If Katie was a man do you think people would be going through git histories and their published papers trying to determine if she is being over-credited for her achievements?
Edit: I just checked Twitter, apparently there are thousands of idiots who believe this "850,000/900,000 lines written by Andrew, therefore he wrote the algorithm" narrative. It's amazing how willing people are to eat up a low-hanging narrative as long as it confirms their world-view. All it takes is a very crude understanding of how software development works to see through this narrative.
> Andrew Chael wrote 850k out of the 900k lines of code. He was also the leader of the project. Michael D. Johnson wrote 12k lines of code. Chanchikwan wrote 5k lines of code. The woman? Only wrote 2.4k lines of code.
It's a little bit unbelievable that the author of this comment (/u/dragonballcell) nailed all of these fine-grained details (red herrings, perhaps?) and yet glossed over an incredibly important and superficial/trivial detail: that Andrew Chael did not "write 850k LOC", he generated hundreds of thousands of lines of data and committed them to the repo. Needless to say, I think this whole drama is incredibly pointless.
You might as well credit the Linux operating system to only a single man, whose effort is certainly largely responsible, but for who also does not in any way represent the whole of effort.
It's the ship of Theseus all over again.
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.
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.
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.  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.
 - https://www.washingtonpost.com/news/morning-mix/wp/2015/04/1...
I guess we'll just both be astonished. Sometimes two people look at the exact same world and see different things.
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 . 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."
 - https://en.wikipedia.org/wiki/Height_and_intelligence
Ok I don't have the energy to keep this conversation going, the distance between us is too great.
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  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.
 - https://www.skidmore.edu/psychology/faculty/moss-racusin.php
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.
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.
 - 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.
I have no idea why people are doing this to Dr. Bouman, if it's gender related or not. Just stating my experiences.
Just so I'm fair, my GitHub does suck.
Some companies addressed it directly and some let it happen. It also was not every co-worker at every job. Just a select few personality types mainly.
The team does work, but someone else gets the credit.
It's not that they don't deserve their fair share of credit, to be clear. It's that they do not deserve the level of overwhelming credit the media intentionally tries to bestow upon them, to create an idol that sells / generates clicks.
You pretty well see it in every thread regarding those two people. The hype train tries to give them credit, whether the media or fans, and other people get annoyed by it and call it out because it's obviously ridiculous to so overly credit such vast accomplishments requiring thousands of contributors to a given individual.
On the other hand, looking at git histories is basically how the social parts of engineering (e.g., money and power) at a place like Google works, at its fundamental level.
This has persisted for a very, very long time. I still remember when people would comment things like, "I worked with so-and-so unorthodox former Google employee, and he didn't commit code."
There are a lot of Googlers on HN. There are a lot of people who work at places that culturally align themselves with how that company runs.
It probably has something to do with why some women feel underpaid or unwelcome at these places.
It definitely has something to do with people commenting things like, "So is this the case of the product manager taking credit..." The tension between the product manager who "didn't do anything" and the engineer who "did all the work" and how the "org" sees that and measures "performance" are all swimming in the back of HN people's heads when they snipe some random academic.
Settling the score in a way so reductive is extremely appealing. But at least in duels, the other person gets to fire back.
In my experience, people don't start looking into these things without some other suspicion. In a work setting, that would be things like impressions of poor productivity, claimed output not matching perceptions of competency, etc. But those involve a ton of data points, based on direct interactions with the person. In this case, the article gives us the following demographic data points:
- 29 years old
- Computer Science doctorate from MIT
- Assistant professor of computing and mathematical sciences at the California Institute of Technology
Which of those data points suggests that her work output should be questioned?
I think people let their own personal biases destroy their impartiality. Replace her name with Musk, algorithm with science/engineering, and 'image of a black-hole' with reusable rocket. The article would (and does) read like something posted by a sycophantic fanboy. It wouldn't be doing him any favors, and certainly isn't doing her any favors. However, I also do not think this article is representative of her in any way, shape, or form.
For instance it tries to frame things in the most narcissistic way possible. They found one image posted where the developer stated, "Watching in disbelief as the first image I ever made of a black hole was in the process of being reconstructed." So she made that image. Not a team, not the project of a coordinate global effort, no - she made that image. Even the image framing itself is indicative. It's a tiny out of focus image of a laptop and a giant in focus image of her with an artificial pose. The article itself continues with a similar narrative in all the eye-catching spots such as the headline and image captions: "Katie Bouman designed an algorithm that made the image possible" "Katie Bouman: The woman behind the first black hole image", and so on.
But as mentioned, I doubt this is indicative of the developer herself. She's probably just being used by the media. She's attractive, young, and has the right genitalia = stories that'll get a million clicks and shares = $$$. When you actually read the very small number of quotes from her, they seem much more realistic and in stark contrast to the media sensationalism:
- "No one of us could've done it alone. It came together because of lots of different people from many different backgrounds."
- "We're a melting pot of astronomers, physicists, mathematicians and engineers, and that's what it took to achieve something once thought impossible".
Also if she was a man her story and contribution wouldn't be as sensationalized as has been done.
Well, I take part of that back. He did have some personal pieces about "he's the guy that's a bully of the project" (when he took a personal hiatus from the project)
So yes, that happens a lot.
>to the exclusion of the algorithm designer and the primary software author?
How can you possibly infer that from a git history?