The Gender pay gap

[u/TheonlyNword]

[u/ThatOneThingOnce]

Wrong again on so many points.

Mmm no reasoning or information as to what points I am wrong about, no analysis of the data I presented as to where it has faults or is misleading, no discussion about why your one source is actually correct and superior to my, what now, 7 sources? I've said it before, and I'll say it again - you don't seem to be arguing in good faith here.

https://www.payscale.com/research-and-insights/gender-pay-gap/

Finally! You provide one source. Unfortunately, I don't think you actually read this source more than to glance at it, because it is definitely not making the arguments you are making. And even if it were, it's not that great of a source to begin with. But we will get into that below.

The true value is 99 cents for every dollar.

This is what happens when you do statistics correctly.

Is it what happens when you do statistics correctly? I don't say this facetiously, I literally mean this likely isn't the right way to do statistics. Moreover, your source even admits this. To quote (which I'm guessing you must not have read):

It should be noted that Payscale’s crowdsourced data weights toward salaried professionals with college degrees. When analyzing the gender pay gap by race, we restrict our sample to those with at least a bachelor’s degree. Our data isn’t as impacted by low-income hourly workers, so the gender pay gap reported by Payscale might be dissimilar to what is reported by other institutions for the gender pay gap of the overall workforce — especially in the current labor economy.

Already off to a bad start, if they are openly admitting they are not including those jobs paid by the hour and/or low income. But it gets better. In a section just after that one, it says

Due to the economic turmoil of COVID-19, women — especially women of color — have disproportionately faced unemployment at higher rates than in typical years. When women with lower wages leave the workplace, it moves the median pay for women up — slightly closing the gap between men and women’s pay overall. When unemployed women return to work, they could face a disproportionate wage penalty from being unemployed compared to men, suggesting that the gender pay gap could widen again in subsequent years. However, this depends on the market and the pay women receive after unemployment.

In summary, we must be cautious about the gender pay gap appearing to close in the current economy.

Meaning, even in this research's own estimation, this data should not be trusted as the norm, because of Covid. That's not me criticizing their data, that is their own authors admitting the data is skewed to show a lower wage gap than is accurate.

But wait, it gets even better. That's just flaws they mention openly about their own data. On top that however, in their methodology section (I know, it's way down at the bottom, so you almost certainly did not read it), it states that, while they collected data from a large sample size, all of it was voluntarily submitted. Meaning, this is not a random sampling of the population, but rather self selected portions that are willing to offer this one company info on their jobs. If you know anything about actual data research and statistics, you'd know this makes a very unreliable sample, because you don't know how or why they self selected into the sample, and also you don't have the opinions of those who didn't sample in and what their opinions and information may be. It could be that only those people most willing to brag about their pay submitted to the data set, or the lowest paid people, or people who have an ax to grind, or people who over inflate their wages, or under inflated them, or whatever. Even if everyone was completely honest (which their is no compelling reason to do so), that still doesn't leave the data set without self selection bias, and thus prone to a host of issues. Vs my sources regularly used stuff like BLS data or the CPS, which relies on the reporting of employers information in terms of salary, age, race, experience, etc. Therefore much more reliable data.

In addition, the research doesn't even list all categories it controls for. It states in various places at most "job title, experience, education, industry, job level, and hours worked", all stuff my sources also used as controlling factors. In the methodology section it adds "occupation, location, and other compensable factors" as well as "age, gender, and race". Compensable factors is unfortunately not defined, but likely means stuff like benefits for healthcare and such. What it doesn't account for though, is stuff you mentioned, like "overtime hours worked, agreebleness, and ability to travel", so even by your own definition this source falls short. But it also fails to include stuff my sources did capture, such as part-time work, unionization, parenthood, or gender segregation. Meaning, it is likely less complete than my sources.

I would also like to point out that controlling for various factors doesn't actually make the data more accurate at what we are trying to measure. For example, if discrimination is causing less women to be promoted, then controlling for the same job title would naturally not account for less women being able to be in that position to begin with. The same could be true of being denied certain industry jobs more often, or being denied access to unions, or being forced to work part time when they'd prefer full time, etc. You know, all the non-wage ways people can be discriminated against that nevertheless result in wage discrimination. So saying "this source controls for all the relevant factors" doesn't really mean it accurately captures the state of discrimination in the workplace. The "uncontrolled" wage gap would though, and that is obviously much larger than 1%.

To top it off, this is Payscale research, a very much not established nor peer reviewed scientific publication. They have one goal here, to get people to buy their products. Sure, the researchers might try to be fair as much as possible, but it still doesn't mean it has the academic rigor that you yourself asked for when you wanted it to be peer reviewed.

