Gender Profiling

Abstract

The current research integrates perspectives on gendered race and person–position fit to introduce the concept of a gender profile. We propose that both the “gender” of a person’s biological sex and the “gender” of a person’s race (Asians are perceived as feminine and Blacks as masculine) help comprise an individual’s gender profile—the overall femininity or masculinity associated with their demographic characteristics. We also propose that occupational positions have gender profiles. Finally, we argue that the overall gender profile of one’s demographics, rather than just one’s biological sex, determines one’s fit and hirability for feminine or masculine occupational roles. The current five studies establish the gender profiles of different races and sexes, and then demonstrate that individuals with feminine-typed and masculine-typed gender profiles are selected for feminine and masculine positions, respectively. These studies provide new insights on who gets ahead in different environments.

Keywords

race gender stereotypes intersectionality

When people hear the word “profiling,” they often immediately think of race. However, many other types of profiling exist outside of the racial context. For example, people of different genders are often stereotyped as having qualities that fit the profile for masculine- and feminine-typed occupations (Heilman, 1983, 1995). Because women are perceived to be feminine, they are seen as more suitable for feminine occupations (e.g., librarian, daycare worker). Similarly, because men are perceived to be masculine, they are seen as more suitable for masculine occupations (e.g., security patrol, firefighter; Eagly & Karau, 2002).

Consistent with recent research on the importance of intersectionality when studying race or gender (e.g., Berdahl & Moore, 2006; Crenshaw, 1989/1993; Nelson & Probst, 2004; Purdie-Vaughns & Eibach, 2008), we argue that the integration of race and gender offers exciting opportunities for more precise empirical examinations and theoretical advancement on profiling. The current research explores profiling on the basis of gender and race for personnel selection, which we define as the selection of employees for a particular occupational position. Specifically, we introduce the concept of a gender profile—the femininity and/or masculinity associated with a specific demographic group—to understand how the gendered characteristics of a person’s race and biological sex simultaneously determine whether they are perceived to fit into, and are hirable for, feminine or masculine occupational positions. Thus, our investigation provides additional insight into the judgments that contribute to the segregation found in many workplaces.

Notably, researchers have suggested that races are gendered, such that Asians are perceived to be more feminine, and Blacks are perceived to be more masculine, than Whites (Galinsky, Hall, & Cuddy, 2013; Johnson, Freeman, & Pauker, 2012). Because both race and biological sex separately contribute to perception of a person’s femininity and masculinity, investigations into the selection of individuals into feminine or masculine occupations need to account for both the gender of the candidate’s race and the gender of the candidate’s biological sex.

Gendered Race

Although the current research is the first to explore the combination of gendered race and biological sex for occupational positions, a few studies have documented an overlap between racial and gender stereotypes (Galinsky et al., 2013; Goff, Thomas, & Jackson, 2008; Johnson et al., 2012). In one study, participants were asked to categorize photos of White and Black women by gender (Goff et al., 2008). Participants made more gender categorization errors for Black women compared to White women, and the researchers theorized that this was due to the implicit perception that Black women were more masculine than White women. Johnson et al. (2012) extended these findings by including Asian and male targets and found that participants were better able to categorize Asian female and Black male faces by gender compared to Black female and Asian male faces.

Racial genderization also extends beyond physical appearances. Galinsky et al. (2013) found that the stereotype content for Blacks was the most masculine, and Asians the most feminine, of all three racial groups. For example, stereotypes of Blacks as aggressive, hostile, and dominating overlapped with U.S.-based conceptions of prototypical masculinity, and stereotypes of Asians as gentle, passive, and weak overlapped with conceptions of prototypical femininity (Galinsky et al., 2013). Although it is not the focus of the present investigation, there may be a number of reasons for this overlap from cultural factors to perceptions of phenotypic differences (e.g., Afrocentric facial features are perceived to be more masculine than Eurocentric features; Goff et al., 2008; Johnson et al., 2012).

We present a model of gender profiling that offers predictions for how candidates are perceived to fit in feminine or masculine occupations based on the masculine and feminine connotations associated with both their gender and racial identities. In our conceptual framework, a feminine-typed demographic group is perceived to be more feminine than masculine and a masculine-typed demographic group is perceived to be more masculine than feminine. For example, Asians are perceived to be feminine-typed, Whites are perceived to be neutral, and Blacks are perceived to be masculine-typed (Galinsky et al., 2013). Thus, the current work goes beyond prior theories that have explored the organizational outcomes of race and gender combinations (Berdahl & Moore, 2006; Kulik, Roberson, & Perry, 2007; Nelson & Probst, 2004) by directly testing the implications of having two “gendered” demographic characteristics. In doing so, we integrate gender profiling perspectives with the larger literature on person–position fit.

Perceptions of Person–Position Fit

Both race researchers (drawing upon leadership categorization theory) and gender researchers (drawing upon role congruity theory and the lack of fit model) have made important advances in explaining the processes of person–position fit (Eagly & Karau, 2002; Heilman, 1983, 1995, 2001; Lord, Foti, & De Vader, 1984). Leadership categorization theory describes the process, whereby perceivers match a candidate’s core qualities with the qualities that are perceived to be necessary for a certain job (Lord et al., 1984; Lord & Maher, 2002). Candidate evaluations are lower when a person’s qualities do not “fit” with the qualities of an occupational prototype, and become higher as the degree of fit increases. Leadership categorization theory posits that a prototype, or “profile,” exists for different types of positions, and that a candidate is measured against this prototype.

Leadership categorization theory has been instrumental in explaining discrimination toward minority race candidates. For example, Rosette, Leonardelli, and Phillips (2008) found that the White stereotype is presumed to be part of the prototype of a leader; thus, participants assumed that a business representative was White, regardless of the representative’s industry or company’s race base rates. Leaders who do not match this “White standard” often suffer from lower leadership evaluations. Additionally, Sy et al. (2010) showed that there were prototypes for sales and engineer occupations, as well as stereotypes for Asians (e.g., mathematical) and Whites (e.g., social). Further, the authors showed that leadership perceptions were higher for Asian candidates in engineering and White candidates in sales because of perceived race-prototype matching. In sum, race is a crucial characteristic in determining perceptions of fit.

Role congruity theory and the lack of fit model have been primarily used in explaining perceived person–position fit in a gender-based context (Eagly & Karau, 2002; Heilman, 1993, 1995, 2001). These theories contend that evaluators assess applicants based on stereotypes related to the applicant’s sex. For example, men do not possess the communal qualities necessary to be teachers and nurses, and women do not possess the dominant qualities necessary to be firefighters and police officers (Eagly & Karau, 2002; Heilman, 1993, 1995, 2001). Thus, the perceived fit between the femininity or masculinity of a candidate and a potential job becomes a crucial element in determining the prospective fit for that position.

Although leadership categorization theory has typically been situated in a different domain from role congruity theory and the lack of fit model, they all share important overlapping qualities. First, they all embody the belief that an overall matching process occurs between a candidate’s qualities and the qualities required for a position. Second, they conclude that incongruence between the candidate’s and job’s qualities will result in lower evaluations of a candidate. These theories collectively serve as a useful lens for studying the domain of gendered race.

