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The Gender Similarities Hypothesis Janet Shibley Hyde University of Wisconsin—Madison The differences model, which argues that males and fe- searchers highlighted gender similarities. Thorndike males are vastly different psychologically, dominates the (1914), for example, believed that psychological gender popular media. Here, the author advances a very different differences were too small, compared with within-gender view, the gender similarities hypothesis, which holds that variation, to be important. Leta Stetter Hollingworth (1918) males and females are similar on most, but not all, psy- reviewed available research on gender differences in men- chological variables. Results from a review of 46 meta- tal traits and found little evidence of gender differences. analyses support the gender similarities hypothesis. Gen- Another important reviewer of gender research in the early der differences can vary substantially in magnitude at 1900s, Helen Thompson Woolley (1914), lamented the gap different ages and depend on the context in which mea- between the data and scientists' views on the question: surement occurs. Overinflated claims of gender differences carry substantial costs in areas such as the workplace and The general discussions of the psychology of sex, whether by relationships. psychologists or by sociologists show such a wide diversity of points of view that one feels that the truest thing to be said at Keywords: gender differences, gender similarities, meta- present is that scientific evidence plays very little part in produc- analysis, aggression ing convictions. (p. 372) T he mass media and the general public are captivated by findings of gender differences. John Gray's (1992) Men Are From Mars, Women Are From Venus, which argued for enormous psychological differ- ences between women and men, has sold over 30 million The Role of Meta-Analysis in Assessing Psychological Gender Differences Reviews of research on psychological gender differences copies and been translated into 40 languages (Gray, 2005). began with Woolley's (1914) and Hollingworth's (1918) Deborah Tannen's (1991) You Just Don't Understand: and extended through Maccoby and Jacklin's (1974) wa- Women and Men in Conversation argued for the different tershed book The Psychology of Sex Differences, in which cultures hypothesis: that men's and women's patterns of they reviewed more than 2,000 studies of gender differ- speaking are so fundamentally different that men and ences in a wide variety of domains, including abilities, women essentially belong to different linguistic communi- personality, social behavior, and memory. Maccoby and ties or cultures. That book was on the New York Times Jacklin dismissed as unfounded many popular beliefs in bestseller list for nearly four years and has been translated psychological gender differences, including beliefs that into 24 languages (AnnOnline, 2005). Both of these works, girls are more "social" than boys; that girls are more and dozens of others like them, have argued for the differ- suggestible; that girls have lower self-esteem; that girls are ences hypothesis: that males and females are, psychologi- better at rote learning and simple tasks, whereas boys are cally, vastly different. Here, I advance a very different better at higher level cognitive processing; and that girls view—the gender similarities hypothesis (for related state- lack achievement motivation. Maccoby and Jacklin con- ments, see Epstein, 1988; Hyde, 1985; Hyde & Plant, 1995; cluded that gender differences were well established in Kimball, 1995). only four areas: verbal ability, visual-spatial ability, math- The Hypothesis ematical ability, and aggression. Overall, then, they found much evidence for gender similarities. Secondary reports The gender similarities hypothesis holds that males of their findings in textbooks and other sources, however, and females are similar on most, but not all, psychological focused almost exclusively on their conclusions about gen- variables. That is, men and women, as well as boys and girls, are more alike than they are different. In terms of ¸ der differences (e.g., Gleitman, 1981; Lefrancois, 1990). effect sizes, the gender similarities hypothesis states that most psychological gender differences are in the close-to- Preparation of this article was supported in part by National Science zero (d 0.10) or small (0.11 d 0.35) range, a few are Foundation Grant REC 0207109. I thank Nicole Else-Quest, Sara Lind- in the moderate range (0.36 d 0.65), and very few are berg, Shelly Grabe, and Jenni Petersen for reviewing and commenting on large (d 0.66 –1.00) or very large (d 1.00). a draft of this article. Correspondence concerning this article should be addressed to Janet Although the fascination with psychological gender Shibley Hyde, Department of Psychology, University of Wisconsin— differences has been present from the dawn of formalized Madison, 1202 West Johnson Street, Madison, WI 53706. E-mail: psychology around 1879 (Shields, 1975), a few early re- email@example.com September 2005 ● American Psychologist 581 Copyright 2005 by the American Psychological Association 0003-066X/05/$12.00 Vol. 60, No. 6, 581–592 DOI: 10.1037/0003-066X.60.6.581 Gender meta-analyses generally proceed in four steps: (a) The researcher locates all studies on the topic being reviewed, typically using databases such as PsycINFO and carefully chosen search terms. (b) Statistics are extracted from each report, and an effect size is computed for each study. (c) A weighted average of the effect sizes is com- puted (weighting by sample size) to obtain an overall assessment of the direction and magnitude of the gender difference when all studies are combined. (d) Homogeneity analyses are conducted to determine whether the group of effect sizes is relatively homogeneous. If it is not, then the studies can be partitioned into theoretically meaningful groups to determine whether the effect size is larger for some types of studies and smaller for other types. The researcher could ask, for example, whether gender differ- ences are larger for measures of physical aggression com- pared with measures of verbal aggression. The Evidence To evaluate the gender similarities hypothesis, I collected Janet Shibley the major meta-analyses that have been conducted on psy- Hyde chological gender differences. They are listed in Table 1, grouped roughly into six categories: those that assessed cognitive variables, such as abilities; those that assessed verbal or nonverbal communication; those that assessed Shortly after this important work appeared, the statistical social or personality variables, such as aggression or lead- method of meta-analysis was developed (e.g., Glass, McGaw, ership; those that assessed measures of psychological well- & Smith, 