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Gender stereotypes and assumptions about expertise in transactive memory
Journal of Experimental Social Psychology Journal of Experimental Social Psychology 39 (2003) 355–363 www.elsevier.com/locate/jesp
Gender stereotypes and assumptions about expertise in transactive memory Andrea B. Hollingshead* and Samuel N. Fraidin Department of Psychology, University of Illinois at Urbana-Champaign, 603 Daniel Street, Champaign, IL 61820, USA Received 1 August 2001; revised 9 January 2002
Abstract This experiment investigated how people use gender stereotypes to infer the relative knowledge of interdependent others, and how those assumptions can affect the division of knowledge responsibilities in transactive memory systems. Participants indicated their expertise relative to the average male and female undergraduate student on six knowledge categories. Two of these were consistent with female stereotypes (soap operas and cosmetics), two were consistent with male stereotypes (sports and cars), and two were neutral (geography and history). Everyone then worked on a collective memorization task with an assumed partner. The design was a 2 2 factorial, with the participantsÕ gender and their assumed partnersÕ gender (same or different as the participantÕs) as factors. The results showed that both male and female participants shared similar gender stereotypes across knowledge domains. Participants with opposite-sex partners were more likely to assign categories based on gender stereotypes than were participants with same-sex partners. As a result, participants with opposite-sex partners learned more information in categories consistent with those stereotypes. These findings suggest that transactive memory systems may perpetuate gender stereotypes. Ó 2003 Elsevier Science (USA). All rights reserved. Keywords: Transactive memory; Stereotypes; Gender; Expertise; Group processes
People who live alone often perform most personal and household tasks themselves. They decide what to wear each day, go shopping, cook, replace light bulbs, pay bills, plan social events, take care of plants, cars, and pets, and so on. As a result, singles often acquire broad expertise. But when singles develop relationships, become couples and live together, they often divide responsibilities for household tasks, so that each person performs fewer tasks, yet collectively all the tasks get done. Heterosexual couples tend to divide responsibility for different tasks across gender in ways based on social roles (Eagly & Steffen, 1984). Despite differences across couples in age, education, employment, and attitudes toward equality between the sexes, for example, men are more often responsible for barbecuing and fixing things around the house, whereas women are more often responsible for planning meals * Corresponding author. Fax: 1-217-244-1598. E-mail address: [email protected] (A.B. Hollingshead).
and keeping the house in order (Blair & Lichter, 1991; Shelton, 1990). People use gender stereotypes as a basis for assigning tasks at work and in other contexts as well. For example, women often become the interpersonal experts and party planners in work groups, even when they are in upper management. Young men, particularly those with glasses, may be asked to solve computer problems, simply because they have the physical characteristics of the prototypical computer expert. Even when both men and women have expertise and experience in a particular knowledge domain, responsibility for that domain may be assigned on the basis of gender stereotypes. In groups, the person who knows or is expected to know more about a particular knowledge domain is typically assigned responsibility for that domain (Wegner, 1987). This experiment investigates how and when people use gender stereotypes to infer the relative knowledge of group members, and how that process can affect the division of knowledge responsibilities.
0022-1031/03/$ - see front matter Ó 2003 Elsevier Science (USA). All rights reserved. doi:10.1016/S0022-1031(02)00549-8
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Transactive memory and the importance of convergent expectations Transactive memory is the shared division of cognitive labor in relationships. It involves the encoding, storage, retrieval, and communication of information from different domains (Wegner, 1987). The basic idea is that people who are interdependent often develop an implicit plan for learning new information based on their shared conception of one anotherÕs expertise. Each individual becomes a specialist in some domains but not others, and individuals rely on one another to access information across domains. Transactive memory develops naturally in relationships, reducing individual cognitive effort and providing members with access to a larger pool of information. Transactive memory systems have been observed in many types of groups including dating couples (Hollingshead, 1998a, 1998b; Wegner, Erber, & Raymond, 1991), co-workers (Hollingshead, 2000), and laboratory work groups (Hollingshead, 1998c; Liang, Moreland, & Argote, 1995; Moreland & Myaskovsky, 2000; Moreland, Argote, & Krishnan, 1998). Transactive memory systems are more likely to develop when group members are interdependent and have convergent expectations about who will learn what (Hollingshead, 2001). An important determinant of convergent expectations is whether group members have shared beliefs about how their own knowledge differs from that of others in the group (Hollingshead, 2001). Convergent expectations can affect how group members tacitly coordinate who will learn what (cf. Wittenbaum, Stasser, & Merry, 1996; Wittenbaum, Vaughan, & Stasser, 1998). For example, Stephanie and Brett, who are siblings, both believe that Brett knows more about navigation than does Stephanie. As a result, Brett buys a map and studies it before they leave on vacation, and Stephanie assumes that Brett will do just that. This experiment investigates whether gender stereotypes are an important source of convergent expectations in situations where group members have little information about one anotherÕs knowledge.
Stereotypes, gender, and assumptions about expertise When people do not know much about the knowledge of their conversational partners, they may rely on stereotypes based on demographic characteristics (e.g., age, gender, ethnicity, and social class) to infer their partnersÕ knowledge in particular domains (Clark & Marshall, 1981; Krauss & Fussell, 1991; Wegner, 1987). In these situations, stereotypes serve an information-gain function (Plaks & Higgins, 2000)—they help people to make predictions about one anotherÕs knowledge and potential task contribu-
tions when no other information is available (Medin, 1988). Gender dominates race, age, and social class as the basis for categorization across many contexts (for a review see Zemore, Fiske, & Kim, 2000). People use gender to make inferences about personality (Friedman & Zebrowitz, 1992), social roles (Eagly, Wood, & Diekman, 2000), and physical characteristics (Biernat, 1993). Gender stereotypes can generate expectations about potential performance (Foddy & Smithson, 1999), which can influence motivation and effort (Kerr & MacCoun, 1984; Plaks & Higgins, 2000; Vancouver, Rubin, & Kerr, 1991). People often have similar gender stereotypes, and often behave in ways that mirror gender roles and stereotypes (Eagly et al., 2000). People are more likely to think of themselves in gender stereotypical ways in mixed-sex than in same-sex groups, because gender stereotypes are less salient in the latter groups (Hogg & Turner, 1987, for a review, see Moreland & Levine, 1992). Previous research suggests that people use gender stereotypes to infer the relative knowledge of others, and that such stereotypes can guide the development of convergent expectations about responsibilities for knowledge in transactive memory systems (Driskell & Mullen, 1990; Foddy & Smithson, 1999; Wood & Karten, 1986). Gender stereotypes should thus affect not only how people make judgments about relative knowledge, but also how they assign knowledge categories to others, how long that process takes, and which information they choose to learn and recall. To investigate these processes in the present experiment, male and female participants assigned different knowledge categories and learned information from those categories with an assumed partner who was either of the same or of the opposite sex, all without meeting or communicating. The following predictions were made: Hypothesis 1. The relative knowledge hypothesis. In the absence of other information, participants will use gender stereotypes to infer their knowledge relative to other group members. Male participants will rate themselves as more knowledgeable than female participants for categories consistent with male stereotypes (‘‘male categories’’) and female participants will rate themselves as more knowledgeable than male participants for categories consistent with female stereotypes (‘‘female categories’’). Hypothesis 2. The category assignment hypothesis. Participants with opposite-sex partners will be more likely to assign responsibility for knowledge categories to their partner based on gender stereotypes than will participants with same-sex partners. Men with female partners will be more likely to assign male categories to themselves and female categories to their partners than
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will men with male partners. In contrast, women with male partners will be more likely to assign female categories to themselves and male categories to their partners than will women with female partners. Hypothesis 3. The reaction time hypothesis. When gender stereotypes are activated, participants will take less time to make category assignments. Participants with opposite-sex partners will thus take less time to assign categories than will participants with same-sex partners. Hypothesis 4. The learning hypothesis. When gender stereotypes are activated, participants will tend to learn information consistent with their own gender stereotypes (‘‘stereotypical information’’). Thus, participants with opposite-sex partners will learn and recall more stereotypical information than will participants with same-sex partners. Men will learn more information in male categories when paired with female than with male partners, and women will learn more information in female categories when paired with male than with female partners.