We suggest that each position has a gender profile—that is, how much the position requires masculinity or femininity. Consistent with prior research, we argue that biological sex will influence hiring for gender-typed positions because women will be perceived to be feminine-typed and men will be perceived to be masculine-typed. Further, we extend past theories to show that the gender of one’s race is similarly consequential for perceptions of person–position fit. We predict that demographic groups that are perceived to embody masculinity (e.g., Blacks) and/or femininity (e.g., Asians) will be perceived to fit or misfit the masculine or feminine positions accordingly.

Although we have discussed the intersection of race and sex, our central hypotheses are main effect predictions. We predict that both the biological sex and race of a candidate will have independent main effects on whether a candidate is seen as a good fit for an occupational position.

Overview of Studies

We conducted five experiments to test our hypotheses about the fit between gendered races and feminine or masculine positions. We selected positions that exemplified femininity or masculinity, but that steered clear of strong stereotypes that are associated with the stereotypes geared to Asians (e.g., mathematical) and Blacks (e.g., athletic).

Study 1 establishes the gender profile of the prototypic librarian (feminine) and security patrol (masculine) positions, as well as the gender profile of the male and female, and Asian, White, and Black demographic groups. Further, Study 1 establishes which demographic groups are seen as having a similar gender profile as these particular occupations. Study 2 builds off these findings to test whether Blacks are perceived to be relatively more hirable than the other racial groups for a masculine-typed position, and whether Asians are perceived to be more hirable than the other racial groups for a feminine-typed position. Study 3 replicates Study 2, while also testing two plausible counter hypotheses. Study 4 holds the title of the position constant (negotiator) and describes the position using feminine- or masculine-typed descriptors. Finally, Study 5 enhances the external validity of the experimental context by using elaborate fictional resumes and a between-subjects design. Overall, we show that the gender of one’s race and the gender of one’s biological sex are independent determinants of one’s gender profile.

Study 1: The Gendered Content in Racial Stereotypes and Occupational Prototypes

Study 1 assessed the gender profile of (a) Asian, White, and Black, female and male stereotypes, and (b) the prototype for a librarian and security patrol position. We utilized a Princeton-Trilogy-based design (Devine & Elliot, 1995; Karlins, Coffman, & Walters, 1969; Katz & Braly, 1933) to determine feminine and masculine content. First, we asked a group of students to assess both the femininity and the masculinity of a preestablished set of traits. To compute the overall femininity and masculinity scores, we applied those “gender” assessments to the traits that a second group of participants perceived to be typical of demographic groups (Asian, White, and Black, women and men) and the traits commonly desired for the masculine and feminine positions (librarians and security patrol positions, respectively). Finally, we compared the gendered connotations associated with each occupation to the gendered connotations associated with these demographic groups to determine whether they matched.

We predicted that Asians would be perceived to be highly feminine-typed, Blacks would be perceived to be highly masculine-typed, and Whites would be perceived to be neutrally gendered in relation to Asians and Blacks. Further, we predicted that the librarian prototype would require highly feminine qualities and security patrol highly masculine qualities.

Participants and Procedure

One hundred sixty-seven participants from a nationwide Amazon Mechanical Turk sample were paid 45 cents to participate in a short online survey (125 women, 2 sex unidentified; 121 White, 26 Asian, 11 Black, 8 other, 1 race unidentified; M_age = 39.8). Sample size was determined in accordance with past Princeton Trilogy Studies (e.g., Devine & Elliot, 1995; Karlins et al., 1969; Katz & Braly, 1933).

Participants were randomly assigned to either make gender attributions or stereotype attributions. In the gender attribution group, 16 participants were told to review a list of 99 traits and assess each trait on both a 1 (not at all feminine) to 7 (extremely feminine) scale and a 1 (not at all masculine) to 7 (extremely masculine) scale. The traits included the 84 original Katz and Braly (1933) stereotypical traits, 9 more that were added in an updated Princeton Trilogy replication (athletic, criminal, hostile, low in intelligence, poor, rhythmic, sexually perverse, uneducated, and violent; see Devine & Elliot, 1995), and 6 that were added when pretests revealed that the list of possible attributes leaned toward masculine traits (gentle, delicate, yielding, polite, shy, and patient). Mean masculinity and femininity scores were computed for each of the 99 traits.

In the stereotype attribution group, 151 participants were given an identical list of 99 traits. Participants were randomly assigned to evaluate one of two occupations (librarian and security patrol) or one of six demographic groups (Asian men, Asian women, White men, White women, Black men, or Black women) and were instructed to choose the 10 traits (of the list of 99) that were most typical of their respective target groups. This resulted in 10 conditions between the two gender attribution and stereotype attribution groups.

Then, we inserted the respective mean femininity and masculinity scores for each of the 10 traits that a participant chose for his or her category. For each participant, we averaged these 10 femininity and 10 masculinity scores to assess the average femininity/masculinity that each participant associated with that respective category. Finally, we averaged these femininity and masculinity scores across all participants, and these overall femininity and masculinity scores were the main unit of analysis.

Results

Determining the sex-type of the demographic groups and occupational prototypes

To empirically measure each gender profile, we created a sex-type score for each of the races, sexes, and demographic groups (Table 1). First, we computed the difference between each category’s femininity and masculinity scores (i.e., femininity score − masculinity score = sex-type score). A positive sex-type score indicates that the group is more feminine than masculine (feminine-typed) and a negative sex-type score indicates that the group is more masculine than feminine (masculine-typed).

Table 1.

Femininity, Masculinity, and Sex-Type Scores by Gender, Race, and Demographic Group (Study 1).

				Sex-type score one-tailed t test from 0		Conceptual sex-type designation
Level of analysis	Femininity	Masculinity	Sex-type score	t	p	Conceptual sex-type designation
Gender
Woman	4.42 (0.34)_a	4.23 (0.23)_a	0.20 (0.45)_a	3.29	.00	Feminine
Man	4.19 (0.32)_b	4.34 (0.19)_b	−0.14 (0.37)_b	3.02	.00	Masculine
Race
Asian	4.47 (0.30)_a	4.23 (0.23)_a	0.24 (0.43)_a	3.49	.00	Feminine
White	4.29 (0.34)_b	4.27 (0.22)_a,b	0.02 (0.45)_b	0.33	.74	Not sex-typed
Black	4.16 (0.34)_b	4.35 (0.18)_b	−0.20 (0.36)_c	3.49	.00	Masculine
Demographic group
Asian woman	4.58 (0.24)_a	4.15 (0.27)_a	0.43 (0.36)_a	5.25	<.01	Highly feminine
White woman	4.45 (0.32)_a,b	4.16 (0.17)_a	0.29 (0.42)_a	2.93	.01	Feminine
Black woman	4.26 (0.38)_c	4.37 (0.16)_b	−0.11 (0.42)_b,c	1.24	.23	Not sex typed
Asian man	4.31 (0.15)_b,c	4.31 (0.15)_b	0.06 (0.41)_b	0.63	.54	Not sex-typed
White man	4.16 (0.31)_c,d	4.38 (0.21)_b	−0.22 (0.33)_c	2.92	.01	Masculine
Black man	4.06 (0.26)_d	4.34 (0.20)_b	−0.28 (0.29)_c	4.32	<.01	Highly masculine

Note. For each level of analysis (gender, race, and demographic group), means in each column that share different subscripts differ significantly, and means in each column that share the same subscripts do not differ significantly. The sex-type score is equal to the difference between femininity and masculinity; positive scores are feminine-typed, negative scores are masculine-typed, and scores near 0 are not sex-typed.