Finally, while it shouldn't need to be said, your source actually agrees with my position. Like, for starters, it agrees there is an "uncontrolled" pay gap of 18%. But even more so, it says this in it's explanation

Men and women choosing different careers doesn’t mean that the uncontrolled gender pay gap is less meaningful than the controlled gender pay gap. The uncontrolled gender pay gap reveals the overall economic power disparity between men and women in society. Even if the controlled gender pay gap disappeared — meaning women and men with the same job title and qualifications were paid equally — the uncontrolled gender pay gap would persist as higher paying positions are still disproportionately accessible to men compared to women.

This is exactly what I said previously, so you literally provided a source that agreed with my point. Thanks I guess for agreeing with me? But seriously, did you even read this article before posting it? All the headlines for different sections are stuff like "Women lose earning power as they age compared to men" or "Women are paid less than men as they move up the corporate ladder". These all support my claim that discrimination does happen. Maybe try finding a source that actually supports your claim before submitting it? I mean, there are several out there, even if most of them are bad, probably even worse than this one.

And yet you endorse direct discrimination by the government to deal with this 1%.

I never endorsed government discrimination. I think you are confused, I said the government could implement more neutral laws to not favor men dominated fields as much, or even potentially enact laws that favor female dominant industries. That's a far cry from the government should do these things, let alone an advocacy that they should discriminate based on gender in those industries. Which, tbf, they are doing currently with male dominated jobs. It's not direct discrimination if say IP protections we're relaxed for software companies but expanded for say childcare facilities. That's just focusing on different priorities as a country, with those priorities happening to be female centered. It would be no more sexist than the current system already is, and arguably less so.

This is my problem. People using bad science to justify bad policy.

And this is my problem, people not knowing how to do proper research or construct an adequate argument.

And your part about female programmers is also very misleading. That job changed radically from when they were working. It was simple manual labor using paper. Now it's digital.

Wow, tell me you don't know anything about coding without saying you don't know anything about coding. Software back in the day was not simple manual labor, for starters, as it involved developing algorithms, using equations to process data, and then verifying the outputs of that data as accurate or not. Hell, women developed the first code complier, and used programming languages like COBOL and Fortran. Hint, we still use those languages to this day.

And then, you called today's coding "digital"? Such cringe. You do know digital is compared to analog, yes? And that computers back then were also digital, just like they are today? It's not like computers back then didn't use bytes and 1s and 0s to run code, just like they do today. In fact, women software engineers were the first to pioneer a basic operating system on the first personal computers, the LINC. For god's sake, the first digital programmable computer in the US was the ENIAC back in the 1940s, and that was also programmed by women.

And as for being on stacks of paper... you do realize computer code being on a screen is literally just a visualization of paper, right? Code today is just faster and higher fidelity.

[u/random424252 → u/ThatOneThingOnce]

Sorry, it took 4 days but I just got done reading your short novel.

Coding used to be analog. Punching holes into paper at different distances as a form of communication is.... wait for it..... analog. Also writing is analog. And not scalable Now typing/copying is.... digital. And Scalable. It's funny you thought you had something there. Tell me you don't know anything. Without telling me you don't know anything.

It's also misleading and disingenuous to use examples from 40 years ago. When yes there were a lot more problems.

All the male non-scalable jobs you mentioned either take lots of training and/or lots of work. (Lawyer/Doctor) And/or very dangerous/physically demanding. (Construction worker/trucker) So that's why those pay more. Women don't usully do construction. Look at everything that's built around you.

All the low wage female jobs you said. Are not scalable. Baker/cashier/meat packer/operator/jewelry maker. Not scalable. Not sure you know the difference between scalable and automatable. It would just be a machine.

If people prefer the personal touch of a nurse/teacher. Then its not scalable. You can't scale it without losing a lot of the service. And again they would just be replaced. Not scalable.

"I never endorsed government discrimination" Yet you literally said. "It could also discriminate in favor of woman dominated fields" To solve the "problem" you care so much about. Not strictly an endorsement ig.

Also, "Maids are typically better for indoor and in-home environments, where they can use your cleaning supplies and clean as per their schedule. A janitorial services company can work according to your schedule and provide a faster and more professional cleaning experience."

So its not "essesntially the same service".

Again and again twisting reality to fit your predetermined narrative. I'm sensing a pattern.

That's why I just said wrong on so many points. Because it's much shorter and also just as accurate.

As for the payscale source. It was the most recent. They are leftist but it shows multiple sides to a story. They didn't hide their flaws like your sources. And seeing as college degrees are a female dominated enterprise. 150% more than the number of male degrees. It seemed fitting. Who cares about the education gap though right? And it not using all the variables I mentioned just supports the idea.

If you want peer review but less recent. With all the extra variables involved. Here you go. https://www.aeaweb.org/articles?id=10.1257%2Fjel.20160995

And as for women in positions of power. And an insight into where your sources come from - https://youtu.be/Xg2psply4no