[johnnyb9]

Crude analysis of gender pay gap. What is the difference in experience level, hours worked, industry, etc.? Pay gap "headed in the wrong direction" could easily be more women entering the field at a junior level, which would actually be heading in the right direction.

[gremloni]

I rarely see these discussions encompass minority populations. With an astounding amount of tech work being done by minority/immigrant populations, I always find it’s a voice that’s missing.

[bradlys]

Which populations are we talking about? In the USA, I presume?

AFAIK - there isn’t an astounding amount of work being done by descendants of american slaves, people who are hispanic, native american, or pacific islander. So, maybe you can speak about which minorities you mean specifically.

[jldugger]

More formally, this is the origin story for Simpson's paradox: when you combine subgroups, trends can disappear or even reverse. The more dimensions you analyze, the close to 'truth' you can get.

This is why you have such varying claims about stuff like women earning equal pay with men. People who want social change (activists, politicans) group together the entire population, and come to the conclusion that women make 83 cents on the dollar. But when you break out along other dimensions (age/YOE, occupation, hours worked), the gap is reduced. But never eliminated!

What I'd really like to do some day is be smart enough to replicate https://www.metafilter.com/126704/with-numbers-like-these-wh... and see how more recent census data compares.

[xenocyon]

"The more dimensions you analyze, the close to 'truth' you can get."

Data scientist here. The above is not the correct takeaway from Simpson's paradox. It is not generally correct that the trends seen in subdivided groups are closer to truth than overall groups; sometimes the opposite is the case. It depends entirely on what the divisions are and whether they make sense.

With regard to gender-based pay disparity, there are a multiplicity of factors, from the most obvious ("equal pay for equal work") to other factors such as the fact that professions largely staffed by women tend to get paid less than professions largely staffed by men. For instance childcare is miserably compensated, despite being a position of high responsibility and impact.

The consensus regarding women during the pandemic (not limited to tech workers) was that women have disproportionately sacrificed their careers to cover the needs of childcare and at-home schooling during the pandemic.

[klipt]

I'm pretty sure the origin of the wage gap is just that relatively, income is a bigger status booster for men than it is for women. Women have other status boosters like being seen as a good parent, and if you look at those dimensions there's a gap in favor of women. People are simply, on average, optimizing for what benefits them most in society, and those things are different for men and women.

This explains observations like, when a field becomes more lucrative, it attracts more men. Or when a field becomes less lucrative, men abandon it and it ends up disproportionately female. So even if there's equal pay for the same job, men will earn more on average by being more likely to pursue the higher earning jobs.

Of course, we could say the fact that society values different things in men and women is sexism. That's true, but I'm not convinced it's sexism exclusively against women: a man who'd rather spend time with his kids is also negatively affected by society pushing him to be a breadwinner instead.

In the end, do wages matter more than general life satisfaction (not sure if either gender does better here), or other measures like life expectancy (which favors women)?

[whiskyant]

>the gap is reduced. But never eliminated!

https://www.payscale.com/data/gender-pay-gap

The controlled salary (same job/qualifications) for Asians, have both men and women earning the same (women a tad higher even).

[oingodoingo]

don’t forget that more women dropped out of work to handle childcare during the pandemic

[chiefalchemist]

It's also self-reported. Men, they say, in general are "bolder". That translates to over-stating and/or those with something to "brag" about are more likely to respond.

[z3c0]

While I believe "boldness" is more related to personality than to gender, I have noticed the "bragging bias" you've described quite a bit. But it goes both ways. That is to say "people respond to surveys when they have something to say." If you believe you're being paid too little, you're just as likely to chime in as somebody who wants to brag about their pay. It's the folks in the middle who end up not chiming in, out of the belief that they have little insight to offer. Because of this, ootional surveys oftentime yield biases towards the extremes.

Source: I've analyzed survey data a lot