1981; Hedges & Olkin, 1985; Rosenthal, 1991). being, such as self-esteem; those that assessed motor be- This method revolutionized the study of psychological gender haviors, such as throwing distance; and those that assessed differences. Meta-analyses quickly appeared on issues such as miscellaneous constructs, such as moral reasoning. I began gender differences in influenceability (Eagly & Carli, 1981), with meta-analyses reviewed previously by Hyde and Plant abilities (Hyde, 1981; Hyde & Linn, 1988; Linn & Petersen, (1995), Hyde and Frost (1993), and Ashmore (1990). I 1985), and aggression (Eagly & Steffen, 1986; Hyde, 1984, updated these lists with more recent meta-analyses and, 1986). where possible, replaced older meta-analyses with more Meta-analysis is a statistical method for aggregating up-to-date meta-analyses that used larger samples and bet- research findings across many studies of the same question ter statistical methods. (Hedges & Becker, 1986). It is ideal for synthesizing re- Hedges and Nowell (1995; see also Feingold, 1988) search on gender differences, an area in which often dozens have argued that the canonical method of meta-analysis— or even hundreds of studies of a particular question have which often aggregates data from many small convenience been conducted. samples—should be augmented or replaced by data from Crucial to meta-analysis is the concept of effect size, large probability samples, at least when that is possible which measures the magnitude of an effect—in this case, (e.g., in areas such as ability testing). Test-norming data as the magnitude of gender difference. In gender meta-anal- well as data from major national surveys such as the yses, the measure of effect size typically is d (Cohen, National Longitudinal Study of Youth provide important 1988): information. Findings from samples such as these are in- MM MF cluded in the summary shown in Table 1, where the num- d , ber of reports is marked with an asterisk. sw Inspection of the effect sizes shown in the rightmost where MM is the mean score for males, MF is the mean column of Table 1 reveals strong evidence for the gender score for females, and sw is the average within-sex standard similarities hypothesis. These effect sizes are summarized deviation. That is, d measures how far apart the male and in Table 2. Of the 128 effect sizes shown in Table 1, 4 were female means are in standardized units. In gender meta- unclassifiable because the meta-analysis provided such a analysis, the effect sizes computed from all individual wide range for the estimate. The remaining 124 effect sizes studies are averaged to obtain an overall effect size reflect- were classified into the categories noted earlier: close-to- ing the magnitude of gender differences across all studies. zero (d 0.10), small (0.11 d 0.35), moderate In the present article, I follow the convention that negative (0.36 d 0.65), large (d 0.66 –1.00), or very large values of d mean that females scored higher on a dimen- ( 1.00). The striking result is that 30% of the effect sizes sion, and positive values of d indicate that males scored are in the close-to-zero range, and an additional 48% are in higher. the small range. That is, 78% of gender differences are 582 September 2005 ● American Psychologist Table 1 Major Meta-Analyses of Research on Psychological Gender Differences Study and variable Age No. of reports d Cognitive variables Hyde, Fennema, & Lamon (1990) Mathematics computation All 45 0.14 Mathematics concepts All 41 0.03 Mathematics problem solving All 48 0.08 Hedges & Nowell (1995) Reading comprehension Adolescents 5* 0.09 Vocabulary Adolescents 4* 0.06 Mathematics Adolescents 6* 0.16 Perceptual speed Adolescents 4* 0.28 Science Adolescents 4* 0.32 Spatial ability Adolescents 2* 0.19 Hyde, Fennema, Ryan, et al. (1990) Mathematics self-confidence All 56 0.16 Mathematics anxiety All 53 0.15 Feingold (1988) DAT spelling Adolescents 5* 0.45 DAT language Adolescents 5* 0.40 DAT verbal reasoning Adolescents 5* 0.02 DAT abstract reasoning Adolescents 5* 0.04 DAT numerical ability Adolescents 5* 0.10 DAT perceptual speed Adolescents 5* 0.34 DAT mechanical reasoning Adolescents 5* 0.76 DAT space relations Adolescents 5* 0.15 Hyde & Linn (1988) Vocabulary All 40 0.02 Reading comprehension All 18 0.03 Speech production All 12 0.33 Linn & Petersen (1985) Spatial perception All 62 0.44 Mental rotation All 29 0.73 Spatial visualization All 81 0.13 Voyer et al. (1995) Spatial perception All 92 0.44 Mental rotation All 78 0.56 Spatial visualization All 116 0.19 Lynn & Irwing (2004) Progressive matrices 6–14 years 15 0.02 Progressive matrices 15–19 years 23 0.16 Progressive matrices Adults 10 0.30 Whitley et al. (1986) Attribution of success to ability All 29 0.13 Attribution of success to effort All 29 0.04 Attribution of success to task All 29 0.01 Attribution of success to luck All 29 0.07 Attribution of failure to ability All 29 0.16 Attribution of failure to effort All 29 0.15 Attribution of failure to task All 29 0.08 Attribution of failure luck All 29 0.15 Communication Anderson & Leaper (1998) Interruptions in conversation Adults 53 0.15 Intrusive interruptions Adults 17 0.33 Leaper & Smith (2004) Talkativeness Children 73 0.11 Affiliative speech Children 46 0.26 Assertive speech Children 75 0.11 (table continues) September 2005 ● American Psychologist 583 Table 1 (continued) Study and variable Age No. of reports d Communication (continued ) Dindia & Allen (1992) Self-disclosure (all studies) — 205 0.18 Self-disclosure to stranger — 99 0.07 Self-disclosure to friend — 50 0.28 LaFrance et al. (2003) Smiling Adolescents and adults 418 0.40 Smiling: Aware of being observed Adolescents and adults 295 0.46 Smiling: Not aware of being observed Adolescents and adults 31 0.19 McClure (2000) Facial expression processing Infants 29 0.18 to 0.92 Facial expression processing Children and adolescents 89 0.13 to 0.18 Social and personality variables Hyde (1984, 1986) Aggression (all types) All 69 0.50 Physical aggression All 26 0.60 Verbal aggression All 6 0.43 Eagly & Steffen (1986) Aggression Adults 50 0.29 Physical aggression Adults 30 0.40 Psychological aggression Adults 20 0.18 Knight et al. (2002) Physical aggression All 41 0.59 Verbal aggression All 22 0.28 Aggression in low emotional arousal context All 40 0.30 Aggression in emotional arousal context All 83 0.56 Bettencourt & Miller (1996) Aggression under provocation Adults 57 0.17 Aggression under neutral conditions Adults 50 0.33 Archer (2004) Aggression in real-world settings All 75 0.30 to 0.63 Physical aggression All 111 0.33 to 0.84 Verbal aggression All 68 0.09 to 0.55 Indirect aggression All 40 0.74 to 0.05 Stuhlmacher & Walters (1999) Negotiation outcomes Adults 53 0.09 Walters et al. (1998) Negotiator competitiveness Adults 79 0.07 Eagly & Crowley (1986) Helping behavior