Good at school = successful on the job? Explaining gender differences in scholastic and vocational success

Personality and Individual Differences 105 (2017) 107–115

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Good at school = successful on the job? Explaining gender differences in scholastic and vocational success Ricarda Steinmayr a,⁎, Ursula Kessels b a b

Technical University Dortmund, Dortmund 44227, Germany Freie Universität Berlin, 14195 Berlin, Germany

a r t i c l e

i n f o

Article history: Received 13 June 2016 Received in revised form 13 September 2016 Accepted 18 September 2016 Available online xxxx Keywords: Personality Academic achievement Career success Human gender differences

a b s t r a c t Whereas girls and women outperform men in academic success, men outperform women on vocational success criteria. The present study sought to explain these opposing gender gaps by hypothesizing that, to some extent, different personality traits would promote success in the school and business environments. Using two samples comprised of academic track 11th graders (236) and adult professionals (124), we tested whether gender differences in personality partly explained the opposing gender gaps in academic and vocational success. Questionnaires measuring the Big Five, personality facets, intelligence, and GPA or vocational success criteria were used. Analyses revealed that intelligence, Conscientiousness, and Need for Achievement (AC) predicted both school and vocational success. Agreeableness and Need for Aggression (AG) (negatively) were associated with only academic success. Need for Affiliation (AF) and Need for Dominance (DO) predicted only professional success. Mediation analyses showed that AC, Openness to Experience, Agreeableness, and Conscientiousness (girls scored higher), and AG (girls scored lower) mediated gender differences in academic success. Gender differences in vocational success were mediated by DO (men scored higher), whereas AF (women scored higher) suppressed this relation. The results are discussed with respect to their theoretical and practical implications for understanding gender differences in school and at work. © 2016 Published by Elsevier Ltd.

Whereas men tend to outperform women on vocational success criteria (Joshi, Son, & Roh, 2015), girls and women tend to outperform men in academic success (Voyer & Voyer, 2014). The reasons for these opposing gender gaps are not well understood. We propose that personality traits might contribute to explaining these differences by referring to the Person-Environment-Fit hypothesis (PEFH; Caplan, 1987). Personality has recently gained considerable attention as a predictor of both vocational success (Caspi, Roberts, & Shiner, 2005; Judge, Rodell, Klinger, Simon, & Crawford, 2013) and academic achievement (Poropat, 2009). In organizational research, the Person-EnvironmentFit hypothesis (PEFH) (Caplan, 1987) has often been used to explain this relation in vocational settings. It posits that individuals function better in a certain environment when their personality characteristics match the attributes of the environment, i.e. both the situation and person's characteristics contribute to success (Terborg, Richardson, & Pritchard, 1980). Besides other outcomes of the PEFH in the work context, better vocational performance has been discussed (Stern, 1970). Furthermore, some authors have already applied the PEFH to the

⁎ Corresponding author. E-mail addresses: [email protected] (R. Steinmayr), [email protected] (U. Kessels).

http://dx.doi.org/10.1016/j.paid.2016.09.032 0191-8869/© 2016 Published by Elsevier Ltd.

academic context by investigating college students (e.g., Le, Robbins, & Westrick, 2014; Harms, Roberts, & Winter, 2006). Harms et al. (2006) found that a better person-environment fit was associated with higher academic achievement. The PEFH has also been applied to explain gender differences in work success (Young & Hurlic, 2007). Referring to gender theories, gender enactment, person-group fit, and the PEFH, the authors hypothesized that success in an organization depends at least in part on gender-related behaviors and attributes. Indeed, metaanalyses have demonstrated that certain personality traits that have shown gender differences (see Costa, Terracciano, & McCrae, 2001) are related to job success (see Judge et al., 2013) such that men outperform women (see Joshi et al., 2015). Also in line with the PEFH are the ideas depicted in the feminization of school hypothesis. According to this hypothesis, the widespread documented underperformance of boys in school (see Voyer & Voyer, 2014) can be explained by an incompatibility between school-related characteristics and the male gender role, which obstructs boys' performance in school (Heyder & Kessels, 2013; Kessels, Heyder, Latsch, & Hannover, 2014; Skelton, 2012; Verniers, Martinot, & Dompnier, 2016). Indeed, a few studies have already demonstrated that personality traits on which boys and girls differ can explain gender differences in academic achievement in school (see Spinath, Eckert, & Steinmayr, 2014).

