12 ms·

Gender and Race Preferences in Hiring at Silicon Valley Tech Firms [pdf]

84 points by elsewhen 6y ago

jefftk 6y ago
> Using matched sample analyses and controlling for a rich set of job and applicant attributes found in applicants’ resumes and LinkedIn profiles, we find that women are 9-10% more likely to receive a callback compared to men, whereas Black, Hispanic, and Asian applicants are 8-13% less likely to receive a callback compared to White applicants. These outcome gaps do not cancel-out in the later stages, as female and White applicants are more likely to receive an interview and offer How accurate this is, however, depends a lot on how well controlling for applicant attributes worked. > An obvious set of confounders is the applicant’s objective qualifications such as years of experience, educational attainment, and field of study, all of which affect the outcome of an application. It is widely known that many of these attributes differ across demographic groups – for example, women are less likely to major in STEM subjects, Asian Americans are more likely to have graduate degrees (Camilie Ryan and Kurt Buaman 2015). To account for these confounds, we control for total years of experience, average tenure, educational attainment (associate or less, bachelors, masters, and doctorate), field of study, and rank of the university attended (Top 10, 21-50, 51-10, ). For experience controls, we use the total number of years of experience at the time of application parsed from resume text. For average tenure, we divide the total years of experience by the number of jobs held. For university rank, we parse the Education section of the applicant’s LinkedIn profile and join this against the U.S News Global University Rankings list. If an applicant attended multiple universities, we take the lowest rank. For the field of study, we parse the Education section of the applicant’s LinkedIn profile and bucket them into one of the following categories: Technical – mathematics, computer science, engineering, economics, etc. Business – business administration, finance, accounting, marketing, etc. Law – law and legal studies. Science – natural sciences such as biology, chemistry, etc. Other – all other majors. > An applicant’s professional and social network is another important signal that employers use to screen applicants (Fernandez and Weinberg 1997; Sterling 2014). Since one’s network tends to be demographically homogeneous, the effect of gender and race could be confounded by these affiliations. We control for this in two ways. First, we use a Referral indicator from the ATS, which indicates whether an applicant has a referral from an existing employee of the firm. Second, we identify whether an applicant has worked at the company’s talent competitor. We identify a company’s talent competitors by taking the top 10 companies from which its current employee pool comes from based on all of LinkedIn data. For example, to identify Company A’s talent competitors, we first search for all the employees of Company A using all of LinkedIn data. Once these employees are identified, we look at the previous company these employees worked at before joining Company A. We then aggregate these previous companies by count, and take the top 10 companies from which Company A’s current employee pool comes from. > Finally, an applicant’s skills, previous job responsibilities, and fit for the job to which they applied are perhaps the most important factors in determining the success of an application. We operationalize this using a text-analytics method called Word2Vec to measure the similarity between skills and competencies listed in the applicant’s resume and the job description (Mikolov et al. 2013). To do so, we first train a Word2vec model on a corpus of resumes. Using this model, we transform each document (i.e resumes and job descriptions) into a vector representation based on skills listed in each document, and measure the cosine similarity between the resume vector vR and job description vector vJ . The higher the cosine similarity between the job description and resume vector, the better the fit. This type of approach is often used in automatic application screening tools I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes, which means I'm not sure I trust the callback numbers. Submitting identical resumes with different demographic characteristics seems like a much more appropriate experimental approach here? As for whether candidates receive an offer, they don't have anything here where they have actually evaluated the candidates' skills. I've given over 200 technical interviews, and resumes are just not that good a predictor of technical competence. It really doesn't seem to me like they have good enough controls to run this as a correlational experiment.
- monoideism 6y ago
  > I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes, You're in the tech industry and you honestly are skeptical that recruiters and hiring managers at most companies aren't extremely eager, to say the very least, to hire female candidates?
  - iguy 6y ago
    But regardless of whether the outcome fits your priors or not, you may wish to know whether the study has decent evidence, or is just noise. And GP has a good point. The authors have some automated scheme for grading how well-qualified people are. The recruiters also have some such scheme. If these two schemes differ, and the distributions aren't identical between the groups being compared, then you will detect group differences like what they see. To label these differences bias in the recruiter's process, you must be confident that you have less bias in your process. The details of this correction are going to be crucial.
