Stereotype Threat Essay (1000 words)

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In the essay,

1. Define stereotype threat.

2.The target of stereotype threat and the source of stereotype threat interact and are believed to result in six possible forms of stereotype threat. Explain at least four possible forms of stereotype threat being sure to include a thorough example for each.

3. Explain how the experience of stereotype threat can depend on self-perception versus group identity. Be sure to include discussion of how that experience might differ if an individual belongs to more than one group at risk for stereotype threat. Use examples to illustrate your point.

4. Explain two consequences of a stereotype threat and elaborate why these consequences can occur.

5. Explain three ways to possibly remediate stereotype threat.

For all of the above, be specific and provide examples to illustrate your points. Also be sure to use the current literature to support your response.

Readings

  • Course Text: Nelson, T. D. (Ed.). (2016). Handbook of prejudice, stereotyping, and discrimination (2nd ed.) . New York, NY: Psychology Press.
    • Chapter 1, "The Study of Stereotyping, Prejudice, and Discrimination Within Social Psychology: A Quick History of Theory and Research"
    • Chapter 4, "Stereotype Threat"
  • Article: Banaji, M. R., & Hardin, C. D. (1996). Automatic stereotyping. Psychological Science, 7(3), 136–141. Retrieved from the Walden Library using the Business Source Complete database.
  • Article: Eagly, A. H. (2009). The his and hers of prosocial behavior: An examination of the social psychology of gender. American Psychologist, 64(8), 644–658. Retrieved from the Walden Library using the PsycINFO database.
  • Article: Inzlicht, M., & Kang, S. K. (2010). Stereotype threat spillover: How coping with threats to social identity affects aggression, eating, decision making, and attention. Journal of Personality and Social Psychology, 99(3), 467-481. Retrieved from the Walden Library using the Business Source Complete database.
  • Article: Plant, E. A., Devine, P. G., Cox, W. T. L., Columb, C., Miller, S. L., Goplen, J., & Peruche, B. M. (2009). The Obama effect: Decreasing implicit prejudice and stereotyping. Journal of Experimental Social Psychology, 45(4), 961–964. Retrieved from the Walden Library using the PsycINFO database.
  • Article: Stone, J., & McWhinnie, C. (2008). Evidence that blatant versus subtle stereotype thread cues impact performance through dual processes. Journal of Experimental Social Psychology, 44(2), 445–452. Retrieved from the Walden Library using the ScienceDirect database.

Websites

Optional Resources

  • Article: Article: Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components.Journal of Personality and Social Psychology, 56(1), 5–18.
  • Book Excerpt: Devine, P. G., & Monteith, M. J. (1999). Automaticity and control in stereotyping (pp. 339–360). In S. Chaiken & Y. Trope (Eds.), Dual process theories in social psychology. New York, NY: Guilford Press.