As illustrated in Table 1, sex-type scores show that women were perceived to be feminine-typed, t(56) = 3.29, p = .002, and men were masculine-typed, t(60) = 3.02, p = .004. Further, we found that Asians were perceived to be feminine-typed, t(39) = 3.49, p = .01, Whites were not significantly sex-typed, t(37) = 0.33, p = .74, and Blacks were masculine-typed, t(39) = 3.49, p = .01. As shown in Table 2, one-sample t tests indicated that the librarian was prescribed to be highly feminine-typed, t(10) = 5.23, p = .001, and the security patrol position was prescribed to be highly masculine-typed, t(21) = −2.17, p = .04.

Table 2.

Femininity, Masculinity, and Sex-Type Scores by Gender, Race, and Demographic Group (Study 1).

				Sex-type score one-tailed t test from 0		Conceptual sex-type designation
Level of analysis	Femininity	Masculinity	Sex-type score	t	p	Conceptual sex-type designation
Occupation
Librarian	4.59 (0.19)_a	4.13 (0.26)_a	0.46 (0.30)_a	5.02	.01	Feminine
Security patrol	4.28 (0.24)_b	4.44 (0.16)_b	−0.17 (0.28)_b	2.17	.04	Masculine

Person–position fit

We tested whether the sex-type score for targets of different sexes and races significantly differed from the sex-type score of an ideal librarian. The sex-type scores for male targets were significantly more masculine-typed than that of the ideal librarian, t(70) = 5.07, p < .001, d = 1.78; however, the sex-type scores for female targets did not differ significantly from that of the librarian prototype, t(66) = 1.85, p = .07. The sex-type scores for the Black targets, t(49) = 5.57, p < .001, d = 1.99, and White targets, t(47) = 3.01, p = .01, d = 1.15, were significantly more masculine-typed than that of the ideal librarian. However, the sex-type scores for the Asian targets, t(49) = 1.64, p = .11, did not significantly differ from that of the librarian prototype.

The sex-type scores for female targets were significantly more feminine-typed than that of the ideal security patrol person, t(77) = 3.31, p = .01, d = 0.99; however, the sex-type scores for male targets did not differ significantly from that of the security patrol prototype, t(81) = 0.11, p = .91. The sex-type scores for the Asian targets, t(60) = 3.71, p < .001, d = 1.13, were significantly more feminine-typed than that of the ideal security patrol person. However, the sex-type scores for the White targets, t(58) = 1.62, p = .11, and Black targets, t(60) = 0.46, p = .65, did not significantly differ from that of the security patrol prototype.

Discussion

As predicted, Blacks were seen as the most masculine, Asians were seen as the most feminine, and Whites were seen as the least sex-typed. Librarians were prescribed to be the most feminine, and security patrol officers were prescribed to be the most masculine. We found congruence between the feminine position and Asians, and the masculine position and the gender groups of Whites and Blacks. These findings support the idea that the prototype for a given occupation has a required level of masculine and feminine qualities. Further, both race and biological sex influence a person’s gender profile.

Study 2: Gender Profiling for Masculine and Feminine Positions

In Study 1, we examined matches and mismatches between demographic gender profiles and the gender profile of occupational prototypes. In Study 2, we test whether a match between a demographic and occupational gender profile makes a candidate of that demographic group more hirable for that occupational position. Specifically, we need to establish that the femininity and masculinity associated with the candidate’s race and sex influence those decisions. In Study 2, we chose the same highly masculine (security patrol) and feminine (librarian) positions, and investigated person–position fit. We expect that biological sex will contribute to hiring, such that men will have an advantage for masculine positions because of the masculinity of their biological sex, and that women will have an advantage for feminine positions because of the femininity associated with their biological sex. Additionally, we predict an additional effect of race, such that Blacks will have an advantage for masculine positions because of the masculinity of their race, and that Asians will have an advantage for feminine positions because of the femininity of their race. Empirically, we expect that a candidate’s sex-type will mediate the effect of sex on hirability and also race on hirability.

Participants and Procedure

Three hundred forty-four participants were recruited from Amazon Mechanical Turk and paid 45 cents to participate in an online survey. In this, and all subsequent studies, sample size was determined in accordance with past statistical guidelines that advise at least 50 participants per focal condition (e.g., race and gender; see Simmons, Nelson, & Simonsohn, 2013). Fifty-seven participants were excluded after incorrectly identifying the race and/or sex of the target and/or incorrectly answering an attention check question (“Please select the answer choice labeled blue”) leaving a total sample of 287 participants (133 women; 198 White, 11 Black, 58 Asian, 20 other; M_age = 33.71).

Manipulation of candidate sex and race

Participants were asked to review an application of an Asian, White, or Black, male or female undergraduate job candidate for two available college work study positions, campus librarian (feminine) and campus security patrol (masculine). The application contained the applicant’s name, current date, address, sex, and ethnicity.

Target race and sex were first communicated through the “please indicate your race/ethnicity” (White, Black, Asian, Hispanic, Others) and “please indicate your gender” check boxes on the application. Further, we used a stereotypical name for the Asian man and woman (Ming Lee and Ming Hoa), and the same name for both the White and Black men and women (Mark and Monica). We also tested more stereotypical names for the Black and White men and women to make sure that the results were not due to differences in stereotypicality of names. Thus, the Black man was either “Mark” or “Jamal,” the Black woman was either “Monica” or “Lakisha,” the White man was either “Mark” or “Greg,” and the White woman was either “Monica” or “Emily” (Bertrand & Mullainathan, 2004). The Asian woman and man remained Ming Lee and Ming Hoa in both conditions, respectively. We manipulated race and gender through names and checkboxes, rather than photos, because we wanted to eliminate candidate attractiveness as a potential confound.

Hirability measure

After reading through the application, participants were asked to review the following two job positions:

Librarian

The librarian will work in the campus library. He or she will assist students in finding books and strive to maintain a quiet and serene atmosphere for the comfort of the student body.

Campus security patrol

The campus security patrol will patrol the residence halls. He or she will check-in outside civilians and enforce rules and regulations.

Hirability for the librarian and campus patrol positions was measured with two statements: “I think this candidate is a good fit for the librarian/campus patrol position” and “I would personally hire this candidate for the librarian/campus patrol position,” α = .89 and α = .93, respectively (1 = strongly disagree to 7 = strongly agree).

Sex-type ratings

Participants indicated the degree to which they found the candidate to be feminine (“I think this candidate is feminine”) and masculine (“I think this candidate is masculine”) on two separate (1 = strongly disagree to 7 = strongly agree) scales. Then, we computed the sex-type score (i.e., the degree to which the candidate was perceived to be masculine-typed or feminine-typed) by subtracting the masculinity score from the femininity score.