    - monoideism 6y ago
      Yes, it's a good point. I made a snap response, and was wrong to do so. I just get tired of the ideological nonsense I see so often propogated by a certain group in the tech industry.
    - thu2111 6y ago
      Yes, but the list of criteria they use for controls is pretty reasonable and more importantly, unbiased by woke ideology. We all know many firms have a very strong bias towards women that grades them as more well qualified (desirable to hire), so we'd expect a re-run using purely objective metrics to detect that. The outcome of this study isn't a surprise, the only surprise is that the bias is "only" 10%.
  - jefftk 6y ago
    That the bottom line results be plausible is not enough. It matters whether the study is a good source of evidence for its claims. Otherwise none of us have any reason to update our views in response, and the study has no value as information.
reader5000 6y ago
They capitalized "white". They are on the wrong side of history.
- nailer 6y ago
  Are you complaining about the capitalisation of racial groups, or the capitalisation of a specific racial group?
  - reader5000 6y ago
    https://apnews.com/article/9105661462 https://apnews.com/article/9105661462
    - eznzt 6y ago
      >AP’s style is now to capitalize Black in a racial, ethnic or cultural sense, conveying an essential and shared sense of history, identity and community among people who identify as Black Ironically, pretending all blacks come from the same ethnic or cultural background is a very ignorant (and racist) thing to do.
      - eplanit 6y ago
        The AP is proving that journalism is dead.
    - ihsw 6y ago
      That is asinine.
    - nailer 6y ago
      OK so the latter. This is racist against both white people that somehow don't deserve capitalisation based on their skin color and black people in the US who don't share the limited concept of black the AP uses.
    - monoideism 6y ago
      So if they don't capitalize "white", because that's what white supremacists do, what does that say about capitalizing "black"? A good number of the people pushing the "Black" spelling are openly Afrocentric, or profess to be.
einpoklum 6y ago
Key point of the abstract: Women: +9 to +10% chance of callback relative to men Black, Hispanic, and Asian: -8 to -13% chance of callback relative to White people. Anyway, kudos (I guess?) to the researchers for choosing the absolutely most fashionable subject they could possibly study in this day and age.
- ginko 6y ago
  Would be interesting to separate Asian applicants into their own group.
  - belly_joe 6y ago
    They do in their model. Being Asian carries with it the worst relative odds of being hired, though it is not responsible for the overall negative non-white male coefficient (Black and Hispanic applicants also have negative coefficients in the logit)
    - dbsmith83 6y ago
      Seems to make sense relative to each other. D&I initiatives often times target Black and Hispanic candidates, but not Asian since they are not underrepresented.
  - CydeWeys 6y ago
    And also separating out Indian, Chinese, and Other Asian. The majority of many tech workforces are broadly Asian, along with over half of the global population. It doesn't make sense to lump them all in together. It may be acceptable in other industries in the US where Asian representation is in line with the US standard of ~6%, but certainly not in tech. If a single bucket accounts for more than half of your entire sample, and that bucket can trivially be broken down further into sub-buckets, then you should absolutely do so. This is something that tech in particular just keeps getting wrong over and over. E.g. look at the 2019 Google diversity report [1] -- on page 52 it shows that 55.5% of new tech hires in the most recent year were Asian, vs 0.7% for the smallest category (Native American). Break out that 55.5%, please! [1] https://kstatic.googleusercontent.com/files/25badfc6b6d1b33f3b87372ff7545d79261520d821e6ee9a82c4ab2de42a01216be2156bc5a60ae3337ffe7176d90b8b2b3000891ac6e516a650ecebf0e3f866 https://kstatic.googleusercontent.com/files/25badfc6b6d1b33f...
lettergram 6y ago
I always try to give the recruiter no indication of race or gender. Frankly, if we all did that it would remove the bias. The challenge is, I suspect they ask for race & gender is intentionally requested to add bias. I’ve worked with recruiters and part of the job is indeed targeting “under represented” groups to improve the figures.
- einpoklum 6y ago
  Well, you do give them their name, that's a strong indication of race and gender for most people, isn't it?
  - lettergram 6y ago
    Sure, my name is unisex though. Race might be obtained, but honestly even that is questionable
    - st1x7 6y ago
      It only seems questionable because of your specific name. If your first name was Zhang or Priya, your race would also be quite obvious.
