If your exposure to men’s issues comes from online resources then you might be surprised to find out that there is actually a pretty strong body of offline literature too. The first two books work well as an overview or introduction to men’s issues (one is more philosophical and the other more personal, so they complement each other well). The other books cover other relevant topics (specific men’s issues, gender roles, feminism, etc.) in more detail.
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.
- 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).
|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).
|Things (vs. people)||Men||74%||Large|
|Data (vs. ideas)||Women||53%||Small|
|Realistic (things, gadgets, outdoors)||Men||72%||Large|
|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|
- 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).
The typical method of dismissing sexism against men is to say it isn’t “institutional”. This usually means claiming that prejudice and discrimination against men occur as isolated events by individuals, without backing of institutional power, and with limited ability to do harm. A clear counterexample is that the criminal justice system is more severe on men than on women in numerous ways, including likelihood of arrest, chance of pretrial detention, bail amount, and chance and length of jail-time. And many are calling for even more special concern and treatment for women in the justice system.