4 ms·
I think unless another reasonable explainations is provided, discrimination is frequently a decent Occam’s razor for large disparities. If, say, a moderately si
by SamoyedFurFluff 4y ago
I think unless another reasonable explainations is provided, discrimination is frequently a decent Occam’s razor for large disparities. If, say, a moderately sized town in America has no black families, I think assuming it’s not by accident is the Occam’s razor choice. It would be better if society wasn’t like this, but yknow.
- kaba0 4y agoI do agree with you, though in this case I am not convinced that the difference is solely discrimination/bias. There is definitely some (from what I gathered, CS courses’ environment can be quite hostile to women as an example), but for example in the case of Scandinavian countries where much more effort has been put into diminishing these differences, the resulting demographic is still overly men, and the reverse is true in case of more social workplaces (nursing, pedagogy, etc). It is not too far fetched of a thought that hormonal differences between sexes does have some effect on thought patterns, and may statistically speaking predispose some to different kinds of careers. Nonetheless, any women pursuing a job in IT should be welcome and if you have any input on what can an ordinary men employee do to help the status quo, I am all ears!
- hn_throwaway_99 4y agoBut the point is that Occam's razor is not an evidentiary argument. Occam's razor is basically saying "we don't have any explanation for why this is going on, so we'll just go with the simplest one" - and I'd even argue that falling back on "discrimination" is not even the simplest explanation in many cases. For example, found an article that stated that 61% of designers are women. Design is a desirable career with lots of opportunities. It doesn't seem correct to me to say "well, we have no better explanation, by Occam's razor there is considerable discrimination against men in design." I guess what I'm trying to say is that looking at discrepancies in population frequency is a great place to start an investigation into why those discrepancies occur, but far too often (definitely not always, but frequently) I see it as the end of an inquiry, without digging into deeper root cause analysis of what is going on.