“Women only make 82 cents for every one dollar made by a man” is a statement most of us have likely heard at some point or another in reference to the wage gap that exists between men and women. If you came to this article expecting to be validated that the wage does not exist, well it does. If you came to this article expecting to be validated that discrimination against women is the reason behind the wage gap existing then you too will be similarly disappointed. Fact is the wage gap between men and women does exist but discrimination is not the reason for its existence. The conversations around discrimination that supposedly causes the wage gap are an example of the Discrimination Fallacy which can be defined as follows:
your argumentation is missing some critically important information. Sure, most people don’t understand how multiple regression works and are subject to all kinds of fallacious thinking. here you’ve also faulted at making the point. You can control for whatever variables you want and the math won’t be upset at your choices. Which is to say, multiple regression is just correlation analysis. As a form of correlation analysis, it has no mechanism for determining causal forces. The theory of causality comes from outside of the math. SO, you’d want to explain how each of the factors in the wage gap analysis has a causal influence on wages. If they don’t have a causal influence then there’s no reason why they can’t be replaced or left out entirely. Moreover, you’d want to explain how gender discrimination DOES NOT account for differences between men and women along those factors. If they’re completely unrelated to gender, then you’re in an even worse analytical position because multiple regression would be the wrong tool for the job. You’d need probably structural equation modeling. While we’re on that point, the data need to be defined at the appropriate level to use multiple regression. If the data are provided in a aggregated form (I.e., at a city, state, industry, country level, etc.) then the statements about causality have to stay at that level because of Simpsons paradox and the ecological fallacy.
Those of us who actually work in the productive sector of the economy can tell you why the wage gap exists without your fancy word salad. The average blue collar white guy on a bar stool can tell you in far fewer words which anyone can understand.
Hahaha, nice try with all the gobblygook. Ooohhh i am soooo impressed by your 16 cylinders word engine. But in the end it misfired and puttered with a puff of blue smoke with no forward momentum to what you were trying to say.
I must admit that I'm curious as to what you find to be so foolish about challenging misinformation at the source. Under less anonymous circumstanced I might even ask you to clarify what you mean (though you and I both know there isn't any substance to clarify.) Whereas you read the comment thinking that its foolish, the comment wasn't written for diehards. Rather, it was written for people who might actually be confused by the substance of blog post and who really only stumbled upon it because it was elevated to millions of potential readers because Elon musk tweeted about it.
Also….proper argumentation: Claim -> Evidence -> Source -> Citation.
your argumentation is missing some critically important information. Sure, most people don’t understand how multiple regression works and are subject to all kinds of fallacious thinking. here you’ve also faulted at making the point. You can control for whatever variables you want and the math won’t be upset at your choices. Which is to say, multiple regression is just correlation analysis. As a form of correlation analysis, it has no mechanism for determining causal forces. The theory of causality comes from outside of the math. SO, you’d want to explain how each of the factors in the wage gap analysis has a causal influence on wages. If they don’t have a causal influence then there’s no reason why they can’t be replaced or left out entirely. Moreover, you’d want to explain how gender discrimination DOES NOT account for differences between men and women along those factors. If they’re completely unrelated to gender, then you’re in an even worse analytical position because multiple regression would be the wrong tool for the job. You’d need probably structural equation modeling. While we’re on that point, the data need to be defined at the appropriate level to use multiple regression. If the data are provided in a aggregated form (I.e., at a city, state, industry, country level, etc.) then the statements about causality have to stay at that level because of Simpsons paradox and the ecological fallacy.
Those of us who actually work in the productive sector of the economy can tell you why the wage gap exists without your fancy word salad. The average blue collar white guy on a bar stool can tell you in far fewer words which anyone can understand.
Hahaha, nice try with all the gobblygook. Ooohhh i am soooo impressed by your 16 cylinders word engine. But in the end it misfired and puttered with a puff of blue smoke with no forward momentum to what you were trying to say.
I'm so sorry that life is so hard for you. Your life has value. You can put it to good use.
Sorry. In trying to come off as so smart with your fancy language, (Its very good actually) you actually come off looking quiet foolish.
I must admit that I'm curious as to what you find to be so foolish about challenging misinformation at the source. Under less anonymous circumstanced I might even ask you to clarify what you mean (though you and I both know there isn't any substance to clarify.) Whereas you read the comment thinking that its foolish, the comment wasn't written for diehards. Rather, it was written for people who might actually be confused by the substance of blog post and who really only stumbled upon it because it was elevated to millions of potential readers because Elon musk tweeted about it.