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PSYCHOLOGICAL SCIENCE Research Article AUTOMATIC STEREOTYPING Mahzarin R. Banaji' and Curtis D. Hardin^ 'Yale University and ^University of California, Los Angeles Abstract—Two experiments tested a form of automatic stereotyping. Subjects saw primes related to gender (e.g., mother, father, nurse, doctorj or neutral with respect to gender (e.g., parent, student, ^p^Kon) followed by target pronouns (stimulus onset asynchrony = 3(X) ms) that were gender related (e.g.. she, he) or neutral (it, me) or followed by nonpronourts (do, all; Experiment 2 only). In Experiment I, subjects judged whether each pronoun was male or female. Automatic gender beliefs (stereotypes) were observed in faster responses to pronouns consistent than inconsistent with the gender component of the prime regardless of subjects' awareness of the prime-target relation, and independently of subjects' explicit beliefs about gender stereotypes and language reform. In Experiment 2, automatic stereotyping was obtained even though a genderirrelevant judgment task (pronouninot pronoun) was used. Together, these experiments demonstrate that gender information imparted by words can automatically infiuence judgment, although the strength of such effects may be moderated hy judgment task and prime type. Based on recent theory and research on the role of unconscious processes in beliefs about social groups (Banaji & Greenwald, 1994; Bargh, 1994; Greenwald & Banaji, 1995), we report two experiments that provide stricter tests than previously conducted of a form of automatic stereotyping. Several recent experiments bave demonstrated tbat stereotyping can occur implicitly, without subjects" conscious awareness of tbe source or use of stereotypic information in judgment (Banaji & Greenwald, 1995; Banaji, Hardin, & Rothman, 1993; Devine, 1989). In this article, we focus on a particular brand of stereotyping than can occur even wben the perceiver retains awareness of the source of influence on judgment, but is unable to readiiy control the stereotypic response. Stereotyping, like other cognitive processes, consists of both automatic and controlled components, and the particular form of automaticity that is involved (e.g., awareness, intentionality, efficiency, and controllability) has been of recent interest (see Bargh, 1994). In the present experiments, we demonstrate that gender, as lexically coded in English, can operate automatically in judgment, even when the primary (denotative) meaning is not about gender.' Address correspondence to Mahzarin Banaji, Department of Psychology, Yale Umversity, P.O. Box 208205, New Haven, CT 065208205, e-mail: mbanaji@minerva.cis.yale.edu, or Curtis Hardin, Department of Psychology, UCLA, 1282A Franz Hall, Box 951563, Los Angeles, CA 90024-1563, e-maih hardin@psych,ucla.edu. All materials may be obtained from the authors. 1. These demonstrations, although showing evidence for the automatic use of gender information, should not be taken to imply that seemingly automatic responses can never be controlled. The effects of automatically activated information are controllable under theoretically specified conditions (Bargh, 1994; Blair & Banaji, 1995). :nirht © 1996 .American Psycholo^cal Society The semantic priming procedure is commonly used to examine automatic information processing and, in particular, to reveal the strength of association between two concepts that exists independently of conscious thought. Developed more than 20 years ago, this procedure has led to important discoveries about attention, signal processing, and semantic memory (Meyer & Schevaneveldt, 1971; Neely, 1977; Posner & Snyder, 1975). The first of these tests showed the now well-known effect that response latency to a target word is facilitated to the extent to which a prime word that appears prior to the target word is semantically related to it. In addition, the technique has recently been successfully adapted to demonstrate the operation of automatically activated attitudes or evaluations (Bargh, Chaiken, Govender, & Pratto, 1992; Fazio, Sanbonmatsu, Powell, & Kardes, 1986; Perdue & Gurtman, 1990). Our primary interest lies in beliefs, and for the present research , we adapted the semantic priming procedure to provide a strict test of the extent to which beliefs about gender (i.e., gender stereotypes) operate automatically. Two words were presented in close succession, and the relationship between them was captured by reaction time (RT) to judge the second (target) word. In both experiments, the central empirical question of interest was, what is the influence of the gender code of a prime on speeded judgments of gender-consistent or genderinconsistent targets? Faster judgments on targets that follow gender-congruent primes than on targets that follow genderincongruent primes (i.e., gender-based priming) are taken as evidence for the automatic use of gender stereotypes.^ We also examine related questions, such as (a) the relationship between automatic stereotyping and traditionally used explicit stereotyping measures, (b) the role of awareness of gender as a potential source of influence on performance, (c) the gender relevance of the judgment task, and (d) the gender strength of the primes. Although variations of the semantic priming procedure have been used in previous research on stereotypes, the experimental procedures of these studies did not adhere to conventional standards for revealing automatic infonnation use,^ For example, Dovidio, Evans, and Tyler (1986) presented a prime (black or white) followed by a target (intelligent or lazy) and asked subjects if the target "couid ever be true" of the prime category. They found that white subjects were reliably faster to respond to stereotype-related traits than stereotype-unrelated traits following the primes white and black. Such experiments 2. The term stereotype has been a construct of changing meaning in social psychology, and our use of it is in keeping with recent definitiotis that reduce it to refer to beliefs about the attributes of social groups (Ashmore & Del Boca, 1981; Greenwald & Banaji, 1995). 3. In experiments in which the currently specified conditions of automaticity were met, the findings addressed the role of automatic evaluation rather than automatic belief (Gaertner & McLaughlin, 1983; Perdue & Gurtman, 1990, Experiment 2). VOL. 7, NO. 3, MAY 19% PSYCHOLOGICAL SCIENCE Mahzarin R, Banaji and Curtis D. Hardin were critical in setting the stage for the present study, but did not strictly test automatic stereotyping. Most notably, the time between the onset of the prime and target (stimulus onset asynchrony, or SO A) in the previous studies was long enough to allow strategic processing, casting doubt about the automaticity of the process being measured. In the present experiments, we used a 300-ms SOA, a condition known to capture relatively automatic processes (Neeiy, 1977, 1991). Further, Dovidio et al. (1986) required subjects to deliberately link the prime and target by asking whether the target "could ever be trtie"' of the prime category, and Neely (1977) demonstrated that such explicit expectations do affect RT under long SOAs such as those used by Dovidio et al. (S986). Although these judgment tasks demonstrate important differences in judgment latencies for stereotyped traits following the prime black or white, these tasks do not index automatic processes that may occur outside conscious deliberation of prime-target relationships. In the present experiments, we used judgment tasks that required no attention to the relationship between prime and target. Indeed, subjects were instructed to ignore the prime word and classify the target word as a male or female pronoun (Experiment 1) or a pronoun or not a pronoun (Experiment 2). In addition, the experiments we report differ from previous research in the number and type of stimuli that were used. Instead of the repeated presentation of two-category labels as primes (black or white, young or old), we used 150 primes signifying gender in a variety of ways, including those associated to gender by definition (e.g., mother, father, waiter, waitress) or by normative base rates (e.g., doctor, nurse, mechanic, secretary), or neutral with respect to gender (e.g., humanity, citizen, people, cousin). The larger set of primes more fully represents the social category, allows use of primes other than category labels alone, and permits a comparison of the strength of primes that denote gender and of primes that connote gender. Primes also included so-called generic masculine terms (e.g., mankind) to allow a test of whether such words automatically connote maleness or perform the more inclusive function that critics of nonsexist language assert is the case. In the choice of target words, we departed from the almost exclusive reliance of past research on trait adjectives. In both experiments, we used pronouns because they inescapably mark gender (e.g., she, he). However, the judgment task itself differed across the two experiments in whether the decision focused on gender (male or female; Experiment 1) or grammatical form (pronoun or not pronoun; Experiment 2). To date, no studies of stereotyping have used a task that does not focus attention on the category of interest (e.g., gender, race). A finding that automatic stereotyping occurs even when a genderirrelevant task is used would attest to the potency of automatic gender stereotypes. nurse-he). In addition, measures of behefs about explicit gender stereotypes, language reform, and the influence of gender in everyday life were included to test the relationship between automatic stereotyping and more traditional explicit measures of gender stereotyping. Method Subjects Sixty-eight subjects (32 female, 36 male) from the introductory psychology pool at Yale University participated in partial fulfillment of a course requirement. Materials and apparatus The experimental task was administered on IBM-PS2 microcomputers running Micro-Experimental Laboratory software (Schneider, 1990). Subjects entered judgments on protruding keys, marked "M" and " F , " affixed to the/and j keys. Key position was reversed for half the subjects. Two hundred primes were divided evenly among four categories; male related, female related, neutral with respect to gender, and nonword letter string (ZZZZZ). Within each of the first three prime categories, words were chosen to appear virtually equally from two subcategories. The first subcategory contained words associated to gender by normative base rates. These words were chosen on the basis of 1990 census data indicating occupations that were heavily skewed (over 90%) toward the participation of either females (e.g., nurse, secretary) or males (e.g., doctor, mechanic) or that had equal participation (e.g., reporter, postal clerk). In addition, several other words having strong stereotypical associations to one gender or the other were included (e.g., feminist, god). The second subcategory contained words associated to gender by definition, that is, words that expressly refer to gender (e,g,, woman, man), kinship terms (e.g., mother, father), and titles (e.g., mr, mrs, king, queen). Within this subcategory, words containing male morphemes (e.g., salesman), female morphemes (e.g., salesgirl), or neutral morphemes (e.g., chairperson) were also included. Targets were the six most common pronouns in English, half male {he, him, his) and half female (she. her, her,s). Three measures were designed to assess exphcit beliefs regarding gender stereotypes, language reform, and the influence of gender in peoples' lives.'' Design and procedure For each trial, events occurred in the following order: First, an orientation symbol (H-) appeared for 500 ms. Then the prime word appeared for 200 ms, followed by a blank screen for 1(X) ms. Finally, the target pronoun appeared and remained on the screen until a response was entered. Subjects made 432 judgEXPERIMENT 1 ments (not including practice and buffer trials) divided equally Experiment 1 tested whether gender information in words is among the eight prime-target categories (prime; male, female. automatically used in judgment as assessed by faster response times when the genders of the prime and target words match 4. For a description of these measures, see Hardin and Banaji (in (e.g., doctor-he, nurse-she) than mismatch (e.g., doctor-she. press). VOL. 7, NO. 3, MAY 19% 137 PSYCHOLOGICAL SCIENCE Automatic Stereotyping 2.73-. 533b ion Time (SUI) neutral, nonword; target: male pronoun, female pronoun) within each of three blocks of trials that were counterbalanced across subjects. Prime and target stimuli were paired randomly for each subject. The design was a 4 (prime gender: female, male, neutral, nonword) x 2 (target gender: female, male) x 2 (subject gender: female, male) mixed factorial, with subject gender the betweensubjects factor. Subjects judged each pronoun as either male or female. They were instructed to ignore the primes and judge the targets as quickly and accurately as possible. Subjects then completed the three explicit measures of gender beliefs. Finally, they were probed for their awareness of the hypotheses and debriefed. nI1 525b ^ H 1 1 ^H 2.71- a 492a j 511b 503a ^ •4943 X Target Gender f1 1 JJ 1 4B7a| q 2.67- u M lie —I— Female Definition Male • MALE n FEMALE Female Normative Base Rate Prime Type Results and Discussion Reported results are based on correct judgments, excluding responses that were extreme outliers. Consistent with other studies employing this procedure, the error rate was low (1,117 of 29,502 judgments, or 3.8%). RTs greater than 3 SD above the mean (> 1,300 ms) were identified as outliers and excluded (208 trials, or 0.7%). In sum, 95.6% (28,193 judgments) were retained in the reported analyses. The pattern of results is unchanged when these data are included. To achieve a better approximation to the normal distribution, analyses were performed on a log transformation of the raw RT latencies. Thirtyseven of 68 subjects were aware of the gender relationship between primes and targets. However, consistent with the assumption that this procedure reflects relatively automatic processing, the pattern of results was identical for both aware and unaware subjects, all i^s < 1. As shown in Figure 1, the predicted gender priming effect was obtained, indicating that judgment was faster when target gender matched than mismatched prime gender. The omnibus Prime Gender (female, male, neutral, nonword) x Target Gender (female, male) x Subject Gender (female, male) three-way analysis of variance yielded the predicted Prime Gender x Target Gender interaction, F(3, 198) = 12.15, p < .0001. The specific Prime Gender x Target Gender interaction (excluding the Fig. 2. Mean reaction time to judge words as male or female as a function of prime type, prime gender, and target gender (Experiment 1, n = 68). Bars with shared subscripts are not significantly different from each other (p > .05). neutral conditions) was also reliable, F(l, 66) = 117.56, p < .0001. Subjects were faster to judge male pronouns after male than female primes,/(67) = 11.59, p = .0001, but faster to judge female pronouns after female than male primes, f(67) = 6.90, p = .0001. In addition, subjects were faster to respond to targets preceded by male (M = 2.702) than female primes (M = 2.708), F(l, 66) = 7.52, p < .01. No other reliable main effects or interactions were obtained as a function of either subject gender or target gender (Fs < 1). The automatic gender priming effect was obtained for primes related to gender both by definition (e.g., mother, father, man. woman), F{1, 67) = 103.97, p < .0001, and by normative base rate, F{\, 67) = 18.61, p < .0001. However, as shown in Figure 2, the gender priming effect was significantly larger for primes related to gender by definition, as revealed by the three-way Prime Type (definition, normative base rate) x Prime Gender (female, male) x Target Gender (female, male) interaction, F(l, 67) = J3.67, p < .0005. Generic masculine terms contributed to the automatic gender priming effect. After primes containing the morpheme man (e.g., fireman, mankind, human, ma«), judgments were faster 2.73for male pronouns (M = 2.687) than female pronouns (M = 627d 2.709), /(67) = 4.06, p < .0001. The relationship also held under 513c the most conservative analysis, in which terms that are somei 2.71times used to refer only to men (e.g., man, fireman) were exTarget Gender cluded. Primes considered to be generic masculine terms in • MALE virtually ali contexts (e.g., mankind, layman) produced faster '' 492a 1 4B9a • FEMALE judgments for male pronouns {M = 2.689) than female pro1 2.69- 49Oa nouns (M = 2.712), /(67) = 2.18, p < .05. 