Straight Talk About Sex Differences in Occupational Choices and Work-Family Tradeoffs

Editor’s Note: This is the third of three posts in a roundtable on men and women at work the Institute for Family Studies is hosting this week.*

The recent firestorm ignited by James Damore’s “Google’s Ideological Echo Chamber” reflects a closed-minded and knee-jerk hostility to issues that need to be discussed in an open and dispassionate manner. The strongest vitriol seems to be directed at any suggestion that women and men may differ in fundamental, biologically-based ways and that any such differences might contribute to the sex disparity in certain occupations and in work-family tradeoffs, among other issues. These are certainly hot button topics, but public censorship of their discussion only ensures that nothing will change. I cannot comment on all of the points raised in Damore’s treatise, but I will make a few points about sex differences in occupational choices and work-family balance in the sections below.

Interests and Occupational Choices

Sex differences in occupational interests have been known for decades, and a recent aggregate analysis of the interests of more than 500,000 people shows that some of these differences are quite large.¹ The most relevant finding here is that about 15% of women have the same level of interest in engineering as the average man; 50% of men, by definition, would have stronger interests in engineering than the average man. Now, today’s math-intensive engineering does not have a direct evolutionary basis to it,² but today’s occupational interests are likely influenced by more basic interests that have an evolutionary foundation.

Among these is a person's interest in people versus things. The gap here is also large, with only about 20% of women showing the same level or a higher interest in things than the average man. The origin of the sex difference in interest in things may track to a male bias in the construction of basic tools (e.g. weapons) in traditional societies, and likely throughout our evolutionary history.³ In any case, individuals—men or women—with an interest in things generally prefer working in technical and engineering occupations, including computer science. On the other hand, individuals with an interest in people gravitate to fields that involve working with living things, which is one reason why women who are interested in science are much more likely to pursue a career in biology or veterinary medicine than computer science.⁴

Occupational choices are also influenced by intra-individual—within the same person—academic strengths and weaknesses, and these and many other sex differences are more strongly expressed in wealthy, democratic, and gender-equal societies.⁵ Let’s take Finland as an example. According to the World Economic Forum (2015), Finland is one of the most gender-equal nations in the world. Moreover, Finnish students are among the highest educational achievers in Europe, and adolescent girls in that country outperform their male peers in science. As a result, Finland should be on the cusp of eliminating educational and occupational sex differences in science, technology, engineering, and mathematics (STEM). Yet Finland has one of the largest college-degree gaps (< 25% are obtained by women) in the world for STEM fields,⁶ and Norway and Sweden, also leading in gender equality rankings, are not far behind. This is only the tip of the iceberg, as this general pattern is found throughout the world: Women’s participation in STEM fields, at any level (from scientist to technician), declines as national levels of economic development and gender equality improve.

One of the luxuries of living in one of these societies is the opportunity to explore and pursue occupational niches that not only fit your interests but also your academic (and other, such as interpersonal) strengths.⁷ And this is where the Finnish results begin to make sense. Although adolescent girls in Finland outperform their male peers in science, the gap is even larger in reading. The result is that more Finnish girls—independent of their absolute level of performance—are relatively better at reading than science or math, whereas more Finnish boys are relatively better at science or math than reading. Individuals with the latter pattern are likely to enter STEM areas, whether as researcher scientists or technicians, and there are more boys than girls with this pattern worldwide.

There are differences in the allocation of time and effort men and women devote to competitive striving versus direct investment in the family—differences that are found throughout the world and for that matter in 95% of mammalian species.

At the same time, there are significant numbers of girls (about 24% in Finland) who exhibit this same academic pattern (relatively better at science or math than reading). And worldwide, there are more adolescent girls with this academic pattern than there are women who graduate with degrees in engineering, computer science, or the physical sciences.⁸ Some of this gap may be related to the broader academic interests of talented women than men.⁹ Nevertheless, these are the girls and women who are the most likely to do well and stay in STEM occupations. Interventions focused on these girls and women may do more to increase in absolute number the women in STEM professions in the long run than will shot-gun type interventions that focus on the contentious and vigorously debated—at least, within the scientific community¹⁰—concepts of microaggression, implicit bias, or stereotype threat.