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However, some but not all personality traits that are related to academic performance are also associated with vocational success. This idea is in line with the PEFH, which posits that certain personality traits are functional only in certain environments. Furthermore, the feminization of school hypothesis depicts the scholastic environment as a rather female environment (Verniers et al., 2016), whereas the business context is often depicted as a “men's world” (Joshi et al., 2015). However, both environments require certain omnipotent characteristics for success such as intelligence and conscientiousness (Deary, Strand, Smith, & Fernandes, 2007; Judge et al., 2013; Kuncel, Hezlett, & Ones, 2004; Poropat, 2009). Consequently, some personality traits that show gender differences in favor of women should be predictive of scholastic success, whereas some personality traits that show gender differences favoring men should be predictive of vocational success. Summing up, the present study seeks to contribute to explaining the opposing gender gaps in academia and school. We suggest that school and business constitute different environments in which different personality traits are required at least to some extent. We first provide an overview of personality predictors of academic achievement and vocational success. Second, we would like to draw attention to gender differences in personality traits and achievement criteria. We suggest that school is an environment in which, when going beyond the above-mentioned omnipotent variables, success is associated with personality traits that are more typical of women, whereas in a vocational environment, traits that are more generally associated with men predict success. 1. Predictors of academic achievement Intelligence is thought to be strongly associated with school performance and is frequently considered to be the strongest predictor of school performance (Kuncel et al., 2004). The average correlation between the two variables is r = 0.50 (cf. Gustafsson & Undheim, 1996), but the association varies by the operationalization of school performance (Steinmayr, Meißner, Weidinger, & Wirthwein, 2014). Poropat (2009) found a small to medium association between intelligence and grade point average (GPA), whereas intelligence and standardized scholastic performance tests were found to be very highly correlated (Deary et al., 2007). A great deal of recent research has focused on the association between personality traits identified in the Five Factor Model of personality (Goldberg, 1990; McCrae & Costa, 1987) and school performance (for an overview see Poropat, 2009). The five personality traits consist of Neuroticism (N), Extraversion (E), Openness to Experience (O), Agreeableness (A), and Conscientiousness (C). N describes differences in emotional stability or how individuals experience negative feelings. Individuals scoring high on E prefer social situations, are outgoing, talkative, spontaneous, active, positive, as well as dominant. O refers to a person's tendency to enjoy different experiences that are expressions of culture (e.g., aesthetics, values). A refers to the quality of social interactions. Persons scoring high on A put great emphasis on their likeability and friendliness. Finally, individuals who score high on C like to plan and tend to be organized, achievement-oriented, ambitious, dependable, and persistent. In his meta-analysis of the relation between grades and personality, Poropat (2009) found GPA to be weakly associated with O and C. However, the results were moderated by the educational level of the students. In secondary education, GPA was associated with O and C even after controlling for intelligence, with higher correlations with C than with O. Studies on university samples have demonstrated that personality facets are good predictors of college grades (e.g., Noftle & Robins, 2007). Grade point average at the university level was associated with Need for Achievement, Endurance, Understanding, and Organization as measured by the Personality Research Form (PRF). Concerning the NEO-PI-R, the following personality facets were correlated with academic success in post-secondary education: achievement striving, self-

discipline, openness to ideas, competence, and dutifulness. Less is known about the relations between personality facets and scholastic success. A few studies have investigated the link between school performance and different personality facets (De Fruyt, van Leeuwen, de Bolle, & de Clercq, 2008; Smrtnik Vitulić & Zupančič, 2013). Other studies have mainly concentrated on certain personality facets and scholastic success. For example, Duckworth and Seligman (2006) concentrated on self-discipline, whereas Steinmayr and Spinath (2007) focused on the personality facet need for achievement. Only Duckworth and Seligman (2006) controlled for intelligence. All studies demonstrated that the links between certain personality facets and scholastic success are higher than the ones most often found for the Big Five. This observation is in line with Paunonen and Ashton's (2013) results, which demonstrated the superiority of personality facets over broad personality domains such as the Big Five in predicting academic success in college. This finding has already been replicated in student samples (Lounsbury, Sundstrom, Loveland, & Gibson, 2003; Steinmayr & Spinath, 2007). Investigating adolescent school student samples, Lounsbury et al. (2003) found that aggression, need for achievement, and work drive all had stronger relations with school grades than any of the Big Five domains. Thus, when investigating the relation between school performance and academic success, researchers should investigate not only the broad personality traits but also personality facets. 2. Predictors of vocational success Different studies and meta-analyses haven frequently shown that intelligence is an important predictor of vocational success (for an overview, see Schmidt & Hunter, 2004). The average association between intelligence and job success is r = 0.5, which is comparable to the association between intelligence and academic achievement. Different meta-analyses have also verified that personality is an important predictor of vocational success (e.g., Judge et al., 2013). C has frequently been shown to be the most important predictor of the Big Five personality domains with average correlations of around r = 0.30 (Judge et al., 2013; Schmidt & Hunter, 1998). The other Big Five domains were found to display the following correlations with job success: N (r = − 0.10), E (r = 0.20), O (r = 0.08), A (r = 0.17; Judge et al., 2013). Comparable to the findings in the academic context, different authors have recommended that more specific personality traits be used as opposed to broad personality traits because the personality facets demonstrate higher correlations with job success (e.g., Tett, Steele, & Beauregard, 2003). 3. Gender differences in intelligence and personality traits Research reviews and meta-analyses on gender differences in intelligence (see Hyde, 2005) have come to different conclusions when stressing either similarities or differences (Halpern, Beninger, & Straight, 2011). Such results have depended on the use of tests and measurements that capture different dimensions. Most attention in research on gender differences in intelligence has been paid to gender differences in general intelligence. Some authors found that men excel women in general intelligence (e.g., Irwing & Lynn, 2005; Lynn & Irwing, 2004, 2008) but others reported no gender differences (e.g., Halpern et al., 2011; Johnson & Bouchard, 2007) or even depict a female advantage in general intelligence (e.g., Keith, Reynolds, Patel, & Ridley, 2008). Concerning gender differences in broad ability domains women tend to outperform men on some verbal tasks, whereas men outperform women on visuospatial tasks (cf. Hyde, 2005). Meta-analyses on gender differences in personality traits have similarly found only small differences between men and women compared with the individual variation that occurs within genders (Costa et al., 2001; Feingold, 1994) when personality domains are taken into account. A more differentiated pattern has been found at the more finegrained facet level. Women tend to score higher on all facets of N and

R. Steinmayr, U. Kessels / Personality and Individual Differences 105 (2017) 107–115

A as well as on some facets of E (warmth, gregariousness, activity, positive emotions) and on most facets of O (aesthetics, feelings, actions). Men tend to score higher on two facets of E on (assertiveness, excitement seeking) as well as on one facet of O (ideas). No significant gender differences have been found for C except for the facets of order and dutifulness (on which women score higher; Costa et al., 2001). Regarding adolescents, research has found that most of the gender differences that are observed in adulthood have already developed by the age of 17 (De Bolle et al., 2015). This is true for most of the respective facets of N, E, O, and A. However, girls at the age of 17 score higher on most facets of C (except competence), whereas these gender differences (except for dutifulness and order) are usually not observed in adulthood.