5 Finally, we examined terms that differed in no way except for the gender of their suffix (e.g., chairman, chairwoman, 2.67chairperson). As expected, the gender of the suffix did influMale Neutral Nonword ence response latencies as indicated by a Prime Gender (male, Prime Gender female, neutral) x Target Gender (male, female) interaction, F(2, 112) = 11.59, p < .0001. Judgments were faster for male Fig. 1. Mean reaction time to judge words as male or female as pronouns after words with male (M = 2.693) than femeile (M = a function of prime gender and target gender (Experiment 1, n 2.722) suffixes, /(67) = 3.29, p < .01, whereas judgments were = 68). Bars with shared subscripts are not significantly differ- marginally faster for female pronouns after primes with female ent from each other (p > .05). (Af = 2.694) than male (M = 2.716) suffixes, r(67) = 1.81, p = I In I 138 l l1 M VOL. 7, NO. 3, MAY 1996 PSYCHOLOGICAL SCIENCE Mahzarin R, Banaji and Curtis D. Hardin .07. In addition, judgments were faster when primes with female suffixes were followed by female pronouns (M = 2.694) than male pronouns (M = 2.722), r(67) = 2.82, p < .01. Interestingly, neutral -person suffixes after the identical words did not produce equivalent responses to female and male pronouns. Instead, after these primes, subjects were still faster to judge male targets (M = 2.704) than female targets (M = 2.722), t{61) = 2.64, p < .05.' Relations between exphcit beliefs and automatic gender stereotyping were examined by computing a correlation between each of the three explicit belief measures and a gender priming score, which was calculated by subtracting log RT for gendercongruent trials from log RT for gender-incongruent trials. None of the three correlations of explicit measures with the priming score was significant (language reform: r[67] = - .003, p = .978; role of gender in everyday life: r[68] = - .050, p = .686; explicit gender stereotypes; r[66] = .037, p = .767). This result is consistent with other research demonstrating a lack of correspondence between explicit and implicit measures of stereotyping (Banaji & Greenwald, 1995). In sum. Experiment 1 provided evidence for automatic gender stereotyping using a broad range of primes and using time and task parameters that reflect automatic information use. The effect occurred regardless of subjects' awareness of the primetarget relation, and independently of explicit beliefs about gender stereotypes. The effect was also obtained for both primes related to gender by definition and primes related to gender by normative base rate, although not surprisingly the effect was larger for primes related to gender by definition. EXPERIMENT 2 Participants in Experiment 1 judged whether each target was male or female, thereby focusing attention on the gender of the target. This form of the judgment task is quite conventional. For example, when theoretical interest has focused on the semantic link between prime and target, the commonly used judgment task is a lexical decision (word/nonword; Neely, 1991). Likewise, when the interest is in the evaluative component of the prime and target, the task is typically a good/bad judgment (Bargh et al., 1992; Fazio et al., 1986; Greenwald, Klinger, & Liu, 1989; Perdue & Gurtman, 1990). However, stronger evidence for automaticity may be obtained if the effect is observed when the judgment task is unrelated to the dimension of the prime-target relationship. For example, Bargh, Chaiken, Raymond, and Hymes (in press) showed that the automatic evaluative effect is obtained even when the judgment involves mere pronunciation, a task unrelated to evaluation. Hence, in Experiment 2, the judgment task was a pronoun/not pronoun decision, unrelated to gender. Method Subjects Sixty subjects (29 female, 31 male) from Yale University participated in exchange for $5 or in partial fulfillment of a course requirement. Materials, design, and procedure For this experiment, 120 of the primes used in Experiment 1, representing male (40 primes), female (40 primes), and neutral (40 primes) categories, were selected. Of the four target pronouns used, she and he allowed the comparisons of primary interest. The pronoun it was included because it is the most frequently occurring gender-neutral pronoun, and me was included for exploratory purposes to examine a possible relationship between prime gender and subject gender (cf. Markus, 1977). The four nonpronouns (is, do, as, all) were chosen to match the critical targets in length, number of syllables, and frequency (Ku^era & Francis, 1967). In all, each subject made 720 experimental judgments divided into five blocks of trials, counterbalanced across subjects. For 480 of these judgments, the correct response to the question "Is this a pronoun?" was "yes," and for 240, the correct answer was "no." Each prime was paired with (a) both critical "yes"-response targets (i.e., she, he), (b) both noncritical "yes"-response targets (i.e., it, me), and (c) two of the four "no"-response targets (i.e., do, all, is, as). For each subject within each block, prime and target items were randomly associated. After completing the priming task, subjects were probed for awareness regarding the hypotheses and debriefed. Results and Discussion As before, resuits are based on a log transformation of the raw RT latencies for correct judgments, excluding outliers (RT > 1,300 ms or > 3 SD above the mean; 1.4% of the total). Also as in Experiment 1, the error rate was low (370 of 28,800 "yes" judgments, or 1.3%; 928 of 43,200 total judgments, or 2.1%); 97.7% (28,134) of the "yes" judgments were retained in the reported analyses. Seven of the 60 subjects revealed some knowledge of a possible gender relation between the prime and target words. Again, however, the pattern of results was identical for both aware and unaware subjects, but no statistical significance tests were conducted because of the small number of aware subjects. As Figure 3 shows, the predicted gender priming effect was obtained, indicating that judgment was faster when target gender matched than mismatched prime gender. The omnibus 3 (prime, gender: male, female, neutral) x 4 (target gender: she, he, it, me) x 2 (subject gender: male, female) analysis of variance yielded the predicted Prime Gender x Target Gender interaction, F(6, 336) = 3.66, p < .01. In addition, a Subject Gender x Target Gender interaction indicated that subjects were faster to respond to targets that matched rather than mismatched their own gender, F(3, 168) = 3.58, p < .02.^ No difference in responding to the male and female targets was observed for dubiously neutral primes such as layman and man- 6. A similar fmding was reported by Zarate and Smith (1990). In addition, a main effect of prime gender indicated that subjects" responses were fastest foUowing male primes and slowest following female primes, f(2, il2) = 3.89, p < .03. A main effect of target gender 5. However, we found (Hardin & Banaji, in press) no bias favoring indicated that subjects were slower to respond to the target it than to she, he, and me, F(3, 168) = 154.33, p < .0001. males in a similar experiment usingfirstnames as targets. VOL. 7, NO. 3, MAY 1996 139 PSYCHOLOGICAL SCIENCE Automatic Stereotyping 2.71 n 2.69- 490b 4S5a.b 491b 4S5a.b4eSa. Target Gender • HE OS 2.67- G SHE o 2.65 Female Neutrai Prime Gender Fig. 3. Mean reaction time to judge words as pronouns or not pronouns as a function of prime gender and target gender (Experiment 2, n = 58). Bars with shared subscripts are not significantly different from each other {p > .05). kind. There was also no main effect of subject's sex, F(l, 56) = 1.49. The more specific interaction of prime gender by target gender (excluding neutral primes) was also significant, indicating that subjects were faster to judge targets in gender-congruent prime-target pairs than in gender-incongruent pairs, F(l, 56) = 4.63, p < .04. Again, the Subject Gender x Target Gender interaction was reliable, indicating that subjects were faster to respond to the target pronouns that were consistent than inconsistent with their own social category, F(l, 56) = 17.95, p < .0001. However, these 2 two-way interactions were qualified by a three-way Subject Gender x Prime Gender x Target Gender interaction, F(l, 56) = 4.15, p < .05. For purposes of clarity, we describe results separately for primes related to gender by definition and primes related to gender by normative base rates. Analyses of primes related to gender by definition (e.g., mother, father, waitress, waiter) yielded the gender priming effect unmoderated by subject gender (Fig, 4, left panel). RT was smaller when prime gender and target gender were congruent than incongruent, as indicated by a reliable two-way interaction, F(l, 56) = 8.70, p < .005. Subjects were faster to identify he when primes were male than fettiale, ?(59) = 2.44, p < .02, but faster to identify she than he when the primes were female, ^59) = 2.53, p < .02. In addition, subjects were faster to identify targets that matched their own gender, as indicated by the reliable interaction between subject gender and target gender, F(l, 56) = 7.43, p < .01. Analyses of primes related to gender by normative base rates (e.g., secretary, mechanic, doctor, nurse) suggest limitations to the generality of automatic gender priming under conditions in which the task does not require subjects to focus on the dimension of gender (see Fig. 4, right panel). Although reliable effects were obtained for the Subject Gender x Target Gender interaction, F(l, 56) = 14.02, p < .0001, and there was a main effect of prime gender, F(l, 56) = 6.49, p - .01, both were qualified by a marginal three-way Subject Gender x Prime Gender x 140 dTarget Gender interaction, F(l, 56) = 3.49, p < .07. Male subjects were faster to identify he than she regardless of prime gender, F(l, 29) = 7.44, p = .01, and faster to identify targets after male than female primes, F(l, 29) = 9.21, p < .01. In contrast, female subjects were faster to identify she than he after female primes, f(28) = 2.81, p < .01, and faster to identify he after male than female primes, r(28) = 2.18, p < .05. Females were also faster, in general, to identify she than he, F(l, 27) = 6.70, p < .05. GENERAL DISCUSSION These two experiments provide the first strict tests of a form of automatic stereotyping. Using a large number and wide range of stimuli, we demonstrated that judgments of targets that follow gender-congruent primes are made faster than judgments of targets that follow gender-incongruent primes. This effect was obtained despite subjects' deliberate attempt to ignore the prime, regardless of whether subjects were aware or unaware of the gender relation of prime-target pairings, independently of subjects' explicit beliefs about gender, regardless of whether the judgment was gender relevant or irrelevant, and on both words that are gender related by definition and words that are gender related by normative base rates. The results, however, also show two moderators of the gender priming effect. First, the effect was stronger when the judgment was gender relevant (e.g., male or female pronoun?) than gender irrelevant (e.g., pronoun or not pronoun?). Further research will investigate whether this difference also obtains on other forms of gender-irrelevant tasks, such as pronunciation. Second, the gender priming effect was stronger for primes related to gender by definition (e.g., mother, father) than by normative base rate (e.g., doctor, nurse). In Experiment 1, for example, the effect size for definition primes was large (Cohen's d = .78), whereas for normative-base-rate primes, the effect size was moderate (d - .47). This difference refiects the differential strength of the two types of primes in evoking gender. Words that are exclusively reserved to denote gender will produce stronger priming than words that connote gender (for a rephcation with names as targets, see Hardin & Banaji, in press). 2.69rarget G«nder • HE • SHE 2.67- 2.6S Male Female Male Definition Female Normative Base Rate Prime Type Fig. 4. Mean reaction time to judge words as pronouns or not pronouns as a function of prime type, prime gender, and target gender (Experiment 2, n = 58). Bars with shared subscripts are not significantly different from each other (p > .05). VOL. 7, NO. 3, MAY 1996 PSYCHOLOGICAL SCIENCE Mahzarin R. Banaji and Curtis D. Hardin Sapir (1963) commented that one of the important functions of language is to repeatedly declare to society the psychological status of its members. These experiments show the automatic effects of such repeated linguistic declarations, in particular, those that convey the social psychological positions that are occupied through gender. A noteworthy aspect of the gender priming effect observed in Experiment 1 is that the effect can obtain not only when the primes denote gender (man, woman), but also when they more tacitly connote gender (mechanic, nurse). That gender-signifying infonnation permeates thought sufficiently to infiuence judgment points to the fundamental nature of gender as a category in verbally communicated thought. This article is not the place to catalogue the various ways in which gender is coded in most languages, but we note that EngUsh stands out as one language that has received a quite extensive analysis of what might be called the "genitalia of language" (Baron, 1986): gender-signifying words, gender-specific pronouns, and the covert presence of gender in grammatical structure. We expect that such automatic gender priming effects are best observed in languages that provide extensive and deep coding of gender in grammar and semantics (Hardin & Banaji, 1993). Further evidence for the generality of automatic gender-stereotyping effects might be obtained by demonstrating such effects independently of language (i.e., through the use of nonverbal, pictoral stimuli that denote and connote gender). Such effects would be especially important in reveahng the degree to which the present effect is a function of gendered language per se or gender stereotypes more generally. Although research on beliefs and attitudes has usually depended on direct, verbal measures of stereotypes (see Greenwald & Banaji, 1995), response latencies may provide a more indirect measure of stereotype strength. A case for RT as a measure of attitude or evaluation has already been effectively made (see Bargh et al., 1992; Fazio et ai.. 1986; Perdue & Gurtman, 1990), and other investigators have used RT as an indicator of stereotypes (Dovidio et al., 1986). However, these experiments, in conjunction with others (Blair & Banaji, 1995; Hardin & Banaji, in press), demonstrate the operation of beliefs under conditions that meet currently accepted standards for measuring automatic processes. Such measures are likely to increasingly complement the more traditional measures of evaluation and belief, especially as their validity and feasibility are further established. Acknowledgments—This research was supported in part by Grants DBC 9120987 and SBR 9422291 from the National Science Foundation. We are grateful to Lisa Driscoll and John Beauvais for assistance with data collection; Kimberly Hinds and Irene Blair for assistance with programming; and R. Bhaskar. Irene Blair. Richard Hackman, and Eliot Smith for comments on a previous draft. REFERENCES Ashmore, D.D.. & Del Boca, F.K. (1981). Conceptua! approaches to stereotypes and stereotyping. In D.L. Hamilton (Ed.). Cognitive proeesses in stereotying and intergroup behavior (pp. t-36). Hillsdale, NJ: Eribaum. VOL. 7, NO. 3, MAY 19% Banaji, M.R., & Greenwald, A.G. (1994). Implicit stereotypes and prejudice. In M.P. Zanna & J.M. Olson (Eds.), The psychotogy of prejudice: The Ontario Symposium (Vol. 7, pp. 55-76). Hillsdale, NJ: Eribaum. Banaji, M.R.. & Greenwald, A.G. (1995). Implicit stereotyping in false fame judgments. Journal of Personality und Social Psychotogy, 68, 1« 1-198. Banaji, M.R.. 