The 0.5 prior thing was an irrelevant use of the principle of indifference. What I really had in mind was a situation with the null hypothesis that having early women on board has no effect on the success rate of a startup whereas H_1 would be that they do have an effect. However, from my description I think what came out was a prior of the kind P(success | women).
Without using any terminology, intuitively the point I was trying to make (ineptly, as you point out) was this: the likelihood that I assign to the statement that "having women early in a startup increases its succeed rate" is very low, I need to see many cases, form startups working on diverse areas for me to update my likelihood value for this. Why? Because I don't think that a subset of population selected with no clear connection to success will affect the success of a startup. Clearly, if the selection has some obvious connection, e.g. coming from a highly educated family, being good in programming, etc. then it will affect success. It's just not clear to me how being a female or black or gay or Indian, etc. has such a connection. I may, of course, be wrong.
And what about the irony of me calling the kettle black: I don't hold my HN posts to the same standard as research reports from a major company.