4. Gender differences in academic and vocational success The reported gender differences in personality traits that predict scholastic and vocational success might be relevant for explaining two widely discussed gender gaps that work in opposite directions: In American and European countries, female students nowadays outperform male students at all levels of education (DiPrete & Buchmann, 2013): Girls graduate from higher school tracks more often than boys (Spinath et al., 2014); female students now earn a larger proportion of bachelor's and master's degrees (Buchmann & DiPrete, 2006); and for decades, girls have gotten better grades than boys in school (DiPrete & Buchmann, 2013). One important factor for boys' underperformance in school seems to be their lower engagement in school (Downey & Vogt Yuan, 2005; Lam et al., 2012). Research has also identified personality traits such as agreeableness, aggressive behavior, conscientiousness or self-discipline as mediating, at least in part, the relation between gender and grades after controlling for intelligence (Duckworth & Seligman, 2006; de Fruyt et al., 2008; Keiser, Sackett, Kuncel, & Brothen, 2016; Steinmayr & Spinath, 2008; for an overview, see Spinath et al., 2014). Regarding vocational success, the gender pattern goes in the opposite direction as men tend to be more successful in their professional lives: Men tend to earn more than women (e.g., Arulampalam, Booth, & Bryan, 2007; Lips, 2013), hold a higher share of prestigious positions, and are more often employed in prestigious professions (Holst & Schimeta, 2013; Mohan, 2014). This finding holds across domains (OECD, 2012). Given that historically, despite their better grades in school (DiPrete & Buchmann, 2013), women have taken inferior career and educational paths compared with men, the gender gap in professional life tends to be more pronounced in older cohorts than in younger ones (e.g., O'Neill & Polachek, 1993; Powell, Butterfield, & Parent, 2002). But even nowadays, equally well-educated or even better educated younger women tend to take a back seat to men in vocational success (Helbig, 2010; Marini & Fan, 1997). A lot of research has identified factors related to women's underrepresentation in leading positions and their lower earnings, such as gender stereotypes (Eagly & Karau, 2002), the demands of family life provided mostly by women (Eagly & Carli, 2007), women's higher rates of career interruptions (Evers & Sieverding, 2014), and the gender segregation of occupations (Hegewisch, Liepmann, Hayes, & Hartmann, 2010). Thus far, only a few studies have tested whether gender differences in the above-mentioned personality dimensions/facets can actually explain gender differences in vocational success, even when several authors have tested whether “agency” (as a cluster of masculine traits), on which men score higher than women, predicts the salary of men and women in combination with other factors (e.g., Evers & Sieverding, 2014). However, Powell, Goffin, and Gellatly (2011) demonstrated that gender differences in personality are associated with gender differences in hiring rates that favor men. This effect was especially pronounced when personality facets were considered.

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5. Study overview and hypotheses The present study sought to test whether gender differences in personality could account for some of the variance in the opposing gender gaps in academic and vocational success. To accomplish this, we drew a sample of school students and a sample of professionals and took measurements of success, personality, and intelligence. Job success depends to a large extent on a person's academic career (Fischbach, Baudson, Preckel, Martin, & Brunner, 2013). In order to minimize such confounding influences, the student sample consisted of German school students attending the Gymnasium, the highest track, which leads to the Abitur (university entrance certificate); and the adult sample consisted of German adult professionals who had graduated from the same kind of school. First, we expected that some traits (intelligence, conscientiousness, and need for achievement) would predict success in both contexts, whereas the other traits would predict success only in school or at work (Hypothesis 1). Second, we expected gender differences in personality traits and facets (Hypothesis 2; cf. Costa et al., 2001; De Bolle et al., 2015). Third, we expected girls to get better grades and men to have higher vocational success. Besides the straightforward comparison of gender differences in success criteria, it is also important to consider subjects' cognitive potential. It might be the case that men and women show different levels of achievement in relation to their cognitive potential (i.e., they might differ in how their cognitive potential translates into success). Therefore, a more effective way to detect gender differences in success criteria is to investigate whether men and women achieve equally well when controlling for cognitive abilities (cf. Duckworth & Seligman, 2006; Steinmayr & Spinath, 2008). In doing so, we expected that girls would have higher GPAs than boys and that men would show greater vocational success than women when controlling for intelligence (Hypothesis 3). Fourth, we hypothesized that personality traits would mediate the direct effects of gender on both academic and vocational success but that different traits would function as mediators of scholastic and vocational success (Hypothesis 4). 6. Method 6.1. Participants 6.1.1. Sample 1 and procedure 1 The student sample was recruited from a Gymnasium, which is a secondary school that represents the highest track in the German school system. The school was located in a mid-sized town, and its students could be considered the typical population of this type of school in Germany (i.e., the majority were Caucasian from medium to high socioeconomic status homes). Two consecutive cohorts of 236 11th-grade students were tested. Of the tested students, 142 were female and 94 were male. The mean age of the students was 16.77 years (SD = 0.69). Only students excused by a medical certificate did not take part in the testing. Testing took place on a day that was specifically reserved for extracurricular activities. Tests were administered in school. Students were separated into groups of about 20 and tested by trained students and research assistants. The test sessions lasted approximately 5 h, including breaks. Below, only the scales that were relevant for the present article are described. 6.1.2. Sample 2 and procedure 2 The adult sample was a subsample from a larger sample (cf. Amelang & Steinmayr, 2006). The total sample was recruited from the local community when they met two criteria: (a) their first language had to be German, and (b) they had to be employed. A total of 207 adults (106 women and 101 men) were tested. The adult participants were recruited through ads in local magazines, bulletins in different companies, and personal contacts. For the