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(RECEIVED 12/8/94; ACCEPTED 3/26/95) 141 Available online at www.sciencedirect.com Journal of Experimental Social Psychology 44 (2008) 445–452 www.elsevier.com/locate/jesp Evidence that blatant versus subtle stereotype threat cues impact performance through dual processes Jeff Stone b a,* , Chad McWhinnie b a Psychology Department, University of Arizona, Tucson, AZ 95721, USA Psychology Department, McGill University, Montreal, Canada QC H3A 1B1 Received 16 August 2005; revised 10 September 2006 Available online 27 February 2007 Communicated by Spencer Abstract An experiment tested three competing hypotheses for how blatant and subtle stereotype threat cues influence the performance of female sports participants on a golf-putting task. A ‘‘predominant’’ model predicts that blatant threat cues have a more negative effect on performance than subtle threat cues, whereas an ‘‘additive’’ model predicts that both cues combine to have a greater negative effect than either threat cue alone. However, a ‘‘dual process’’ model predicts that each threat cue has an independent negative influence through separate mechanisms. To test these predictions, we varied the presence of blatant (e.g., the task frame) and subtle cues (e.g., the gender of the experimenter) for negative stereotypes about female athletes, and then measured both the number of strokes required to finish the course and accuracy on the last putt of each hole. The results supported the dual process model prediction: females required more strokes to finish the golf task when it was framed as measuring gender differences compared to racial differences in athletic ability, and females performed less accurately on the last putt of each hole in the presence of a male versus a female experimenter. The discussion focuses on how the presence of multiple stereotype threat cues can induce independent mechanisms that may have separate but simultaneously deleterious effects on performance.  2007 Elsevier Inc. All rights reserved. Keywords: Stereotype threat; Female; Athlete; Sports; Dual process The theory of stereotype threat proposes that for individual members of a stigmatized group, the salience of a negative stereotype in a performance context causes concern about confirming the validity of the negative characterization (Steele, 1997; Steele, Spencer, & Aronson, 2002). Numerous studies now show that the salience of negative stereotypes in a performance context can impair the performance of African-American students on standardized tests of verbal ability (Steele & Aronson, 1995), women on tests of math ability (Schmader & Johns, 2003; Spencer, Steele, & Quinn, 1999), and the performance of other groups (e.g., White men) on other tasks * Corresponding author. Fax: +1 520 631 9306. E-mail address: jeffs@u.arizona.edu (J. Stone). 0022-1031/$ - see front matter  2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jesp.2007.02.006 (golf-putting, see Beilock, Jellison, Rydell, McConnell, & Carr, 2006). The purpose of the current study was to examine how stereotype threat processes unfold when multiple cues for threat are present in a performance situation. Steele et al. (2002) proposed that when stigmatized targets are in a stereotype relevant situation, their assumptions about the existence and application of negative stereotypes to their group—their ‘‘theory of context’’—causes targets to become vigilant about detecting the presence of bias. To accomplish this goal, targets ‘‘evaluate a broad set of cues in the setting’’ to assess the potential for a negative characterization. Little is know, however, about how targets detect and react to the presence of multiple stereotype threat cues in a performance context. 446 J. Stone, C. McWhinnie / Journal of Experimental Social Psychology 44 (2008) 445–452 We speculate that the way multiple threat cues impact performance depends in part on the nature of the cues themselves. Some cues for threat are relatively blatant, such as when a task is explicitly framed as measuring attributes that relate to a negative ingroup stereotype (e.g., Steele & Aronson, 1995; Stone, Lynch, Sjomeling, & Darley, 1999), or when targets are directly told that their group tends to perform more poorly on the task in comparison to some other group (e.g., Spencer et al., 1999). Other cues for threat, however, present the potential for bias in a subtler manner. For example, research indicates that the performance of stigmatized targets can be adversely affected when they hold minority status in the performance context (Inzlicht & Ben-Zeev, 2000; Sekaquaptewa & Thompson, 2002), or when the task is administered by an outgroup member (e.g., Danso & Esses, 2001; Marx & Goff, 2005). This suggests that the theory of context held by targets includes not only knowledge about the content of the negative ingroup stereotypes, but also information about the conditions under which the stereotypes are likely to bias perceptions of their behavior. It is also possible that different threat cues negatively impact performance through different mechanisms. For example, the subtle nature of cues like the outgroup identity of the test administrator may cause targets to focus part of their cognitive and emotional resources on reducing uncertainty about the presence of bias. The cognitive load that results from the attention paid to subtle cues impacts working memory capacity, which then reduces performance on the task. Thus, when the threat is induced through subtle cues in the situation, performance is more likely to be mediated by the negative impact on working memory (Croizet et al., 2004; Schmader & Johns, 2003). In contrast, when negative stereotypes are blatantly tied to performance, targets do not have to expend cognitive resources assessing the potential for bias, it is clearly present. Instead, blatant cues cause targets to adopt a prevention focus orientation designed to minimize mistakes and avoid the failure that would confirm the negative stereotype (Keller & Dauenheimer, 2003; Seibt & Forster, 2004). However, their attempt to avoid failure can backfire if it causes them to adopt strategies that disrupt the effective execution of task-relevant skills. Thus, blatant cues for threat may reduce performance by inducing prevention focus processes that negatively impact their approach to the task. If blatant and subtle stereotype threat cues impact performance through their effects on separate processes, then there are at least three predictions that can be made for how the presence of both cues influence performance. One possibility is that when both cues are present in a performance context, one cue has more influence on performance than the other. Targets may perceive both cues as a source of bias, but one may be perceived as a more likely threat than the other. An obvious prediction is that blatantly framing a task as measuring a negative stereotype makes the threat more concrete, and as a result, prevention focus processes consume more cognitive and emotional resources than does the cognitive load a subtle threat cue. This ‘‘predominant cue’’ model predicts when both types of cues are present during performance, blatant cues have a greater negative impact on performance than subtle cues. A second possibility is that blatant and subtle threat cues operate together to influence task performance. The assumption in an ‘‘additive cues’’ model is that all cues are perceived as a potential source of threat and that both cognitive load and prevention focus strategies work in tandem to impact the processes that determine performance on the task. When an outgroup member frames the task in terms of a negative ingroup stereotype, targets are simultaneously overloaded by assessing the meaning of the subtle cue and motivated to avoid being negatively characterized as per the blatant cue information (Seibt & Forster, 2004). Thus, an additive cues model would predict that two threat cues have a greater negative impact on performance than when either cue is presented alone. A third possibility is that blatant and subtle threat cues operate independently of each other to influence task performance (e.g., Strack & Deutsch, 2004). Here the assumption is that each cue induces processes that influence different aspects of performance. Those aspects of performance that depend on effortful processing skills for successful execution may be more influenced by reductions in working memory, whereas those aspects of performance that require fluent, automatic execution are influenced more by prevention focus processes (Beilock et al., 2006). Whereas some tasks may depend more heavily on one set of skills than another, other tasks may require both skills for a successful performance. However, because most studies to date have focused on manipulating a single cue to measure its mediational effect on one performance measure, previous research has not addressed a ‘‘dual process’’ explanation for the effect of multiple threat cues on performance. The current study tested the three competing predictions for how multiple threat cues impact performance by using the golf-putting task from previous research on stereotype threat in sports (e.g. Stone et al., 1999). Performance on the putting task can be measured in two ways: As the total number of putts needed to complete the course, which is the standard measure of performance in golf, and it can also measure how accurate participants are as they putt the ball into the hole on their last shot (Beilock et al., 2006). Accordingly, cognitive load or prevention focus processes may influence each of these outcomes independently. For example, if blatant cues such as framing the task in terms of a negative ingroup stereotype induce a prevention focus orientation, targets should become motivated to try to avoid failure during the task. A ‘‘try not to miss’’ strategy on each putt would focus them on the micro elements of their putting stroke, but if this response disrupts the automatic and fluent elements of execution, targets might ‘‘choke’’ under the pressure. As a result, the blatant task frame would increase the number of strokes they would J. Stone, C. McWhinnie / Journal of Experimental Social Psychology 44 (2008) 445–452 need to complete the overall course (e.g., Stone et al., 1999). In contrast, if subtle cues such as the outgroup identity of the test administrator induce cognitive load, this could influence the accuracy of their final putt into the hole. After getting close to the hole on the previous putt, accuracy on the last putt takes considerable concentration, which is likely to be influenced by working memory capacity. Note that in addition to providing a task that can measure the potential independent effect of dual processes on performance, the putting task permits a test of the competing models as well. That is, if one cue is predominant, the results will reveal a main effect for the predominant cue, or if both cues add up to create more threat than either alone, then the results will show an additive effect for both cues on both performance measures. A second purpose of the proposed study was to examine the influence of negative stereotypes on the performance of female athletes. Research indicates that whereas ‘‘poor athletic ability’’ is a negative stereotype about North American White athletes (Sailes, 1996; Stone, Perry, & Darley, 1997), it is perhaps more widely held as a negative stereotype about female athletes (Biernat & Vescio, 2002; Knight & Guiliano, 2001). We believe that in the domain of sports, women have considerably more experience being negatively compared to men than they have being compared to females from other ethnic or racial groups. For example, in the United States, women’s sports received less funding and institutional support than men’s sports until Title IX legislation was passed in 1972. Whereas Title IX has significantly increased the number of girls and women who participate in organized sports, women still occupy fewer administrative, management, and training positions than men, implying that off the field, men are more qualified than women to run the show (Roper, 2002). The belief that women are less athletic than men is also conveyed in the media, as women’s sports at the high school, college and professional level receive less media attention than men’s sports at the same level (Tuggle & Owen, 1999). A third source for negative stereotypes about female athleticism is transmitted interpersonally when people participate in sports, such as when a coach admonishes a young player to ‘‘stop throwing like a girl’’ (Fredrickson & Harrison, 2005). These various sources instantiate and support the culturally held belief that females possess less athletic ability than males. Racial differences between female athletes, in comparison, do not have the same history of discourse or institutionalized segregation and discrimination, and therefore, do not carry the same burden that gender does for female athletes. It was hypothesized in the present research that blatantly framing the golf task as a measure of gender differences in athletic ability would be perceived as more threatening to White female participants than would framing the task as a measure of racial differences in athletic ability. In addition to manipulating the type of blatant cue present, the presence of a subtle threat cue was manip- 447 ulated by having either a male or female experimenter conduct the putting task. Thus, the procedure was designed to test three competing hypotheses for how multiple threat cues influence the performance of female sports participants on a task that was capable of revealing more than one mediational process. Method Participants Participants were 110 female undergraduates at the University of Arizona who participated in the study for partial course credit. All were recruited after they identified their ethnicity as ‘‘Caucasian American’’ during a mass pre-testing of the introductory psychology courses. Participants also rated their athleticism as above average but reported they played golf no more than one day per week (see Stone et al., 1999). Thus, the sample consisted of women who perceived themselves to be athletic but novice golfers. Procedure Participants completed the procedures individually. When they arrived at the laboratory, they were greeted by one of two male or two female experimenters (who were blind to the experimental hypothesis1), which served as the subtle cue manipulation. The experimenter explained that they would complete brief questionnaires and perform a sports test based on the game of golf. The athletic test was based on the golf task described in Stone et al. (1999). Participants first read a handout that described the athletic task as a standardized measure of sports aptitude. Ostensibly, performance on the test had been shown to correlate with actual performance on many of the physical and mental activities relevant to most college varsity sports, such as basketball, hockey and golf. At this point, the instructions changed course according to condition. Blatant cue manipulation Participants were randomly assigned to one of three task frame conditions. Participants in one of the two athletic ability conditions read that the test was designed to measure ‘‘personal factors correlated with natural athletic ability’’. Natural athletic ability was defined as ’’one’s natural ability to perform complex tasks that require hand-eye coordination, such as shooting, throwing, or hitting a ball or other moving object’’. It was explained that as test difficulty increased, so would the demand on their natural athletic ability or hand-eye coordination. 