If you don't have time to bother to learn about a topic, why do you assume you are more knowledgable on it than people who do spend their time studying the topic at hand? Your theory boils down to "Tide goes in, tide goes out. Never a miscommunication. You can't explain that." You can "take apart" as many papers as you want to maintain your ignorance, but all you do is make yourself irrelevant to the discussion.
If you want to "prove" that the disparity is due to men and women experiencing different cultural dynamics in male-dominated spaces (which is why research regarding male-dominated scientific fields and financial firms are relevant to the question at hand) all you need is the Census Bureau's labor statistics. The interesting research questions are what specific dynamics are at play and how we can disrupt them.
Lest you assume my contemptuous response to your willful ignorance can be ignored due to a [citation needed] tag, one paper that perhaps offers more of the background you are looking for would be the FLOSSPOLS overview of their gender-related findings in Open Source communities: http://www.flosspols.org/deliverables/FLOSSPOLS-D16-Gender_I... For background on the mechanisms involved on a micro level I'd suggest the book Thinking, Fast and Slow, and on a more macro level specifically regarding gender, I recommend Pink Brain, Blue Brain.
If you want to claim that the highly statistically-unlikely and culturally-variable gender disparities in pay, promotion and participation are not due to sexist dynamics, you need to provide both an alternative theory and evidence to support it. Given that the only evidence required to prove that sexist behavior is present in technical spaces are the comments to this article, the burden of proof is on those who disregard the published research on the topic and claim those behaviors are either isolated aberrations or have no effect on women's willingness to be employed in the field.
About the labor statistics: if you say they're all I need, it seems that you dismiss the argument I made above, that disparity of outcome does not imply discrimination all by itself. Why?
About the paper: it looks much more sloppy to me than the previous one you linked. This quote from p.12 is at the root of my dislike:
> Unlike the survey data, where claims to generality can be made via mathematical operations, generalising from ethnographic work is done via interpretation as in the humanities.
The humanities haven't been scientifically tested, so we don't know if their method leads to truth. For example, on pp. 16-17 the authors note that many women are computer users but few become IT professionals - and immediately conclude, from that fact alone, that hostile work environment must be the reason. It's fishy that there are no intermediate steps of reasoning and no alternative hypotheses. There are many such examples in the paper.
About the books: I'm already a big fan of Kahneman. Why specifically do you mention his book as support? Pink Brain, Blue Brain seems to deal with the development of children rather than with sexism in mostly-adult fields like IT, and if its conclusions are right, then sexism of male IT workers is not required to explain the small number of women in IT because differences in development are already enough. Why are you mentioning it as support?
Also, do you disagree with what I said about the previous paper? It's a little frustrating when people abandon lines of argument to start new ones.
If you want to "prove" that the disparity is due to men and women experiencing different cultural dynamics in male-dominated spaces (which is why research regarding male-dominated scientific fields and financial firms are relevant to the question at hand) all you need is the Census Bureau's labor statistics. The interesting research questions are what specific dynamics are at play and how we can disrupt them.
Lest you assume my contemptuous response to your willful ignorance can be ignored due to a [citation needed] tag, one paper that perhaps offers more of the background you are looking for would be the FLOSSPOLS overview of their gender-related findings in Open Source communities: http://www.flosspols.org/deliverables/FLOSSPOLS-D16-Gender_I... For background on the mechanisms involved on a micro level I'd suggest the book Thinking, Fast and Slow, and on a more macro level specifically regarding gender, I recommend Pink Brain, Blue Brain.
If you want to claim that the highly statistically-unlikely and culturally-variable gender disparities in pay, promotion and participation are not due to sexist dynamics, you need to provide both an alternative theory and evidence to support it. Given that the only evidence required to prove that sexist behavior is present in technical spaces are the comments to this article, the burden of proof is on those who disregard the published research on the topic and claim those behaviors are either isolated aberrations or have no effect on women's willingness to be employed in the field.