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present study, we considered only those adults who had completed the Abitur, a school-leaving certificate and school degree that one attains when successfully completing the Gymnasium, the school type that was attended by the student sample (Sample 1). This subsample consisted of 124 adults (64 female and 60 male). The subsample had a mean age of 33.65 years (SD = 3.84). Participants were tested in two sessions, each lasting approximately two and a half hours. After the second test session, participants were paid 40 €. Below, only the scales that were relevant for the present article are described. 6.2. Measures 6.2.1. Intelligence Intelligence was assessed by means of the basic module of the Intelligence-Structure-Test 2000-R (Intelligenz-Struktur-Test 2000-R, IST; Liepmann, Beauducel, Brocke, & Amthauer, 2007). The basic module of the test assesses verbal, numerical, and figural intelligence as well as a composite of these three facets of intelligence, which is interpreted as reasoning. Because reasoning is very closely related to general intelligence (Horn, 1988), the composite score was used as a proxy for general intelligence g in the current study.1 Internal consistency of reasoning in the norm sample was α = 0.96. The validity of the test was demonstrated as well. The reasoning composite score's correlation with the Culture Fair Test was r = 0.63 and with the Raven Advanced Matrices r = 0.69. 6.2.2. Big Five All participants completed the German version of the NEO-FFI (Borkenau & Ostendorf, 1993). This widely used measure assesses the Big Five factors of personality: neuroticism (N), extraversion (E), openness to experience (O), agreeableness (A), and conscientiousness (C). The internal consistencies of all scales were at least satisfactory in both the student and adult samples (N: α = 0.85/0.90; E: α = 0.77/ 0.80; O: α = 0.68/0.72; A: α = 0.78/0.75; C: α = 0.84/0.85). 6.2.3. Personality facets Both samples completed only five of the 12 subscales of the German version of the Personality Research Form (PRF; Stumpf, Angleitner, Wieck, Jackson, & Beloch-Till, 1985). The subscales were the following: need for achievement (AC), need for affiliation (AF), need for aggression (AG), need for dominance (DO), and need for nurturance (NU). We chose the first one (AC) as it is known to be highly related to achievement criteria in adult and student samples (e.g., Paunonen & Ashton, 2013; Sackett, Gruys, & Ellingson, 1998). The others were chosen because they have shown relations with overall job performance (Judge et al., 2013) and have displayed gender differences (Costa et al., 2001). All scales consisted of 16 items that were answered on a 5-point Likert scale. The internal consistencies of all scales were at least satisfactory in both the student and adult samples (AC: α = 0.78/0.78; AF: α = 0.83/0.86; AG: α = 0.81/0.77; DO: α = 0.87/0.90; NU: α = 0.83/0.76). 6.2.4. School performance The school delivered report cards for all students from the term before testing. The interval between delivery and testing was about three months. In Germany, grades are coded such that 1 indicates outstanding achievement and 6 indicates complete failure. Scales for grades were reversed to facilitate the interpretation of the results. School performance was determined by the grade point average (GPA) of each student. 6.2.5. Vocational success Before testing, participants were asked to respond to different demographic variables and self-estimations (SE), including “Average 1 We additionally performed an exploratory factor analysis with varimax rotation on the three subtests which clearly yielded a one-factor solution explaining about 68% of the variance. All analyses with intelligence were run with the composite score and the factor score. Results did not change depending on the intelligence indicator.

Income” (Range = 1–7 with 1 = “b10,000 €” and 7 = “N 60,000 €”), and the “Self-estimated general Social Recognition of one's Profession” (Range = 1–7). Furthermore, subjects were asked to have three relatives or peers give peer-ratings (PE) that were analogous to the self-ratings (SE), including the “Estimated general Social Recognition of the target person's Profession.” All vocational success variables were highly correlated. A factor analysis (varimax rotation) yielded one factor that explained 57% of the variance. The factor loadings of all variables were very high (Average Income: λ = 0.78; SE social status: λ = 0.73; PE social status: λ = 0.76). Thus, we considered it appropriate to form one factor called “vocational success” (see Amelang & Steinmayr, 2006). 6.3. Statistical analyses All statistical analyses were computed in SPSS 22.0 and by means of the SPSS macro PROCESS (Hayes, 2013). First, criterion-validity coefficients for all investigated predictors (personality and intelligence) were computed as bivariate correlations. Second, we checked for gender differences in the success criteria and the different predictors by computing univariate analyses of variance (ANOVAs). In addition, we tested for gender differences in the success criteria while controlling for intelligence by computing univariate analyses of covariance (ANCOVAs). The mediation hypotheses were tested by checking whether the indirect effect was significantly different from zero by means of bootstrapped confidence intervals. The advantage of this procedure in comparison with others (e.g., the Sobel test) is that it does not require the indirect effect to be normally distributed (MacKinnon, Fairchild, & Fritz, 2007). Older studies have demonstrated that confidence intervals that are based on a normal distribution of the mediated effect are often inaccurate (e.g., MacKinnon, Warsi, & Dwyer, 1995), whereas bootstrap estimation of asymmetric confidence intervals provide more accurate results (MacKinnon, Lockwood, & Williams, 2004). Bootstrap analyses were conducted by means of the SPSS macro PROCESS (Hayes, 2013). Bootstrapping for the indirect effect was based on 1000 bootstrapped samples and provided the 95% confidence interval for the indirect effect. If the confidence interval did not include zero, the indirect effect (i.e., the mediation effect) was significant. Intelligence plays a major role in explaining academic and vocational success criteria (Kuncel et al., 2004). Furthermore, gender differences in success criteria yield a clearer picture when intelligence is controlled for (see above). Last but not least, girls and boys attending the highest academic school track in Germany are presumably differently preselected for this kind of school on the basis of intelligence (cf. Steinmayr, Beauducel, & Spinath, 2010). Consequently, intelligence was controlled for in all mediation analyses that tested whether gender differences in success criteria were mediated via different personality traits. 7. Results Descriptive statistics and intercorrelations for all variables are reported in Table 1. Academic achievement demonstrated positive associations with intelligence, O, A, C, and AC. It was negatively associated with AG. No significant correlations were found between school grades and N, E, AF, DO, and NU. Vocational success was significantly positively correlated with intelligence, C, AC, AF, and DO. It was negatively correlated with N. The correlational analyses yielded no relations between vocational success and E, A, AG, or NU. Thus, in accordance with Hypothesis 1, intelligence, C, and AC were correlated with both school and vocational success. O, A, and AG were associated only with school success but not with vocational success, whereas AF and DO were correlated only with vocational success but not with success in school. Thus, to some extent, different variables were correlated with academic and vocational success. In accordance with Hypothesis 2, we found gender differences in personality on most dimensions and facets that were measured. In the following measures, girls attained higher scores than boys in the