1 The experimenters were kept blind to the primary hypothesis by telling them that the purpose of the study was to investigate personality differences in reactions to how the task was framed. Thus, the experimenters were led to believe that they could not guess how a specific participant would react to the task frame manipulation and they were carefully trained to treat every participant in the same manner. 448 J. Stone, C. McWhinnie / Journal of Experimental Social Psychology 44 (2008) 445–452 Within the two athletic ability frame conditions, those assigned to the Gender-differences frame were told the following: ‘‘Now you are probably aware that there are gender differences in sports performance. Previous studies using this test of natural athletic ability have reported differences in the performance of men and women. So even though there may be gender differences on this test, we ask that you give 100% effort on the task so we can accurately measure your natural skills. Do you have any questions?’’ Those in the athletic ability condition that were assigned to the Racial-differences frame were told the following, ‘‘Now you are probably aware that there are racial differences in sports performance. Previous studies using this test of natural athletic ability have reported differences in the performance of Blacks and Whites. So even though there may be racial differences on this test, we ask that you give 100% effort on the task so we can accurately measure your natural skills. Do you have any questions?’’ Participants randomly assigned to the Sport psychology control condition read that the test was designed to measure ’’psychological factors correlated with general sports performance’’. The handout explained that as test difficulty increased, so would the demand on the psychological factors that correlate with general sports performance. After they read the handout, the experimenter reiterated the instructions verbally and answered questions. They were then led into an adjoining room to complete the golf-putting task. The golf-putting task Based on Stone et al. (1999), the task was designed to resemble a miniature golf course on which participants used a putter to hit a golf ball down a 3 ft · 10 ft stretch of carpet into a hole apparatus—an inclined felt mat with a hole 5 in. in diameter, a hole 4 in. in diameter, and a hole 3 in. in diameter. To complete each ‘‘course layout’’ in the test, participants were told the ball had to roll up the incline and stop in one of the holes. Participants were told they would complete eight different holes that would be created by placing 2 · 4s either on or under the carpet and by moving the hole apparatus. Once the test began, the experimenter said he or she would change the putting surface according to a pre-tested pattern of increasing difficulty. Participants were told that their goal on each course layout was to putt the ball into the smallest hole using the fewest strokes possible. In addition to the number of strokes, they were told that the hole that received the ball would be recorded, and that both strokes and the hole would be summed to yield an overall performance score for each layout. Participants were then allowed to ‘‘warm up’’ by practicing on the first course layout three times. When finished practicing, the experimenter directed participants to the wall where the diagram of each course layout was displayed. Before they played each layout, participants were instructed to examine the diagram and estimate how many strokes they would need to complete it. They were also instructed to predict which hole the ball would stop in. Participants were instructed to make their predictions on a sheet while the experimenter set up each new layout. After participants made their prediction for the first layout, the task proceeded with participants making a prediction for each new layout, putting until their ball stopped in a hole, and then making their predictions for the next layout, until all eight layouts had been finished. After the last putt, the experimenter announced that the study was complete, and provided participants with a full debriefing and course credit as compensation for their time. Results The data were initially analyzed to examine if variability due to the two different male and female experimenters influenced the results. All of the performance and selfreport data were analyzed using a 3 (Blatant Cue) · 4 (Experimenter) between-subjects analysis of variance (ANOVA). No main or interactive effects were found for the experimenter variable. Thus, we collapsed this variable to reflect the gender of the experimenter in order to test the influence of the subtle cue on performance. Unless otherwise noted, all of the data were analyzed using a 3 (Blatant Cue) · 2 (Subtle Cue) ANOVA. Achievement: strokes The number of strokes needed to complete each of the eight holes of the golf course was summed to create one overall performance score. The ANOVA revealed only a significant main effect for the Blatant Cue manipulation, F(2, 104) = 3.34, p < .04. As seen in Table 1, a planned contrast of the mean differences between each group showed that when the task was framed as a measure of gender differences in athletic ability, female participants performed significantly worse (M = 27.38, SD = 8.33) compared to when the task was linked to racial differences in athletic ability (M = 23.58, SD = 4.62) or to sports psychology (M = 25.03, SD = 5.09), F(1, 104) = 5.67, p < .02. The difference between the racial-differences task frame and the sport psychology control condition did not approach significance, F < 1. The subtle cue manipulation did not modTable 1 Average number of achieved and expected strokes required to complete the course for the blatant threat cue conditions Blatant cue Strokes Achieved Expected Gender Race Control 27.38a 25.90 23.58b 23.58 25.03b 24.15 p < .05 p < .10 Higher numbers indicate a poorer performance. Different superscripts indicate which means are significantly different from each other a p < .05. J. Stone, C. McWhinnie / Journal of Experimental Social Psychology 44 (2008) 445–452 erate the effect of blatant cue on achieved strokes, Blatant Cue · Subtle Cue interaction F < 1. This latter finding does not support the additive model of how blatant and subtle cues impact performance. The main effect for the blatant cue, however, supports both the ‘‘predominant’’ and ‘‘dual process’’ predictions. Sorting these out requires analyzing the effects of the subtle cue manipulation on achieved accuracy. 449 dicted they would be less accurate when the experimenter was male (M = 2.22) compared to female (M = 2.20). Neither the main effect nor the interaction with the blatant cue manipulation reached significance, all ps < .12. As with the achievement scores, the two sources of threat exerted independent influences on expectancies for strokes and accuracy on the overall course. Correlational analyses Achievement: accuracy The hole they stopped the ball in on the final putt was analyzed by assigning the small, medium and large holes a score of 1, 2 and 3, respectively. To create an overall measure of accuracy, the scores received on each final putt were summed and averaged across the eight course layouts. The ANOVA revealed a main effect for the Subtle Cue manipulation, F(1, 104) = 3.93, p < .05, which as seen in Table 2, revealed that on average, female participants were less accurate (i.e., stopped the ball in a larger hole) when the experimenter was male (M = 2.02) compared to when the experimenter was female (M = 1.88). Neither the main effect nor the interaction with the Blatant Cue manipulation reached significance, all ps < .12. When put together with the data on achieved strokes, the results for achieved accuracy provide support for the dual process model over the ‘‘predominant’’ model of how multiple threat cues impact performance. Performance expectancies Participants’ predictions for the number of strokes they would need to complete each hole were summed and subjected to the ANOVA. The analysis revealed only a marginal main effect for the Blatant cue manipulation, F(2, 104) = 2.26, p < .10. The data shown in Table 1 mirrored the number of strokes required to finish the course, with participants told the task measured gender differences in athletic ability making somewhat higher predictions (M = 25.90) than those told the task measured racial differences in athletic ability (M = 23.18) or sports psychology (M = 24.15). No other effects approached significance. A similar analysis of which hole participants predicted that the ball would stop in revealed only a significant main effect for the Subtle Cue manipulation, F(1, 104) = 7.22, p < .008. As shown in Table 2, female participants preTable 2 Average achieved and expected accuracy on the last putt of each course layout for the subtle threat cue conditions Subtle cue Accuracy Achieved Expected Male experimenter Female experimenter 2.05 2.23 1.91 2.02 Lower numbers indicate higher accuracy (smaller hole). Examination of the correlations within the stroke and accuracy performance measures revealed that in general, expectancies and achievement were moderately related. For example, as seen in Table 3, the correlation between expected and achieved strokes was moderate and significant, r(110) = .44, p < .0001, as was the correlation between expected and achieved accuracy, r(110) = .60, p < .0001. However, the performance measures were relatively less related to each other. For example, the correlation between achieved strokes and achieved accuracy was significant but small, r(110) = .28, p < .003, while expected strokes and expected accuracy were not related to each other, r(110) = .03, p > .72. As predicted by a dual process model, these patterns indicate that the two measures of performance were relatively independent of each other at the within subjects level. Discussion The overall results provide support for a dual process model of how multiple stereotype threat cues impact performance. When both blatant and subtle cues signal the potential for a negative ingroup stereotype to characterize the meaning of a poor performance, each source can induce relatively independent processes that impact different aspects of performance. The data suggest that blatant cues, such as framing the task as a measure of a negative ingroup stereotype, induced a prevention focus orientation whereby targets became more conservative in their approach to the task. However, their prevention strategies tended to interrupt the fluid processes that facilitate successful performance on this aspect of the task, and they performed more poorly, even when an ingroup member (i.e., a female experimenter) blatantly made the negative stereotype salient. Table 3 Bivariate correlations between the achieved and expected performance measures 1 1. 2. 3. 4. Achieved strokes Expected strokes Achieved accuracy Expected accuracy * ** *** p < .01. p < .005. p < .0001. 2 3 4 — .10 .03 — .60*** — — .44*** .28** .21* 450 J. Stone, C. McWhinnie / Journal of Experimental Social Psychology 44 (2008) 445–452 The effect of the blatant cue on performance also supports the hypothesized link between athletic ability and negative gender stereotypes about female athletes. Specifically, White female participants required more strokes to finish the course, and therefore performed more poorly, when the task was framed as measuring gender differences in athletic ability, compared to when the task was framed as measuring racial differences in athletic ability or a non-stereotype relevant attribute (i.e., sports psychology). This is consistent with the hypothesis that negative group comparisons to men represent a more prominent concern for White females who play sports relative to negative group comparisons to females from other racial or ethnic groups. Given the long history of gender differences and inequities at all levels of international sports competition, it is likely that poor athletic ability operates as a ‘‘universal’’ negative stereotype about female athletes, which when made salient by blatant cues in the performance context, can reduce their performance in sports. Also as predicted by the dual process model, the outgroup gender of the experimenter caused participants to perform less accurately on the final putt, and this occurred regardless of how the task was framed. This supports the hypothesis that when subtle threat cues are simultaneously present in the situation, they are capable of influencing performance through a separate mechanism. Subtle cues appear to operate primarily as distractions that create cognitive load demands, which in turn, influence those aspects of task performance that depend upon working memory capacity. Trying to stop the ball in the smallest hole on the last putt requires substantial concentration, but if the cognitive processes are disrupted by thoughts about how one is being evaluated by an outgroup member, accuracy can suffer. Thus, when more than one source of stereotype threat is present in a performance situation, each source can impact different aspects of performance through different processes (e.g., Strack & Deutsch, 2004). The pattern of correlations between the two achievement and expectancy measures provided further evidence for a dual process interpretation of the multiple cue effects. First, the small correlation observed between achieved strokes and achieved accuracy, and the zero-order correlation between expected strokes and expected accuracy, indicates that these two aspects of performance were processed somewhat independently of each other. However, the moderate correlations between expected and achieved strokes, and between expected and achieved accuracy on the final putt, suggests that participants were consciously and deliberating processing their progress toward these goals. This is not surprising given the sequential nature of the task; for each hole on the course, participants started by making a prediction for the number of strokes they would use and also for how accurate they would be on the last putt. They then played the hole, and subsequently used their achieved strokes and accuracy from the previous hole to generate predictions