How much of the difference between men and women in terms of employment outcomes (different fields, positions within a field, salary, leadership roles, etc.) is a result of men’s and women’s different priorities and interests? Here I look at two large meta-analyses covering over one million subjects to find out. The main findings:

While men care more than women about earnings and having a leadership role, the difference is actually very small, and so it would be only a small factor in explaining men’s higher salaries and higher chance of being in a leadership role. There are quite large differences between men and women in vocational interests, with men being more thing-oriented and women being more people-oriented. These differences in interests would thus be relatively large factors in explaining men’s predominance in fields like engineering and computer science, and women’s predominance in fields like education and nursing.

Are there any preferences that can explain (partially) gender differences in leadership roles and average salary? Yes: mothers are much more likely than fathers to prefer to stay home with their children, which puts career development on hold.

I see nothing fundamentally wrong with encouraging men and women to consider different options and interests, but we can’t ignore when differences exist.

Read on for a closer look at the evidence.

Sections:

Effect Sizes Job Attribute Preferences Interest Areas Stay-at-Home Parenthood

(Length: 900 words)

1. Effect Sizes

If you take a random man and a random woman, there’s a very high (92%) chance that the man will be taller. That’s a very large gender difference in height. If this chance was 50% it would mean they both have an equal (50:50) chance of being taller, which would indicate no gender difference. As a simple rule of thumb, let’s say that 50-60% is a small difference, 60-70% is a moderate difference, and above 70% is a large difference.

(This percentage is called CL, or common language effect size. I’m calculating it from Cohen’s d statistic provided in the meta-analyses, using this tool from R Psychologist.)

2. Job Attribute Preferences

The first meta-analysis looks at men’s and women’s preferences for different qualities and outcomes in their work. It surveys 242 previous studies, covering 600,000+ Americans, 1970 to 1998. Of the 40 job attributes looked at, 33 had gender differences, but the effect sizes were generally quite small.

Surprisingly, men were only a bit more likely to care about earnings (and women a bit more likely to care about benefits). The (relatively) larger and more notable differences (as pointed out by the authors) involved women being more socially-oriented.

Here are some of the findings. Note that the 53% by earnings does not mean that men care 53% more—it means that given a random man and a random woman, there’s a 53% chance that the man cares more (and a 47% chance that the woman does).

Attribute Cares more CL Size Power/influence/authority Men 51% Small Earnings Men 53% Small Benefits Women 53% Small Leadership role Men 54% Small Physical work conditions Women 54% Small Feeling of accomplishment Women 54% Small Opportunity to make friends Women 56% Small Leisure time off job Men 57% Small Solitude (n/s: small sample size) Men 57% Small Easy commute (n/s: small sample size) Women 58% Small Opportunity to help others Women 60% Moderate Working with people Women 60% Moderate

Study: “Sex Differences and Similarities in Job Attribute Preferences: A Meta-Analysis” by Alison M. Konrad, J. Edgar Ritchie, Pamela Lieb, and Elizabeth Corrigall (2000, Psychological Bulletin)

3. Interest Areas

The second meta-analysis looks at men’s and women’s broad vocational interests. It includes 47 inventories published between 1964 and 2007 with a total of 81 samples consisting of ~500,000 (American and/or Canadian) men and women.

This study uses a few different ways to measure interest areas and they overlap with each other. It looks at two dimensions (things–people and data–ideas), six RIASEC types (widely-used vocational choice categories), and three STEM interests.

Their results both support and expand on those from the previous meta-analysis. They find only small gender differences in the interest category (enterprising) that includes leadership roles and economic objectives (in line with the minimal gender difference in desire of influence/authority and leadership roles from the previous meta-analysis).

They find quite large differences in preferring to work with things rather than people. This backs up the finding from the previous meta-analysis of women being more socially-oriented (although these effect sizes are larger and thus even more notable).

Here are all of the findings. Given a random man and a random woman, there is a 74% chance that the man will be more things-oriented than the woman. This difference is highly visible in other categories as well (realistic, social, and engineering).

Attribute Higher CL Size Dimensions Things (vs. people) Men 74% Large Data (vs. ideas) Women 53% Small RIASEC types Realistic (things, gadgets, outdoors) Men 72% Large Investigative (science/math/biology/medicine) Men 57% Small Artistic (creative expression) Women 60% Moderate Social (helping people) Women 68% Moderate Enterprising (leadership, economic objectives) Men 51% Small Conventional (well-structured environments, e.g. business) Women 59% Small STEM interests Science Men 60% Moderate Mathematics Men 60% Moderate Engineering Men 78% Large

Study: “Men and Things, Women and People: A Meta-Analysis of Sex Differences in Interests” by Rong Su, James Rounds, and Patrick Ian Armstrong (2009, Psychological Bulletin)

4. Stay-at-Home Parenthood

According to a 2015 Gallup poll, almost 6 in 10 mothers would prefer to stay home with their children, compared to almost 3 in 10 fathers. Even for couples without children, almost 4 in 10 women prefer to stay home (compared to over 2 in 10 men).