Results

Hirability for feminine and masculine positions

We analyzed the data using a 3 (target race: Asian, White, or Black) × 2 (target sex: man or woman) × 2 (participant sex: man or woman) × 2 (target name: stereotypical or non-stereotypical) × 2 (position: librarian vs. campus patrol) mixed-measures ANOVA with the final factor within-subjects. Participant gender did not moderate any of the predicted effects, all ps > .06.¹

As predicted, the position × target sex effect, F(1, 267) = 102.80, p < .001, ηρ² = .28, and position × target race effect, F(2, 267) = 12.51, p < .001, ηρ² = .09, were significant. As shown in Table 3, women were perceived to be more hirable for the feminine position than men, t(285) = 8.16, p < .001, d = 0.97, and men were perceived to be more hirable for the masculine position than women, t(285) = 9.31, p < .001, d = 1.09. As predicted, Asians were perceived to be more hirable for the feminine position than Whites, p = .01, d = 0.46, or Blacks, p = .01, d = 0.54. However, Whites were not perceived to be significantly more hirable for the feminine position than Blacks, p = .58.² Conversely, Asians were perceived to be less hirable for the masculine position than Whites, p = .01, d = 0.55, and Blacks, p < .001, d = 0.83. However, Whites were perceived to be only marginally less hirable for the masculine position than Blacks, p = .07. There were no other significant effects.

Table 3.

Hirability for Feminine and Masculine Positions by Gender, Race, and Demographic Group (Studies 2 and 3).

Level of analysis	Feminine position (Study 2)	Masculine position (Study 2)	Feminine position^a (Study 3)	Masculine position^a (Study 3)
Gender
Woman	5.45 (1.02)_a	3.30 (1.41)_a	5.46 (1.04)_a	3.06 (1.37)_a
Man	4.33 (1.28)_b	4.81 (1.35)_b	4.63 (1.40)_b	4.69 (1.55)_b
Race
Asian	5.38 (0.99)_a	3.20 (1.48)_a	5.36 (1.11)_a	3.38 (1.56)_a
White	4.84 (1.34)_b	4.05 (1.62)_b	5.07 (1.23)_a	3.86 (1.62)_b
Black	4.75 (1.32)_b	4.41 (1.42)_c	4.76 (1.44)_b	4.28 (1.72)_c
Demographic group
Asian woman	5.76 (0.74)_a	2.78 (1.52)_a	5.62 (0.88)_a	2.78 (1.15)_a
White woman	5.47 (1.02)_a	3.14 (1.39)_a	5.64 (0.87)_a	3.02 (1.28)_a,b
Black woman	5.28 (1.13)_a,b	3.71 (1.27)_b	5.11 (1.25)_b	3.38 (1.59)_b
Asian man	4.94 (1.07)_b	3.70 (1.31)_b	5.06 (1.28)_b	4.08 (1.68)_c
White man	4.20 (1.32)_c	4.97 (1.29)_c	4.50 (1.28)_c	4.70 (1.49)_d
Black man	4.20 (1.29)_c	5.14 (1.10)_c	4.42 (1.54)_c	5.16 (1.34)_d

Means shown are collapsed across the height and weight and control conditions.

Table 4.

Perceived Femininity, Masculinity, and Sex-Type Scores by Target Gender, Race, and Demographic Group (Studies 2 and 3).

Level of analysis	Femininity (Study 2)	Masculinity (Study 2)	Sex-type (Study 2)	Femininity^a (Study 3)	Masculinity^a (Study 3)	Sex-type^a (Study 3)
Gender
Woman	5.86 (0.87)_a	2.15 (0.89)_a	3.71 (1.63)_a	5.71 (0.97)_a	2.20 (1.02)_a	3.51 (1.89)_a
Man	2.46 (1.24)_b	5.45 (1.15)_b	−2.99 (2.23)_b	2.66 (1.16)_b	5.29 (1.07)_b	−2.63 (2.08)_b
Race
Asian	4.65 (1.93)_a	3.04 (1.72)_a	1.61 (3.56)_a	4.59 (1.77)_a	3.27 (1.76)_a	1.32 (3.44)_a
White	4.13 (1.99)_a	3.85 (1.89)_b	0.28 (3.84)_b	4.19 (1.78)_a,b	3.78 (1.89)_b	0.42 (3.60)_a,b
Black	4.08 (2.04)_a	4.01 (2.02)_b	0.07 (3.99)_b	3.89 (1.98)_b	4.06 (1.87)_b	−0.18 (3.79)_b
Demographic group
Asian woman	6.00 (0.76)_a	1.86 (0.74)_a	4.14 (1.43)_a	5.88 (0.88)_a	1.96 (0.76)_a	3.93 (1.48)_a
White woman	5.85 (0.91)_a	2.22 (0.93)_a	3.63 (1.68)_a	5.74 (0.81)_a	2.12 (0.91)_a	3.62 (1.63)_a
Black woman	5.81 (0.88)_a	2.22 (0.89)_a	3.59 (1.67)_a	5.51 (1.16)_b	2.53 (1.27)_b	2.99 (2.36)_b
Asian man	3.08 (1.68)_b	4.40 (1.50)_b	−1.32 (2.99)_b	3.08 (1.29)_c	4.81 (1.28)_c	−1.73 (2.41)_c
White man	2.38 (1.04)_c	5.50 (0.94)_c	−3.12 (1.92)_c	2.67 (0.95)_d	5.41 (0.92)_d	−2.75 (1.72)_d
Black man	2.28 (1.13)_c	5.86 (0.85)_c	−3.58 (1.76)_c	2.31 (1.13)_e	5.56 (0.90)_d	−3.25 (1.91)_d

Means shown are collapsed across the height and weight and control conditions.

Examining the Mechanism With Sex-Type Ratings

We used the sex-type ratings to explore whether both sex and race separately influenced perceptions of masculinity and femininity, which, in turn, affected hirability for the masculine and feminine positions. For the target sex mediations, we used binary categories (Man = 0 and Woman = 1). Following the recommended processes for mediation with a multi-categorical independent variable (Aiken & West, 1991; Hayes & Preacher, 2014), we conducted our target race mediation analyses using indicator coding. First, we created two dummy variables (d1 and d2). Asians were our control group because they were the baseline “most feminine” demographic identity. Additionally, because we found no significant difference in hirability for the gendered positions between Whites and Blacks, we focused on the contrasts between Asians and Whites, and between Asians and Blacks. Each dummy code was set to 0 for Asians (e.g., d1 = 0 and d2 = 0). Furthermore, one dummy code was set to 1 for Whites (e.g., d1 = 1 and d2 = 0), and the contrasting dummy code was set to 1 for Blacks (e.g., d1 = 0 and d2 = 1).

Feminine position (librarian)

Female targets were associated with a more feminine (less masculine) sex-type (B = 6.70, p < .001; confidence interval [CI] = [6.2471, 7.1529]). Further, a more feminine sex-type was associated with hirability for the librarian position (B = 0.20, p < .001; CI = [0.1376, 0.2687]). Sex-type mediated the effect of target sex on hirability for the librarian position, and the conditional indirect effect of sex-type was significant (indirect effect = 1.36, CI = [0.8912, 1.8487]; 10,000 bootstrap iterations; Figure 1A).