Before moving to the next topic, I want to point out that women and men who enter the same STEM field are more similar than different in terms of academic strengths (math > language), interests (e.g., investigative > artistic), and values (e.g., theoretical > political).¹¹ This does not mean that there will necessarily be equal numbers of women and men in these fields, but it does mean that men in computer science, for instance, probably have more in common with their female colleagues than they do with men in non-STEM fields, and vice versa.

Work-Family Balance

Anything in life that involves significant investments of time, energy, and intellectual capital (among other things) comes at a cost, and this includes trade-offs between investment in work (higher in men) and family (higher in women). These well-documented sex differences are found even among men and women with the academic and interest profiles that would make for a very successful STEM career. A long-term study of mathematically gifted people revealed that men devoted about 25% more time to their careers than their equally-capable female peers, with the inverse in time devoted to family.¹² Moreover, these men valued economic success and having an impact on the field more strongly than their female-peers, whereas these women valued career flexibility and time for friends and family more strongly than their male-peers.

These differences are not simply a reflection of cultural norms or expectations, but rather have a deep evolutionary history. Males invest little to nothing in their offspring in at least 95% of mammalian species,¹³ including chimpanzees and bonobos. Humans are a curious exception to this pattern, with some men investing little to nothing in their children to other men investing substantially. The differences among men reflect a variety of factors, including the quality of the relationship with their wives, hormone levels, and wider cultural mores.¹⁴ In terms of direct engagement with children, even the highest investing men typically invest less than their wives, throughout the world; these men, however, invest in other ways (e.g., financially).

The flip side of investment in parenting is competing for social and cultural resources, achievements that will make the man attractive to a prospective wife. This also follows a pattern that goes much deeper than social convention. Across species, males who compete (especially if it’s physical) more than parent are physically larger, grow at a slower rate, and have a shorter lifespan than same-species females.¹⁵ Humans clearly fit this pattern and other patterns in ways that are consistent with an evolutionary history of intense male-male completion.¹⁶ This is not to say that women are not competitive—they clearly are¹⁷—but rather that the cost-benefit tradeoffs of intense competition have differed for men and women throughout human evolution, following a more basic pattern among mammals and many other species.¹⁸

For people, status is achieved and competition is expressed in much more flexible ways than in other species and influenced by a host of economic and social factors. In the modern world, this striving for cultural success is achieved, in part, by being successful in one’s occupation, and the predicted sex difference—men strive more than women—is borne out in the just described differences in the investment men and women make in work versus family.

Sex Differences Matter

There are important and sometimes substantive differences between boys and girls and men and women, and some of these differences are built upon a biological and evolutionary foundation. The ways in which any such differences are expressed can be influenced by childhood experiences, cultural mores, or explicit social rules (e.g., laws), but they are there nevertheless. Basic sex differences in one’s interest in people and living things versus an interest in how the inorganic world works are found throughout the world, but these are expressed differently in specific cultural contexts. In the work world in economically advanced nations, these differences express themselves as sex differences in educational and occupational interests and contribute to differences in the numbers of men and women in some STEM fields, including computer science.

Educationally, these differences, along with other factors, can influence students’ relative investment in language-related versus math- and science-related coursework and thus preparation for a STEM or non-STEM career. Almost all of the associated research on these academic sex differences has focused on the average gap between boys and girls, but the real and heretofore overlooked factor is each individual students’ relative strengths and weaknesses. Independent of absolute levels of achievement, more girls than boys are better at reading than math or science, a pattern associated with the pursuit of non-STEM degrees, whereas more boys than girls are better at math or science than reading, a pattern associated with the pursuit of STEM degrees. Still, there are significant numbers of girls with a STEM-like academic pattern who have been overlooked, and they might provide an untapped pool of talent.

