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Absolutely not.

That said, if Katie was a man, her story would not be as groundbreaking in a social context, and thus she would not be as celebrated.




We celebrated Mohawk NASA dude just as much as she’s being celebrated. Maybe we just like unabashedly enthusiastic engineers.


This article has 832 up vote points.

Can you link the HN article with the "Mohawk NASA dude". Searching on "Mohawk NASA" gave me a 1 point article that didn't get a single upvote.

Searching on "Bobak Ferdowsi" gives zero articles on HN, and I could not find any article where even comments were celebrating the achievements of Bobak Ferdowsi, and obviously no 832 point upvoted ones.

No, I must conclude that there is no articled named "Bobak Ferdowsi, the scientist behind the Curiosity rover", and definitively not one that got just as much celebration as this one.


Oh, not on here: this site is clearly full of people who hate both fun and science. But the complaint was about how she was being covered by the media, not how she is being discussed here, and there wasn’t a 800+ comment thread complaining about how Ferdowsi, Who got fat more vapid coverage, must not actually have done anything and didn’t deserve attention, and he wasn’t even first author of something.


I don't think he received this much praise.

So how do you explain all the famous male scientists and inventors of history? The most famous of them all are because they discovered cool things, not necessarily the "hardest" or "most significant" thing. Everyone knows e=mc2, but most people do not know about von neuman architecture, even though the latter has had a significantly greater impact on peoples lives. Taking the first picture of a black hole is as sexy as it gets in science. Katie would be famous no matter what she was.

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Social, historical, and cultural factors undoubtedly make the level of effort required to be successful as a woman in tech or science spaces higher than the level of effort a man has to make for the same level of success (if you could control everything else). This can be true without any derogatory implication about the inherent capabilities of women generally. That you can't tell the difference astonishes me.


What do you base your first sentence on?

Unsurprisingly there is now research indicating that female candidates are now twice as likely to be chosen as equally qualified men for tenure track positions in university science departments. [1] And I'm sure my computer science class was no exception in that the generally ~three females in the class had about 90% of the rest of the class willing to do any and everything they possible could to help them, mostly being happy to just be able to spend time around a woman interested in CS. I have an inside track there as one of those three is now my wife!

I don't understand how people can think it would be harder to achieve as a female in STEM in the current environment (and neither does my wife for that matter). You get jobs easier, you get tenure tracks easier, you have enormous support networks, and so on. 30 years ago I'd agree with you, but I think we've long since radically overcorrected and, as you would say, that somebody can't see this does genuinely astonish me.

[1] - https://www.washingtonpost.com/news/morning-mix/wp/2015/04/1...


It's based on things I've listened to women say about working in male-dominated fields, and on the many other studies that contradict the one in that article. Even the author of that study doesn't go as far as you, she admits the results do not mean there is no discrimination. "Radically overcorrecting" seems a couple of steps beyond that.

I guess we'll just both be astonished. Sometimes two people look at the exact same world and see different things.


Please do share these studies. I'm reasonably well read on this topic and have found all contemporary studies to be of a similar result. The thing you may be misunderstanding, as it's often made less than clear, is that there is an inequality of result - not of opportunity. Women who choose to pursue STEM are embraced with open arms. BUT very few choose to pursue it in the first place and, of those that do, many end up swapping pursuits later in life. And so studies focus on this as if it's a problem, because it surely cannot be the case that genders may be intrinsically attracted to different pursuits in life. This inequality of result, and the inability to attribute such to intrinsic factors, is the great "gender bias."

I did not say women do not face discrimination. They do. And, to varying degrees, everybody does. This is true even in the most homogeneous of societies. The region of birth based discrimination in China is far more vigorous than any form of discrimination we've had in many decades. What matters of course are the consequences of such discrimination. Cultures, interests, and aptitudes vary among any selection of individuals. Even what seem to be completely 'agnostic' selection criterion such as height will yield extreme differences in distributions [1]. So the presumption of equal opportunity leading to equal results is nonsensical. "Bias" is a loaded word, and not completely equal is not the same thing as biased, or at least the connotation of such.

I think there are two salient issues here:

1. There is a severe publication bias both against negative results and results that are not 'meaningful.' Negative results are results that indicate a hypothesis is not true. This sounds reasonable but it isn't in practice as it leads to the scenario we are currently in where finding evidence of discrimination is generally publication worthy. Yet, and this study notwithstanding, finding a lack of discrimination is generally not publication worthy. I expect the replication crisis, which is hitting the social sciences particularly hard, is in part driven by this. People need to publish something, and it generally needs to be shocking. That leads to...

2. Many people's careers and livelihoods depend upon the presence of discrimination. At one time astrology was a science at least as reputable and scholarly as psychology is today. And it's quite likely that a good number people who studied the field for decades had some inclining, perhaps buried deep in the back of their mind, that it was a bunch of crap. But of course they would quickly snuff such wrongthink out simply because such a possibility was unacceptable. After all, what are you to do when you've dedicated your life to something and you come to no longer see it as relevant? You go from a well regarded expert, to a master of nothing perhaps past thee point of being able to reboot your direction in life. No, such possibilities cannot be accepted. This is not to say discrimination is no more real than astrology. It certainly is. But rather I emphasize only that when people's livelihood depends upon finding evidence of discrimination, they will find it - whether or not it exists. "Science advances one funeral at a time."

[1] - https://en.wikipedia.org/wiki/Height_and_intelligence


> This inequality of result, and the inability to attribute such to intrinsic factors, is the great "gender bias."