Figure 1.

Mediation of candidate race on hirability for librarian position via perceived sex-type (Study 2). (A) The effect of target sex on librarian position. (B) The effect of target race on librarian position.

Compared to Asians, White targets (B = −1.33, p = .04; CI = [−2.5755, −0.0826]) and Black targets (B = −1.54, p = .02; CI = [−2.7903, −0.2940]) were associated with a more masculine (less feminine) sex-type. Further, a more feminine sex-type was positively associated with hirability for the librarian position (B = 0.17, p < .001; CI = [0.1380, 0.2043]). Sex-type mediated the effect of race on hirability for the librarian position, and the conditional indirect effect of sex-type reached significance for both White (indirect effect = −.23, CI = [−0.4411, −0.0247]; 10,000 bootstrap iterations) and Black targets (indirect effect = −.26, CI = [−0.4847, −0.0596]; 10,000 bootstrap iterations). A feminine sex-type was required for the position and Asians were perceived to be more strongly feminine-typed than all other racial groups (Figure 1B).

Masculine position (security patrol)

Male targets were associated with a more masculine (less feminine) sex-type (B = 6.70, p < .001; CI = [6.2471, 7.1529]). Further, a more masculine sex-type was associated with hirability for the security patrol position (B = −0.31, p < .001; CI = [−.3891, −.2407]). Sex-type mediated the effect of target sex on hirability for the security patrol position, and the conditional indirect effect of sex-type was significant (indirect effect = −2.11, CI = [−2.6297, −1.5521]; 10,000 bootstrap iterations; Figure 2A).

Figure 2.

Mediation of candidate race on hirability for security patrol position via perceived sex-type (Study 2). (A) The effect of target sex on security patrol position. (B) The effect of target race on security patrol position.

Compared to Asians, White targets (B = −1.33, p = .04; CI = [−2.5755, −0.0826]) and Black targets (B = −1.54, p = .02; CI = [−2.7903, −0.2940]) were associated with a more masculine (less feminine) sex-type. Further, a more masculine sex-type was positively associated with hirability for the security patrol position (B = −0.24, p < .001; CI = [−0.2747, −0.2011]). Sex-type mediated the effect of race on hirability for the security patrol position, and the conditional indirect effect of sex-type reached significance for both White (indirect effect = .32, CI = [−0.0356, 0.6092]; 10,000 bootstrap iterations) and Black targets (indirect effect = .37, CI = [0.0773, 0.6741]; 10,000 bootstrap iterations). A masculine sex-type was required for the position, and Asians were perceived to be less masculine-typed than all other racial groups (Figure 2B).³

Study 3: Exploring Status, and Height and Weight as an Alternative Explanation

Study 2 found that both biological sex and race contributed to perceptions of a job candidates’ relative sex-typing. Further, this sex-typing influenced whether the candidate was perceived to be hirable for a masculine or feminine occupational position. In Study 3, we seek to replicate the findings from Study 2, while also testing two plausible alternative explanations for this effect.

First, the librarian position may be perceived to be a higher-status position than the security patrol position. Thus, it is plausible that Asians were matched to the higher-status position due to their relatively high socioeconomic status in society (as compared to Whites and Blacks; see “Earnings” section, Bureau of Labor Statistics, 2011). To account for this plausible alternative explanation, we attempted to hold status constant in the manipulation in Study 3. As in Study 2, we provided a cover story, such that all candidates were college students (with equal levels of educational attainment) looking for work study positions to fund their college education. In Study 3, to account for perceptions of different earnings potential for each position, we told participants that each position paid the exact same salary (US$9.00/hr). Finally, we measured the level of status that each participant attributed to each position. We hypothesized that the match between candidate and job position would be due to perceptions of the candidate’s masculinity and femininity (in support of the gender profiling theory), even after controlling for perceptions of status.

Second, people may perceive that the security patrol position requires a candidate who is large and sturdy. Data suggest that Blacks may be larger than Asians within the United States. For example, 35.6% of Blacks are obese compared to 10.7% of Asians (Mendes, Newport, & McGeeney, 2012).⁴ Thus, it is possible that Blacks (vs. Asians) were matched to the security patrol position because they are perceived to have the height and weight requirements for the job. To test this alternative explanation, we included a “Height & Weight” condition where we listed identical height and weight information for all candidates on their student application. If the matching process is driven by height and weight, rather than masculinity and femininity, we would expect that Blacks would only be perceived to be more hirable for the security patrol position when this height and weight information is not on the application.

Participants and Procedure

Four hundred sixty-one participants were recruited from Amazon Mechanical Turk and paid 50 cents to participate in a short online survey. Forty-two participants were excluded after incorrectly identifying the race and/or gender of the target and/or incorrectly answering an attention check question (“Please select the answer choice labeled blue”) leaving a total sample of 419 participants (266 women; 318 White, 17 Black, 41 Asian, 43 other; M_age = 30.75).

Manipulation of candidate sex and race

Consistent with the manipulation described in Study 2, participants were asked to review an application of an Asian, White, or Black, male or female job candidate for two available college work study positions, campus librarian (feminine) and campus security patrol (masculine). Consistent with Study 2, race and sex were manipulated through check boxes on the application. However, in this study, we used both a stereotypical name (Ming Hoa and Ming Lee) and a non-stereotypical name (Mark or Monica) for the Asian man and woman. In the Height and Weight information condition, we listed the female (5′4, 138) and male (5′9, 169) candidates’ height and weight information, which reflected the 50th percentile height and weight for 19-year-olds in the United States (US Department of Health and Human Services, 2012, Tables 2 and 8). In the control condition, the height and weight information was left off of the application.

Hirability measure

Consistent with Study 2, participants then rated the candidate’s hirability for the librarian and campus patrol position. Hirability for the librarian and campus patrol positions was measured with two statements: “I think this candidate is a good fit for the librarian/campus patrol position” and “I would personally hire this candidate for the librarian/campus patrol position,” α = .91 and α = .94, respectively (1 = strongly disagree to 7 = strongly agree).

Sex-type ratings

Participants indicated the degree to which they found the candidate to be feminine (“I think this candidate is feminine”) and masculine (“I think this candidate is masculine”), on two separate (1 = strongly disagree to 7 = strongly agree) scales. We then computed the sex-type score (i.e., the degree to which the candidate was perceived to be masculine-typed or feminine-typed) by subtracting the masculinity score from the femininity score.

Status measure

Finally, the participants indicated how high status they believed each position to be (1 = extremely low status to 7 = extremely high status).

Results

Hirability for feminine and masculine position

We analyzed the data using a 3 (target race: Asian, White, or Black) × 2 (target sex: man or woman) × 2 (participant sex: man or woman) × 2 (height and weight information: control vs. information) × 2 (target name: stereotypical vs. non-stereotypical) × 2 (position: librarian vs. campus patrol) mixed-measures ANCOVA with the final factor within-subjects. Because the librarian position was perceived to be a higher-status position (M = 4.55, SD = 1.04) than the security patrol position (M = 3.96, SD = 1.27), t(418) = 7.52, p < .001, we also added the status scores as covariates.⁵ Target name (stereotypical vs. non-stereotypical) did not moderate any of the predicted effects, all Fs < .79, all ps > .46. Target name was collapsed across conditions in all subsequent analyses.