Adults 99 0.13 Helping: Surveillance context Adults 16 0.74 Helping: No surveillance Adults 41 0.02 Oliver & Hyde (1993) Sexuality: Masturbation All 26 0.96 Sexuality: Attitudes about casual sex All 10 0.81 Sexual satisfaction All 15 0.06 Attitudes about extramarital sex All 17 0.29 Murnen & Stockton (1997) Arousal to sexual stimuli Adults 62 0.31 Eagly & Johnson (1990) Leadership: Interpersonal style Adults 153 0.04 to 0.07 Leadership: Task style Adults 154 0.00 to 0.09 Leadership: Democratic vs. autocratic Adults 28 0.22 to 0.34 Eagly et al. (1992) Leadership: Evaluation Adults 114 0.05 Eagly et al. (1995) Leadership effectiveness Adults 76 0.02 584 September 2005 ● American Psychologist Table 1 (continued) Study and variable Age No. of reports d Social and personality variables (continued) Eagly et al. (2003) Leadership: Transformational Adults 44 0.10 Leadership: Transactional Adults 51 0.13 to 0.27 Leadership: Laissez-faire Adults 16 0.16 Feingold (1994) Neuroticism: Anxiety Adolescents and adults 13* 0.32 Neuroticism: Impulsiveness Adolescents and adults 6* 0.01 Extraversion: Gregariousness Adolescents and adults 10* 0.07 Extraversion: Assertiveness Adolescents and adults 10* 0.51 Extraversion: Activity Adolescents and adults 5 0.08 Openness Adolescents and adults 4* 0.19 Agreeableness: Trust Adolescents and adults 4* 0.35 Agreeableness: Tendermindedness Adolescents and adults 10* 0.91 Conscientiousness Adolescents and adults 4 0.18 Psychological well-being Kling et al. (1999, Analysis I) Self-esteem All 216 0.21 Kling et al. (1999, Analysis II) Self-esteem Adolescents 15* 0.04 to 0.16 Major et al. (1999) Self-esteem All 226 0.14 Feingold & Mazzella (1998) Body esteem All — 0.58 Twenge & Nolen-Hoeksema (2002) Depression symptoms 8–16 years 310 0.02 Wood et al. (1989) Life satisfaction Adults 17 0.03 Happiness Adults 22 0.07 ¨ Pinquart & Sorensen (2001) Life satisfaction Elderly 176 0.08 Self-esteem Elderly 59 0.08 Happiness Elderly 56 0.06 Tamres et al. (2002) Coping: Problem-focused All 22 0.13 Coping: Rumination All 10 0.19 Motor behaviors Thomas & French (1985) Balance 3–20 years 67 0.09 Grip strength 3–20 years 37 0.66 Throw velocity 3–20 years 12 2.18 Throw distance 3–20 years 47 1.98 Vertical jump 3–20 years 20 0.18 Sprinting 3–20 years 66 0.63 Flexibility 5–10 years 13 0.29 Eaton & Enns (1986) Activity level All 127 0.49 Miscellaneous Thoma (1986) Moral reasoning: Stage Adolescents and adults 56 0.21 Jaffee & Hyde (2000) Moral reasoning: Justice orientation All 95 0.19 Moral reasoning: Care orientation All 160 0.28 Silverman (2003) Delay of gratification All 38 0.12 Whitley et al. (1999) Cheating behavior All 36 0.17 Cheating attitudes All 14 0.35 (table continues) September 2005 ● American Psychologist 585 Table 1 (continued) Study and variable Age No. of reports d Whitley (1997) Computer use: Current All 18 0.33 Computer self-efficacy All 29 0.41 Konrad et al. (2000) Job attribute preference: Earnings Adults 207 0.12 Job attribute preference: Security Adults 182 0.02 Job attribute preference: Challenge Adults 63 0.05 Job attribute preference: Physical work environment Adults 96 0.13 Job attribute preference: Power Adults 68 0.04 Note. Positive values of d represent higher scores for men and/or boys; negative values of d represent higher scores for women and/or girls. Asterisks indicate that data were from major, large national samples. Dashes indicate that data were not available (i.e., the study in question did not provide this information clearly). No. number; DAT Differential Aptitude Test. small or close to zero. This result is similar to that of Hyde are particularly large after puberty, when the gender gap in and Plant (1995), who found that 60% of effect sizes for muscle mass and bone size widens. gender differences were in the small or close-to-zero range. A second area in which large gender differences are The small magnitude of these effects is even more found is some— but not all—measures of sexuality (Oliver striking given that most of the meta-analyses addressed the & Hyde, 1993). Gender differences are strikingly large for classic gender differences questions—that is, areas in incidences of masturbation and for attitudes about sex in a which gender differences were reputed to be reliable, such casual, uncommitted relationship. In contrast, the gender as mathematics performance, verbal ability, and aggressive difference in reported sexual satisfaction is close to zero. behavior. For example, despite Tannen's (1991) assertions, Across several meta-analyses, aggression has repeat- gender differences in most aspects of communication are edly shown gender differences that are moderate in mag- small. Gilligan (1982) has argued that males and females nitude (Archer, 2004; Eagly & Steffen, 1986; Hyde, 1984, speak in a different moral "voice," yet meta-analyses show 1986). The gender difference in physical aggression is that gender differences in moral reasoning and moral ori- particularly reliable and is larger than the gender difference entation are small (Jaffee & Hyde, 2000). in verbal aggression. Much publicity has been given to gender differences in relational aggression, with girls scor- The Exceptions ing higher (e.g., Crick & Grotpeter, 1995). According to As noted earlier, the gender similarities hypothesis does not the Archer (2004) meta-analysis, indirect or relational ag- assert that males and females are similar in absolutely gression showed an effect size for gender differences of every domain. The exceptions—areas in which gender dif- 0.45 when measured by direct observation, but it was ferences are moderate or large in magnitude—should be only 0.19 for peer ratings, 0.02 for self-reports, and recognized. 0.13 for teacher reports. Therefore, the evidence is am- The largest gender differences in Table 1 are in the biguous regarding the magnitude of the gender difference domain of motor performance, particularly for measures in relational aggression. such as throwing velocity (d 2.18) and throwing distance (d 1.98) (Thomas & French, 1985). These differences The Interpretation of Effect Sizes The interpretation of effect sizes is contested. On one side of the argument, the classic source is the statistician Cohen (1969, 1988), who recommended that 0.20 be considered a Table 2 small effect, 0.50 be considered medium, and 0.80 be Effect Sizes (n 124) for Psychological Gender considered large. It is important to note that he set these Differences, Based on Meta-Analyses, Categorized by guidelines before the advent of meta-analysis, and they Range of Magnitude have been the standards used in statistical power analysis for decades. Effect size range In support of these guidelines are indicators of overlap Effect sizes 0–0.10 0.11–0.35 0.36–0.65 0.66–1.00 1.00 between two distributions. For example, Kling, Hyde, Showers, and Buswell (1999) graphed two distributions Number 37 59 19 7 2 differing on average by an effect size of 0.21, the effect size % of total 30 48 15 6 2 they found for gender differences in self-esteem. This graph is shown in Figure 1. Clearly, this small effect size 586 September 2005 ● American Psychologist Second, Rosenthal used the r metric, and when this is Figure 1 translated into d, the effects look much less impressive. For Graphic Representation of a 0.21 Effect Size example, a d of 0.20 is equivalent to an r of 0.10, and Rosenthal's BESD indicates that that effect is equivalent to cancer survival increasing from 45% to 55%— once again, a small effect. A close-to-zero effect size of 0.10 is equiv- alent to an r of .05, which translates to cancer survival rates increasing only from 47.5% to 52.5% in the treatment group compared with the control group. In short, I believe that Cohen's guidelines provide a reasonable standard for the interpretation of gender differences effect sizes. One caveat should be noted, however. The foregoing discussion is implicitly based on the assumption that the variabilities in the male and female distributions are equal. Yet the greater male variability hypothesis was originally proposed more than a century ago, and it survives today (Feingold, 1992; Hedges & Friedman, 1993). In the 1800s, Note. Two normal distributions that are 0.21 standard deviations apart (i.e., this hypothesis was proposed to explain why there were d 0.21). This is the approximate magnitude of the gender difference in more male than female geniuses and, at the same time, self-esteem, averaged over all samples, found by Kling et al. (1999). From "Gender Differences in Self-Esteem: A Meta-Analysis," by K. C. Kling, J. S. more males among the mentally retarded. Statistically, the Hyde, C. J. Showers, and B. N. Buswell, 1999, Psychological Bulletin, 125, p. combination of a small average difference favoring males 484. Copyright 1999 by the American Psychological Association. and a larger standard deviation for males, for some trait such as mathematics performance, could lead to a lopsided gender ratio favoring males in the upper tail of the distri- bution reflecting exceptional talent. The statistic used to investigate this question is the variance ratio (VR), the ratio reflects distributions that overlap greatly—that is, that of the male variance to the female variance. Empirical show more similarity than difference. Cohen (1988) devel- investigations of the VR have found values of 1.00 –1.08 oped a U statistic that quantifies the percentage of nonover- for vocabulary (Hedges & Nowell, 1995), 1.05–1.25 for lap of distributions. For d 0.20, U 15%; that is, 85% mathematics performance (Hedges & Nowell), and 0.87– of the areas of the distributions overlap. According to 1.04 for self-esteem (Kling et al., 1999). Therefore, it another Cohen measure of overlap, for d 0.20, 54% of appears that whether males or females are more variable individuals in Group A exceed the 50th percentile for depends on the domain under consideration. Moreover, Group B. most VR estimates are close to 1.00, indicating similar For another way to consider the interpretation of effect variances for males and females. Nonetheless, this issue of sizes, d can also be expressed as an equivalent value of the possible gender differences in variability merits continued Pearson correlation, r (Cohen, 1988). For the small effect investigation. size of 0.20, r .10, certainly a small correlation. A d of 0.50 is equivalent to an r of .24, and for d 0.80, r .37. Developmental Trends Rosenthal (1991; Rosenthal & Rubin, 1982) has ar- Not all meta-analyses have examined developmental trends gued the other side of the case—namely, that seemingly and, given the preponderance of psychological research on small effect sizes can be important and make for impressive college students, developmental analysis is not always pos- applied effects. As an example, he took a two-group ex- sible. However, meta-analysis can be powerful for identi- perimental design in which one group is treated for cancer fying age trends in the magnitude of gender differences. and the other group receives a placebo. He used the method Here, I consider a few key examples of meta-analyses that of binomial effect size display (BESD) to illustrate the have taken this developmental approach (see Table 3). consequences. Using this method, for example, an r of .32 At the time of the meta-analysis by Hyde, Fennema, between treatment and outcome, accounting for only 10% and Lamon (1990), it was believed that gender differences of the variance, translates into a survival rate of 34% in the in mathematics performance were small or nonexistent in placebo group and 66% in the treated group. Certainly, the childhood and that the male advantage appeared beginning effect is impressive. around the time of puberty (Maccoby & Jacklin, 1974). It How does this apply to the study of gender differ- was also believed that males were better at high-level ences? First, in terms of costs of errors in scientific decision mathematical problems that required complex processing, making, psychological gender differences are quite a dif- whereas females were better at low-level mathematics that ferent matter from curing cancer. So, interpretation of the required only simple computation. Hyde and colleagues magnitude of effects must be heavily conditioned by the addressed both hypotheses in their meta-analysis. They costs of making Type I and Type II errors for the particular found a small gender difference favoring girls in compu- question under consideration. I look forward to statisticians tation in elementary school and middle school and no developing indicators that take these factors into account. gender difference in computation in the high school years. September 2005 ● American Psychologist 587 Table 3 Selected Meta-Analyses Showing Developmental Trends in the Magnitude of Gender Differences Study and variable Age (years) No. of reports d Hyde, Fennema, & Lamon (1990) Mathematics: Complex problem solving 5–10 11 0.00 11–14 21 0.02 15–18 10 0.29 19–25 15 0.32 Kling et al. (1999) Self-esteem 7–10 22 0.16 11–14 53 0.23 15–18 44 0.33 19–22 72 0.18 23–59 16 0.10 60 6 0.03 Major et al. (1999) Self-esteem 5–10 24 0.01 11–13 34 0.12 14–18 65 0.16 19 or older 97 0.13 Twenge & Nolen-Hoeksema (2002) Depressive symptoms 8–12 86 0.04 13–16 49 0.16 Thomas & French (1985) Throwing distance 3–8 — 1.50 to 2.00 16–18 — 3.50 Note. Positive values of d represent higher scores for men and/or boys; negative values of d represent higher scores for women and/or girls. Dashes indicate that data were not available (i.e., the study in question did not provide this information clearly). No. number. There was no gender difference in complex problem solv- These examples illustrate the extent to which the ing