Yes and no - The underlying issue that prompted me to bring up the lack of adequate mathematical tools to discuss sociological notions is the following:
Mathematical truth and logic is often used as a gold standard for universal truth. And it is then often used as a straw argument to simply push away complex and uncomfortable questions. (A hyperbole of such a misguided line of reasoning would be "Software is just maths/logic and therefore pure and we so don't need to think about sexism and other social issues in sofware engineering.". A more nuanced version would be parts of the article we are discussing.)
But the "default tech" when thinking about mathematical truth (for example predicate logic) is in itself biased towards universally definable truths: A given predicate is universally defined a-priori.
There's no tools for things such as conflicting definitions and speakers positions in predicate logic: In reality, different actors in a discussion might not agree on what even they are talking about.
Take as an example the often discussed statement "White people can not experience racism". If you try to naively approach this with the toolset of universally definable notions you quickly realize that it can not be true (assuming a definition of racism that is not in itself skewed).
But there is a lot of things going on here: Who are these white people? Is the statement "This person is white" even based on a well defined predicate (Hint: It's not)? Etc etc.
And so: If the only logic in your toolset is predicate logic, it's hard to grasp sociological issues.