    - BoorishBears 6y ago
      > Race might be obtained, but honestly even that is questionable If you mean "irrevocably determined with a 100% certainty" maybe... But you know, most people who think their name doesn't give away their race, are a certain race... - Funny that this is really such an uncomfortable truth for some people here... I'm a black guy with a Ghanaian name, so I laughed out loud reading the comment. It's not like black people aren't allowed to have "euro-centric" names, but, surprise surprise, Caucasians represent a large majority of people with those names Likewise there are names that almost no Caucasians have (like mine) If someone is reading your resume intent on being biased, a name like "Austin Walters" is going to appear as... a white guy. There black guys named Austin Walters but they're also not conducting a census... if someone really wants to discriminate against you based on race, your name is plenty to go on. https://www.mynamestats.com/First-Names/A/AU/AUSTIN/chart-distribution-by-race.svg https://www.mynamestats.com/First-Names/A/AU/AUSTIN/chart-di... https://www.mynamestats.com/Last-Names/W/WA/WALTERS/chart-distribution-by-race.svg https://www.mynamestats.com/Last-Names/W/WA/WALTERS/chart-di... Again, they're not conducting a science study, an 80% chance is plenty for the kind of person trying to discriminate... Likewise, someone who reads my name, which uses consonants in a way that English doesn't usually ( causing people to mispronounce my very simple last name even when reading it verbatim) will instantly assume I'm black. It's something I accept as a person with a very black name, it tells you the main audience of HN is this is really such a revelation for some of you lol
Communitivity 6y ago
Surprising study results regarding women being more likely to receive a callback than men. From personal experience and the teams I've been on, women have always been in the minority, along the lines of 8-10 men for every two women. However, I am not in Silicon Valley. We need more studies in this area. I'd also like to see studies that include other possible sources of discrimination (gender identity, age) that are known to exist in some areas. Without those other sources included in the data it's possible those sources could be skewing the data. One scenario might be that most of the women were young (20s-early 30s), while many of the men were older (late 30s to early 50s). Just one possible scenario, I'm not saying that was the case. But in that scenario the bias could be against older candidates rather than for female ones.
- jackfrodo 6y ago
  There's a contradiction in your second sentence, I'm not sure what your meaning is. >women have always been in the majority, along the lines of 8-10 men for every two women.
  - nicoburns 6y ago
    From context I think they meant that "men have always been in the majority".
  - Communitivity 6y ago
    Yes, thanks - it was meant to be minority. I've fixed in the original post.
- GhostVII 6y ago
  There are less women in the tech industry, so it is very possible for them to be more likely to get a callback and still be underrepresented.
- giantg2 6y ago
  The graph on page 13 was interesting. The gender distribution of applicants stays about the same, but the gender distribution for hires has dropped for men and risen for women. So were the women previously dropping out of the workforce? Do we now have men dropping out of the workforce? Or are they simply being reshuffled among the various companies within the industry? I ask this because there are other studies that say the industry in the US is facing a shortage of tech workers, so it seems unlikely to be that a significant number of people would be dropping out, or that this study accurately represents the industry as a whole.
SuoDuanDao 6y ago
I'm reminded of a quip I came across in the conversation around the George Floyd killing - "Being a black man in America is like being a man only more so". I guess in the case of SV hiring outcomes, this is literally true!
candu 6y ago
There's a fascinating study on orchestra auditions, where it was found that performing blind auditions (where the interviewee's identity is hidden to the interviewer) led to more equitable gender representation: https://gap.hks.harvard.edu/orchestrating-impartiality-impact-%E2%80%9Cblind%E2%80%9D-auditions-female-musicians https://gap.hks.harvard.edu/orchestrating-impartiality-impac... IMHO, if the tech industry wants to live up to its narrative of meritocracy, this is one obvious improvement over existing processes. No, it won't take care of pipeline problems; no, it won't solve the "tipping point" problem (i.e. where candidates of underrepresented groups are dissuaded by a lack of pre-existing representation, making it very hard to go from zero to one, so to speak). That said, we're uniquely positioned as an industry to do this - technical interviews are similar to auditions in that they hinge on skill-based performance - so why not? It can't be any less arbitrary than asking random questions about manhole covers and light bulbs. I'd posit that even the "show your thinking process" parts could be done in this way - e.g. via text chat, or inline comments, or maybe even using voice obfuscation and/or neutral avatars.