in elementary school or middle school, but a small magnitude of gender differences can fluctuate with age. gender difference favoring males emerged in the high Gender differences grow larger or smaller at different times school years (d 0.29). Age differences in the magnitude in the life span, and meta-analysis is a powerful tool for of the gender effect were significant for both computation detecting these trends. Moreover, the fluctuating magnitude and problem solving. of gender differences at different ages argues against the Kling et al. (1999) used a developmental approach in differences model and notions that gender differences are their meta-analysis of studies of gender differences in self- large and stable. esteem, on the basis of the assertion of prominent authors such as Mary Pipher (1994) that girls' self-esteem takes a The Importance of Context nosedive at the beginning of adolescence. They found that Gender researchers have emphasized the importance of the magnitude of the gender difference did grow larger context in creating, erasing, or even reversing psychologi- from childhood to adolescence: In childhood (ages 7–10), cal gender differences (Bussey & Bandura, 1999; Deaux & d 0.16; for early adolescence (ages 11–14), d 0.23; Major, 1987; Eagly & Wood, 1999). Context may exert and for the high school years (ages 15–18), d 0.33. influence at numerous levels, including the written instruc- However, the gender difference did not suddenly become tions given for an exam, dyadic interactions between par- large in early adolescence, and even in high school, the ticipants or between a participant and an experimenter, or difference was still not large. Moreover, the gender differ- the sociocultural level. ence was smaller in older samples; for example, for ages In an important experiment, Lightdale and Prentice 23–59, d 0.10. (1994) demonstrated the importance of gender roles and Whitley's (1997) analysis of age trends in computer social context in creating or erasing the purportedly robust self-efficacy are revealing. In grammar school samples, gender difference in aggression. Lightdale and Prentice d 0.09, whereas in high school samples, d 0.66. This used the technique of deindividuation to produce a situation dramatic trend leads to questions about what forces are at that removed the influence of gender roles. Deindividuation work transforming girls from feeling as effective with refers to a state in which the person has lost his or her computers as boys do to showing a large difference in individual identity; that is, the person has become anony- self-efficacy by high school. mous. Under such conditions, people should feel no obli- 588 September 2005 ● American Psychologist gation to conform to social norms such as gender roles. present, d 0.02. Moreover, the magnitude of the gender Half of the participants, who were college students, were difference was highly correlated with the degree of danger assigned to an individuated condition by having them sit in the helping situation; gender differences were largest close to the experimenter, identify themselves by name, favoring males in situations with the most danger. In short, wear large name tags, and answer personal questions. Par- the gender difference in helping behavior can be large, ticipants in the deindividuation condition sat far from the favoring males, or close to zero, depending on the social experimenter, wore no name tags, and were simply told to context in which the behavior is measured. Moreover, the wait. All participants were also told that the experiment pattern of gender differences is consistent with social-role required information from only half of the participants, theory. whose behavior would be monitored, and that the other half Anderson and Leaper (1998) obtained similar context would remain anonymous. Participants then played an in- effects in their meta-analysis of gender differences in con- teractive video game in which they first defended and then versational interruption. At the time of their meta-analysis, attacked by dropping bombs. The number of bombs it was widely believed that men interrupted women con- dropped was the measure of aggressive behavior. siderably more than the reverse. Averaged over all studies, The results indicated that in the individuated condi- however, Anderson and Leaper found a d of 0.15, a small tion, men dropped significantly more bombs (M 31.1) effect. The effect size for intrusive interruptions (excluding than women did (M 26.8). In the deindividuated condi- back-channel interruptions) was larger: 0.33. It is important tion, however, there were no significant gender differences to note that the magnitude of the gender difference varied and, in fact, women dropped somewhat more bombs (M greatly depending on the social context in which interrup- 41.1) than men (M 36.8). In short, the significant gender tions were studied. When dyads were observed, d 0.06, difference in aggression disappeared when gender norms but with larger groups of three or more, d 0.26. When were removed. participants were strangers, d 0.17, but when they were Steele's (1997; Steele & Aronson, 1995) work on friends, d 0.14. Here, again, it is clear that gender stereotype threat has produced similar evidence in the differences can be created, erased, or reversed, depending cognitive domain. Although the original experiments con- on the context. cerned African Americans and the stereotype that they are In their meta-analysis, LaFrance, Hecht, and Paluck intellectually inferior, the theory was quickly applied to (2003) found a moderate gender difference in smiling (d gender and stereotypes that girls and women are bad at 0.41), with girls and women smiling more. Again, the math (Brown & Josephs, 1999; Quinn & Spencer, 2001; magnitude of the gender difference was highly dependent Spencer, Steele, & Quinn, 1999; Walsh, Hickey, & Duffy, on the context. If participants had a clear awareness that 1999). In one experiment, male and female college students they were being observed, the gender difference was larger with equivalent math backgrounds were tested (Spencer et (d 0.46) than it was if they were not aware of being al., 1999). In one condition, participants were told that the observed (d 0.19). The magnitude of the gender dif- math test had shown gender difference in the past, and in ference also depended on culture and age. the other condition, they were told that the test had been Dindia and Allen (1992) and Bettencourt and Miller shown to be gender fair—that men and women had per- (1996) also found marked context effects in their gender formed equally on it. In the condition in which participants meta-analyses. The conclusion is clear: The magnitude and had been told that the math test was gender fair, there were even the direction of gender differences depends on the no gender