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10/13/24: Still here, tomorrow gets a new post, one that I didn't want to write. Many things going on, not enough time in the day. I have a dozen articles that I need to finish. I am working on them. I promise.

Lying statistics

This article stemmed from doing my due diligence in researching for the article Have you noticed?, I started reading about the Gender Pay Gap that was the basis of Obama’s EO that Trump abolished with one of his EO’s. I had to split it into a pinned post of its own, The Gender Pay Gap to detail what the issue is about, and then this article about the disingenuousness that exists when your research shows what you don’t want it to show.

The overall lesson of this article is supplied by Mark Twain:

He uses statistics as a drunk uses a lamp post: for support rather than illumination.

Numbers are numbers and cannot show anything but facts. If you collect the numbers incorrectly or incompletely, or you parse the data to show what you want rather than the logical conclusion the whole data shows, then you are lying. You could say “obfuscating,” “exaggerating,” or any of several other adjectives, but they all come back to lying. The context of the subject and data will determine if the lies are from incompetence or intentional.

Basically, the basis of the “Gender Pay Gap” says that women make 77% of men’s earnings. Some Liberals love to drag this “statistic” out at every possible opportunity, which was derived from taking the average earnings of all full-time female workers and comparing it to the average earnings of all full-time male workers.

Now comes another applicable quote, this one by Neil deGrasse Tyson:

In science, when human behavior enters the equation, things go nonlinear. That's why Physics is easy and Sociology is hard.

In other words, when human choice enters the equation, numbers now have other factors that change their context and thus their significance.

While researching Have you noticed?, I found an article on the Huffington Post (a Liberal-leaning website if there ever was one), Wage Gap Myth Exposed — By Feminists. I also found pretty much the same article by Art Gutman here, AAUW Releases Report on Gender Gap in Wages.

The curious thing is, the link to the document on the American Association of University Women website in both articles leads to this image:

AAUW 404

My curiosity, piqued before, now has gone on full alert. Here are two articles that say the gender pay gap is 7 percent. They reference a document that proves this. When you go to try and find this document however, you get the above image. Someone is lying here. I do want to make clear that I am not stating or implying that AAUW intentionally hid this document from these articles. It could be merely a broken link due to an upgraded version of the document, or the document was moved to another directory. I will confess my website is probably guilty of that somewhere. What I am saying is that their data shows way different results than what their images are saying.

With some additional searching, I found the PDF referenced by the links and I am hosting it here to make sure it doesn’t go anywhere. Here it is: Graduating to a Pay Gap The Earnings of Women and Men One Year after College Graduation.

I have detailed the why and how women make less in my Gender Pay Gap post and I will not repeat it here. Suffice it to say is that the “Gender Pay Gap,” is there, but it’s 7 percent, not 23 percent. The 16 percent (23 - 7 = 16) are things like the particular career chosen, negotiation of job pay/hours/scope and so on. They spend 63.5 out of 64 pages decrying this humongous pay gap, yet if you read, really read this document, you will see one sentence in the Executive Summary on page two and this paragraph at the end of page 20. The sentence in the executive summary is a summary of this passage:

One-third of the pay gap is unexplained.

Although education and employment factors explain a substantial part of the pay gap, they do not explain it in its entirety. Regression analysis allows us to analyze the effect of multiple factors on earnings at the same time. One might expect

that when you compare men and women with the same major, who attended the same type of institution and worked the same hours in the same job in the same economic sector, the pay gap would disappear. But this is not what our analysis shows. Our regression analysis finds that just over one-third of the pay gap cannot be explained by any of these factors and appears to be attributable to gender alone. That is, after we controlled for all the factors included in our analysis that we found to affect earnings, college educated women working full time earned an unexplained 7 percent less than their male peers did one year out of college (see figure 10; see also figure 13 in the appendix).

Let me translate that passage: “After the variables for human choice to select a less-than-optimal career path is accounted for, there is a pay gap, but it’s less than the numbers we want to promote, so while we are mentioning it to be ‘honest,’ this will be the only mention of it.”

There is also a subtle accounting trick being used here as well that you won’t see if you’re not looking for it. Have you noticed it?

Let me rewrite the last sentence from above and shift it to the same measurement value:

That is, after we controlled for all the factors included in our analysis that we found to affect earnings, college educated women working full time actually earned 93 percent of what their male peers did one year out of college.

Compare “Women makes 77 percent of what a man makes,” and “Women really make 7 percent less than a man,” versus “Women makes 77 percent of what a man makes,” and “Women really makes 93 percent of what a man makes,”

Does that not change the whole context of the case? It sounds very different and a whole lot better than the doom and gloom AAUW is pushing, does it not? In my pinned post conclusion I do state that we should work toward eliminating that 7 percent difference.

Just as an aside, what is AAUW's "solution" to this "problem"? You guessed it. Government intervention by way of laws and regulations to mandate equal pay.

This is why when you see a lot of graphs and numbers being thrown around, it always merits a second, hard and detailed look at the raw data.

 

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