Method Overview and design The experiment was run entirely on a computer network. Participants indicated their expertise relative to the average male and female University of Illinois undergraduate student on six knowledge categories. Two of these were consistent with female stereotypes, two were consistent with male stereotypes, and two were gender neutral. Everyone then worked on a learning task with an assumed partner. The task involved memorizing words in the six knowledge categories. The design was a 2 2 factorial, with the participantsÕ gender and the gender of their assumed partners (same or different as the participant) as the factors. The only information given to participants about their partners was their partnersÕ names. Participants Fifty-two students enrolled in an introductory psychology course at the University of Illinois at UrbanaChampaign took part in the experiment. They received course credit for their participation. There were between 12 and 14 participants in each experimental condition. Procedure Six participants were run at a time, in a computer lab with six private rooms. Participants were randomly assigned to experimental conditions, and multiple condi-
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tions were run during each session. Special care was taken so that participants would not meet, see, or talk to one another before or during their sessions. The computers were all connected to a network; the pacing of the experiment was controlled by a central workstation. The experimenter began each session by describing the experiment as research on distributed collaboration. He explained that participants would be asked questions about different topic areas and then work on a collaborative learning task with a partner, without ever meeting or communicating with that person. A prize of $20 would be awarded to each member of the five pairs who performed best in the experiment.1 Participants were assured that their responses would be confidential, and that they could withdraw from the experiment at any time without penalty. The same experimenter conducted all experimental sessions. After typing their names into the computer, participants were shown the six categories and asked how much they knew about each one. We chose the six categories based on the results of a pilot study. Two categories were consistent with male stereotypes (cars and sports), two were consistent with female stereotypes (cosmetics and soap operas) and two were gender neutral (geography and US history). Participants compared their own knowledge in each category to that of the average male and female undergraduate on 7-point scales (1, I know much less about this topic; 7, I know much more about this topic). Participants were also asked to type a short description of their experience in each category, or to type ‘‘none’’ if they had no experience. After completing the expertise ratings, each participant was told that the computer would randomly assign another person to be his or her partner. After a short delay, the partnerÕs name (Amanda, Jennifer, Scott, or Patrick) was presented. The partners were not real people, and those names (common among University of Illinois undergraduates) were intended to convey information about gender. Either Amanda or Jennifer was the partnerÕs name in the female partner condition; and either Scott or Patrick was the partnerÕs name in the male partner condition. Participants were then told they would work with their partners to memorize as many items as they could. They were told that one partner would be randomly chosen to divide the knowledge categories between the partners. After a short delay, participants learned that they had been chosen to assign the categories. The participantÕs name then appeared on the left side of the computer screen and the partnerÕs name appeared on the right side of the screen. The category names were listed in the middle of the screen, with option buttons on 1 We actually awarded $20 cash prizes to the highest performing individual in each condition.
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each side. Participants were told to click on the right button to assign a category to their partner, and the left button to assign a category to themselves. Participants could assign between one and five categories to each person, with the constraints that each partner had to be assigned at least one category, and each category could be assigned to only one partner. The computer program did not allow participants to proceed until these requirements were satisfied. After all participants in a session completed the category assignment, the word lists from categories that participants assigned to themselves appeared on their screens. Participants had exactly 4 min to memorize their words. Afterward, participants were asked to type all of the words they could remember into a general list without category labels. Participants were given exactly 4 min for recall. A set of post-experimental questions was then presented. Participants listed their partnerÕs names and rated how difficult it was to learn the words (1, very easy; 7, very difficult), how difficult it was for their partner to learn the words (same scale), how hard they tried to learn the words (1, I didnÕt try very hard; 7, I tried very hard), the extent to which they considered their partnersÕ knowledge when they assigned categories (1, not at all; 7, a lot), and their typing speed (1, very slow; 7, very fast). Finally, participants were thanked and debriefed. Task. The learning task included 20 words from each of six knowledge categories. These categories were selected in a pilot study. In that study, 35 undergraduates (19 male and 16 female) rated (on 5-point scales) how much they knew, and how much they thought the average male and female University of Illinois undergraduate would know, about several different categories. Participants expected women to know more than men about soap operas (g2 ¼ :92),2 cosmetics (.92), celebrities (.71), cooking (.65), and clothing (.50), and they expected men to know more than women about cars (g2 ¼ .87), sports trivia (.86), and computers (.67). A smaller gender difference (favoring men) was found for alcoholic beverages (.34), and no significant gender difference was found for geography (p > :17). The two male and female categories with the largest effect sizes were selected, along with geography and US history3 as the neutral categories. The authors generated items (of varying difficulty) for each category by examining relevant websites. Brief descriptions of each category were provided to partici2 2 g is a calculation for t tests that is analogous to r2 in correlations and regressions. This number can be interpreted in exactly the same way as r2 . 3 US History was chosen as the second neutral category based on data from Hollingshead (1998b) In that study, similar questions were asked about knowledge relative to the average male and female undergraduate at the University of Illinois across different categories. No significant differences were obtained for US History.
pants when they rated their own knowledge, and again when they made category assignments. See Table 1 for category descriptions and specific items.
Results Manipulation check One question on the post-experimental questionnaire asked participants to list the names of their partners. All 52 participants remembered their partnersÕ names correctly, suggesting that gender was salient to them. Total recall The results showed that participants divided categories evenly between partners. With one exception (a person who assigned four categories to himself), participants assigned three categories to themselves, and three to their partners (M ¼ 3:01, 2.99, respectively). On average, participants recalled 27.61 items.4 A twoway analysis of variance was conducted on the number of categories participants assigned to their partners, and then again on their total recall, with participant gender and partner gender (same or different as the participant) as between-participant factors. There were no significant main or interaction effects on either dependent measure. Hypothesis testing Hypothesis 1. The relative knowledge hypothesis. Men were expected to rate themselves as more knowledgeable than women for male categories, and women were expected to rate themselves as more knowledgeable than men for female categories. This hypothesis was tested by examining participantsÕ ratings of their own expertise relative to that of the average University of Illinois male (male target) or female undergraduate (female target). A 2 2 3 repeated measures analysis of variance was conducted with participant gender as the between-participant factor and target gender and category type (male, female, or neutral) as the repeated measures factors. See Table 2 for the results. The only significant main effect was for category type, F ð2; 100Þ ¼ 12:14, p < :0001, MSE ¼ 2.12. Participants rated themselves as more knowledgeable for neutral
4 The recall coding was done entirely by computer. We used two methods: (1) counting letters that matched in the correct location (e.g., ‘‘scottee pippen’’ is just one letter different from ‘‘scottie pippen’’), and (2) counting the number of letters that matched regardless of location (e.g., ‘‘ttcsoei pppnei’’ contains all the letters of ‘‘scottie pippen’’). Each method produced a ‘‘quality of match’’ index (percentage of correct letters), and the higher index was used. Words with an index score of 66% or higher were counted as correct.
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categories than for female categories, F ð1; 50Þ ¼ 27:96, p < :0001, MSE ¼ 7.26. A similar tendency was apparent, but not significant, for the neutral and male categories, F ð1; 50Þ ¼ 3:39, p < :08, MSE ¼ 9.01. The two-way interaction between participant gender and category type was significant, F ð2; 100Þ ¼ 56:31, Table 1 Memory task: Category labels and items Car and driver: Parts, makes, and models of cars
Sports: Professional sports teams and superstars
Transmission Rims Ignition Radiator Alignment Saab Coupe Clutch Rollbar 5 series Boxster OHC Tailpipe Flywheel Evaporator Differential Tachometer Spoiler Octane Manifold
Utah Jazz Darryl Strawberry Tiger Woods Vince Carter Detroit Redwings Cynthia Cooper Green Bay Packers Elton Brand Mario Lemieux Picabo Street Serena Williams Chicago Fire Scottie Pippen Andre Agassi Florida Marlins Ken Griffey Jr. St. Louis Rams Ryne Sandberg Mike Tyson Jackie Joyner-Kersee
Looking good: Cosmetics and companies that produce them Max Factor Blush Moisturizer Clinique Lip liner Collagen Top coat Almay Tweezers Maybelline Avon Eye shadow Toner Alpha Hydroxy Revlon Acetone Cover Girl Lancome Mascara Facial
Soaps: Soap operas and characters Sunset Beach Erica Kane Young and Restless Guiding Light Mac Scorpio Days of Our Lives Bo Buchanan Santa Barbara As the World Turns One Life to Live Guiding Light Lucky Spencer All My Children Another World Bold and Beautiful Days of Our Lives General Hospital One Life to Live Port Charles Passions
World geography: World cities, countries, and bodies of water Sweden Jerusalem Indian Ocean Canada Brazil Maine Lake Michigan Bali
US history: People, places, and events in US history War of 1812 FDR Benjamin Franklin Frederick Douglass Civil War John F. Kennedy Revolutionary War Susan B. Anthony
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Table 1 (continued) World geography: World cities, countries, and bodies of water
US history: People, places, and events in US history
Danube River New Zealand Puget Sound Honduras Mozambique Saskatchewan North Sea Malaysia Mediterranean Sea China Rome Greenland
Louisiana Purchase John Adams Watergate Philadelphia Antietam Alamo Sojourner Truth Boston Tea Party The Cold War Harriet Tubman Westward Expansion Henry Ford
Table 2 Mean ratings of participantsÕ own knowledge relative to the average male and female undergraduate Participant gender
Knowledge category
Average male undergraduate
Average female undergraduate
Male
Male Female Neutral Male Female Neutral
3.68 2.20 4.12 2.02 5.15 3.39
5.04 1.12 4.08 3.54 3.39 3.80
Female
(1.34) (1.10) (1.17) (.89) (1.73) (1.06)
(1.54)a (.26)a (.92) (1.06)a (1.06)a (.93)
Note. N ¼ 52. Values ranged from 1 to 7. 1, I know much less about this topic (than target); 4, I know about the same about this topic; 7, I know much more about this topic (than target). Standard deviations are in parentheses. a Row means are significantly different at p < :001.
