Want to comment on the importance of organizing data when it comes to the gender pay gap chart presented in this section. I’ve seen things like this before and I think there is likely errors in data organization and interpretation; not comparing apples to apples
For anyone who would like some insight into the data presented regarding the gender pay gap, I suggest looking into Warren Farrell’s work, who is a gender studies major and has done some amazing work in support of second wave feminism. He had daughters of his own, and talk about the gender pay gap was a concern for his girls’ future, so he started digging. What he found was interesting.
What you start to find is, as you get more and more specialized, the gap gets smaller and smaller. For example, it’s often noted that male doctors get paid more than female, and at first glance one would say “look! that’s the same work and there is a 15-20% gap! outrage!” But comparing doctors to doctors isn’t always apples to apples. An optometrist gets paid more than a general practitioner, and when you look at the data a higher percentage of women who are doctors are general practitioners when compared to men, and as things get more and more specialized (optometrists can also be a highly specialized retinal surgeon rather than just an general optometrist) a higher percentage of men occupy increasingly specialized fields than women, and the gap in pay really starts to disappear.
Farrell explored about 13 reasons why men earn more (which, btw, usually does not lead to better lives for men on the aggregate) including:
-willingness to work longer hours in their late 20s, 30s & 40s
-willingness to take hazardous jobs that women will not
-Women having a better focus on a balanced lifestyle
-women’s preference for types of work that pay less (teaching, caregiving)
…and more
So these kinds of subtleties are important when trying to get more accurate interpretations of the data. When it comes to this chart I would be very interested to see how the data was cleaned and organized.
We also ought to be careful how we present incomplete representations of data to women as I fear it is doing them no good and might cultivate a victim mentality. Cathie Wood, a role model of mine and likely (guessing) the most important person in investing in the 21st century, is big on women “self selecting”. In the ARK fund talent is self selecting and she mentions in the video below how she wishes more women would self select. I love Cathie Wood btw, she is such an inspiration!
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