for these outcomes on the next hole. Nevertheless, the reciprocation between achievement and expec- tancy on strokes and accuracy was negatively impacted by different threat cues, suggesting that these conscious strategic processes were operating through separate channels. The threat induced by the blatant cue caused lower expectations and performance on one set of task-relevant skills, while the threat induced by the subtle cue lowered expectations and performance on a different set of task-relevant skills. If so, then the observed relationship between expectancy and performance also suggests that the dual process effect of multiple threat cues may be limited to situations in which each cue is processed consciously and deliberately. An intriguing possibility is that under some conditions, targets may process one or more multiple threat cues in a relatively heuristic or implicit manner. Such may be the case, for example, on tasks like a math test or other cognitive performance measure, during which targets are not asked to predict their performance on each item before they attempt it. When one or more cues are processed through less deliberate mechanisms, the impact of multiple cues may operate as predicted by a predominant or additive model. Thus, an important direction for future research is to explore how the presence of multiple threat cues influence performance on other types of tasks while varying the type of cue and how it is processed. Another potential limitation to the current research is that it focused on novice golfers. Beilock and colleagues (2006) have argued that stereotype threat can impact the performance of experts and novices on tasks that require sensimotor skills through different mechanisms. Specifically, because the lack of experience of novice golfers requires them to concentrate more attention on their execution of the task, stereotype threat cues are most likely to reduce their performance through distraction processes. In contrast, because the performance of experts is more proceduralized and automatic, the salience of a negative stereotype is more likely to reduce performance by increasing their attention to the task via explicit monitoring or ‘‘choking under pressure’’ processes. Indeed, studies have shown that when a single blatant threat cue is made salient before a golf-putting task, the performance of experts is reduced, unless they simultaneously perform a second task that distracts them from monitoring their execution of the primary task (Beilock et al., 2006). This might predict that when both blatant and subtle threat cues are salient, the distracting presence of the subtle threat cue could improve the performance of experts on a sensimotor task like golf putting. However, we believe subtle threat cues distract because they represent a source of ambiguity about threat; they attract attention because they represent a separate source of evaluation apprehension. Thus, the distraction processes induced by subtle threat cues are different than those induced by backwards counting or other memory intensive tasks. We might then expect multiple threat cues to cause experts to perform as poorly as novices, assuming that both groups are highly engaged in doing well on the task (Stone, 2002; Stone et al., 1999). J. Stone, C. McWhinnie / Journal of Experimental Social Psychology 44 (2008) 445–452 Finally, if multiple threat cues can operate as independent sources of concern, then our findings have important implications for reducing the effect of negative stereotypes on the performance of targets. For example, the data suggest that the presence of a positive source cue, like an ingroup role model, may not overcome the effect of a blatant threat cue (Marx & Roman, 2002; Steele et al., 2002). Whereas it is possible that our female experimenters were not perceived to be the type of ‘‘athletically gifted’’ role models that may imbue a sense of confidence in novice female athletes (Marx & Roman, 2002), another determining factor may be the attribute under investigation. For example, Li and colleagues (2004) reported that females are more likely to view athleticism as a fixed entity than men. As the research by Aronson and colleagues (2002) showed, viewing performance in a domain as a fixed entity induces higher susceptibility to stereotype threat compared to perceived the domain as malleable. Thus, if athletic ability is perceived by women to be immutable to effort, blatant cues may cause them to suffer stereotype threat and perform more poorly even when in the presence of a female role model. Overcoming this problem likely necessitates framing gender differences in athletic ability as amendable through effort or as irrelevant to how performance in sports is evaluated. In conclusion, sports, like the academic domains of math, computer science and engineering, have a long history of conveying the message that women are less capable than men. Consequently, the domain of sports is replete with negative stereotypes about the athletic ability of females that place them at risk for stereotype threat when they perform a sports task. The current data show that this can occur in two different ways: By the presence of a male who is in a position to evaluate their performance, and by explicit statements about the poor athletic ability of females. Importantly, each source of threat appeared to operate independent of the other to simultaneously impact different aspects of performance, and potentially through different mechanisms. These dual processes suggest that in some performance situations, stigmatized targets may be forced to cope with more than one social identity threat at a time while they attempt to show their potential. Acknowledgments The authors thank Stephanie Claudio, Kate Waliszewski, Ross Parnell and Scott Shanks for serving as experimenters on the project. We are also indebted to Anna Chalabaev, Anna Woodcock, Toni Schmader, Joel Cooper, and Mark Zanna for their insightful comments on this work. References Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African-American college students by reshaping theories of intelligence. Journal of Experimental Social Psychology, 38, 113–125. 451 Beilock, S. R., Jellison, W. A., Rydell, R. J., McConnell, A. R., & Carr, T. H. (2006). On the causal mechanism of stereotype threat: Can skills that don’t rely heavily on working memory still be threatened? Personality and Social Psychology Bulletin, 32, 1059–1071. Biernat, M., & Vescio, T. K. (2002). She swings, she hits, she’s great, she’s benched: implications for gender based shifting standards for judgment and behavior. Personality and Social Psychology Bulletin, 28, 66–77. Croizet, J. C., Despres, G., Gauzins, M., Huguet, P., Leyens, J., & Meot, A. (2004). Stereotype threat undermines intellectual performance by triggering a disruptive mental load. Personality and Social Psychology Bulletin, 30, 721–731. Danso, H. A., & Esses, V. M. (2001). Black experimenters and the intellectual test performance of White participants: the tables are turned. Journal of Experimental Social Psychology, 37, 158–165. Fredrickson, B. L., & Harrison, K. (2005). Throwing like a girl: selfobjectification predicts adolescent girls’ motor performance. Journal of Sport & Social Issues, 29, 79–101. Inzlicht, M., & Ben-Zeev, T. (2000). A threatening intellectual environment: why females are susceptible to experiencing problemsolving deficits in the presence of males. Psychological Science, 11, 365–371. Keller, J., & Dauenheimer, D. (2003). Stereotype threat in the classroom: Dejection mediates the disrupting threat effect on women’s math performance. Personality and Social Psychology Bulletin, 29, 371–381. Knight, J. L., & Guiliano, T. A. (2001). He’s a laker; she’s a looker: the consequences of gender-stereotyped portrayals of male and female athletes by the print media. Sex Roles, 45, 217–229. Li, W., Harrison, L., & Solmon, M. (2004). College students’ implicit theories of ability in sports: race and gender differences. Journal of Sport Behavior, 27, 291–304. Marx, D. M., & Goff, P. A. (2005). Clearing the air: the effect of experimenter race on target’s test performance and subjective experience. British Journal of Social Psychology, 44, 645–657. Marx, D. M., & Roman, J. S. (2002). Female role models: protecting women’s math test performance. Personality and Social Psychology Bulletin, 28, 1183–1193. Roper, E. A. (2002). Women working in the applied domain: examining the gender bias in applied sport psychology. Journal of Applied Sport Psychology, 14, 53–66. Sailes, G. A. (1996). An investigation of campus stereotypes: the myth of Black athletic superiority and the dumb jock stereotype. In R. E. Lapchick (Ed.), Sport in society: Equal opportunity or business as usual? (pp 193–202). Thousand Oaks, CA: Sage. Schmader, T., & Johns, M. (2003). Converging evidence that stereotype threat reduces working memory capacity. Journal of Personality and Social Psychology, 85, 440–452. Seibt, B., & Forster, J. (2004). Stereotype threat and performance: how self-stereotypes influence processing by inducing regulatory foci. Journal of Personality and Social Psychology, 87, 38–56. Sekaquaptewa, D., & Thompson, M. (2002). Solo status, stereotype threat, and performance expectancies: their effects on women’s performance. Psychological Science, 39, 68–74. Spencer, S. J., Steele, C. M., & Quinn, D. M. (1999). Stereotype threat and women’s math performance. Journal of Experimental Social Psychology, 35, 4–28. Steele, C. M. (1997). A threat in the air: how stereotypes shape intellectual identity and performance. American Psychologist, 52, 613–629. Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69, 797–811. Steele, C. M., Spencer, S. J., & Aronson, J. (2002). Contending with group image: the psychology of stereotype and social identity threat. In M. P. Zanna (Ed.). Advances in experimental social psychology (Vol. 34, pp. 379–440). San Diego: Erlbaum. Stone, J. (2002). Battling doubt by avoiding practice: the effects of stereotype threat on self-handicapping in White athletes. Personality and Social Psychology Bulletin, 28, 1667–1678. 452 J. Stone, C. McWhinnie / Journal of Experimental Social Psychology 44 (2008) 445–452 Stone, J., Lynch, C. I., Sjomeling, M., & Darley, J. M. (1999). Stereotype threat effects on Black and White athletic performance. Journal of Personality and Social Psychology, 77, 1213–1227. Stone, J., Perry, Z. W., & Darley, J. M. (1997). ‘‘White men can’t jump’’: evidence for the perceptual confirmation of racial stereotypes following a basketball game. Basic and Applied Social Psychology, 19, 291–306. Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8, 220–247. Tuggle, C. A., & Owen, A. (1999). A descriptive analysis of NBC’s coverage of the centennial Olympics. Journal of Sport and Social Issues, 23, 171–182. Eagly, A. H., & Carli, L. L. (2007). Through the labyrinth: The truth about how women become leaders. Boston: Harvard Business School Press Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth, TX: Harcourt Brace Jovanovich. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Eagly, A. H., & Chaiken, S. (1998). Attitude structure and function. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (4th ed., Vol. 1, pp. 269 –322). New York: McGraw-Hill. Eagly, A. H., Chen, S., Chaiken, S., & Shaw-Barnes, K. (1999). The impact of attitudes on memory: An affair to remember. Psychological Bulletin, 125, 64 – 89. Eagly, A. H., & Crowley, M. (1986). Gender and helping behavior: A meta-analytic review of the social psychological literature. Psychological Bulletin, 100, 283–308. Eagly, A. H., Diekman, A. B., Johannesen-Schmidt, M. C., & Koenig, A. M. (2004). Gender gaps in sociopolitical attitudes: A social psychological analysis. Journal of Personality and Social Psychology, 87, 796 – 816. Eagly, A. H., Johannesen-Schmidt, M. C., & van Engen, M. (2003). Transformational, transactional, and laissez-faire leadership styles: A meta-analysis comparing women and men. Psychological Bulletin, 129, 569 –591. Eagly, A. H., & Johnson, B. T. (1990). Gender and leadership style: A meta-analysis. Psychological Bulletin, 108, 233–256. Eagly, A. H., & Karau, S. (1991). Gender and the emergence of leaders: A meta-analysis. Journal of Personality and Social Psychology, 60, 685–710. Eagly, A. H., & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological Review, 109, 573–598. Eagly, A. H., Karau, S. J., & Makhijani, M. G. (1995). Gender and the effectiveness of leaders: A meta-analysis. Psychological Bulletin, 117, 125–145. Eagly, A. H., & Kite, M. E. (1987). Are stereotypes of nationalities applied to both women and men? Journal of Personality and Social Psychology, 53, 451– 462. Eagly, A. H., & Steffen, V. J. (1986). Gender and aggressive behavior: A meta-analytic review of the social psychological literature. Psychological Bulletin, 100, 309–330. 644 Eagly, A. H., Wood, W., & Chaiken, S. (1978). Causal inferences about communicators and their effect on opinion change. Journal of Personality and Social Psychology, 36, 424 – 435. Wood, W., & Eagly, A. H. (2002). A cross-cultural analysis of the behavior of women and men: Implications for the origins of sex differences. Psychological Bulletin, 128, 699 –727. Wood, W., & Eagly, A. H. (in press). Gender. In S. T. Fiske, D. T. Gilbert, & G. Lindzey (Eds.), Handbook of social psychology (5th ed.). New York: Wiley. The His and Hers of Prosocial Behavior: An Examination of the Social Psychology of Gender Alice H. Eagly Northwestern University Prosocial behavior consists of behaviors regarded as beneficial to others, including helping, sharing, comforting, guiding, rescuing, and defending others. Although women and men are similar in engaging in extensive prosocial behavior, they are different in their emphasis on particular classes of these behaviors. The specialty of women is prosocial behaviors that are more communal and relational, and that of men is behaviors that are more agentic and collectively oriented as well as strength intensive. These sex differences, which appear in research in various settings, match widely shared gender role beliefs. The origins of these beliefs lie in the division of labor, which reflects a biosocial interaction between male and female physical attributes and the social structure. The effects of gender roles on behavior are mediated by hormonal processes, social expectations, and individual dispositions. Editor’s Note Alice H. Eagly received the Award for Distinguished Scientific Contributions. Award winners are invited to deliver an award address at the APA’s annual convention. A version of this award address was delivered at the 117th annual meeting, held August 6 –9, 2009, in Toronto, Ontario, Canada. Articles based on award addresses are reviewed, but they differ from unsolicited articles in that they are expressions of the winners’ reflections on their work and their views of the field. November 2009 ● American Psychologist This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Keywords: prosocial behavior, gender, sex differences, altruism, helping Gender fascinates the public and scientists alike, inspiring continuing debate about how nature and nurture intertwine in influencing female and male behavior. The fact that the keyword gender garnered 24,169 hits in 2000 –2008 in the PsycINFO database shows the thriving state of scholarship on gender. These publications contain an abundance of information about male–female similarities and differences. Although the aggregation of large amounts of such information in meta-analyses or other summaries is useful, such approaches can also be limiting. If the puzzles