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Table 1 Descriptives and intercorrelations between all measures presented separately for the student sample (above diagonal, n = 232) and the adult sample (below diagonal, n = 126). Students M

Adults SD

Success criteria 1) GPA 4.09 2) Social status Big Five 3) Neuroticism 2.80 4) Extraversion 3.53 5) Openness to Experience 3.21 6) Agreeableness 3.47 7) Conscientiousness 3.42 Personality facets 8) Need for achievement 2.68 9) Need for affiliation 3.10 10) Need for aggression 2.38 11) Need for dominance 2.54 12) Need for nurturance 3.75 13) Reasoning 108.97

α

M

α

SD

2)

3)

4)

−.08

0.59

0.61 0.49 0.48 0.45 0.58

15.17

2.96

2.60 3.48 3.77 3.67 3.64

0.76 0.57 0.52 0.51 0.61

.78 3.40 .83 3.65 .81 2.96 .87 2.97 .83 3.31 .90 114.21

0.50 0.59 0.55 0.61 0.48 20.18

.85 .77 .68 .78 .84

0.31 0.36 0.36 0.40 0.36 18.33

5) .01

6) .22

7) .14

9)

10)

11)

12)

13)

.31

.39 −.10

−.17

−.20 −.22 .29 .72 .26 −.05 .06 .34 .56 .17

.08 −.08 −.08 −.69 −.19

−.40 .29 .11 −.39 .13

.08 .50 .19 .36 .18

.15

−.10 −.26

.29 .17 .38

.28 .63 −.34 −.03

.90 −.21 .80 .14 .72 −.17 .75 .001 .85 .41

−.41 −.002 −.07 −.18

−.31 −.04 −.12 −.23 .01 .22 .22 .20 .01 −.03 .20 .17 .19 .03 .03 .12

.78 .86 .77 .90 .76 .92

−.15 −.09 −.09 −.27 .01 −.21

.33 .11 .09 .60 .11 .40 −.03 −.19 −.07 .32 .01 −.28 .29 .32 .32 .20 .08 −.04

.42 .21 .16 .34 .03 .32

8)

.52 .05 .19 .19 .10 .14

.29 .11 .35 .25 .15

.04 .05 .42 .10

.008

.33 .06 .03

.13 .14

.002

.31

.19 −.13 .15 −.10 −.02 .01 −.29 .001 .06 −.24

−.02

Note. For students: r ≥ ∣.14∣ p ≤ .05, r ≥ ∣.19∣ p ≤ .01; for adults: r ≥ ∣.18∣ p ≤ .05, r ≥ ∣ .23∣ p ≤ .01.

student sample: N, E, O, A, AC, AF, and NU. Boys had higher scores than girls on the following scales: AG, DO, and intelligence. No gender differences were found in academic achievement and C. In the adult sample, women scored higher than men on the following measures: N, O, A, AF, and NU. Men scored high on the measure of vocational success, AG, DO, and intelligence. No gender differences were found in E, C, and AC (see Table 2). Next, we computed ANCOVAs to check for gender differences in success criteria after controlling for intelligence (Hypothesis 3). Gender served as the factor, and the particular success criterion served as the dependent variable. After controlling for general intelligence, there was a main effect of child's gender on academic achievement, F(1, 231) = 8.67, p = .004, d = 0.41. Girls attained significantly better GPAs than boys when intelligence was controlled for (estimated Mboys = 3.95, estimated Mgirls = 4.19). In the adult sample, men still had higher vocational success scores than women after intelligence was controlled for, F(1, 121) = 4.72, p = .032, d = 0.40 (estimated Mmen = 6.72, estimated Mwomen = 5.52). In order to determine whether different personality traits mediated the gender differences that were found in the success criteria, we conducted bootstrap analyses that controlled for intelligence. We report the indirect effect of gender on the particular success criterion accounted for by the specific personality trait, its 95% confidence interval (95CI), as well as the ratio of the indirect to the total effect (ratio) of