- jefftk 6y ago
  > performing blind auditions (where the interviewee's identity is hidden to the interviewer) led to more equitable gender representation There has recently been quite a bit of pushback on this: https://www.nytimes.com/2020/07/16/arts/music/blind-auditions-orchestras-race.html https://www.nytimes.com/2020/07/16/arts/music/blind-audition... > It can't be any less arbitrary than asking random questions about manhole covers and light bulbs. Asking random questions about manhole covers and lightbulbs doesn't work very well! Don't take that as your comparison.
  - travisoneill1 6y ago
    Well of course the people who want to hire by race want to get rid of blind auditions!
- in3d 6y ago
  You may want to read https://statmodeling.stat.columbia.edu/2019/05/11/did-blind-orchestra-auditions-really-benefit-women/ https://statmodeling.stat.columbia.edu/2019/05/11/did-blind-... “One of the more interesting findings of the study that I have not often seen reported: overall, women did worse in the blinded auditions.”
protomyth 6y ago
And once again a race study that doesn't list Native Americans at all. It would be nice if they remembered 2% of the US population, since certain policies ("Actual Name") have discriminated against Native Americans because of the ignorance of silicon valley firms. AIHEC and American Indian College Fund (collegefund.org) could really use the help to get placements for students.
- lumberjack 6y ago
  They don't care about you because you're not a politically influential demographic. Notice how the demographic that dominates this debate is the second most privileged and influential demographic in the country: white women; yet they are portrayed as being some powerless minority. It's always powerful demographics fighting each other. Nobody cares about the actual minorities that have no representation. That is almost tautological.
- bradlys 6y ago
  If it makes you feel better, you're not alone - middle eastern is never broken out either. In fact - we're grouped with white people. Some of us are white passing - some of us are very much not. Fun article about it... https://www.latimes.com/projects/la-me-census-middle-east-north-africa-race/ https://www.latimes.com/projects/la-me-census-middle-east-no... I can tell ya - after 9/11 - being middle eastern sure didn't feel like being white!
deleted 6y ago
[deleted]
simonebrunozzi 6y ago
Obligatory mention of the Google engineer, James Damore, fired for the internal memo on gender discrimination [0]. Latest news on the subject: [1]. So relevant, in fact, to deserve its own Wikipedia page [2]. [0]: https://www.nytimes.com/2017/08/07/business/google-women-engineer-fired-memo.html https://www.nytimes.com/2017/08/07/business/google-women-eng... [1]: https://www.mercurynews.com/2020/05/14/former-google-engineer-fired-over-memo-drops-discrimination-lawsuit/ https://www.mercurynews.com/2020/05/14/former-google-enginee... [2]: https://en.wikipedia.org/wiki/Google%27s_Ideological_Echo_Chamber https://en.wikipedia.org/wiki/Google%27s_Ideological_Echo_Ch...
- godelzilla 6y ago
  His memo was about "gender discrimination"? Sure, keep telling yourself that.
meraar8 6y ago
OK.
treeman79 6y ago
Personal experience. Got hired into a company that did everything possible to avoid hiring straight white men. Everything was completely dominated by not offending anyone over anything. Unless you were the aforementioned group. Turns out there simply isn’t a lot of the right race/gender/sex. I’m sure that’ll be different as time progresses, but for now there is clearly some catching up to do. So it was all jr developers. A couple of which truly cared about technology, and I see good things in their future. The rest were the most arrogant sexist bigots imaginable. Most days were filled with hatred. Full rant fest about how evil “my kind” were. But it wasn’t personal as I was clearly one of the good ones... So yeah, n=1 personal experience. But crude that echo chamber was scary.
- osipov 6y ago
  If it was just n=1, then we wouldn't have this brilliant social commentary: https://www.youtube.com/watch?v=pZy4QXLKHlI https://www.youtube.com/watch?v=pZy4QXLKHlI
  - treeman79 6y ago
    Wow. That was exactly my experience. I tried so hard to stay out of it and just code. That really upset several people.
- fraktl 6y ago
  So what you're saying is that.. I am responsible for my happiness, and that other people are not to blame for the choices I made in regards to my behavior and life, especially straight white men? Wow, that's a hard cookie to swallow. (for the ones who read this far, what I wrote is sarcastic).
