.R., 1990. Demystifying Mentalities. Cambridge University Press, New York. Lopez, A., Gelman, S.A., Gutheil, G., Smith, E.E., 1992. The development of category-based induction. Child Development, 63, 1070–1090. Lopez, A., Atran, S., Coley, J.D., Medin, D.L., Smith, E.E., 1997. The tree of life: universal and cultural features of folkbiological taxonomies and inductions. Cognitive Psychology, 32, 251– 295. Markus, H.R., Kitayama, S., 1991. Culture and self: implications for cognition, emotion, and motivation. Psychological Review, 98, 224–253. McDonald, J., Samuels, M., Rispoli, J., 1996. A hypothesis-assessment model of categorical argument strength. Cognition, 59, 199–217. Medin, D.L., Lynch, E.B., Coley, J.D., Atran, S., 1997. Categorization and reasoning among tree experts: do all roads lead to Rome?. Cognitive Psychology, 32, 49–96. Miller, J.G., 1984. Culture and the development of everyday social explanation. Journal of Personality and Social Psychology, 46, 961–978. Morris, M.W., Peng, K., 1994. Culture and cause: American and Chinese attributions for social and physical events. Journal of Personality and Social Psychology, 67, 949–971. Morris, M.W., Nisbett, R.E., Peng, K., 1993. Causal understanding across domains and cultures. In: Sperber, D., Premack, D., Premack, A.J. (Eds.), Causal Cognition: A Multidisciplinary Debate. Oxford University Press, Oxford. Munro, D., 1985. Individualism and Holism: Studies in Confucian and Taoist Values. Center for Chinese Studies, University of Michigan, Ann Arbor, MI. Murphy, G.L., Medin, D.L., 1985. The role of theories in conceptual coherence. Psychological Review, 92, 289–316. Nagashima, N., 1973. A reversed world: or is it? In: Horton, R., Finnegan, R. (Eds.), Modes of Thought. Faber and Faber, London. Nakamura, H., 1985. Ways of Thinking of Eastern People. University of Hawaii Press, Honolulu, 1964/ 1985. Needham, J., 1962. Science and Civilization in China. Cambridge University Press, New York. Osherson, D.N., Smith, E.E., Wilke, O., Lopez, A., Shafer, E., 1990. Category-based induction. Psychological Review, 97, 185–200. Peng, K., Nisbett, R.E., 1997a. Culture and covariation detection. (submitted). Peng, K., Nisbett, R.E., 1997b. Cross-cultural similarities and differences in the understanding of physical causality. In: Shield, M. (Ed.), Proceedings of Conference on Culture and Science. Kentucky State University Press, Kentucky. Rhee, E., Uleman, J., Lee, H., Roman, R., 1995. Spontaneous self-descriptions and ethnic identities in individualistic and collectivisitic cultures. Journal of Personality and Social Psychology, 69, 142– 152.

32

I. Choi et al. / Cognition 65 (1997) 15–32

Shweder, R.A., Bourne, L., 1984. Does the concept of the person vary cross-culturally? In: Shweder, R.A., ReVine, R.A. (Eds.), Culture Theory: Essays on Mind, Self and Emotion. Cambridge University Press, New York. Sloman, S.A., 1993. Feature-based induction. Cognitive Psychology, 25, 231–280. Smith, E.E., Medin, D.L., 1981. Categories and Concepts. Harvard University Press, Cambridge, MA. Smith, E.E., Shafir, E., Osherson, D., 1993. Similarity, plausibility, and judgment of probability. Cognition, 49, 67–96. Triandis, H.C., 1995. Individualism and Collectivism. Westview Press, Boulder, CO. Triandis, H.C., McCusker, C., Hiu, C.H., 1990. Multimethod probes of individualism and collectivism: cross-cultural perspectives on self-in group relationships. Journal of Personality and Social Psychology, 59, 1006–1020. Witkin, H.A., Berry, J.W., 1975. Psychological differentiation in cross-cultural perspectives. Journal of Cross-Cultural Psychology, 6, 4–87.