Consistent with Study 2, the Position × Target sex effect, F(1, 391) = 121.17, p < .001, ηρ² = .24, and Position × Target race effect, F(2, 391) = 10.52, p < .001, ηρ² = .05, were significant. However, contrary to the height and weight alternative explanation, the three-way height and weight information by position by target race effect did not reach significance, F(2, 391) = 0.43, p = .65 (Table 3).⁶ No other effects were significant.

As shown in Table 3, female targets were perceived to be more hirable for the feminine position than male targets, t(416) = 6.86, p < .001, d = 0.67, and male targets were perceived to be more hirable for the masculine position than female targets, t(416) = 11.36, p ≤ .001, d = 1.18.

As predicted, Asian targets were perceived to be more hirable for the feminine position than the White targets, p = .055, and more hirable than the Black targets, p < .001, d = 0.47. Further, the White targets were perceived to be more hirable for the feminine position than the Black targets, p = .04, d = 0.23. Also as predicted, Black targets were perceived to be significantly more hirable for the masculine position than the White targets, p = .03, d = 0.25, and the Asian targets, p < .001, d = 0.12. Further, the White targets were perceived to be more hirable for the masculine position than the Asian targets, p = .02, d = 0.30.⁷

Examining the Mechanism With Sex-Type Ratings

We used the sex-type ratings to explore whether Asians relative hirability for the feminine position and Blacks relative hirability for the masculine position could be empirically explained by peoples’ perceptions of their sex-types (masculine or feminine) controlling for status. Following the recommended processes for mediation with a multi-categorical independent variable (Aiken & West, 1991; Hayes & Preacher, 2014), we conducted our mediation analyses using the processes described in Study 2.

Feminine positions (librarian)

Female targets were associated with a more feminine (less masculine) sex-type (B = 6.19, p < .001; CI = [5.8108, 6.5733]). Further, a more feminine sex-type was associated with hirability for the librarian position (B = 0.23, p < .001; CI = [0.1750, 0.2685]). Sex-type mediated the effect of target sex on hirability for the librarian position, and the conditional indirect effect of sex-type was significant (indirect effect = 1.43, CI = [1.0400, 1.8142]; 10,000 bootstrap iterations; Figure 3A).

Figure 3.

Mediation of candidate race on hirability for librarian position via perceived sex-type (Study 3). (A) The effect of target sex on librarian position. (B) The effect of target race on librarian position.

Compared to Asians, White (B = −0.90, p = .04; CI = [−1.7581, −0.0354]) and Black targets (B = −1.50, p < .001; CI = [−2.3679, −0.6296]) were associated with a more masculine (less feminine) sex-type. Further, a more feminine sex-type was associated with hirability for the librarian position (B = 0.15, p < .001; CI = [0.1244, 0.1854]). Sex-type mediated the effect of race on hirability for the librarian position, and the conditional indirect effect of sex-type reached significance for both White (indirect effect = −.1389, CI = [−0.2821, −0.0131]; 10,000 bootstrap iterations) and Black targets (indirect effect = −.23, CI = [−0.3977, −0.0993]; 10,000 bootstrap iterations). A feminine sex-type was required for the position, and Asians were perceived to be more strongly feminine-typed, than all other racial groups (Figure 3B).

Masculine positions (security patrol position)

Male targets were associated with a more masculine (less feminine) sex-type (B = 6.14, p < .0001; CI = [5.7610, 6.5267]). Further, a more masculine sex-type was associated with hirability for the security patrol position (B = −0.35, p < .001; CI = [−0.4133, −0.2901]). Sex-type mediated the effect of target sex on hirability for the security patrol position, and the conditional indirect effect of sex-type was significant (indirect effect = −2.16, CI = [−2.5513, −1.7734]; 10,000 bootstrap iterations; Figure 4A).

Figure 4.

Mediation of candidate race on hirability for security patrol position via perceived sex-type (Study 3). (A) The effect of target sex on security patrol position. (B) The effect of target race on security patrol position.

Compared to Asians, White targets (B = −0.93, p = .03; CI = [−1.7853, −0.0680]) and Black targets (B = −1.46, p < .001; CI = [−2.3367, −0.6024]) were associated with a more masculine (less feminine) sex-type. Further, a more masculine sex-type was associated with hirability for the security patrol position (B = −0.28, p < .001; CI = [−0.3123, −0.2446]). Sex-type mediated the effect of race on hirability for the security patrol position, and the conditional indirect effect of sex-type reached significance for both White (indirect effect = .26, CI = [0.0245, 0.5027]; 10,000 bootstrap iterations) and Black targets (indirect effect = .41, CI = [0.1646, 0.6688]; 10,000 bootstrap iterations). A masculine sex-type was required for the position, and Asians were perceived to be less masculine-typed than all other racial groups (Figure 4B).

Study 3 reaffirmed that gendered person–position fit perceptions for demographic groups are determined by the level of femininity and/or masculinity associated with a candidate’s biological sex and race and the level of femininity and/or masculinity required for the particular position. In Study 3, Asians were perceived to be the most hirable for the feminine position, and Blacks were perceived to be the most hirable for the masculine position. Collectively, these experimental studies show that both the gender of a person’s race and the gender of a person’s biological sex are crucial to determine their perceived fit for gendered positions.

Study 4: Gender Profiling in Negotiations

To increase the robustness of our assertions, we need to establish that our effects are not specific to the librarian and security positions. In Study 4, we used a single position, a “negotiator,” and described the position in either a masculine- or feminine-typed manner. We predicted that Blacks would have an advantage for the position when it was described using masculine terms, whereas Asians would have an advantage for the position when it was described using feminine terms.

Participants and Procedure

Three hundred thirty-four participants were recruited from Amazon Mechanical Turk and paid 45 cents to participate in a short online survey. Forty-seven participants were excluded after incorrectly identifying the race and/or sex of the target, leaving a total sample of 287 participants (178 women; 218 White, 16 Black, 27 Asian, 26 Other; M_age = 30.87).

Manipulation

Participants were asked to review an application of an Asian, White, or Black, male or female job candidate for two available college work study positions. The manipulation of candidate race and sex was consistent with the method described in Study 3. Both work study positions were described as “negotiator” positions; however, Position A required stereotypically masculine qualities and Position B required stereotypically feminine qualities. For example, Position A required that the candidate have a “dominant and/or strong mannered way of resolving disputes” and an “assertive or forceful disposition.” Position B required that the candidate have a “delicate and/or mild mannered way of resolving disputes” and a “soft or gentle disposition” (see supplemental materials for the complete stimulus prompt). Pretests (N = 48; 23 women) indicated that participants perceived Position A (M = 2.19, SD = 0.82) to be significantly more masculine than Position B (M = 3.83, SD = 0.66) on a 1 = very masculine to 5 = very feminine scale. Additionally, Position A was perceived to be significantly more masculine than the 3 (neutral) scale midpoint, t(47) = 6.90, p < .001, while Position B was perceived to be significantly more feminine than the 3 (neutral) scale midpoint, t(47) = 8.71, p < .001, indicating that each position was perceived as sufficiently masculine and feminine, respectively.

