The Gender Similarities Hypothesis Janet Shibley Hyde University of Wisconsin���Madison The differences model, which argues that males and fe- males are vastly different psychologically, dominates the popular media. Here, the author advances a very different view, the gender similarities hypothesis, which holds that males and females are similar on most, but not all, psy- chological variables. Results from a review of 46 meta- analyses support the gender similarities hypothesis. Gen- der differences can vary substantially in magnitude at different ages and depend on the context in which mea- surement occurs. Overinflated claims of gender differences carry substantial costs in areas such as the workplace and relationships. Keywords: gender differences, gender similarities, meta- analysis, aggression T(1992) he mass media and the general public are captivated by findings of gender differences. John Gray���s Men Are From Mars, Women Are From Venus, which argued for enormous psychological differ- ences between women and men, has sold over 30 million copies and been translated into 40 languages (Gray, 2005). Deborah Tannen���s (1991) You Just Don���t Understand: Women and Men in Conversation argued for the different cultures hypothesis: that men���s and women���s patterns of speaking are so fundamentally different that men and women essentially belong to different linguistic communi- ties or cultures. That book was on the New York Times bestseller list for nearly four years and has been translated into 24 languages (AnnOnline, 2005). Both of these works, and dozens of others like them, have argued for the differ- ences hypothesis: that males and females are, psychologi- cally, vastly different. Here, I advance a very different view���the gender similarities hypothesis (for related state- ments, see Epstein, 1988 Hyde, 1985 Hyde & Plant, 1995 Kimball, 1995). The Hypothesis The gender similarities hypothesis holds that males and females are similar on most, but not all, psychological variables. That is, men and women, as well as boys and girls, are more alike than they are different. In terms of effect sizes, the gender similarities hypothesis states that most psychological gender differences are in the close-to- zero (d 0.10) or small (0.11 d 0.35) range, a few are in the moderate range (0.36 d 0.65), and very few are large (d 0.66���1.00) or very large (d 1.00). Although the fascination with psychological gender differences has been present from the dawn of formalized psychology around 1879 (Shields, 1975), a few early re- searchers highlighted gender similarities. Thorndike (1914), for example, believed that psychological gender differences were too small, compared with within-gender variation, to be important. Leta Stetter Hollingworth (1918) reviewed available research on gender differences in men- tal traits and found little evidence of gender differences. Another important reviewer of gender research in the early 1900s, Helen Thompson Woolley (1914), lamented the gap between the data and scientists��� views on the question: The general discussions of the psychology of sex, whether by psychologists or by sociologists show such a wide diversity of points of view that one feels that the truest thing to be said at present is that scientific evidence plays very little part in produc- ing convictions. (p. 372) The Role of Meta-Analysis in Assessing Psychological Gender Differences Reviews of research on psychological gender differences began with Woolley���s (1914) and Hollingworth���s (1918) and extended through Maccoby and Jacklin���s (1974) wa- tershed book The Psychology of Sex Differences, in which they reviewed more than 2,000 studies of gender differ- ences in a wide variety of domains, including abilities, personality, social behavior, and memory. Maccoby and Jacklin dismissed as unfounded many popular beliefs in psychological gender differences, including beliefs that girls are more ���social��� than boys that girls are more suggestible that girls have lower self-esteem that girls are better at rote learning and simple tasks, whereas boys are better at higher level cognitive processing and that girls lack achievement motivation. Maccoby and Jacklin con- cluded that gender differences were well established in only four areas: verbal ability, visual-spatial ability, math- ematical ability, and aggression. Overall, then, they found much evidence for gender similarities. Secondary reports of their findings in textbooks and other sources, however, focused almost exclusively on their conclusions about gen- der differences (e.g., Gleitman, 1981 Lefranc ��ois, 1990). Preparation of this article was supported in part by National Science Foundation Grant REC 0207109. I thank Nicole Else-Quest, Sara Lind- berg, Shelly Grabe, and Jenni Petersen for reviewing and commenting on a draft of this article. Correspondence concerning this article should be addressed to Janet Shibley Hyde, Department of Psychology, University of Wisconsin��� Madison, 1202 West Johnson Street, Madison, WI 53706. E-mail: jshyde@wisc.edu 581 September 2005 ��� American Psychologist 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

Shortly after this important work appeared, the statistical method of meta-analysis was developed (e.g., Glass, McGaw, & Smith, 1981 Hedges & Olkin, 1985 Rosenthal, 1991). This method revolutionized the study of psychological gender differences. Meta-analyses quickly appeared on issues such as gender differences in influenceability (Eagly & Carli, 1981), abilities (Hyde, 1981 Hyde & Linn, 1988 Linn & Petersen, 1985), and aggression (Eagly & Steffen, 1986 Hyde, 1984, 1986). Meta-analysis is a statistical method for aggregating research findings across many studies of the same question (Hedges & Becker, 1986). It is ideal for synthesizing re- search on gender differences, an area in which often dozens or even hundreds of studies of a particular question have been conducted. Crucial to meta-analysis is the concept of effect size, which measures the magnitude of an effect���in this case, the magnitude of gender difference. In gender meta-anal- yses, the measure of effect size typically is d (Cohen, 1988): d MM MF sw , where MM is the mean score for males, MF is the mean score for females, and sw is the average within-sex standard deviation. That is, d measures how far apart the male and female means are in standardized units. In gender meta- analysis, the effect sizes computed from all individual studies are averaged to obtain an overall effect size reflect- ing the magnitude of gender differences across all studies. In the present article, I follow the convention that negative values of d mean that females scored higher on a dimen- sion, and positive values of d indicate that males scored higher. 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 the major meta-analyses that have been conducted on psy- 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 social or personality variables, such as aggression or lead- ership those that assessed measures of psychological well- being, such as self-esteem those that assessed motor be- haviors, such as throwing distance and those that assessed miscellaneous constructs, such as moral reasoning. I began with meta-analyses reviewed previously by Hyde and Plant (1995), Hyde and Frost (1993), and Ashmore (1990). I updated these lists with more recent meta-analyses and, where possible, replaced older meta-analyses with more up-to-date meta-analyses that used larger samples and bet- ter statistical methods. Hedges and Nowell (1995 see also Feingold, 1988) have argued that the canonical method of meta-analysis��� which often aggregates data from many small convenience samples���should be augmented or replaced by data from large probability samples, at least when that is possible (e.g., in areas such as ability testing). Test-norming data as well as data from major national surveys such as the National Longitudinal Study of Youth provide important information. Findings from samples such as these are in- cluded in the summary shown in Table 1, where the num- ber of reports is marked with an asterisk. Inspection of the effect sizes shown in the rightmost column of Table 1 reveals strong evidence for the gender similarities hypothesis. These effect sizes are summarized in Table 2. Of the 128 effect sizes shown in Table 1, 4 were unclassifiable because the meta-analysis provided such a wide range for the estimate. The remaining 124 effect sizes were classified into the categories noted earlier: close-to- zero (d 0.10), small (0.11 d 0.35), moderate (0.36 d 0.65), large (d 0.66���1.00), or very large ( 1.00). The striking result is that 30% of the effect sizes are in the close-to-zero range, and an additional 48% are in the small range. That is, 78% of gender differences are Janet Shibley Hyde 582 September 2005 ��� American Psychologist