p < :0001, MSE ¼ 2.12. Men rated their knowledge higher than did women for male categories, F ð1; 50Þ ¼ 23:11, p < :0001, MSE ¼ 1.40. Women rated their knowledge higher than did men for female categories, F ð1; 50Þ ¼ 114:90, p < :0001, MSE ¼ 0.67. ParticipantsÕ knowledge ratings did not differ by gender for the neutral categories. The two-way interaction between target gender and category type was also significant, F ð2; 100Þ ¼ 154:97, p < :0001, MSE ¼ .34. For male categories, participants rated themselves as relatively more knowledgeable when they compared their knowledge to a female target than to a male target, F ð1; 51Þ ¼ 285:45, p < :0001, MSE ¼ 0.19. The opposite pattern was obtained for female categories, F ð1; 51Þ ¼ 84:42, p < :0001, MSE ¼ 0.53. This result suggests that both male and female participants shared similar gender stereotypes. ParticipantsÕ ratings did not differ significantly by target gender for neutral categories. Finally, the three-way interaction was also significant, indicating that men and women rated their knowledge relative to a male and to a female target differently across categories, F ð2; 100Þ ¼ 3:83, p < :03, MSE ¼ .34. Male participants rated themselves as more knowledgeable than the average female for male
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categories. Similarly, women rated themselves more knowledgeable than the average male for female categories. These findings provide further support for Hypothesis 1. Hypothesis 2. The category assignment hypothesis. Participants with opposite-sex partners were expected to assign their partner categories consistent with gender stereotypes more often than were participants with same-sex partners. To test this hypothesis, a 2 2 3 repeated measures analysis was conducted with participant gender and partner gender as the between-participants factors and category type (male, female, or neutral) as the repeated measures factor. See Table 3 for the results. The analysis revealed a significant main effect of category type, (F ð2; 96Þ ¼ 6:58, p < :001, MSE ¼ .40), indicating that participants assigned fewer neutral than male or female categories to their partners (F ð1; 48Þ ¼ 5:61, p < :03, MSE ¼ .99 for male versus neutral categories; F ð1; 48Þ ¼ 17:49, p < :0001, MSE ¼ .99 for female versus neutral categories. M ¼ 1:08, 1.15, .75 for male, female, and neutral categories respectively). There was also a significant two-way interaction between participant gender and category type, F ð2; 96Þ ¼ 27:07, p < :0001, MSE ¼ .40, showing that men were more likely to assign female categories to their partners, F ð1; 23Þ ¼ 24:64, p < :0001, MSE ¼ .91, whereas women were more likely to assign male categories to their partners, F ð1; 25Þ ¼ 17:57, p < :001, MSE ¼ .42. Support for the hypothesis was found in a significant three-way interaction, F ð2; 96Þ ¼ 22:15, p < :0001, MSE ¼ .40. Men with female (rather than male) partners assigned more male categories to themselves and more female categories to their partners, F ð1; 23Þ ¼ 14:55, p < :001, MSE ¼ .91. In fact, every male participant with a female partner assigned the two female categories to her. In contrast, women with male (rather than female) partners assigned more female categories to themselves and more male categories to their partners, F ð1; 25Þ ¼ 25:06, p < :0001, MSE ¼ .83. All but one of the female participants with a male partner assigned the two male categories to him. Hypothesis 3. The reaction time hypothesis. Participants with opposite-sex partners were expected to assign Table 3 Mean number of categories assigned to partners by category type and experimental condition Condition
Male with male partner Male with female partner Female with male partner Female with female partner
Category type
categories more quickly than participants with same-sex partners. The computer recorded the total time participants took to assign the six categories. On average, participants spent a total of 47.56 s on category assignments. A 2 2 analysis of variance was conducted with participant gender and the partner gender as the between-participant factors. Contrary to the prediction, there were no significant differences in category assignment times. Hypothesis 4. The learning hypothesis. Participants were expected to learn and recall more stereotypical information when paired with opposite-sex than samesex partners. To test this hypothesis, items that participants recalled were categorized as stereotypical or not stereotypical. For female participants, items recalled in female categories were considered stereotypical, and items recalled in male or neutral categories were not. For male participants, items recalled in male categories were considered stereotypical, and items recalled in female or neutral categories were not. A 2 2 2 repeated measures analysis was conducted with participant gender and partner gender as the between-participant factors and category type (stereotypical or not stereotypical) as the repeated measures factor. On average, participants recalled 12.25 items that were stereotypical and 15.35 items that were not stereotypical. See Table 4 for the results. There were no significant main or two-way interaction effects. However, consistent with the hypothesis, there was a significant three-way interaction, F ð1; 48Þ ¼ 16:97, p < :0001, MSE ¼ 76.73. Overall, men with female (rather than male) partners learned more words in male categories and fewer words in female or neutral categories, F ð1; 23Þ ¼ 9:88, p < :01, MSE ¼ 192.35. In contrast, women with male (rather than female) partners learned more words in female categories and fewer words in male or neutral categories, F ð1; 25Þ ¼ 6:80, p < :02, MSE ¼ 117.70. Post-experimental questions In general, participants rated the task as moderately difficult (M ¼ 4:36), tried hard to learn as many items as they could (M ¼ 5:75), thought about what their partners might know when they assigned categories (M ¼ 4:57), and believed that their typing speed was Table 4 ParticipantsÕ mean recall by experimental condition
Male
Female
Neutral
Condition
Stereotypical
Not stereotypical
1.15 0.33 1.92 0.86
1.38 2.00 0.31 1.00
0.46 0.58 0.77 1.14
Male with male partner Male with female partner Female with male partner Female with female partner
7.38 16.25 15.77 10.07
19.92 11.33 12.23 17.42
(.80) (.49) (.28) (.66)
(.51) (.00) (.48) (.55)
(.52) (.52) (.44) (.53)
Note. N ¼ 52. Values ranged from 0 to 2. Standard deviations are in parentheses.
(8.39) (6.90) (5.36) (5.64)
(8.34) (5.61) (4.71) (8.14)
Note. N ¼ 52. Values ranged from 0 to 40. Standard deviations are in parentheses.
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moderately fast (M ¼ 4:5). All of these means were significantly different (all p’s < :05) from 4, the midpoint of the rating scale. There were no significant differences across conditions for any of the post-experimental measures.
Discussion Our findings show that in the absence of other information, people use gender stereotypes to infer differences in expertise among group members. Both male and female participants shared similar gender stereotypes about the knowledge of male and female undergraduates across domains. We also found that people behave in ways consistent with those stereotypes, particularly when gender is salient. Participants with opposite-sex partners were more likely to assign categories and learn information consistent with gender stereotypes than were participants with same-sex partners. These findings support the claim that gender stereotypes facilitate the development of convergent expectations in mixed-sex relationships. Both men and women assigned categories and learned information consistent with gender stereotypes when they believed their partner was of the opposite sex. Answers to an open-ended question about the strategies that participants used to assign categories provide additional insight into this issue. Many participants in the same-sex condition indicated that they assigned categories based primarily on their own knowledge of the categories. Participants in the mixed-sex condition also indicated that their own knowledge played a role, but many of them considered their partnerÕs knowledge as well. Several of these participants explicitly mentioned their partnerÕs gender, and most said that they made inferences about what their partner was likely to know. These responses are consistent with the claim that people use gender stereotypes to infer the knowledge of others in the absence of other information (Medin, 1988; Wegner, 1987). Our findings suggest that expectations based on gender stereotypes can be a self-fulfilling prophecy in transactive memory systems (cf. Geis, 1993; Skrypnek & Snyder, 1982). For example, if both partners in a mixedsex relationship expect the woman to know more about categories consistent with female stereotypes (e.g., cooking), then she may assume responsibility for relevant activities and eventually become the expert, regardless of whether or not she actually knew more about that category initially. As a result, transactive memory systems may perpetuate gender stereotypes in mixed-sex situations, because convergent expectations lead people to become experts in areas consistent with those stereotypes. This can be problematic if people would rather
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take responsibility for categories that are not stereotypical. All of our hypotheses but one were supported. Contrary to Hypothesis 3, participants with oppositesex partners did not take less time than participants with same-sex partners to assign categories. Participants could assign knowledge categories in any order, and we did not measure the time taken to assign each category separately. It may be that participants with opposite-sex partners took less time to assign stereotypical categories, but relatively more time to assign neutral categories. Participants generally rated their own knowledge as similar to that of a typical undergraduate of the same gender for categories consistent with their gender stereotype. And they rated themselves as less knowledgeable than a typical undergraduate of the opposite gender for categories consistent with the opposite gender stereotype. Thus, the general tendency to see oneself as ‘‘above average’’ may not be present for knowledge consistent with male or female gender stereotypes (cf. Alicke, Klotz, Breitenbecher, & Yurak, 1995; Kruger, 1999). However, we did not measure participantsÕ actual knowledge across the categories, so it was not possible to determine whether participants were accurate in their knowledge assessments. Unlike Plaks and Higgins (2000) and Vancouver et al. (1991), we found no significant differences in motivation, effort, or performance across the experimental conditions. In those studies, participants adjusted their effort on collective tasks based on the fit between task requirements and the stereotypic strengths of their partners. The collective task used in this experiment was different—it involved a division of labor and knowledge consistent with both male and female stereotypes. It is likely that participants believed a good fit existed between the stereotypic strengths of their partners and the categories assigned to them. This suggests that motivation and accountability may be other benefits of transactive memory. In transactive memory systems, group members are often assigned categories they know something about, and they have unique responsibility for the categories assigned to them. As a result, each member may believe his or her contributions are critical to the group (cf. Kerr & Kaufman-Gilliland, 1997). Our findings also show that transactive memory effects can arise without communication (cf., Hollingshead, 2000, 2001; Moreland & Myaskovsky, 2000). This experiment extended previous research by simulating how gender stereotypes might affect the division of cognitive labor in the initial stages of relationships, when people are unfamiliar with one another. The procedures we used in the experiment may have created the ‘‘ideal’’ conditions for gender stereotypes to have an effect: participants could not meet, see, or talk to one another. Future research should investigate how com-
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munication can affect and change group membersÕ expectations about one anotherÕs knowledge. It is possible that the strong effects of gender stereotypes observed in this experiment would be attenuated if communication were allowed between partners. In addition, people often have experiential knowledge about their own abilities and those of others. For example, a woman may know that she knows more about mathematics than most men based on her performance on standardized tests. Future research should also investigate whether specific knowledge about oneÕs own and othersÕ abilities can mitigate the impact of gender stereotypes. However, initial expectations of expertise based on gender stereotypes may be difficult to overcome, given that the delegation of responsibilities based on those stereotypes is so prevalent in our society. People with expertise in counter-stereotypical areas may need to display more evidence of their knowledge to be considered experts, particularly in mixed-sex groups. Future research should also investigate whether the findings from this experiment will extend to stereotypes about expertise based on age, race, occupation, and culture.