differences in performance on the test. In the context. These findings provide strong evidence against the condition in which participants expected gender differ- differences model and its notions that psychological gender ences, women underperformed compared with men. This differences are large and stable. simple manipulation of context was capable of creating or erasing gender differences in math performance. Costs of Inflated Claims of Gender Meta-analysts have addressed the importance of con- Differences text for gender differences. In one of the earliest demon- strations of context effects, Eagly and Crowley (1986) The question of the magnitude of psychological gender meta-analyzed studies of gender differences in helping differences is more than just an academic concern. There behavior, basing the analysis in social-role theory. They are serious costs of overinflated claims of gender differ- argued that certain kinds of helping are part of the male ences (for an extended discussion of this point, see Barnett role: helping that is heroic or chivalrous. Other kinds of & Rivers, 2004; see also White & Kowalski, 1994). These helping are part of the female role: helping that is nurturant costs occur in many areas, including work, parenting, and and caring, such as caring for children. Heroic helping relationships. involves danger to the self, and both heroic and chivalrous Gilligan's (1982) argument that women speak in a helping are facilitated when onlookers are present. Wom- different moral "voice" than men is a well-known example en's nurturant helping more often occurs in private, with no of the differences model. Women, according to Gilligan, onlookers. Averaged over all studies, men helped more speak in a moral voice of caring, whereas men speak in a (d 0.34). However, when studies were separated into voice of justice. Despite the fact that meta-analyses discon- those in which onlookers were present and participants firm her arguments for large gender differences (Jaffee & were aware of it, d 0.74. When no onlookers were Hyde, 2000; Thoma, 1986; Walker, 1984), Gilligan's ideas September 2005 ● American Psychologist 589 have permeated American culture. One consequence of this In the realm of intimate heterosexual relationships, overinflated claim of gender differences is that it reifies the women and men are told that they are as different as if they stereotype of women as caring and nurturant and men as came from different planets and that they communicate in lacking in nurturance. One cost to men is that they may dramatically different ways (Gray, 1992; Tannen, 1991). believe that they cannot be nurturant, even in their role as When relationship conflicts occur, good communication is father. For women, the cost in the workplace can be enor- essential to resolving the conflict (Gottman, 1994). If, mous. Women who violate the stereotype of being nur- however, women and men believe what they have been turant and nice can be penalized in hiring and evaluations. told—that it is almost impossible for them to communicate Rudman and Glick (1999), for example, found that female with each other—they may simply give up on trying to job applicants who displayed agentic qualities received resolve the conflict through better communication. Thera- considerably lower hireability ratings than agentic male pists will need to dispel erroneous beliefs in massive, applicants (d 0.92) for a managerial job that had been unbridgeable gender differences. "feminized" to require not only technical skills and the Inflated claims about psychological gender differ- ability to work under pressure but also the ability to be ences can hurt boys as well. A large gender gap in self- helpful and sensitive to the needs of others. The researchers esteem beginning in adolescence has been touted in popular concluded that women must present themselves as compe- sources (American Association of University Women, tent and agentic to be hired, but they may then be viewed 1991; Orenstein, 1994; Pipher, 1994). Girls' self-esteem is as interpersonally deficient and uncaring and receive biased purported to take a nosedive at the beginning of adoles- work evaluations because of their violation of the female cence, with the implication that boys' self-esteem does not. nurturance stereotype. Yet meta-analytic estimates of the magnitude of the gender A second example of the costs of unwarranted vali- difference have all been small or close to zero: d 0.21 dation of the stereotype of women as caring nurturers (Kling et al., 1999, Analysis I), d 0.04 – 0.16 (Kling et comes from Eagly, Makhijani, and Klonsky's (1992) meta- al., 1999, Analysis II), and d 0.14 (Major, Barr, Zubek, analysis of studies of gender and the evaluation of leaders. & Babey, 1999). In short, self-esteem is roughly as much a Overall, women leaders were evaluated as positively as problem for adolescent boys as it is for adolescent girls. men leaders (d 0.05). However, women leaders por- The popular media's focus on girls as the ones with self- esteem problems may carry a huge cost in leading parents, trayed as uncaring autocrats were at a more substantial teachers, and other professionals to overlook boys' self- disadvantage than were men leaders portrayed similarly esteem problems, so that boys do not receive the interven- (d 0.30). Women who violated the caring stereotype paid tions they need. for it in their evaluations. The persistence of the stereotype As several of these examples indicate, the gender of women as nurturers leads to serious costs for women similarities hypothesis carries strong implications for prac- who violate this stereotype in the workplace. titioners. The scientific evidence does not support the belief The costs of overinflated claims of gender differences that men and women have inherent difficulties in commu- hit children as well. According to stereotypes, boys are nicating across gender. Neither does the evidence support better at math than girls are (Hyde, Fennema, Ryan, Frost, the belief that adolescent girls are the only ones with & Hopp, 1990). This stereotype is proclaimed in mass self-esteem problems. Therapists who base their practice in media headlines (Barnett & Rivers, 2004). Meta-analyses, the differences model should reconsider their approach on however, indicate a pattern of gender similarities for math the basis of the best scientific evidence. performance. Hedges and Nowell (1995) found a d of 0.16 for large national samples of adolescents, and Hyde, Fen- Conclusion nema, and Lamon (1990) found a d of 0.05 for samples The gender similarities hypothesis stands in stark contrast of the general population (see also Leahey & Guo, 2000). to the differences model, which holds that men and women, One cost to children is that mathematically talented girls and boys and girls, are vastly different psychologically. may