of gender are to be solved, the integration of male–female comparisons must be coordinated with effective theory. In its absence, variation in the direction and magnitude of these differences and similarities can appear to be random and can even give the impression that gender has little or no effect on behavior. Yet, the experiences and observations of everyday life suggest that gender remains a multifaceted system of influences on personal choices, social interaction, and societal institutions. In this article, I examine how these influences operate in one domain of human behavior. This domain is prosocial behavior, which consists of behaviors consensually regarded as beneficial to others. It includes actions such as helping, sharing, comforting, guiding, rescuing, and defending (Batson, 1998; Dovidio, Piliavin, Schroeder, & Penner, 2006). Much prosocial behavior is directed to helping individuals, but it can be directed as well to supporting a collective, such as a group, organization, or nation. Although such actions are not necessarily altruistic in the sense of being devoid of self-oriented motivation, they deliver help to others. A simple first question might be whether there is a more helpful sex. If armchair analysis answers this question, one’s first thoughts, be they implicit or explicit, might well reflect gender stereotypes that ascribe kindness and concern with others more to women than to men (e.g., Diekman & Goodfriend, 2006; Williams & Best, 1990). Yet, probing for second thoughts should bring to mind examples of helpful men. What about heroic men who take enormous risks for others and warriors who protect their tribe or nation from external assault? Given these disparate images, a first step toward understanding the prosocial behavior of women and men involves an examination of gender roles. Subsequent steps involve explaining the origins of gender roles and the processes by which they affect behavior. Gender Roles as a Tool for Understanding Prosocial Behavior Elementary insights about social behavior follow from scrutiny of a society’s gender roles, which are the shared beliefs that apply to individuals on the basis of their soNovember 2009 ● American Psychologist cially identified sex (Eagly, 1987). Gender role beliefs are both descriptive and prescriptive in that they indicate what men and women usually do and what they should do. The descriptive aspect of gender roles, or stereotypes, tells people what is typical for their sex. Especially if a situation is ambiguous or confusing, people tend to enact sex-typical behaviors. The prescriptive aspect of gender roles tells people what is considered admirable for their sex in their cultural context. People may enact these desirable behaviors to gain social approval or bolster their own esteem. To varying extents, gender role beliefs are embedded both in others’ expectations, thereby acting as social norms, and in individuals’ internalized gender identities, thereby acting as personal dispositions (Wood & Eagly, 2009, in press). These culturally shared beliefs provide a general framework for understanding why male and female behavior can be different or similar, depending on the behavior and its circumstances. Gender role beliefs imply different prosocial behaviors for women and men. Following concepts introduced by Bakan (1966), most beliefs about men and women can be summarized in two dimensions, which are most often labeled communion, or connection with others, and agency, or self-assertion. Women, more than men, are thought to be communal—that is, friendly, unselfish, concerned with others, and emotionally expressive. Men, more than women, are thought to be agentic—that is, masterful, assertive, competitive, and dominant (e.g., Newport, 2001; Spence & Buckner, 2000). Studies of gender stereotypes have consistently found that their content is heavily saturated with communion and agency, with more minor themes pertaining to other qualities (e.g., Kite, Deaux, & Haines, 2007). This predominance of communion and agency is widespread in world cultures (Williams & Best, 1990). To understand the relevance of these beliefs for prosocial behavior, it is helpful to consider their implications for the types of social bonds that people form. Social bonds can take a relational form by linking people to particular others in close relationships or a collective form by linking people to groups and organizations (Brewer & Gardner, 1996). This distinction between relational and collective interdependence corresponds to the communal and agentic dimensions of gender stereotypes (Gardner & Gabriel, 2004). By ascribing warm, sympathetic, and kind qualities to women, gender role beliefs imply that women have a propensity for bonding with others in close, dyadic relationships. Expressive, affectionate qualities facilitate friendships, romantic relationships, and family relationships and convey cooperative interdependence with others (Fiske, Cuddy, Glick, & Xu, 2002). In contrast, by ascribing assertive, ambitious, and competitive qualities to men, gender role beliefs imply a social context in which people differ in status and men strive to improve their hierarchical position (Baumeister & Sommer, 645 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1997; Gardner & Gabriel, 2004). Such qualities are consistent with men’s directing of much of their prosocial behavior to collectives (Gilmore, 1990). Although independence is also one of the agentic qualities commonly ascribed to men, demonstrating a degree of independence in a group setting can produce influence (Moscovici & Nemeth, 1974; Shackelford, Wood, & Worchel, 1996) and potentially provide an opportunity for leadership (Eagly, Wood, & Fishbaugh, 1981). In general, superior social status is conveyed by the agentic attributes ascribed to men, such as being dominant and masterful (Ridgeway & Bourg, 2004), even though these attributes are not as favorably evaluated as the communal attributes ascribed to women (Eagly & Mladinic, 1994; Langford & MacKinnon, 2000). In the next section of this article I classify prosocial behaviors according to their agentic or communal emphasis. A gender role analysis suggests that prosocial behaviors are more common in women to the extent that these behaviors have primarily a communal focus and more common in men to the extent that they have primarily an agentic focus. A corollary of this prediction is that prosocial behaviors are more common in women if they have a relational emphasis (e.g., supporting or caring for an individual). A second corollary is that prosocial behaviors are more common in men if they have a collective emphasis, facilitate gaining status, or imply higher status. Yet another consideration is that some differences in male and female behavior reflect sex differences in physical size and strength. Women’s lesser physical prowess can act as a deterrent to their participation in highly strength-intensive activities, which include some prosocial behaviors (Wood & Eagly, 2002, in press). These predictions should be understood as implying not dichotomous male–female differences but general trends (or main effects of participant sex) that emerge across situational and other individual factors that also affect prosocial behavior and that can moderate or compete with the effects of gender roles. The logic of prediction for gender effects is thus similar to that for other personal characteristics (see Leary & Hoyle, 2009). In particular, gender roles influence behavior in conjunction with many other roles, including those associated with other group memberships (e.g., ethnicity, religion) and specific obligations (e.g., family, occupation). Despite the myriad of influences on social behaviors, gender roles are important, acting in part through others’ expectations and broader social norms. These external pressures range from subtle (e.g., stereotype threat) to obvious (e.g., laws or norms forbidding one sex access to certain roles or opportunities). Gender roles also act through individuals’ personal identification with their gender and are intertwined with hormonal processes that facilitate masculine and feminine behavior (Wood & Eagly, 2009). In addition, all behaviors are contextually situated, and this con646 text can influence the salience of gender norms and the accessibility of gender identities (e.g., Deaux & Major, 1987; Piliavin & Unger, 1985). A convenient organization of trends in agentic and communal prosocial behavior classifies findings by their social context: interactions with strangers, interactions in close relationships, interactions in workplaces, and interactions in other social settings. Meta-analyses are informative, as are archival data and individual field and laboratory studies. Invoking these rich sources of data, in the next section I report male–female differences and similarities, organized by gender role beliefs and social context. In a subsequent section (The Origin and Consequences of Gender Roles), I consider the causal relations in which these beliefs and behaviors are embedded. Male–female comparisons from meta-analyses appear in this article as averaged findings in the d metric, defined as the difference between the male and female mean values divided by the pooled standard deviation (see Borenstein, Hedges, Higgins, & Rothstein, 2009). Effect sizes from single studies, which are less reliable, are omitted. In contemplating the effect sizes, readers should keep in mind that the cumulative impact of small effects can be considerable. This insight was compellingly explained by Abelson (1985, p. 133), who concluded that “small variance contributions of independent variables in single-shot studies grossly understate the variance contribution in the long run” (see also Epstein, 1980; Rosenthal, 1990). If studies’ measures are not “single-shot” but are appropriately aggregated across multiple observations of behaviors, effect magnitudes are generally larger. Given these considerations, the most relevant baseline for interpreting effect magnitudes for prosocial behavior incorporates the methodological characteristics of its typical research paradigms. In this domain, single-shot studies are common, depressing effect magnitudes. It is therefore not surprising that averaging the effects from all available meta-analyses of prosocial behaviors in social psychology, regardless of hypothesis, yielded a d of only 0.37 (Richard, Bond, & Stokes-Zoota, 2003). Research Comparing Female and Male Prosocial Behavior Interactions With Strangers Helping strangers, a domain that includes many agentic behaviors, became a focus of social psychological research in the wake of Darley and Latané’s (1968) research addressing the failure of bystanders to intervene in the infamous Kitty Genovese murder. Social psychologists then carried out numerous field and laboratory experiments on helping behavior (see Batson, 1998; Dovidio et al., 2006). Many of these researchers, like Darley and Latané, studied bystander interventions in emergency situations in which another person appeared to be distressed or endangered (e.g., helping a man who fell in the subway). Other types November 2009 ● American Psychologist This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. of helping that attracted experimentation included assistance in response to requests (e.g., giving someone money for the subway) as well as polite behaviors (e.g., helping someone pick up dropped packages). A meta-analysis of these experiments revealed that in general men helped more than women (d ⫽ 0.34, Eagly & Crowley, 1986; see Johnson et al., 1989, for cross-cultural replication with a self-report questionnaire). Although all of the behaviors assessed in these experiments required some attentiveness to the needs of others, only a portion required taking the initiative, thus calling on the assertive qualities central to the male gender role. Therefore, the studies were classified by whether a need merely presented itself to bystanders (e.g., through observation that someone was ill or distressed) or an explicit request to help was directed to them (e.g., an appeal for a charity donation). When a need is merely present, helpers assert themselves to deliver aid, whereas when a request is made, helpers acquiesce to someone else’s wishes. A finding consistent with the agentic theme of the male gender role was that men were especially more helpful than women when helpers had to take the initiative (d ⫽ 0.55) than when helpers had to acquiesce to a request (d ⫽ 0.07). Many of these helping behaviors drew on agency’s implications for status—that is, the common, albeit eroding, expectation that men are dominant over women. In a prosocial context, male dominance implies directing benevolent protectiveness and politeness toward women. Men are expected not only to protect women from dangers but to deliver acts of courtesy such as helping them put on their coats. With cultural roots in medieval codes of chivalry, such norms have survived in common paternalistic beliefs and behaviors (Glick & Fiske, 2001). Aspects of the helping behavior findings suggest male chivalry. Specifically, in experiments that had divided data by the sex of the person receiving aid, men helped more than women for female recipients of help (d ⫽ 0.27); this effect slightly reversed for male recipients (d ⫽ ⫺0.08, Eagly & Crowley, 1986). In a finding consistent with the idea that men’s helping is driven in part by social norms that can be made salient by others’ presence, another analysis showed that the tendency for men to help more than women was substantial when the potential helpers were in the presence of onlookers (d ⫽ 0.74) but not when they were the only bystander (d ⫽ ⫺0.02). Some prosocial behaviors, often labeled heroic, require that the helper take considerable personal risk to aid another person (Becker & Eagly, 2004). Heroic acts of rescuing others in emergencies are consistent with the male gender role in that they are highly agentic in their requirement for quick and decisive intervention that often places the rescuer’s own life at risk. Many such actions also advantage men’s greater size and strength, as suggested by the larger physical size of interveners than of noninterveners in November 2009 ● American Psychologist crimes and emergencies (Huston, Ruggiero, Conner, & Geis, 1981). Relevant archival data come from the Carnegie Hero Fund Commission (2009), which recognizes individuals who voluntarily risk their own lives while saving or attempting to save the life of another person. People whose job roles or parental responsibilities require acts of rescuing are ineligible for this recognition. Men have received the great majority of these heroism awards (91% in 1904 – 2008), and there is no evidence of systematic change in this distribution over the years (e.g., 92% men in 2004 – 2008; W. F. Rutkowsky, Executive Director of the Carnegie Hero Fund Commission, personal communication, May 27, 2009). This disproportion is very unlikely to reflect a bias against honoring eligible women (see Becker & Eagly, 2004). Replication of this pattern has emerged from the Canadian government’s awarding of a similar Medal of Bravery; 87% of these awards in 2004 –2008 have honored men (Governor General of Canada, 2009). In addition, men have strongly predominated in contemporary newspaper accounts of heroic interventions (Lyons, 2005) and among people recognized for intervening in dangerous criminal events such as muggings and bank holdups (e.g., Huston et al., 1981). Also, in the social psychological helpin...
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Running Head: STEREOTYPE THREAT