Acknowledgments This research was supported by the National Science Foundation: Knowledge and Distributed Intelligence program: IIS-9980109NSF and the University of Illinois Research Board.
References Alicke, M. D., Klotz, M. L., Breitenbecher, D. L., & Yurak, T. J. (1995). Personal contact, individuation, and the better-than-average effect. Journal of Personality and Social Psychology, 68, 804– 825. Biernat, M. (1993). Gender and height: Developmental patterns in knowledge and use of an accurate stereotype. Sex Roles, 29, 691– 713. Blair, S. L., & Lichter, D. T. (1991). Measuring the division of household labor: Gender segregation of housework among American couples. Journal of Family Issues, 12, 91–113. Clark, H. H., & Marshall, C. (1981). Definite reference and mutual knowledge. In A. Joshi, I. Sag, & B. Webber (Eds.), Elements of discourse understanding (pp. 10–63). Cambridge: Cambridge University Press. Driskell, J. E., & Mullen, B. (1990). Status, expectations, and behavior: A metaanalytic review and test of the theory. Personality and Social Psychology Bulletin, 16, 541–553. Eagly, A. H., & Steffen, V. J. (1984). Gender stereotypes stem from the distribution of women and men into social roles. Journal of Personality and Social Psychology, 46, 735–754. Eagly, A. H., Wood, W., & Diekman, A. B. (2000). Social role theory of sex differences and similarities: A current appraisal. In T. Eckes, & H. M. Trautner (Eds.), The developmental social psychology of gender (pp. 123–174). Mahwah, NJ: Erlbaum. Foddy, M., & Smithson, M. (1999). Can gender inequalities be eliminated? Social Psychology Quarterly, 62, 307–324.
Friedman, H., & Zebrowitz, L. (1992). The contribution of typical sex differences in facial maturity to sex role stereotypes. Personality and Social Psychology Bulletin, 18, 430–438. Geis, F. L. (1993). Self-fulfilling prophecies: A social psychological view of gender. In A. E. Beall, & R. J. Sternberg (Eds.), The psychology of gender (pp. 9–54). New York: Guilford. Hogg, M. A, & Turner, J. C. (1987). Intergroup behaviour, selfstereotyping and the salience of social categories. British Journal of Social Psychology, 26, 325–340. Hollingshead, A. B. (1998a). Retrieval processes in transactive memory systems. Journal of Personality and Social Psychology, 74, 659–671. Hollingshead, A. B. (1998b). Communication, learning, and retrieval in transactive memory systems. Journal of Experimental Social Psychology, 34, 423–442. Hollingshead, A. B. (1998c). Group and individual training: The impact of practice on performance. Small Group Research, 29(2), 254–280. Hollingshead, A. B. (2000). Perceptions of expertise and transactive memory in work relationships. Group Processes and Intergroup Relations, 3, 257–267. Hollingshead, A. B. (2001). Cognitive interdependence and convergent expectations in transactive memory. Journal of Personality and Social Psychology, 1080–1089. Kerr, N. L., & Kaufman-Gilliland, C. M. (1997). ‘‘. . .and besides, I probably couldnÕt have made a difference anyway’’: Justification of social dilemma defection via perceived self-inefficacy. Journal of Experimental Social Psychology, 33, 211–230. Kerr, N. L., & MacCoun, R. J. (1984). Sex composition of groups and member motivation: II. Effects of relative task ability. Basic and Applied Social Psychology, 5, 255–271. Krauss, R. M., & Fussell, S. R. (1991). Constructing shared communicative environments. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 172–200). Washington DC: American Psychological Association. Kruger, J. (1999). Lake Wobegon be gone! The ‘‘below-average effect’’ and the egocentric nature of comparative ability judgments. Journal of Personality and Social Psychology, 77, 221– 232. Liang, D. W., Moreland, R., & Argote, L. (1995). Group versus individual training and group performance: The mediating role of transactive memory. Personality and Social Psychology Bulletin, 21, 384–393. Medin, D. L. (1988). Social categorization: Structures, processes, and purposes. In R. Wyer, & T. Srull (Eds.), Advances in social cognition: Vol. 1 (pp. 119–125). Hillsdale, NJ: Erlbaum. Moreland, R. L., & Levine, J. M. (1992). The composition of small groups. In E. Lawler, B. Markovsky, C. Ridgeway, & H. Walker (Eds.), Advances in group processes: Vol. 9 (pp. 237–280). Greenwich, CT: JAI Press. Moreland, R. L., & Myaskovsky, L. (2000). Exploring the performance benefits of group training: Transactive memory or improved communication? Organizational Behavior and Human Decision Processes, 82, 117–133. Moreland, R. L., Argote, L., & Krishnan, R. (1998). Training people to work in groups. In R. S. Tindale, L. Heath, J. Edwards, E. J. Posavac, F. B. Bryant, Y. Suarez-Balcazar, E. Henderson-King, & J. Myers (Eds.), Theory and research on small groups (pp. 37–60). New York: Plenum. Plaks, J. E., & Higgins, E. T. (2000). Pragmatic use of stereotyping in teamwork: Social loafing and compensation as a function of inferred partner-situation fit. Journal of Personality and Social Psychology, 79, 962–974. Shelton, B. A. (1990). The distribution of household tasks: Does wifeÕs employment status make a difference? Journal of Family Issues, 11, 115–135.
A.B. Hollingshead, S.N. Fraidin / Journal of Experimental Social Psychology 39 (2003) 355–363 Skrypnek, B. J., & Snyder, M. (1982). On the self-perpetuating nature of stereotypes about women and men. Journal of Experimental Social Psychology, 18, 277–291. Vancouver, J. B., Rubin, B., & Kerr, N. L. (1991). Sex composition of groups and member motivation: III. Motivational losses at a feminine task. Basic and Applied Social Psychology, 12, 133–144. Wegner, D. M. (1987). Transactive memory: A contemporary analysis of the group mind. In B. Mullen, & G. R. Goethals (Eds.), Theories of group behavior (pp. 185–208). New York: Springer-Verlag. Wegner, D. M., Erber, R., & Raymond, P. (1991). Transactive memory in close relationships. Journal of Personality and Social Psychology, 61, 923–929.
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Wittenbaum, G. M., Stasser, G., & Merry, C. J. (1996). Tacit coordination in anticipation of small group task completion. Journal of Experimental Social Psychology, 32, 129–152. Wittenbaum, G. M., Vaughan, S. I., & Stasser, G. (1998). Coordination in task-performing groups. In R. S. Tindale et al. (Eds.), Theory and research on small groups (pp. 177–204). New York: Plenum Press. Wood, W., & Karten, S. J. (1986). Sex differences in interaction style as a product of perceived difference in competence. Journal of Personality and Social Psychology, 50, 341–347. Zemore, S. E., Fiske, S. T., & Kim, H. (2000). Gender stereotypes and the dynamics of social interaction. In T. Eckes, & H. M. Trautner (Eds.), The developmental social psychology of gender (pp. 207–242). Mahwah, NJ: Erlbaum.