gender on academic success, which indicates the percentage of the total amount of variance explained in the success criterion by gender that could be accounted for by the mediator. The following personality traits significantly mediated the relation between gender and GPA in the student sample after controlling for intelligence: O (indirect effect: 0.039; 95CI: 0.010–0.090; ratio: 0.166), A (indirect effect: 0.038; 95CI: 0.001–0.10; ratio: 0.167), C (indirect effect: 0.052; 95CI: 0.007–0.117; ratio: 0.224), AC (indirect effect: 0.075; 95CI: 0.013–0.150; ratio: 0.323), and AG (indirect effect: 0.031; 95CI: 0.005– 0.076; ratio: 0.136). All other mediation analyses did not yield significant results. Thus, after intelligence was controlled for, girls attained higher grades because they had higher scores on O, A, C, and AC and lower scores on AG. In the adult sample, the following personality traits and facets significantly mediated the relation between gender and vocational success: AF (indirect effect: − 0.405; 95CI: − 0.908 – -0.119; ratio: − 0.376) and DO (indirect effect: 0.393; 95CI: 0.097–0.808; ratio: 0.328). All other mediation analyses did not yield significant results. Consequently, in our sample, after intelligence was controlled for, men still had more vocational success than women because they scored higher on dominance. As AF was positively correlated with vocational success, and women scored higher on AF, the mediation effect was negative; or stated differently, the gender gap in vocational success would widen by 37.6% if men and women scored equally on AF.

Table 2 Means (M) and standard deviations (SD) of all variables presented separately for boys and girls and women and men, respectively, as well as results testing for sex differences in means (univariate analysis of variance) and effect sizes (Cohen's d). Students

Adults

Girls

1) Success criterion 2) N 3) E 4) O 5) A 6) C 7) AC 8) AF 9) AG 10) DO 11) NU 12) Reasoning

Boys

Women

Men

M

SD

M

SD

F

p

d

M

SD

M

SD

F

p

d

4.13 2.98 3.60 3.26 3.58 3.47 2.71 3.16 2.33 2.45 2.96 104.06

0.58 0.61 0.46 0.46 0.45 0.54 0.31 0.35 0.36 0.38 0.33 17.64

4.05 2.53 3.43 3.13 3.31 3.33 2.63 3.01 2.46 2.68 2.67 116.39

0.61 0.51 0.51 0.51 0.41 0.62 0.32 0.37 0.34 0.39 0.34 16.88

1.02 34.69 7.36 4.47 21.90 3.47 4.20 10.10 7.48 19.52 42.84 18.59

.31 b.001 .007 .036 b.001 .064 .042 .002 .007 b.001 b.001 b.001

0.13 0.80 0.35 0.27 0.63 0.24 0.25 0.42 −0.37 −0.60 0.87 −0.71

5.27 2.74 3.57 3.87 3.78 3.66 3.44 3.77 2.84 2.82 3.44 107.63

3.17 0.76 0.57 0.48 0.43 0.59 0.47 0.51 0.50 0.59 0.43 20.32

6.99 2.45 3.39 3.67 3.56 3.61 3.36 3.52 3.08 3.13 3.17 121.23

2.76 0.73 0.60 0.55 0.57 0.63 0.53 0.65 0.58 0.61 0.50 17.62

10.39 4.49 3.23 4.52 6.20 0.15 0.86 5.62 6.27 7.97 9.82 15.78

.002 .036 .075 .036 .014 .697 .356 .019 .014 .006 .002 b.001

−0.58 0.39 0.31 0.39 0.44 0.08 0.16 0.43 −0.44 −0.52 0.58 −0.72

Note. Success criterion: Students: GPA recoded (better marks are indicated by higher numbers); Adults: Vocational Success; N = neuroticism, E = extraversion, O = openness to experience, A = agreeableness, C = conscientiousness, AC = Need for Achievement, AF = Need for Affiliation, AG = Need for Aggression, DO = Need for Dominance, NU = Need for Nurturance. Student sample: df = 1, 234; Adults: df = 1, 122.

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Summing up, the personality traits that explained the gender differences in scholastic achievement differed from those that explained the gender differences in vocational success. 8. Discussion The present study sought to investigate whether personality traits could contribute to answering the question of why women have more academic success, whereas men outperform women in professional life. Hitherto, some researchers had identified personality traits as mediators of the gender gap in academic success (e.g., Steinmayr & Spinath, 2008), but no study had directly tested whether the Big Five or its facets functioned as mediators of the relation between gender and vocational success or whether these would be found to be the same as the ones that mediated the gender gap in academic performance. The answers to these questions can add to our understanding of existing gender inequalities in these two areas and can shed light on potential differences, if not incompatibilities, between school and work. In line with our first hypothesis, we found that, besides the finding that some variables (intelligence, C, and AC) predicted both school and vocational success, A and AG were associated only with academic success, whereas AF and DO were correlated only with professional success. These results are in line with the PEFH, which posits that professional and academic lives constitute different environments in which different personality traits are associated with success. However, in accordance with other meta-analytic findings, they also demonstrate that for samples that are comparable in education but differ in age, the variables of intelligence, C, and its facet AC were important for success irrespective of the environment (see Poropat, 2009; Schmidt & Hunter, 1998; Keiser et al., 2016). Thus, intelligence is not the only construct that predicts success in different environments (see Kuncel et al., 2004), but C and its facet AC also do. Overall, in accordance with our second hypothesis, we found gender differences in personality that were comparable to the ones reported in earlier studies in adult and adolescent samples (Costa et al., 2001; De Bolle et al., 2015; Feingold, 1994). The effect sizes of these differences were mostly small (E, O, A [adult sample], C [student sample], AC [student sample], AF, AG) or medium (N [adult sample], A [student], DO, NU [adult]) in size and generally similar in size in both samples. However, we found large effects for N and NU only in the student sample. The first might be linked to changes in circulating gonadal hormones during puberty that put teenage girls, in particular, at higher risk for depression (De Bolle et al., 2015). As depression and N are highly correlated (Sosnowsky, 2007), it might also explain the exceptionally high gender differences in N. The large gender difference in NU might reflect a more gender-stereotyped self-description in adolescence that is attenuated in later life when both men and women tend to have more responsibility for others and both describe themselves as more nurturing than before. No differences between adult men and women were found on C and AC, whereas small differences on C and AC in favor of female school students reflect the findings reported by De Bolle et al. (2015). However, the gender differences in reasoning were surprisingly large (d = − 0.71/–0.72) and in favor of male students/adults. Even though the gender difference favoring men was relatively high, the results for the student sample were in line with other studies that investigated students of the same age and educational background (e.g., Steinmayr et al., 2010). The study by Steinmayr and colleagues as well as the present study investigated an academically preselected sample. Meta-analyses have demonstrated that gender differences favoring men increase in academically preselected studies (Hyde, 2005; Hyde, Fennema, & Lamon, 1990). This effect is higher in Germany because, in addition to other selection processes, selection for the highest academic track in Germany, which all students in the present study attended, strongly depends on grades. Because boys have worse grades than girls on average (see Voyer & Voyer, 2014), even when they possess