Ok I don't have the energy to keep this conversation going, the distance between us is too great.


Sure thing. Do shoot me the links to those studies you referenced though. I'm unaware of any such thing, but of course I am always be willing to consider the possibility that my preconceptions are inaccurate - something everybody ought be willing to do.

Three were linked in the same Washington Post article you referenced.

I do see two. I'm not sure the third you're referencing:

http://www.pnas.org/content/111/28/10107 - This is the exact sort of study I was referencing. It only shows that there is a different in result, not opportunity. It further shows that as the baseline competency standard increases (up to labs being operated by Nobel Laureates) - so does the "bias". It proposes explanations for this being either self selection by women, or bias by men. It ignores the most likely explanation which is that though the pool is split about 50/50 by gender, competencies are not.

----

http://www.pnas.org/content/109/41/16474.full.pdf - I was familiar with this study, and it's a good example of the ongoing issues with social psychology toy study. For reference the replication rate in social psychology is now at around 25%. Put another way, if a social psychology study tells you something - you'd generally be vastly more well informed if you assumed the opposite, or at least assumed what was stated, was not true!

This study offers a demonstration in a number of ways this has occurred. One major issue is that there was no effort to manage a response bias, other than in broad characteristics (race/gender) of applicants. Corinne Moss-Raucin [1] personally mailed a number of faculty asking them to respond and rate a variety of potential students. One glance at her faculty page will tell you what she's actually doing. So who voluntarily opts into this? In total just around 30% of contacted faculty chose to. I think there is a 0% chance that this is not a biased sample.

The questions were also framed in a context that seems to imply a potential personal "affinity" for an individual. One important nuance here is that the students offered up for consideration were all low quality. The questions to demonstrate bias included:

- "How likely would you be to encourage the applicant to continue to focus on research if he/she was considering switching focus to teaching?"

- "Would you characterize the applicant as someone you want to get to know better?"

Do you think you'd try to keep low performing Jennifer in your office, even if she was looking into teaching instead? Would you like to get to know her better? I mean come on this is just absurd, and a reason that the social sciences and especially social psychology is imploding in on itself. It's like if the "biases" went in the opposite direction our researcher was ready to write up an article about unhealthy professional attitudes towards females and female independence.

[1] - https://www.skidmore.edu/psychology/faculty/moss-racusin.php


Definitely not wading into specific methodological arguments. All studies require interpretation is context of their methodological strengths and weaknesses in terms of what was actually measured, and how much weight to give the study's results in context of other studies of related topics.

I feel the same way about the the studies that form the basis of the article you linked. You don't seem sceptical about those results.

I'm not going hunting for a meta-analysis that addresses this, which is really what would be ideal.

I think you are off by orders of magnitude in terms of how much influence a person's physical body has over their interests, choices, and likelihood of success. I can't relate to that, I can't argue with it, you might as well be telling me that that the sky is made of cheese.

This is why I don't see the point continuing the conversation. We'd first have to agree on what the sky is made of.


Sure thing, this [1] is one better than a meta-analysis. This is a typically extensive report from The National Academy of Sciences in 2010 carried out on gender differences. It involves a mixture of an academic meta-analysis, extensive surveying (with high response rates), and an analysis of real hiring data across six different fields: biology, chemistry, civil engineering, electrical engineering, mathematics, and physics. If it's not clear, that book is available for free in PDF format (right hand side) - you just need provide an email address, which is not validated.

Key findings are covered on page 153. Various highlights:

- The findings on academic hiring suggest that many women fared well in the hiring process at Research I institutions, which contradicts some commonly held perceptions of research-intensive universities. If women applied for positions at RI institutions, they had a better chance of being interviewed and receiving offers than had male job candidates.

- The percentage of women who were interviewed for tenure-track or tenured positions was higher than the percentage of women who applied.

- For all disciplines the percentage of tenure-track women who received the first job offer was greater than the percentage in the interview pool.

- Female tenure-track and tenured faculty reported that they were more likely to have mentors than male faculty.

- Women were more likely than men to receive tenure when they came up for tenure review.

It's the same story everywhere. Women are more than embraced in science and tech. The problem is not about equality of opportunity, but about equality of result: in spite of the very favorable treatment of women, they remain underrepresented.

[1] - https://www.nap.edu/catalog/12062/gender-differences-at-crit...

---------

I think this is already getting quite long, but one other thing I'd also add is that you can find relevant studies from Scandinavia as well. Norway is generally considered the most gender equal nation in the world. And they too went through a phase of trying to push women into various roles generally filled by men. What they found is that there was a small and roughly constant bump in participation in these fields, as opposed to the self increasing bump you might expect if gender itself produced a strong feedback mechanism. And as soon as the push lapsed, everything went back to "normal" with a great rapidity. I think the thing this really emphasizes is that you can try to push people in one direction or another, much as with some effort you can form a sponge into nearly any shape, yet what happens when you stop pushing that sponge? It just goes back to its normal form.

I'm full on with you about ensuring complete and equal opportunity for any and all women who want to focus on STEM or whatever else, to do so. But in hindsight I sometimes wonder if we go too far with "encouragement." Now going on quite a number of years after graduation, I work with computers. My wife works with people. She was majoring in sociology before I, like the good egalitarian I thought myself to be, persuaded her to swap to computer science. It was probably still for the best overall (as computer science yields skills beyond just tech) but I've always found the irony thought provoking.




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