Both men and women are competitive, striving for social influence and control of culturally important resources (e.g., a high paying job), and most men and women invest in the well-being of their children. There are, however, differences in the allocation of time and effort men and women devote to competitive striving versus direct investment in the family—differences that are found throughout the world and for that matter in 95% of mammalian species. In economically advanced nations, these differences express themselves, on average, as sex differences in time devoted to work and in time spent with family, and these, in turn, contribute to the sex differences in occupational success and earnings.

David C. Geary, Ph.D., is a Curators’ Distinguished Professor in the Department of Psychological Sciences and Interdisciplinary Neuroscience Program at the University of Missouri. In addition to numerous scientific publications on sex differences, he has written several books on the topic, including Male, female: The evolution of human sex differences (2010, American Psychological Association).

*The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or views of the Institute for Family Studies.

1. Su, R., Rounds, J., & Armstrong, P. I. (2009). Men and things, women, and people. Psychological Bulletin, 135, 859-884.

2. Geary, D. C. (1995). Reflections of evolution and culture in children's cognition: Implications for mathematical development and instruction. American Psychologist, 50, 24-37.

3. Murdock, G. P. (1981). Atlas of world cultures. Pittsburgh, PA: University of Pittsburgh Press.

4. Lofstedt, J. (2003). Gender and veterinary medicine. The Canadian Veterinary Journal, 44, 533-535.

5. Lippa, R.A., Collaer, M.L, & Peters, M. (2010). Sex differences in mental rotation and line angle judgments are positively associated with gender equality and economic development across 53 nations. Archives of Sexual Behavior, 39, 990-997.

6. Stoet, G., & Geary, D. C. (2015). Sex differences in academic achievement are not related to political, economic, or social equality. Intelligence, 48, 137-151.

7. Stoet, G., & Geary, D. C. (2015). Sex differences in academic achievement are not related to political, economic, or social equality. Intelligence, 48, 137-151.

8. Stoet, G., & Geary, D. C. The gender equality paradox in STEM education. Under editorial review. 2017.

9. Lubinski, D., & Benbow, C. P. (1992). Gender differences in abilities and preferences among the gifted: Implications for the math/science pipeline. Current Directions in Psychological Science, 1, 61-66.

10. Lilienfeld, S. O. (2017). Microaggressions: Strong claims, inadequate evidence. Perspectives on Psychological Science, 12, 138-169.

11. Lubinski, D., Benbow, C. P., Shea, D. L., Eftekhari-Sanjani, H., & Halvorson, M. B. (2001).Men and women at promise for scientific excellence: Similarity not dissimilarity. Psychological Science, 12(4), 309-317.

12 Lubinski, D., Benbow, C. P., & Kell, H. J. (2014). Life paths and accomplishments ofmathematically precocious males and females four decades later. Psychological Science, 25, 2217-2232.

13. Clutton-Brock, T. H. (1989). Mammalian mating systems. Proceedings of the Royal Society of London B, 236, 339-372.

14. Geary, D. C. (2010). Male, female: The evolution of human sex differences (second ed). Washington, DC: American Psychological Association.

15. Clutton-Brock, T. H., & Isvaran, K. (2007). Sex differences in ageing in natural populations of vertebrates. Proceedings of the Royal Society of London B, 274, 3097-3104. See also: Leigh, S. R. (1996). Evolution of human growth spurts. American Journal of Physical Anthropology, 101, 455-474

16. Geary, D. C. (2010). Male, female: The evolution of human sex differences (second ed). Washington, DC: American Psychological Association.

17. Geary, D. C., Winegard, B., & Winegard, B. (2014). Reflections on the evolution of human sex differences: Social selection and the evolution of competition among women. In V. A. Weekes-Shackelford & T. K. Shackelford (Eds.), Evolutionary perspectives on human sexual psychology and behavior (pp. 395-414). New York: Springer.

18. Andersson, M. (1994). Sexual selection. Princeton, NJ: Princeton University Press.