Measures

After reading through the application, participants rated the candidate’s hirability for the feminine-typed and masculine-typed negotiator position. Hirability for the feminine- (described as Position A) and masculine-typed (described as Position B) positions was measured with two statements: “I think this candidate is a good fit for Position (A/B)” and “I would personally hire this candidate for Position (A/B),” α = .85 and α = .85, respectively (1 = strongly disagree to 7 = strongly agree).

Results

We analyzed the data using a 3 (target race: Asian, White, or Black) × 2 (target sex: man or woman) × 2 (participant sex: man or woman) × 2 (target name: stereotypical or non-stereotypical) × 2 (position: feminine vs. masculine) mixed-measures ANOVA with the final factor within-subjects. Participant gender did not moderate any of the predicted effects, all ps > .91.

Consistent with Studies 2 and 3, the Position × Target sex effect, F(1, 263) = 10.15, p = .01, ηρ² = .04, and Position × Target race effect, F(2, 263) = 6.49, p = .01, ηρ² = .05, were significant. Women (M = 5.06, SD = 1.30) were perceived to be more hirable for the feminine position than men (M = 4.38, SD = 1.53), t(285) = 4.08, p < .001, d = 0.48. Surprisingly, men (M = 4.49, SD = 1.48) were not perceived to be significantly more hirable for the masculine position than women (M = 4.25, SD = 1.64), t(285) = 1.32, p = .19. As predicted, Asians (M = 5.16, SD = 1.29) were perceived to be more hirable for the feminine position than Whites (M = 4.64, SD = 1.52), t(186) = 2.52, p = .01, d = 0.37, and Blacks (M = 4.39, SD = 1.47), t(186) = 3.79, p < .001, d = 0.56. Whites were not perceived to be significantly more hirable for the feminine position than Blacks, t(196) = 1.16, p = .25. Further, Blacks (M = 4.63, SD = 1.53) were perceived to be more hirable for the masculine position than Asians (M = 4.08, SD = 1.62), t(186) = 2.38, p = .02, d = 0.35. Finally, Whites (M = 4.39, SD = 1.51) did not differ in hirability from Asians, t(186) = 1.36, p = .18, or Blacks, t(196) = 1.10, p = .27.

The overall pattern of Study 4 replicated the prior studies, with both biological sex and race determining hirability and person–position fit.

Study 5: Enhancing the External Validity

To increase the external validity of our findings, we conducted a final study that enhanced the realism of the hiring process. For example, in typical hiring situations, a candidate would be hired for a single position, rather than choosing between two vastly different occupations. Furthermore, employers would most likely require a resume as well as the application form we used in Studies 2 to 4. Importantly in Study 5, we also used a between-subjects design, in which participants were randomly assigned to evaluate an Asian, White, or Black male or female candidate’s application form and resume for a single negotiation specialist position, which was either described in masculine or feminine terms. Consistent with Study 4, we predicted that Blacks would have an advantage for the position when it was described using masculine terms, whereas Asians would have an advantage for the position when it was described using feminine terms.

Participants and Procedure

Eight hundred forty-four participants were recruited from Amazon Mechanical Turk and paid 45 cents to participate in a short online survey. One hundred thirty-nine participants were excluded after incorrectly identifying the race and/or gender of the target, leaving a total sample of 705 participants (276 women, 5 sex unidentified; 486 White, 40 Black, 129 Asian, 49 Other, 1 race unidentified; M_age = 32.08).

Manipulation

Participants were asked to review an application form and resume of an Asian, White, or Black, male or female job candidate for an available college work study position. The manipulation of candidate race and sex on the application form was consistent with the procedure in Studies 3 and 4. The resume was constructed to reflect a believable candidate. Participants learned that the candidate worked in four prior positions (e.g., office assistant), was a member of three clubs (e.g., Media and Journalism Club), and had a 3.12 grade-point average (GPA) in the Department of General Studies at Akron College. In addition to the race and gender checkboxes on the application, as well as the candidate names, race was further manipulated through candidate work experience and activities. The candidates indicated that they were members of a race-based student union (e.g., Black Student Union) and had held the position of a coordinator of a race-based American heritage parade (e.g., Annual Asian American Heritage Parade). In contrast to Studies 2 through 4, participants were assigned to view one of the two negotiation positions to mimic a real-world hiring decision.

Measures

Hirability for the feminine and masculine negotiation positions was measured with two statements: “I think this candidate is a good fit for this position” and “I would personally hire this candidate for this position,” α = .96 and α = .93, respectively (1 = strongly disagree to 7 = strongly agree).

Results

We analyzed the data using a 3 (target race: Asian, White, or Black) × 2 (target sex: man or woman) × 2 (participant sex: man or woman) × 2 (target name: stereotypical or non-stereotypical) × 2 (position: feminine vs. masculine) between-subjects ANOVA. Neither participant gender, all ps > .37, nor stereotypical name, all ps > .51, moderated any of the predicted effects, so they were dropped from all subsequent analyses.

As predicted, the Position × Target race effect was significant, F(2, 693) = 5.31, p = .01, ηρ² = .02. However, the Position × Target gender effect did not reach significance, F(1, 693) = 1.37, p = .24. Asians (M = 4.33, SD = 1.49) were perceived to be less hirable for the masculine position than Blacks (M = 4.81, SD = 1.30), t(227) = 2.62, p = .01, d = 0.34, but not significantly less so than Whites (M = 4.61, SD = 1.47), t(219) = 1.45, p = .15. Furthermore, there was no significant difference in hirability between Whites and Blacks, t(242) = 1.10, p = .27.

Asians (M = 5.56, SD = 1.01) were perceived to be marginally more hirable for the feminine position than Blacks (M = 5.28, SD = 1.29), t(234) = 1.86, p = .06, d = 0.24, but not significantly more so than Whites (M = 5.41, SD = 0.96), t(251) = 1.14, p = .25. Furthermore, there was no significant difference in hirability between Whites and Blacks, t(225) = 0.91, p = .36, or Whites and Asians, p = .13, for the feminine position.

Meta-ANOVA of Studies 2 to 5

Recently, researchers have called for meta-analytic techniques to assess the replicability of psychological effects (see Asendorpf et al., 2013). To assess the robustness of the findings, we conducted a meta-analysis of Studies 2 through 5 using meta-ANOVA techniques. Meta-ANOVAs synthesize two or more studies within a research paper and accurately account for between-study variation (McShane & Böckenholt, 2013). We used McShane and Böckenholt’s online web portal for computing meta-ANOVA estimates (specifically, meta-condition estimates, contrast estimates, and standard errors). Then, using contrast estimates and standard errors, we computed z scores and p values for each contrast test.

