i agree. and this goes both ways. some people start from the axiom that racism/sexism don't exist and modify their interpretation of the data to match that. "There's no pay difference".
others perceive racism/sexism everywhere and only read that the 95 percentile and unweighted pays are different.
We can get off the political topic and start with other axioms as well. IE some believe more women need to be involved in tech, while others want less competition in their respective field (lower vs higher salary).
> i agree. and this goes both ways. some people start from the axiom that racism/sexism don't exist and modify their interpretation of the data to match that. "There's no pay difference".
Yes, of course. Really, for all the talk about convoluted biases clouding people's decision-making, it's pretty telling that most of the time, they don't even manage to get past the basic challenge of actually letting the evidence lead them to a conclusion.
A huge part of the problem is the "evidence" is terrible. There are so many degrees of freedom and so much entropy in what you're trying to measure that anyone can easily make the numbers say whatever they want.
The answer to "is it society or biology" is both. And it will always be both, because you can't change biology and you can't "balance" society without being able to disentangle biology, and disentangling biology from society would violate both causality and the Heisenberg uncertainty principle. Even measuring how much of each it is has the same problem.
People want to say we just need better evidence. We just need to measure it better or be more diligent or think about it more carefully. But it isn't that. It's that the problem is NP-complete and n is large. It may even be incomputable because some of the necessary information was lost to history and not knowable.
Which is why it's a political football. People choose their team and see how far they can run with the ball, because the score isn't based on science or math.
others perceive racism/sexism everywhere and only read that the 95 percentile and unweighted pays are different.
We can get off the political topic and start with other axioms as well. IE some believe more women need to be involved in tech, while others want less competition in their respective field (lower vs higher salary).