Why do girls tend to earn better grades in school than boys? Why are men still far more likely than women to earn degrees in the fields of science, technology, engineering, and mathematics? And why are men on average more likely to be injured in accidents and fights than women? These and many other questions are the subject of both informal investigation in the media and formal investigation in academic and scientific circles. In his landmark book "Male, Female: The Evolution of Human Sex Differences", author David Geary provided the first comprehensive evolutionary model to explain human sex differences. Using the principles of sexual selection such as female choice and male-male competition, the author systematically reviewed and discussed the evolution of sex differences and their expression throughout the animal kingdom, as a means of not just describing but explaining the same process in Homo sapiens. Now, over ten years since the first edition, Geary has completed a massive update, expansion and theoretical revision of his classic text. New findings in brain and genetic research inform a wealth of new material, including a new chapter on sex differences in patterns of life history development; expanded coverage of genetic research (e.g. DNA finger printing to determine paternity as related to male-male competition in primates); fatherhood in humans; cross-cultural patterns of sex differences in choosing and competing for mates; and, genetic, hormonal, and socio-cultural influences on the expression of sex differences. Finally, through his motivation to control framework (introduction in the first edition and expanded in "The Origin of Mind", 2005), Geary presents a theoretical bridge linking parenting, mate choices, and competition, with children's development and sex differences in brain and cognition. The result is an even better book than the original - a lively and nuanced application of Darwin's insight to help explain our heritage and our place in the natural world.

Male, Female: The Evolution of Human Sex Differences

Using Panel Study of Income Dynamics (PSID) microdata over the 1980-2010 period, we provide new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably during this time. By 2010, conventional human capital variables taken together explained little of the gender wage gap, while gender differences in occupation and industry continued to be important. Moreover, the gender pay gap declined much more slowly at the top of the wage distribution than at the middle or bottom and by 2010 was noticeably higher at the top. We then survey the literature to identify what has been learned about the explanations for the gap. We conclude that many of the traditional explanations continue to have salience. Although human-capital factors are now relatively unimportant in the aggregate, women's work force interruptions and shorter hours remain significant in high-skilled occupations, possibly due to compensating differentials. Gender differences in occupations and industries, as well as differences in gender roles and the gender division of labor remain important, and research based on experimental evidence strongly suggests that discrimination cannot be discounted. Psychological attributes or noncognitive skills comprise one of the newer explanations for gender differences in outcomes. Our effort to assess the quantitative evidence on the importance of these factors suggests that they account for a small to moderate portion of the gender pay gap, considerably smaller than, say, occupation and industry effects, though they appear to modestly contribute to these differences.

/pdf/the-gender-wage-gap-extent-trends-and-explanations-3m2c5a7dft.pdf

The Gender Wage Gap: Extent, Trends, and Explanations

Sex differences in central tendency, variability, and numbers of high scores on mental tests have been extensively studied. Research has not always seemed to yield consistent results, partly because most studies have not used representative samples of national populations. An analysis of mental test scores from six studies that used national probability samples provided evidence that although average sex differences have been generally small and stable over time, the test scores of males consistently have larger variance. Except in tests of reading comprehension, perceptual speed, and associative memory, males typically outnumber females substantially among high-scoring individuals.

https://science.sciencemag.org/content/sci/269/5220/41.full.pdf

Sex differences in mental test scores, variability, and numbers of high-scoring individuals

Using PSID microdata over the 1980-2010, we provide new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably over this period. By 2010, conventional human capital variables taken together explained little of the gender wage gap, while gender differences in occupation and industry continued to be important. Moreover, the gender pay gap declined much more slowly at the top of the wage distribution that at the middle or the bottom and by 2010 was noticeably higher at the top. We then survey the literature to identify what has been learned about the explanations for the gap. We conclude that many of the traditional explanations continue to have salience. Although human capital factors are now relatively unimportant in the aggregate, women’s work force interruptions and shorter hours remain significant in high skilled occupations, possibly due to compensating differentials. Gender differences in occupations and industries, as well as differences in gender roles and the gender division of labor remain important, and research based on experimental evidence strongly suggests that discrimination cannot be discounted. Psychological attributes or noncognitive skills comprise one of the newer explanations for gender differences in outcomes. Our effort to assess the quantitative evidence on the importance of these factors suggests that they account for a small to moderate portion of the gender pay gap, considerably smaller than say occupation and industry effects, though they appear to modestly contribute to these differences.

https://papers.ssrn.com/sol3/Delivery.cfm/dp9656.pdf?abstractid=2716597&mirid=1

SUMMARY—Amid ongoing public speculation about the reasons for sex differences in careers in science and mathematics, we present a consensus statement that is based on the best available scientific evidence. Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive. Successful careers in math and science require many types of cognitive abilities. Females tend to excel in verbal abilities, with large differences between females andmalesfound whenassessmentsincludewriting samples. High-level achievement in science and math requires the ability to communicate effectively and comprehend abstract ideas, so the female advantage in writing should be helpful in all academic domains. Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized examsin mathematics and science. An evolutionary account of sex differences in mathematics and science supports the conclusion that, although sex differences in math and science performance have not directly evolved, they could be indirectly related to differences in interests and specific brain and cognitive systems. We review the brain basis for sex differences in science and mathematics, describe consistent effects, and identify numerous possible correlates. Experience alters brain structures and functioning, so causal statements about brain differences and success in math and science are circular. A wide range of sociocultural forces contribute to sex differences in mathematics and science achievement and ability—including the effects of family,neighborhood,peer,andschoolinfluences;training and experience; and cultural practices. We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics.

/pdf/the-science-of-sex-differences-in-science-and-mathematics-z189hy1b2o.pdf

The Science of Sex Differences in Science and Mathematics

Human capital models have mainly focused on the rate of return to investment in a homogeneous stock of capital. Yet individuals have different initial attributes that determine comparative advantage in producing different types of human capital. We find that mathematical ability is an important determinant of field choice for college students and that differences in earnings across fields are largely explained as a return to the use of scarce quantitative abilities in the production of each type of human capital. The model successfully accounts for the observed male-female differences in earnings and occupational choices of recent college graduates.

Morton Paglin

Papers

Heterogeneous Human Capital, Occupational Choice, and Male-Female Earnings Differences