be overlooked by parents and teachers because these The gender similarities hypothesis states, instead, that adults do not expect to find mathematical talent among males and females are alike on most— but not all—psy- girls. Parents have lower expectations for their daughters' chological variables. Extensive evidence from meta-analy- math success than for their sons' (Lummis & Stevenson, ses of research on gender differences supports the gender 1990), despite the fact that girls earn better grades in math similarities hypothesis. A few notable exceptions are some than boys do (Kimball, 1989). Research has shown repeat- motor behaviors (e.g., throwing distance) and some aspects edly that parents' expectations for their children's mathe- of sexuality, which show large gender differences. Aggres- matics success relate strongly to outcomes such as the sion shows a gender difference that is moderate in child's mathematics self-confidence and performance, with magnitude. support for a model in which parents' expectations influ- It is time to consider the costs of overinflated claims of ence children (e.g., Frome & Eccles, 1998). In short, girls gender differences. Arguably, they cause harm in numerous may find their confidence in their ability to succeed in realms, including women's opportunities in the workplace, challenging math courses or in a mathematically oriented couple conflict and communication, and analyses of self- career undermined by parents' and teachers' beliefs that esteem problems among adolescents. Most important, these girls are weak in math ability. claims are not consistent with the scientific data. 590 September 2005 ● American Psychologist REFERENCES Feingold, A., & Mazzella, R. (1998). Gender differences in body image are increasing. Psychological Science, 9, 190 –195. American Association of University Women. (1991). Shortchanging girls, Frome, P. M., & Eccles, J. S. (1998). Parents' influence on children's shortchanging America: Full data report. Washington, DC: Author. achievement-related perceptions. Journal of Personality and Social Anderson, K. J., & Leaper, C. (1998). Meta-analyses of gender effects on Psychology, 74, 435– 452. conversational interruption: Who, what, when, where, and how. Sex Gilligan, C. (1982). In a different voice: Psychological theory and wom- Roles, 39, 225–252. en's development. Cambridge, MA: Harvard University Press. AnnOnline. (2005). Biography: Deborah Tannen. Retrieved January 10, Glass, G. V., McGaw, B., & Smith, M. L. (1981). 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Functionalism, Darwinism, and the psychology of well-being: A consideration of emotional style and marital status. women: A study in social myth. American Psychologist, 30, 739 –754. Psychological Bulletin, 106, 249 –264. Silverman, I. W. (2003). Gender differences in delay of gratification: A Woolley, H. T. (1914). The psychology of sex. Psychological Bulletin, 11, meta-analysis. Sex Roles, 49, 451– 463. 353–379. 592 September 2005 ● American Psychologist
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Grade Range: 9-12Resource Type(s): Interactives & MediaDuration: 9 MinutesDate Posted: 7/7/2008
Three short videos provide an overview of transportation technology in three eras: 1800-1900, 1900-1950, and 1950-2000. These videos are included in the online exhibition entitled America on the Move, which focuses on transportation in US history.
Museum education, Self-paced learning modules, Thematic approach, Visual instruction
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The steam locomotive "John Bull" was built in 1831 and ran for 35 years, pulling trains of passen...
1800, immigrant, American, 1900's, century, Transportation, history, travel, 20th, culture, twentieth, nineteenth, environment, Immigration, rail, jet, America, motor, 19th, 1900
Ride a train with a friendly conductor who teaches a young boy how to talk like a railroader.
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Would my RZ120 three hold up at this place? I'm not going to go on anything crazy. What trails could I ride here without making my bike fall apart. It's my understanding the RZ is pretty durable.
PS I plan to not have my tires leave the ground more than 6 inches ever
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Feature Productions Delivers MMA Coverage with Broadcast Pix
Billerica, Massachusetts â Broadcast Pix⢠today announced that Feature Productions, a live production company based in Lethbridge, Alberta, Canada, is using Broadcast Pix Slate⢠1000 Video Control Centers⢠as part of two portable production flypacks for live coverage of Mixed Martial Arts (MMA) matches and other events. The company had been renting a Slate-equipped flypack since 2009, but began using its own flypack in late May.
In southern Alberta, Feature Productions has gained a reputation for MMA video production and now works with four different MMA affiliations. According to co-owner Chris Cooke, the company was originally hired to provide image magnification (I-MAG) â featuring live coverage, instant replays, graphics, and commercials â to on-site audiences. However, event promoters took notice of the HD productions and began offering them to broadcasters. Some matches are also streamed to GoFightLive, an online pay-per-view service.
Although Cooke and co-owner Steve Prankard designed and built the first flypack three years ago, pairing the Slate with Sony cameras and a Yamaha audio board, the system was purchased through an investor. Earlier this year, Feature Productions purchased the new flypack, which is also anchored by a Slate but features JVC cameras and some logistical improvements. âWe did our research and we decided Broadcast Pix was the best for us,â said Cooke.
Important selling points were Slateâs built-in clip store, CG, multi-viewer, and other Fluent⢠workflow tools, which improve production efficiencies and minimize additional components in the flypacks. For example, Cooke rarely uses a USB stick to transfer files. Instead, he relies on Fluent Watch-Folders, which allow him to insert commercials and other elements into a program over the network, even in the middle of a live production. âThatâs a great aspect of the Broadcast Pix,â he explained. âItâs a pretty quick process and itâs so easy during a show.â
Cooke estimated that 80 percent of the companyâs business is live production. Beyond MMA, Feature Productions produces corporate events, conferences, and Western Major Baseball League (WMBL) coverage. Currently in the second year of a three-year contract, Feature Productions also handles video scoreboard productions for the ENMAX Centre in Lethbridge. Home of the Western Hockey League (WHL) Lethbridge Hurricanes and host to a number of concerts and other events, the venue features a control room built around a Broadcast Pix Granite 2000.