Gender stereotypes and assumptions about expertise in transactive memory Andrea B. Hollingshead* and Samuel N. Fraidin Department of Psychology, University of Illinois at Urbana-Champaign, 603 Daniel Street, Champaign, IL 61820, USA Received 1 August 2001; revised 9 January 2002
Abstract This experiment investigated how people use gender stereotypes to infer the relative knowledge of interdependent others, and how those assumptions can affect the division of knowledge responsibilities in transactive memory systems. Participants indicated their expertise relative to the average male and female undergraduate student on six knowledge categories. Two of these were consistent with female stereotypes (soap operas and cosmetics), two were consistent with male stereotypes (sports and cars), and two were neutral (geography and history). Everyone then worked on a collective memorization task with an assumed partner. The design was a 2 2 factorial, with the participantsÕ gender and their assumed partnersÕ gender (same or different as the participantÕs) as factors. The results showed that both male and female participants shared similar gender stereotypes across knowledge domains. Participants with opposite-sex partners were more likely to assign categories based on gender stereotypes than were participants with same-sex partners. As a result, participants with opposite-sex partners learned more information in categories consistent with those stereotypes. These findings suggest that transactive memory systems may perpetuate gender stereotypes. Ó 2003 Elsevier Science (USA). All rights reserved. Keywords: Transactive memory; Stereotypes; Gender; Expertise; Group processes
People who live alone often perform most personal and household tasks themselves. They decide what to wear each day, go shopping, cook, replace light bulbs, pay bills, plan social events, take care of plants, cars, and pets, and so on. As a result, singles often acquire broad expertise. But when singles develop relationships, become couples and live together, they often divide responsibilities for household tasks, so that each person performs fewer tasks, yet collectively all the tasks get done. Heterosexual couples tend to divide responsibility for different tasks across gender in ways based on social roles (Eagly & Steffen, 1984). Despite differences across couples in age, education, employment, and attitudes toward equality between the sexes, for example, men are more often responsible for barbecuing and fixing things around the house, whereas women are more often responsible for planning meals * Corresponding author. Fax: 1-217-244-1598. E-mail address: [email protected] (A.B. Hollingshead).
and keeping the house in order (Blair & Lichter, 1991; Shelton, 1990). People use gender stereotypes as a basis for assigning tasks at work and in other contexts as well. For example, women often become the interpersonal experts and party planners in work groups, even when they are in upper management. Young men, particularly those with glasses, may be asked to solve computer problems, simply because they have the physical characteristics of the prototypical computer expert. Even when both men and women have expertise and experience in a particular knowledge domain, responsibility for that domain may be assigned on the basis of gender stereotypes. In groups, the person who knows or is expected to know more about a particular knowledge domain is typically assigned responsibility for that domain (Wegner, 1987). This experiment investigates how and when people use gender stereotypes to infer the relative knowledge of group members, and how that process can affect the division of knowledge responsibilities.
0022-1031/03/$ - see front matter Ó 2003 Elsevier Science (USA). All rights reserved. doi:10.1016/S0022-1031(02)00549-8
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Transactive memory and the importance of convergent expectations Transactive memory is the shared division of cognitive labor in relationships. It involves the encoding, storage, retrieval, and communication of information from different domains (Wegner, 1987). The basic idea is that people who are interdependent often develop an implicit plan for learning new information based on their shared conception of one anotherÕs expertise. Each individual becomes a specialist in some domains but not others, and individuals rely on one another to access information across domains. Transactive memory develops naturally in relationships, reducing individual cognitive effort and providing members with access to a larger pool of information. Transactive memory systems have been observed in many types of groups including dating couples (Hollingshead, 1998a, 1998b; Wegner, Erber, & Raymond, 1991), co-workers (Hollingshead, 2000), and laboratory work groups (Hollingshead, 1998c; Liang, Moreland, & Argote, 1995; Moreland & Myaskovsky, 2000; Moreland, Argote, & Krishnan, 1998). Transactive memory systems are more likely to develop when group members are interdependent and have convergent expectations about who will learn what (Hollingshead, 2001). An important determinant of convergent expectations is whether group members have shared beliefs about how their own knowledge differs from that of others in the group (Hollingshead, 2001). Convergent expectations can affect how group members tacitly coordinate who will learn what (cf. Wittenbaum, Stasser, & Merry, 1996; Wittenbaum, Vaughan, & Stasser, 1998). For example, Stephanie and Brett, who are siblings, both believe that Brett knows more about navigation than does Stephanie. As a result, Brett buys a map and studies it before they leave on vacation, and Stephanie assumes that Brett will do just that. This experiment investigates whether gender stereotypes are an important source of convergent expectations in situations where group members have little information about one anotherÕs knowledge.
Stereotypes, gender, and assumptions about expertise When people do not know much about the knowledge of their conversational partners, they may rely on stereotypes based on demographic characteristics (e.g., age, gender, ethnicity, and social class) to infer their partnersÕ knowledge in particular domains (Clark & Marshall, 1981; Krauss & Fussell, 1991; Wegner, 1987). In these situations, stereotypes serve an information-gain function (Plaks & Higgins, 2000)—they help people to make predictions about one anotherÕs knowledge and potential task contribu-
tions when no other information is available (Medin, 1988). Gender dominates race, age, and social class as the basis for categorization across many contexts (for a review see Zemore, Fiske, & Kim, 2000). People use gender to make inferences about personality (Friedman & Zebrowitz, 1992), social roles (Eagly, Wood, & Diekman, 2000), and physical characteristics (Biernat, 1993). Gender stereotypes can generate expectations about potential performance (Foddy & Smithson, 1999), which can influence motivation and effort (Kerr & MacCoun, 1984; Plaks & Higgins, 2000; Vancouver, Rubin, & Kerr, 1991). People often have similar gender stereotypes, and often behave in ways that mirror gender roles and stereotypes (Eagly et al., 2000). People are more likely to think of themselves in gender stereotypical ways in mixed-sex than in same-sex groups, because gender stereotypes are less salient in the latter groups (Hogg & Turner, 1987, for a review, see Moreland & Levine, 1992). Previous research suggests that people use gender stereotypes to infer the relative knowledge of others, and that such stereotypes can guide the development of convergent expectations about responsibilities for knowledge in transactive memory systems (Driskell & Mullen, 1990; Foddy & Smithson, 1999; Wood & Karten, 1986). Gender stereotypes should thus affect not only how people make judgments about relative knowledge, but also how they assign knowledge categories to others, how long that process takes, and which information they choose to learn and recall. To investigate these processes in the present experiment, male and female participants assigned different knowledge categories and learned information from those categories with an assumed partner who was either of the same or of the opposite sex, all without meeting or communicating. The following predictions were made: Hypothesis 1. The relative knowledge hypothesis. In the absence of other information, participants will use gender stereotypes to infer their knowledge relative to other group members. Male participants will rate themselves as more knowledgeable than female participants for categories consistent with male stereotypes (‘‘male categories’’) and female participants will rate themselves as more knowledgeable than male participants for categories consistent with female stereotypes (‘‘female categories’’). Hypothesis 2. The category assignment hypothesis. Participants with opposite-sex partners will be more likely to assign responsibility for knowledge categories to their partner based on gender stereotypes than will participants with same-sex partners. Men with female partners will be more likely to assign male categories to themselves and female categories to their partners than
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will men with male partners. In contrast, women with male partners will be more likely to assign female categories to themselves and male categories to their partners than will women with female partners. Hypothesis 3. The reaction time hypothesis. When gender stereotypes are activated, participants will take less time to make category assignments. Participants with opposite-sex partners will thus take less time to assign categories than will participants with same-sex partners. Hypothesis 4. The learning hypothesis. When gender stereotypes are activated, participants will tend to learn information consistent with their own gender stereotypes (‘‘stereotypical information’’). Thus, participants with opposite-sex partners will learn and recall more stereotypical information than will participants with same-sex partners. Men will learn more information in male categories when paired with female than with male partners, and women will learn more information in female categories when paired with male than with female partners.