the same intelligence and competencies as girls (e.g., Helbig, 2010), they are more strongly selected than girls. This might result in the fact that male students attending a Gymnasium in Germany are more intelligent than girls who are attending the same school track. According to the present study, this is true not only for student samples attending a Gymnasium but also for adults who have graduated from this kind of school. This idea is in line with Hypothesis 3 because, in our student sample, girls attained better GPAs than boys only after intelligence was controlled for. As already demonstrated in other studies (e.g., Steinmayr & Spinath, 2008), the gender differences in grades in the present two comparable German samples increased when intelligence was controlled for. However, this effect was reversed for vocational success. After intelligence was controlled for, gender differences in vocational success decreased but did not vanish. On the one hand, these results mirror many existing findings on the gender gap in career success (e.g., Arulampalam et al., 2007; Joshi et al., 2015). On the other hand, our findings demonstrate that men's advantages on vocational success criteria cannot be attributed solely to differences in cognitive potential. In line with Hypothesis 4, gender differences in academic and vocational success were both mediated by personality traits. However, in line with our expectations, different personality traits mediated the gender differences in these two areas. All traits that predicted grades, all of which demonstrated significant differences between boys and girls, also mediated the relation between gender and grades. However, only one personality trait, dominance, on which men scored higher, actually mediated the relation between gender and career success. In addition, affiliation, on which women scored higher, suppressed this relation. The finding that girls attained higher grades than boys after controlling for intelligence because they have a higher Need for Achievement, are more open, more agreeable, slightly more conscientiousness, and less aggressive than boys are in line with previous research (e.g., Steinmayr & Spinath, 2008). Like the SAT in college samples, the used intelligence tests seem to underpredict girls' and overpredict boys' success in school (cf. Keiser et al., 2016). Keiser et al. (2016) further demonstrated that girls' overprediction is slightly explained by course taking pattern. As students in the present sample were also allowed to make some class choices, e.g. if they take advance or basic math, class taking pattern might further contribute to the explanation of gender differences in the present study and should be considered in further studies. Furthermore, the results provide some support for the feminization of school hypothesis (for an overview, see Heyder & Kessels, 2013). For instance, Orr (2011) found that the more parents made their children (of both genders) participate in female activities (e.g., singing, chores), the better the children's kindergarten grades were. Our results extend these findings with regard to personality traits that are linked to better (A) or worse (AG) grades in school. Many studies have found that boys behave more aggressively than girls (e.g., Hyde, 1984), and the trait “aggressive” is included in measures for assessing masculinity in adolescent samples (Krahé, Berger, & Möller, 2007). At the same time, A is usually higher in girls (e.g., Spinath et al., 2014), and being “kind” and “sensitive to others' needs” are items that are used to assess femininity in adolescents (Krahé et al., 2007). This gender stereotyping of traits seems to affect the academic success of both genders. Hence, the more these traits are stereotyped as being typical and socially desirable for one gender only, and the higher their impact on grades are, the more difficulties boys will encounter in school when behaving in a typically male fashion. However, the results concerning the mediators of the relation between gender and school success beg the question of whether these traits have a direct impact on performance or whether different mechanisms are at work. Regarding academic success, mediation analyses have revealed that the impacts of conscientiousness and agreeableness on grades are mediated by effort and effort regulation (Bidjerano & Dai, 2007; Noftle & Robins, 2007; Richardson, Abraham, & Bond, 2012), both