âWeâre comfortable with Broadcast Pix, and it has a very good track record with us. Weâre very confident with its reliability,â Cooke said. âOur clients love the results, and thatâs the true test.â
About Broadcast Pix The leader in live video production systems, Broadcast Pix was founded in 2002 and has customers in more than 110 countries. Its Video Control Centers⢠combine an integrated switcher, clip server, CG, and device control software with patented control panels, unique touch-screens, and exceptional displays that enable operators to create with confidence. That confidence is further enhanced with rock-solid stability, patented technologies to maintain lip sync, and great technical support. Systems range from compact systems controlled by touch-screen or voice automation to sophisticated 2 M/E control panels. Customers include leading broadcast, corporate, education, religious, government, webcast, entertainment and mobile studios. Learn more at www.broadcastpix.com.
Broadcast Pix, Fluent, Slate, and Video Control Centers are trademarks of Broadcast Pix, Inc. Patented. Made in USA.
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Is this the 2016 Hyundai Elantra?An image has surfaced on the internet that is supposed to be the new Hyundai Elantra . The South Korean car manufacturer is expected to showcase the new Elantra in April 2015 at the Seoul Motor Show in South Korea. Provided by MotorTrend ... MSN News, 1 week ago
New Hyundai Elantra India Launch 2016 - Motor Trend India, 1 week ago
Recall roundup: Hyundai Elantra for power steering issues
According to the National Highway Traffic Safety Administration, owners of several Hyundai Elantra models will have to take a trip back to the dealers because of a problem with the electrically assisted power steering. The NHTSA says that the EPS ...Inautonews, 3 weeks ago HYUNDAI HCN : Elantra for power steering issues 4 Traders, 3 weeks ago Hyundai recalls 205K Elantra sedans for possible power steering failure Christian Science Monitor, 4 weeks ago Hyundai Elantra, Dodge Charger and Challenger Hellcat Recalled Automobile Magazine, 4 weeks ago
More from: CNBC, CNBC...and 78 other sources
Is this the next-gen Hyundai Elantra?
An image of what is believed to be the 2016 Hyundai Elantra has surfaced on the internet. The next-generation Elantra is expected to be based on a new-platform. Going by the image, the front of the car is radically different to the current model.Team-BHP.com, 2 weeks ago 2016 Hyundai Elantra spied before April unveil, gets new gen styling Rush Lane, 2 weeks ago New Hyundai Elantra Revealed In Leaked Marketing Shot Motor Report, 2 weeks ago Is this the next-generation Hyundai Elantra? MSN Canada, 2 weeks ago
2016 Hyundai Elantra image leaked
It appears the Korean car maker Hyundai, has leaked an image of the upcoming 2016 model of its Elantra ahead of its debut at the upcoming Seoul Motor Show scheduled for April 2015 in South Korea. Follow Hyundai ElantraView SpecificationsView ...Gaadi.com, 2 weeks ago New Generation Hyundai Elantra's Picture Leaked CarTrade.com, 2 weeks ago Photo Leak: Is this the new 2016 Hyundai Elantra? Free-i-News, 2 weeks ago 2016 Hyundai Elantra Leaked AutoGuide.com, 2 weeks ago
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Refreshed Hyundai Elantra
16Mar, 2015 08:03 am PDT Visited : 0 times | 0 Visits Today HYUNDAI-Sime Darby Motors (HSDM) recently introduced the new and refreshed Hyundai Elantra C-segment sedan for the Malaysian market. The face-lifted Elantra boasts 14 improvements and ...Social Dashboard, 2 weeks ago Gallery: Hyundai Elantra 1.6L Elegance facelift AutoBuzz.my, 3 weeks ago 2015 Hyundai Elantra gets enhancements to become even better value for money Motor Trader Malaysia, 3 weeks ago Elantra Upgrade for 2015 Available Now In Malaysian Showrooms Autoworld.com.my, 3 weeks ago
Volkswagen Jetta Takes On Toyota Corolla Altis, Skoda Octavia, Renault Fluence, Hyundai Elantra and Chev...
Jaipur: As the Volkswagen launches Jetta facelift in the price band of Rs 13.87 lacs to Rs 19.77 lacs, the competition in the luxury saloon gets more interesting. Up until now, Toyota Corolla Altis was the latest updated car in the segment but now ...CarDekho, 1 month ago Facelift Volkswagen Jetta comparison with Skoda Octavia, Hyundai Elantra, Toyota Corolla Rush Lane, 1 month ago
Spotted: 2016 Hyundai Elantra ahead of probable April debut
The new face for the South Korean automaker's D-segment sedan has now moved from flowing to muscular and this is very evident by the sharp lines and large chrome grille. The shape of the headlights too has changed and they now have chrome eyebrows. A ...Jagran Post, 2 weeks ago 2016 Hyundai Elantra spotted ahead of probable April debut CarWale, 2 weeks ago Autoleaks: 2016 Hyundai Elantra Revealed Ahead Of Local Market Launch The Truth About Cars, 2 weeks ago
Hyundai announces recall of over 2,00,00 Elantras due to power steering defect
Korean carmaker Hyundai has reportedly announced a recall for more than 2,00,000 units of Elantra sedan over power steering defect that may cause crash. The affected sedans have been produced between 2008 to 2010, whereas the affected list also ...CarTrade.com, 4 weeks ago Hyundai recalls 204,768 units of Elantras due to defect in power steering Automotive Business Review, 4 weeks ago Hyundai Hcn : recalls 204,768 units of Elantras due to defect in power steering 4 Traders, 4 weeks ago
Hyundai recalls Elantras due to power steering
Are you Bullish or Bearish on ? Bullish Bearish Results for ( ) Bullish Bearish Thanks for sharing your thoughts. Submit & View Results Skip toSeeking Alpha, 4 weeks ago
Hyundai Motor America Recalls 204,768 Cars Due to Power Steering
(Bloomberg) -- Hyundai Motor America is recalling more than 200,000 Elantra vehicles because their electronic power steering might be flawed, the U.S. National Highway Traffic Safety Administration said. The recall covers certain Elantras ...Bloomberg, 1 month ago Hyundai Recalling North American Vehicles Because of Power-Steering Issue, Covers 263,000 Cars Hngn.com, 1 month ago
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