Method Overview and design The experiment was run entirely on a computer network. Participants indicated their expertise relative to the average male and female University of Illinois undergraduate student on six knowledge categories. Two of these were consistent with female stereotypes, two were consistent with male stereotypes, and two were gender neutral. Everyone then worked on a learning task with an assumed partner. The task involved memorizing words in the six knowledge categories. The design was a 2 2 factorial, with the participantsÕ gender and the gender of their assumed partners (same or different as the participant) as the factors. The only information given to participants about their partners was their partnersÕ names. Participants Fifty-two students enrolled in an introductory psychology course at the University of Illinois at UrbanaChampaign took part in the experiment. They received course credit for their participation. There were between 12 and 14 participants in each experimental condition. Procedure Six participants were run at a time, in a computer lab with six private rooms. Participants were randomly assigned to experimental conditions, and multiple condi-
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tions were run during each session. Special care was taken so that participants would not meet, see, or talk to one another before or during their sessions. The computers were all connected to a network; the pacing of the experiment was controlled by a central workstation. The experimenter began each session by describing the experiment as research on distributed collaboration. He explained that participants would be asked questions about different topic areas and then work on a collaborative learning task with a partner, without ever meeting or communicating with that person. A prize of $20 would be awarded to each member of the five pairs who performed best in the experiment.1 Participants were assured that their responses would be confidential, and that they could withdraw from the experiment at any time without penalty. The same experimenter conducted all experimental sessions. After typing their names into the computer, participants were shown the six categories and asked how much they knew about each one. We chose the six categories based on the results of a pilot study. Two categories were consistent with male stereotypes (cars and sports), two were consistent with female stereotypes (cosmetics and soap operas) and two were gender neutral (geography and US history). Participants compared their own knowledge in each category to that of the average male and female undergraduate on 7-point scales (1, I know much less about this topic; 7, I know much more about this topic). Participants were also asked to type a short description of their experience in each category, or to type ‘‘none’’ if they had no experience. After completing the expertise ratings, each participant was told that the computer would randomly assign another person to be his or her partner. After a short delay, the partnerÕs name (Amanda, Jennifer, Scott, or Patrick) was presented. The partners were not real people, and those names (common among University of Illinois undergraduates) were intended to convey information about gender. Either Amanda or Jennifer was the partnerÕs name in the female partner condition; and either Scott or Patrick was the partnerÕs name in the male partner condition. Participants were then told they would work with their partners to memorize as many items as they could. They were told that one partner would be randomly chosen to divide the knowledge categories between the partners. After a short delay, participants learned that they had been chosen to assign the categories. The participantÕs name then appeared on the left side of the computer screen and the partnerÕs name appeared on the right side of the screen. The category names were listed in the middle of the screen, with option buttons on 1 We actually awarded $20 cash prizes to the highest performing individual in each condition.
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each side. Participants were told to click on the right button to assign a category to their partner, and the left button to assign a category to themselves. Participants could assign between one and five categories to each person, with the constraints that each partner had to be assigned at least one category, and each category could be assigned to only one partner. The computer program did not allow participants to proceed until these requirements were satisfied. After all participants in a session completed the category assignment, the word lists from categories that participants assigned to themselves appeared on their screens. Participants had exactly 4 min to memorize their words. Afterward, participants were asked to type all of the words they could remember into a general list without category labels. Participants were given exactly 4 min for recall. A set of post-experimental questions was then presented. Participants listed their partnerÕs names and rated how difficult it was to learn the words (1, very easy; 7, very difficult), how difficult it was for their partner to learn the words (same scale), how hard they tried to learn the words (1, I didnÕt try very hard; 7, I tried very hard), the extent to which they considered their partnersÕ knowledge when they assigned categories (1, not at all; 7, a lot), and their typing speed (1, very slow; 7, very fast). Finally, participants were thanked and debriefed. Task. The learning task included 20 words from each of six knowledge categories. These categories were selected in a pilot study. In that study, 35 undergraduates (19 male and 16 female) rated (on 5-point scales) how much they knew, and how much they thought the average male and female University of Illinois undergraduate would know, about several different categories. Participants expected women to know more than men about soap operas (g2 ¼ :92),2 cosmetics (.92), celebrities (.71), cooking (.65), and clothing (.50), and they expected men to know more than women about cars (g2 ¼ .87), sports trivia (.86), and computers (.67). A smaller gender difference (favoring men) was found for alcoholic beverages (.34), and no significant gender difference was found for geography (p > :17). The two male and female categories with the largest effect sizes were selected, along with geography and US history3 as the neutral categories. The authors generated items (of varying difficulty) for each category by examining relevant websites. Brief descriptions of each category were provided to partici2 2 g is a calculation for t tests that is analogous to r2 in correlations and regressions. This number can be interpreted in exactly the same way as r2 . 3 US History was chosen as the second neutral category based on data from Hollingshead (1998b) In that study, similar questions were asked about knowledge relative to the average male and female undergraduate at the University of Illinois across different categories. No significant differences were obtained for US History.
pants when they rated their own knowledge, and again when they made category assignments. See Table 1 for category descriptions and specific items.
Results Manipulation check One question on the post-experimental questionnaire asked participants to list the names of their partners. All 52 participants remembered their partnersÕ names correctly, suggesting that gender was salient to them. Total recall The results showed that participants divided categories evenly between partners. With one exception (a person who assigned four categories to himself), participants assigned three categories to themselves, and three to their partners (M ¼ 3:01, 2.99, respectively). On average, participants recalled 27.61 items.4 A twoway analysis of variance was conducted on the number of categories participants assigned to their partners, and then again on their total recall, with participant gender and partner gender (same or different as the participant) as between-participant factors. There were no significant main or interaction effects on either dependent measure. Hypothesis testing Hypothesis 1. The relative knowledge hypothesis. Men were expected to rate themselves as more knowledgeable than women for male categories, and women were expected to rate themselves as more knowledgeable than men for female categories. This hypothesis was tested by examining participantsÕ ratings of their own expertise relative to that of the average University of Illinois male (male target) or female undergraduate (female target). A 2 2 3 repeated measures analysis of variance was conducted with participant gender as the between-participant factor and target gender and category type (male, female, or neutral) as the repeated measures factors. See Table 2 for the results. The only significant main effect was for category type, F ð2; 100Þ ¼ 12:14, p < :0001, MSE ¼ 2.12. Participants rated themselves as more knowledgeable for neutral
4 The recall coding was done entirely by computer. We used two methods: (1) counting letters that matched in the correct location (e.g., ‘‘scottee pippen’’ is just one letter different from ‘‘scottie pippen’’), and (2) counting the number of letters that matched regardless of location (e.g., ‘‘ttcsoei pppnei’’ contains all the letters of ‘‘scottie pippen’’). Each method produced a ‘‘quality of match’’ index (percentage of correct letters), and the higher index was used. Words with an index score of 66% or higher were counted as correct.
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categories than for female categories, F ð1; 50Þ ¼ 27:96, p < :0001, MSE ¼ 7.26. A similar tendency was apparent, but not significant, for the neutral and male categories, F ð1; 50Þ ¼ 3:39, p < :08, MSE ¼ 9.01. The two-way interaction between participant gender and category type was significant, F ð2; 100Þ ¼ 56:31, Table 1 Memory task: Category labels and items Car and driver: Parts, makes, and models of cars
Sports: Professional sports teams and superstars
Transmission Rims Ignition Radiator Alignment Saab Coupe Clutch Rollbar 5 series Boxster OHC Tailpipe Flywheel Evaporator Differential Tachometer Spoiler Octane Manifold
Utah Jazz Darryl Strawberry Tiger Woods Vince Carter Detroit Redwings Cynthia Cooper Green Bay Packers Elton Brand Mario Lemieux Picabo Street Serena Williams Chicago Fire Scottie Pippen Andre Agassi Florida Marlins Ken Griffey Jr. St. Louis Rams Ryne Sandberg Mike Tyson Jackie Joyner-Kersee
Looking good: Cosmetics and companies that produce them Max Factor Blush Moisturizer Clinique Lip liner Collagen Top coat Almay Tweezers Maybelline Avon Eye shadow Toner Alpha Hydroxy Revlon Acetone Cover Girl Lancome Mascara Facial
Soaps: Soap operas and characters Sunset Beach Erica Kane Young and Restless Guiding Light Mac Scorpio Days of Our Lives Bo Buchanan Santa Barbara As the World Turns One Life to Live Guiding Light Lucky Spencer All My Children Another World Bold and Beautiful Days of Our Lives General Hospital One Life to Live Port Charles Passions
World geography: World cities, countries, and bodies of water Sweden Jerusalem Indian Ocean Canada Brazil Maine Lake Michigan Bali
US history: People, places, and events in US history War of 1812 FDR Benjamin Franklin Frederick Douglass Civil War John F. Kennedy Revolutionary War Susan B. Anthony
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Table 1 (continued) World geography: World cities, countries, and bodies of water
US history: People, places, and events in US history
Danube River New Zealand Puget Sound Honduras Mozambique Saskatchewan North Sea Malaysia Mediterranean Sea China Rome Greenland
Louisiana Purchase John Adams Watergate Philadelphia Antietam Alamo Sojourner Truth Boston Tea Party The Cold War Harriet Tubman Westward Expansion Henry Ford
Table 2 Mean ratings of participantsÕ own knowledge relative to the average male and female undergraduate Participant gender
Knowledge category
Average male undergraduate
Average female undergraduate
Male
Male Female Neutral Male Female Neutral
3.68 2.20 4.12 2.02 5.15 3.39
5.04 1.12 4.08 3.54 3.39 3.80
Female
(1.34) (1.10) (1.17) (.89) (1.73) (1.06)
(1.54)a (.26)a (.92) (1.06)a (1.06)a (.93)
Note. N ¼ 52. Values ranged from 1 to 7. 1, I know much less about this topic (than target); 4, I know about the same about this topic; 7, I know much more about this topic (than target). Standard deviations are in parentheses. a Row means are significantly different at p < :001.