The meta-analytic estimates revealed consistent effects across the four studies. Female targets were perceived to be more hirable than male targets for the feminine position, p < .001, and male targets were perceived to be more hirable than female targets for the masculine position, p < .001. Asian targets were perceived to be significantly more hirable for the feminine position than Blacks, p < .001, and more so than Whites, p = .055. However, there was no perceived difference in hirability for the feminine position between Whites and Blacks, p = .19. Black targets were perceived to be significantly more hirable for the masculine position than Asians, p = .02. However, there were no significant differences between Whites and Asians, p = .12, and Whites and Blacks, p = .41, for the masculine position. Thus, the most robust finding throughout the studies was the predicted one: The demographic groups that were perceived to embody masculinity (e.g., Blacks) and/or femininity (e.g., Asians) were perceived to be more hirable for the masculine or feminine positions, accordingly.

General Discussion

The current research introduced the concept of gender profiles and conceptually connected it to both demographic and occupational groups to add new insights into the processes of person–position fit. First, we found evidence that demographic groups vary on how masculine or feminine they are perceived to be. In Study 1, we found that race and gender independently influence the gender profile of individuals. Consequently, we found matches between the gender profiles of Asians and feminine-typed occupations, and the gender profiles of Blacks and masculine-typed occupations. Studies 2 to 5 found that masculine-typed demographic group members (Black men and women) were perceived to be more hirable for the highly masculine position, whereas feminine-typed demographic group members (Asian women and men) were perceived to be more hirable for the highly feminine position. We also ruled out status and body size perceptions as alternative accounts for the gender profiling effects.

The current studies make a significant contribution to the literature on person–position fit, diversity, and gendered races. First and foremost, we demonstrate that gender of one’s race as well as one’s biological sex creates one’s gender profile that offers critical information for predicting person–position fit perceptions. By taking into account the perceived femininity or masculinity of demographic groups, we can more precisely determine which individuals will be seen as a good or bad fit for feminine or masculine positions.

Limitations and Opportunities for Future Research

The gender profile paradigm is a fertile ground for exploring the femininity and masculinity of other demographic groups beyond race and biological sex. For example, Eagly and Kite (1987) showed that the U.S.-based stereotypes of different nationalities embodied agentic or communal—and therefore, masculine and feminine—connotations. By these designations, candidates from Sweden may be funneled into feminine positions in the United States, whereas candidates from Iran may be funneled into masculine positions.

Interestingly, Eagly and Kite (1987) also showed that the stereotypes of these nationalities tended to best match the stereotypes of the nationalities’ male members. In other words, this suggests that the male members are perceived to be most prototypical of their nationalities, and therefore, their feminine and masculine connotations are applied across the entire nationality. Consistent with this line of thinking, Black women are perceived to be less prototypical of their racial group than Black men (Purdie-Vaughns & Eibach, 2008; Sesko & Biernat, 2010). However, a recent study suggests that Asian men are perceived to be less prototypical of their racial group than Asian women (Schug, Alt, & Klauer, 2015). Because Asians are perceived to be feminine, Asian male masculinity is not perceived to epitomize the Asian identity. Future research should disentangle this discrepancy and determine whether prototypicality is determined by androcentric hegemony as Eagly and Kite (1987) suggest or gendered race theory as was shown by Schug et al. (2015).

Further, there is an opportunity for future research to explore whether there are other factors beyond status and size that can account for the person–position fit that we did not explore in the current text. The stereotypes that pertain to both races and occupations are plentiful, making it difficult to account for an exhaustive list of stereotypes and alternative explanations in the current text.

Finally, we were limited in the number of positions that we were able to test (librarian vs. security patrol; feminine vs. masculine negotiator) because with every new study, we tried to keep the context constant and sequentially rule out potential alternative accounts from the preceding study. Future research should explore the robustness of the phenomenon with more gender-typed occupations. Take the example of science, technology, engineering, and mathematics (STEM) positions: They may be perceived to be stereotypically masculine because they require rationality, intelligence, and competence. However, Asians, who are often stereotyped as having these qualities, may be perceived to be more hirable to STEM positions than Blacks. Nonetheless, although these cognitive traits (e.g., analytical, quantitatively skilled) were once thought to be masculinized, Cejka and Eagly (1999) showed only a small (albeit significant) difference between participants’ perceptions of the likelihood of the average man (M = 3.44) versus the average woman (M = 3.26) to embody these traits. Thus, although Asians may be perceived to be a better fit for STEM positions, these positions may not be perceived as masculine as they were once perceived to be.

Another possibility is that there are different types of masculinities and femininities rather than one unitary masculine and feminine dimension. Thus, the stereotypes associated with each racial group may coincide with a few, but not all of these femininities and masculinities. For example, Cejka and Eagly (1999) illustrated several different masculine and feminine physical (athletic vs. dainty, respectively), personality (aggressive vs. nurturing, respectively), and cognitive (mathematical vs. creative, respectively) gender-stereotypic dimensions. An exemplar-based model would suggest that exposure to a position that requires physical and personality-based masculinity might shift a perceiver’s attention to Blacks (vs. Asians; Smith & Zarate, 1992). However, that perceiver may fundamentally redefine masculinity when met with a position that requires cognitive masculinity, such that they then perceive Asians to be more masculine.

Although we found two independent gender profiling effects for race and sex, our research informs studies that investigate intersectionality. Intersectionality research emerged to study the interplay of different demographic identities on important legal and economic outcomes. Leveraging the legal experiences of Black women, Kimberlé Crenshaw (1989/1993) initially championed intersectional ideas to understand the discriminatory experiences that Black women shared with White women and Black men, versus experienced on their own. More recently, Biernat and Sesko (2013) found that gender bias was only evident in intersex pairs involving White, but not Black, women. If the masculinity associated with the Black race influences the masculinity in a Black woman’s gender profile, Black women may be less subject to the feminine expectations and gender-based discrimination that White women face (see also Goff et al., 2008; Livingston, Rosette, & Washington, 2012). Notably, in Study 1, we found that the Black woman’s sex-type was closer in magnitude to the sex-type for White and Black men, rather than Asian and White women.

Also in Study 1, the Asian man’s sex-type was closer to the sex-type of Asian and White women. Thus, our perspective can even inform the study of social groups, such as Asian men, that have been understudied through the classical intersectionality lens. Future research should continue to determine the unique gender and racial experiences of intersectional targets, while considering how their gender profiles may affect these nuanced experiences. Of note, even though we found main effects for race and sex, there are suggestions in our own data that the experience of women was not uniform across races and the experience of different racial groups was not always consistent across sexes.

Finally, the effect sizes in our within-subjects studies were stronger than the effect sizes in our between-subjects study. This could indicate that the effect of gender profiling is most prevalent in situations where a candidate is placed in one of many task assignments or positions. For example, the effect may be bolstered for candidates who are first accepted in a cohort within the organization and then allocated to one of many available job opportunities.

Conclusion

The workplace is growing increasingly diverse (Bureau of Labor Statistics, 2011). Although an abundance of research has focused on the orchestrating role of gender in social sanctioning and human behavior, the current research broadens and extends these perspectives by introducing the concept of the gender profile to the conversation. The gender profile perspective suggests the need to incorporate the fact that any demographic characteristic, not just biological sex, can contribute to one’s gender profile. By conceiving of people as having gender profiles based on a range of demographic characteristics and conceiving positions as having preferred gender profiles, we offer a new perspective on personnel selection and person–position fit that can shed light on how occupational gender and racial segregation persist.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Supplemental Material

The online supplemental material is available at .

Notes

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