Wage Gaps & The Discrimination Fallacy
Wage Gaps & The Discrimination Fallacy
“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:
The Discrimination Fallacy occurs when disparities are attributed too discrimination without substantial evidence being given to prove that discrimination was indeed the driving factor behind the aforementioned disparities.
The Discrimination Fallacy is a type of ‘Hasty Generalization’ as exemplified in the below visual:
When discussing the Wage Gap there are two terms to be aware of:
Uncontrolled Wage Gap: This represents how much the average woman makes relative to the average man.
Controlled Wage Gap: This represents how much the average woman makes relative to the average man once factors like job title, education, experience, industry, job level, and hours worked have been accounted for.
Payscale has an excellent report on the Wage Gap that breaks down the variance into both uncontrolled and controlled along with sub-categories representing race and various industries.
Drawing from the Payscale report, we see that the Uncontrolled Wage Gap indicates that women make 82 cents for every $1 men make and the Controlled Wage Gap indicates that women make 99 cents for every $1 men make. It’s important to note how much the Wage Gap shrinks once we factor in job title, education, experience, industry, job level, and hours worked; this also indicates that raw discrimination, at most, accounts for 1 entire cent when calculating the Wage Gap and could account for even less when considering other differences that exist between men and women. This is not to imply that discrimination never happens, but to simply acknowledge society has progressed to a point where discrimination plays a very minor role in gender pay disparities.
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.