p < :0001, MSE ¼ 2.12. Men rated their knowledge higher than did women for male categories, F ð1; 50Þ ¼ 23:11, p < :0001, MSE ¼ 1.40. Women rated their knowledge higher than did men for female categories, F ð1; 50Þ ¼ 114:90, p < :0001, MSE ¼ 0.67. ParticipantsÕ knowledge ratings did not differ by gender for the neutral categories. The two-way interaction between target gender and category type was also significant, F ð2; 100Þ ¼ 154:97, p < :0001, MSE ¼ .34. For male categories, participants rated themselves as relatively more knowledgeable when they compared their knowledge to a female target than to a male target, F ð1; 51Þ ¼ 285:45, p < :0001, MSE ¼ 0.19. The opposite pattern was obtained for female categories, F ð1; 51Þ ¼ 84:42, p < :0001, MSE ¼ 0.53. This result suggests that both male and female participants shared similar gender stereotypes. ParticipantsÕ ratings did not differ significantly by target gender for neutral categories. Finally, the three-way interaction was also significant, indicating that men and women rated their knowledge relative to a male and to a female target differently across categories, F ð2; 100Þ ¼ 3:83, p < :03, MSE ¼ .34. Male participants rated themselves as more knowledgeable than the average female for male
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categories. Similarly, women rated themselves more knowledgeable than the average male for female categories. These findings provide further support for Hypothesis 1. Hypothesis 2. The category assignment hypothesis. Participants with opposite-sex partners were expected to assign their partner categories consistent with gender stereotypes more often than were participants with same-sex partners. To test this hypothesis, a 2 2 3 repeated measures analysis was conducted with participant gender and partner gender as the between-participants factors and category type (male, female, or neutral) as the repeated measures factor. See Table 3 for the results. The analysis revealed a significant main effect of category type, (F ð2; 96Þ ¼ 6:58, p < :001, MSE ¼ .40), indicating that participants assigned fewer neutral than male or female categories to their partners (F ð1; 48Þ ¼ 5:61, p < :03, MSE ¼ .99 for male versus neutral categories; F ð1; 48Þ ¼ 17:49, p < :0001, MSE ¼ .99 for female versus neutral categories. M ¼ 1:08, 1.15, .75 for male, female, and neutral categories respectively). There was also a significant two-way interaction between participant gender and category type, F ð2; 96Þ ¼ 27:07, p < :0001, MSE ¼ .40, showing that men were more likely to assign female categories to their partners, F ð1; 23Þ ¼ 24:64, p < :0001, MSE ¼ .91, whereas women were more likely to assign male categories to their partners, F ð1; 25Þ ¼ 17:57, p < :001, MSE ¼ .42. Support for the hypothesis was found in a significant three-way interaction, F ð2; 96Þ ¼ 22:15, p < :0001, MSE ¼ .40. Men with female (rather than male) partners assigned more male categories to themselves and more female categories to their partners, F ð1; 23Þ ¼ 14:55, p < :001, MSE ¼ .91. In fact, every male participant with a female partner assigned the two female categories to her. In contrast, women with male (rather than female) partners assigned more female categories to themselves and more male categories to their partners, F ð1; 25Þ ¼ 25:06, p < :0001, MSE ¼ .83. All but one of the female participants with a male partner assigned the two male categories to him. Hypothesis 3. The reaction time hypothesis. Participants with opposite-sex partners were expected to assign Table 3 Mean number of categories assigned to partners by category type and experimental condition Condition
Male with male partner Male with female partner Female with male partner Female with female partner
Category type
categories more quickly than participants with same-sex partners. The computer recorded the total time participants took to assign the six categories. On average, participants spent a total of 47.56 s on category assignments. A 2 2 analysis of variance was conducted with participant gender and the partner gender as the between-participant factors. Contrary to the prediction, there were no significant differences in category assignment times. Hypothesis 4. The learning hypothesis. Participants were expected to learn and recall more stereotypical information when paired with opposite-sex than samesex partners. To test this hypothesis, items that participants recalled were categorized as stereotypical or not stereotypical. For female participants, items recalled in female categories were considered stereotypical, and items recalled in male or neutral categories were not. For male participants, items recalled in male categories were considered stereotypical, and items recalled in female or neutral categories were not. A 2 2 2 repeated measures analysis was conducted with participant gender and partner gender as the between-participant factors and category type (stereotypical or not stereotypical) as the repeated measures factor. On average, participants recalled 12.25 items that were stereotypical and 15.35 items that were not stereotypical. See Table 4 for the results. There were no significant main or two-way interaction effects. However, consistent with the hypothesis, there was a significant three-way interaction, F ð1; 48Þ ¼ 16:97, p < :0001, MSE ¼ 76.73. Overall, men with female (rather than male) partners learned more words in male categories and fewer words in female or neutral categories, F ð1; 23Þ ¼ 9:88, p < :01, MSE ¼ 192.35. In contrast, women with male (rather than female) partners learned more words in female categories and fewer words in male or neutral categories, F ð1; 25Þ ¼ 6:80, p < :02, MSE ¼ 117.70. Post-experimental questions In general, participants rated the task as moderately difficult (M ¼ 4:36), tried hard to learn as many items as they could (M ¼ 5:75), thought about what their partners might know when they assigned categories (M ¼ 4:57), and believed that their typing speed was Table 4 ParticipantsÕ mean recall by experimental condition
Male
Female
Neutral
Condition
Stereotypical
Not stereotypical
1.15 0.33 1.92 0.86
1.38 2.00 0.31 1.00
0.46 0.58 0.77 1.14
Male with male partner Male with female partner Female with male partner Female with female partner
7.38 16.25 15.77 10.07
19.92 11.33 12.23 17.42
(.80) (.49) (.28) (.66)
(.51) (.00) (.48) (.55)
(.52) (.52) (.44) (.53)
Note. N ¼ 52. Values ranged from 0 to 2. Standard deviations are in parentheses.
(8.39) (6.90) (5.36) (5.64)
(8.34) (5.61) (4.71) (8.14)
Note. N ¼ 52. Values ranged from 0 to 40. Standard deviations are in parentheses.
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moderately fast (M ¼ 4:5). All of these means were significantly different (all p’s < :05) from 4, the midpoint of the rating scale. There were no significant differences across conditions for any of the post-experimental measures.
Discussion Our findings show that in the absence of other information, people use gender stereotypes to infer differences in expertise among group members. Both male and female participants shared similar gender stereotypes about the knowledge of male and female undergraduates across domains. We also found that people behave in ways consistent with those stereotypes, particularly when gender is salient. Participants with opposite-sex partners were more likely to assign categories and learn information consistent with gender stereotypes than were participants with same-sex partners. These findings support the claim that gender stereotypes facilitate the development of convergent expectations in mixed-sex relationships. Both men and women assigned categories and learned information consistent with gender stereotypes when they believed their partner was of the opposite sex. Answers to an open-ended question about the strategies that participants used to assign categories provide additional insight into this issue. Many participants in the same-sex condition indicated that they assigned categories based primarily on their own knowledge of the categories. Participants in the mixed-sex condition also indicated that their own knowledge played a role, but many of them considered their partnerÕs knowledge as well. Several of these participants explicitly mentioned their partnerÕs gender, and most said that they made inferences about what their partner was likely to know. These responses are consistent with the claim that people use gender stereotypes to infer the knowledge of others in the absence of other information (Medin, 1988; Wegner, 1987). Our findings suggest that expectations based on gender stereotypes can be a self-fulfilling prophecy in transactive memory systems (cf. Geis, 1993; Skrypnek & Snyder, 1982). For example, if both partners in a mixedsex relationship expect the woman to know more about categories consistent with female stereotypes (e.g., cooking), then she may assume responsibility for relevant activities and eventually become the expert, regardless of whether or not she actually knew more about that category initially. As a result, transactive memory systems may perpetuate gender stereotypes in mixed-sex situations, because convergent expectations lead people to become experts in areas consistent with those stereotypes. This can be problematic if people would rather
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take responsibility for categories that are not stereotypical. All of our hypotheses but one were supported. Contrary to Hypothesis 3, participants with oppositesex partners did not take less time than participants with same-sex partners to assign categories. Participants could assign knowledge categories in any order, and we did not measure the time taken to assign each category separately. It may be that participants with opposite-sex partners took less time to assign stereotypical categories, but relatively more time to assign neutral categories. Participants generally rated their own knowledge as similar to that of a typical undergraduate of the same gender for categories consistent with their gender stereotype. And they rated themselves as less knowledgeable than a typical undergraduate of the opposite gender for categories consistent with the opposite gender stereotype. Thus, the general tendency to see oneself as ‘‘above average’’ may not be present for knowledge consistent with male or female gender stereotypes (cf. Alicke, Klotz, Breitenbecher, & Yurak, 1995; Kruger, 1999). However, we did not measure participantsÕ actual knowledge across the categories, so it was not possible to determine whether participants were accurate in their knowledge assessments. Unlike Plaks and Higgins (2000) and Vancouver et al. (1991), we found no significant differences in motivation, effort, or performance across the experimental conditions. In those studies, participants adjusted their effort on collective tasks based on the fit between task requirements and the stereotypic strengths of their partners. The collective task used in this experiment was different—it involved a division of labor and knowledge consistent with both male and female stereotypes. It is likely that participants believed a good fit existed between the stereotypic strengths of their partners and the categories assigned to them. This suggests that motivation and accountability may be other benefits of transactive memory. In transactive memory systems, group members are often assigned categories they know something about, and they have unique responsibility for the categories assigned to them. As a result, each member may believe his or her contributions are critical to the group (cf. Kerr & Kaufman-Gilliland, 1997). Our findings also show that transactive memory effects can arise without communication (cf., Hollingshead, 2000, 2001; Moreland & Myaskovsky, 2000). This experiment extended previous research by simulating how gender stereotypes might affect the division of cognitive labor in the initial stages of relationships, when people are unfamiliar with one another. The procedures we used in the experiment may have created the ‘‘ideal’’ conditions for gender stereotypes to have an effect: participants could not meet, see, or talk to one another. Future research should investigate how com-
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munication can affect and change group membersÕ expectations about one anotherÕs knowledge. It is possible that the strong effects of gender stereotypes observed in this experiment would be attenuated if communication were allowed between partners. In addition, people often have experiential knowledge about their own abilities and those of others. For example, a woman may know that she knows more about mathematics than most men based on her performance on standardized tests. Future research should also investigate whether specific knowledge about oneÕs own and othersÕ abilities can mitigate the impact of gender stereotypes. However, initial expectations of expertise based on gender stereotypes may be difficult to overcome, given that the delegation of responsibilities based on those stereotypes is so prevalent in our society. People with expertise in counter-stereotypical areas may need to display more evidence of their knowledge to be considered experts, particularly in mixed-sex groups. Future research should also investigate whether the findings from this experiment will extend to stereotypes about expertise based on age, race, occupation, and culture.