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Stereotype Threat
Student’s Name
Institution Of Affiliation
Course
Date

STEREOTYPE THREAT

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Definition of Stereotype Threat

The term stereotype threat refers to the situational predicament which makes people to be
exposed to the risk of conforming to institutionalized stereotypes within their social settings.
According to Banaji & Hardin, (1996), stereotype threat threatens the individual performance
who fear being victimized, ridiculed and subjected to prejudice for belonging to small or
minority groups. In the case of negative stereotypes, the members of such groups develop
anxiety that negatively influences their performance. Devine, (1989), also notes that in the long
run, the people who are subjected to negative stereotype may end up experiencing reduced
ability to perform to their maximum potential. Even though an individual is not forced to
subscribe to such negative stereotype, the mechanism through which the stereotype threat
induces anxiety is attributed to the depletion of the working memory which affects the
phonological aspects of the mind.
The Target of Stereotype Threat and the Source of Stereotype Threat
According to the Multi-Threat Framework proposed by Shapiro and Neuberg (2007),
there are six targets of stereotype threat were the source of stereotypes are believed to interact
with individuals or groups. According to Eagly, (2009), targets of stereotype threat emergences
from the intersection of two dimensions. While the target of the stereotype threat may emerge
from the individual or the group in which the individual belongs to, the stereotype threat is the
concern over the possibility of an individual’s abilities drawing negative reactions from others.
The anticipated reflection of an individual’s performance on the ability of the group is also a
stereotype threat.
The source of stereotype threat is the second dimension of the Multi-Threat Framework
proposed by Inzlicht & Kang, (2010). According to this dimension, stereotype threats arise from

STEREOTYPE THREAT

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self, from an in-group other, or from an outgroup other. This includes the concern that
individual performance may cause certain negative evaluation of ...


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