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of which will lead to better performance and better grades, as teachers also tend to reward effort (e.g., Resh, 2009). Beyond these ideas, teachers' might also reward “better behaved” students and therefore sanction students who are more aggressive and less agreeable. Overall, our mediation analyses provide support for the notion that girls' higher academic success is due to a better fit between “typical” girls and the school setting, whereas traits that are typical of boys make boys' success in school less likely. However, apart from the gender differences in traits that actually exist, teachers' stereotypical perceptions of boys and girls and the teachers' corresponding expectations of students' school work might also act to increase gender differences in grades. An experimental study by Heyder and Kessels (2015) revealed that not only did teachers hold lower expectations of boys' academic engagement in general, but they also ascribed the lowest levels of behavior that fostered learning and the highest levels of behavior that impeded learning to those boys who visibly enacted their masculinity (by behaving in a very masculine way). As students' enactment of gender in school seems to trigger teachers' stereotypes of diligent, good girls and troublesome, lazy boys, when students exhibit personality profiles that are in line with female or male gender roles, this might have the same effects on teachers' perceptions and expectations. Whereas the feminization of school hypothesis states that female behavior is expected and rewarded in school, research on the “thinkmanager-think-male” stereotype (e.g., Schein, 1973, 2007) has suggested that one of the main barriers for women in management is that the characteristics required for success as a leader are seen as more commonly held by men than by women. However, in these studies on leadership stereotypes, only traits that were pretested as maximizing differences in men and women were used as descriptors, which might also have maximized any effects on gender stereotyping. It is interesting that our results show that when we measured self-descriptions with the NEO-FFI and the PRF, only one personality facet on which men scored higher than women was associated with vocational success (DO), whereas one facet on which women scored higher (AF) was also positively related to vocational success. However, we did not test for success as a manager but instead tested for vocational success in general, which was comprised of assessments of income and reputation. This might explain the diverging results. In this explanation of gender differences in vocational success, it is important to stress that we do not believe that personality factors are the sole or main contributors to gender differences in the workplace. Many studies have identified many other important factors that contribute to gender differences in salaries and in the share of top positions, such as gender stereotypes and women's higher share of family work (Eagly & Carli, 2007; Eagly & Karau, 2002; Evers & Sieverding, 2014; Hegewisch et al., 2010). Summing up, in line with our expectations, different traits were beneficial for academic and vocational success, and different variables mediated the relation between gender and success in these two contexts. The key to girls' higher success in school is of no advantage to them when it comes to careers, and traits that were deemed problematic for boys in school did not hinder them from being top performers on the job. The affordances and rules in these two contexts seem to overlap only in part because intelligence, C, and striving for achievement led to better performance in both school and work, but other traits were beneficial for success in only one context. 9. Limitations and practical implications The limitations of our study concern the correlational and cross-sectional nature of our data, which restricted causal inferences. We cannot rule out the possibility that some personality traits that are correlated with success might not be the cause, but might just as well be the result of having the respective success. For instance, it might be the case that a better career position contributes to the feeling of being in charge of people, thus stimulating both dominance and affiliation. Furthermore,

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our study was limited to a nonrepresentative sample of German adolescents attending the Gymnasium, the highest school track in Germany, and a matching sample of adults that had graduated from that type of school. As girls have better grades than boys at the transition from primary to secondary school (in Germany, e.g., Helbig, 2010), there is greater selectivity for boys enrolled in a Gymnasium and completing the Abitur. As such, male students and professionals scored higher than females on the intelligence test in our sample, replicating the findings of other German studies (cf. Fischer, Schult, & Hell, 2013; Steinmayr & Spinath, 2008), and female students had better grades than boys only when intelligence was controlled for. Different results might be obtained for other age groups. Furthermore, job success was investigated across domains. It might be that results change when data are broken down to occupation and industry. Even though men's professional advantage holds across domains (OECD, 2012) it might well be that the size of gender differences might interact with domains as different personality traits are known to be differently predictive in different occupations (Judge & Zapata, 2015). However, despite these limitations, the present study contributes, first, to our understanding of the feminization of school hypothesis. Indeed, some personality traits that are rather typical of girls were found to mediate the relation between gender and school success, but this was not true for all variables related to school success. Thus, school is not an environment in which only rather feminine attributes lead to success, a finding that attenuates the feminization of school hypothesis a little bit. On the other hand, the study demonstrated that personality traits also contribute to our understanding of gender gaps in vocational success, which held true only for the more specific personality facets that we investigated but not for the Big Five. As we investigated only a few personality facets related to vocational success on which gender differences are usually found, further studies investigating gender gaps in vocational success should apply a personality questionnaire such as the NEO-PI-R for investigating other personality facets. However, we demonstrated that personality traits that can account for gender gaps in school students' success do not contribute to our understanding of gender gaps in vocational success. In school, girls' tendencies to exhibit behaviors that are rather typically female seem to be reinforced by good grades (independent of their cognitive potential). But showing such behaviors that are indicative of these traits does not contribute to professional success. Here, beyond intelligence, C, and AC, other traits count. Among them is DO, which has a medium to high correlation with professional success but is not related to school success. Thus, both girls and boys might be led up the garden path if they trust solely in the norms and rules that govern their academic experiences. References Amelang, M., & Steinmayr, R. (2006). Is there a validity increment for tests of emotional intelligence in explaining the variance of performance criteria? Intelligence, 34(5), 459–468. Arulampalam, W., Booth, A. L., & Bryan, M. L. (2007). Is there a glass ceiling over Europe? Exploring the gender pay gap across the wage distribution. Industrial & Labor Relations Review, 60(2), 163–186. Bidjerano, T., & Dai, D. Y. (2007). The relationship between the big-five model of personality and self-regulated learning strategies. Learning and Individual Differences, 17, 69–81. Borkenau, P., & Ostendorf, F. (1993). NEO-5-Faktoren-Inventar (NEO-FFI). Göttingen: Hogrefe. Buchmann, C., & DiPrete, T. A. (2006). The growing female advantage in college completion: The role of family background and academic achievement. American Sociological Review, 71(4), 515–541. Caplan, R. D. (1987). Person-environment fit theory and organizations: Commensurate dimensions, time perspectives, and mechanisms. Journal of Vocational Behavior, 31, 248–267. Caspi, A., Roberts, B. W., & Shiner, R. L. (2005). Personality development: Stability and change. Annual Review of Psychology, 56, 453–484. Costa, P. T., Jr., Terracciano, A., & McCrae, R. R. (2001). Gender differences in personality traits across cultures: Robust and surprising findings. Journal of Personality and Social Psychology, 81, 322–331. De Bolle, M., De Fruyt, F., McCrae, R. R., Löckenhoff, C. E., Costa, P. T., Jr., Aguilar-Vafaie, M. E., ... Avdeyeva, T. V. (2015). The emergence of sex differences in personality traits in early adolescence: A cross-sectional, cross-cultural study. Journal of Personality and Social Psychology, 108(1), 171–185.

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