Acknowledgments This research was supported by the National Science Foundation: Knowledge and Distributed Intelligence program: IIS-9980109NSF and the University of Illinois Research Board.
References Alicke, M. D., Klotz, M. L., Breitenbecher, D. L., & Yurak, T. J. (1995). Personal contact, individuation, and the better-than-average effect. Journal of Personality and Social Psychology, 68, 804– 825. Biernat, M. (1993). Gender and height: Developmental patterns in knowledge and use of an accurate stereotype. Sex Roles, 29, 691– 713. Blair, S. L., & Lichter, D. T. (1991). Measuring the division of household labor: Gender segregation of housework among American couples. Journal of Family Issues, 12, 91–113. Clark, H. H., & Marshall, C. (1981). Definite reference and mutual knowledge. In A. Joshi, I. Sag, & B. Webber (Eds.), Elements of discourse understanding (pp. 10–63). Cambridge: Cambridge University Press. Driskell, J. E., & Mullen, B. (1990). Status, expectations, and behavior: A metaanalytic review and test of the theory. Personality and Social Psychology Bulletin, 16, 541–553. Eagly, A. H., & Steffen, V. J. (1984). Gender stereotypes stem from the distribution of women and men into social roles. Journal of Personality and Social Psychology, 46, 735–754. Eagly, A. H., Wood, W., & Diekman, A. B. (2000). Social role theory of sex differences and similarities: A current appraisal. In T. Eckes, & H. M. Trautner (Eds.), The developmental social psychology of gender (pp. 123–174). Mahwah, NJ: Erlbaum. Foddy, M., & Smithson, M. (1999). Can gender inequalities be eliminated? Social Psychology Quarterly, 62, 307–324.
Friedman, H., & Zebrowitz, L. (1992). The contribution of typical sex differences in facial maturity to sex role stereotypes. Personality and Social Psychology Bulletin, 18, 430–438. Geis, F. L. (1993). Self-fulfilling prophecies: A social psychological view of gender. In A. E. Beall, & R. J. Sternberg (Eds.), The psychology of gender (pp. 9–54). New York: Guilford. Hogg, M. A, & Turner, J. C. (1987). Intergroup behaviour, selfstereotyping and the salience of social categories. British Journal of Social Psychology, 26, 325–340. Hollingshead, A. B. (1998a). Retrieval processes in transactive memory systems. Journal of Personality and Social Psychology, 74, 659–671. Hollingshead, A. B. (1998b). Communication, learning, and retrieval in transactive memory systems. Journal of Experimental Social Psychology, 34, 423–442. Hollingshead, A. B. (1998c). Group and individual training: The impact of practice on performance. Small Group Research, 29(2), 254–280. Hollingshead, A. B. (2000). Perceptions of expertise and transactive memory in work relationships. Group Processes and Intergroup Relations, 3, 257–267. Hollingshead, A. B. (2001). Cognitive interdependence and convergent expectations in transactive memory. Journal of Personality and Social Psychology, 1080–1089. Kerr, N. L., & Kaufman-Gilliland, C. M. (1997). ‘‘. . .and besides, I probably couldnÕt have made a difference anyway’’: Justification of social dilemma defection via perceived self-inefficacy. Journal of Experimental Social Psychology, 33, 211–230. Kerr, N. L., & MacCoun, R. J. (1984). Sex composition of groups and member motivation: II. Effects of relative task ability. Basic and Applied Social Psychology, 5, 255–271. Krauss, R. M., & Fussell, S. R. (1991). Constructing shared communicative environments. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 172–200). Washington DC: American Psychological Association. Kruger, J. (1999). Lake Wobegon be gone! The ‘‘below-average effect’’ and the egocentric nature of comparative ability judgments. Journal of Personality and Social Psychology, 77, 221– 232. Liang, D. W., Moreland, R., & Argote, L. (1995). Group versus individual training and group performance: The mediating role of transactive memory. Personality and Social Psychology Bulletin, 21, 384–393. Medin, D. L. (1988). Social categorization: Structures, processes, and purposes. In R. Wyer, & T. Srull (Eds.), Advances in social cognition: Vol. 1 (pp. 119–125). Hillsdale, NJ: Erlbaum. Moreland, R. L., & Levine, J. M. (1992). The composition of small groups. In E. Lawler, B. Markovsky, C. Ridgeway, & H. Walker (Eds.), Advances in group processes: Vol. 9 (pp. 237–280). Greenwich, CT: JAI Press. Moreland, R. L., & Myaskovsky, L. (2000). Exploring the performance benefits of group training: Transactive memory or improved communication? Organizational Behavior and Human Decision Processes, 82, 117–133. Moreland, R. L., Argote, L., & Krishnan, R. (1998). Training people to work in groups. In R. S. Tindale, L. Heath, J. Edwards, E. J. Posavac, F. B. Bryant, Y. Suarez-Balcazar, E. Henderson-King, & J. Myers (Eds.), Theory and research on small groups (pp. 37–60). New York: Plenum. Plaks, J. E., & Higgins, E. T. (2000). Pragmatic use of stereotyping in teamwork: Social loafing and compensation as a function of inferred partner-situation fit. Journal of Personality and Social Psychology, 79, 962–974. Shelton, B. A. (1990). The distribution of household tasks: Does wifeÕs employment status make a difference? Journal of Family Issues, 11, 115–135.
A.B. Hollingshead, S.N. Fraidin / Journal of Experimental Social Psychology 39 (2003) 355–363 Skrypnek, B. J., & Snyder, M. (1982). On the self-perpetuating nature of stereotypes about women and men. Journal of Experimental Social Psychology, 18, 277–291. Vancouver, J. B., Rubin, B., & Kerr, N. L. (1991). Sex composition of groups and member motivation: III. Motivational losses at a feminine task. Basic and Applied Social Psychology, 12, 133–144. Wegner, D. M. (1987). Transactive memory: A contemporary analysis of the group mind. In B. Mullen, & G. R. Goethals (Eds.), Theories of group behavior (pp. 185–208). New York: Springer-Verlag. Wegner, D. M., Erber, R., & Raymond, P. (1991). Transactive memory in close relationships. Journal of Personality and Social Psychology, 61, 923–929.
363
Wittenbaum, G. M., Stasser, G., & Merry, C. J. (1996). Tacit coordination in anticipation of small group task completion. Journal of Experimental Social Psychology, 32, 129–152. Wittenbaum, G. M., Vaughan, S. I., & Stasser, G. (1998). Coordination in task-performing groups. In R. S. Tindale et al. (Eds.), Theory and research on small groups (pp. 177–204). New York: Plenum Press. Wood, W., & Karten, S. J. (1986). Sex differences in interaction style as a product of perceived difference in competence. Journal of Personality and Social Psychology, 50, 341–347. Zemore, S. E., Fiske, S. T., & Kim, H. (2000). Gender stereotypes and the dynamics of social interaction. In T. Eckes, & H. M. Trautner (Eds.), The developmental social psychology of gender (pp. 207–242). Mahwah, NJ: Erlbaum.