- throwawaympfsin 6y ago
  That's one of the reasons I left tech and went to work for an investment bank. At least here no one pretends to be in it to "make the world a better place" or whatever agenda tech companies are selling nowadays. YMMV
ChrisMarshallNY 6y ago
The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/fitness/attractiveness/age (I'm an old fart, so I can tell you a thing or two about ageism in tech) becomes apparent. I have heard story after story from peers (around my age), about passing numerous rounds of phone and test interviews, only to see the interviewer's face fall, as soon as they walk in the door. It's happened to me, but, thankfully, before being flown out (if it's a contract application, then we're on the hook for the cost), and revealing the age. It happens with highly qualified older white guys, so I'm sure that it will happen with other distinguishing characteristics. The simple fact of the matter is, is that people have certain traits they are looking for, and the final call is always a "gut feeling." I've learned to just avoid all the agita by making it clear that I'm "of a certain age," right up front. I don't get many offers, but at least I don't have those blasted recruiters, gushing about my résumé, only to shred my contact card, as soon as they find out I'm old (I guess the industry is crawling with 32-year-olds with 30 years' experience). I don't think it's a good idea to have AIs do the selection (as has been suggested numerous times -usually by folks in the AI business). Humans need to work with humans. If an AI puts someone into a situation where they are treated like garbage by their managers and/or co-workers, then they will be miserable (and unproductive); especially if they have done something like uproot their lives to move somewhere (I have also heard many stories from people that have uprooted their lives to go to "the perfect" job, only to come back, a few months later, broken and cynical). If the people involved don't want to work with someone like me, then I don't want to work with them. That's easy for me to say, though. It can really stink, when you're hungry and need the work.
- coldcode 6y ago
  Happened to me I aced everything and when the interview walked into the room I saw it on their face (too old). Thankfully that only happened once and the company wen under at some point thereafter so good thing I didn't get hired.
- secondcoming 6y ago
  This is absolutely one of my nightmares. I'm turning 40 soon and I know my opportunities of being paid to write software will become more and more limited.
bookmarkable 6y ago
Are we still going to call it Silicon Valley when everyone is remote?
giantg2 6y ago
So according to this, high-potential women are receiving a pay premium. But I thought the BLS listed tech jobs as one of the few industries that does have an actual wage gap favoring men?
imglorp 6y ago
Okay, honest question coming from ignorance. In computing at least, there's a well known diversity disparity going back to STEM graduation rates. It seems financial is a similar boat: Wells Fargo recently claimed a “limited talent pool" but got criticized by AOC for lacking "talent to recruit Black workers". Obviously society, including industry, could do more to get kids into school. But right now, in the resume pile, what should employers be doing, and why is "not enough X talent" not a good defense? https://www.washingtonpost.com/business/2020/09/23/wells-fargo-ceo-black-employees/ https://www.washingtonpost.com/business/2020/09/23/wells-far...
- deleted 6y ago
  [deleted]
- benjaminjosephw 6y ago
  The pipelines have problems for sure but this study was about whether or not a focus on diversity in hiring was effective. I think the important bit is here: > Our results in light of these considerations suggest that the push for diversity without any effort towards inclusion is unlikely to be sustainable in the long term.
- jdmichal 6y ago
  There's a lot of implicit assumptions around this stuff that actually matter a lot, and the demographics of the actual candidate pool [0] as opposed to the general population is a huge one. I would venture that most people pushing diversity agenda want representation to match the general population, but that may not be supported the candidate pool. As you point out, it's well studied that women don't graduate with STEM degrees at a rate that matches the general population. That means that for every company that matches general population for women in STEM fields, there's other companies that literally cannot unless they hire unqualified women from outside the candidate pool. [0] I'm defining this as the group of all possible people who are qualified to be hired into a role.
HideousKojima 6y ago
Personal anecdote: I knew someone who worked as a recruiter at Boeing a few years ago, and she told me the pressure from higher ups to give preferential treatment to female applicants was crazy. She said they couldn't explicitly discriminate, but would use things like "Women in Tech" events to try to increase their female applicant pool.
JansjoFromIkea 6y ago
Searched the article for "visa" and "migrant" found no results, surely that hugely skews the data with respect to Asians? I fully imagine there is bias towards Asians within SV but it'd be heavily weighted towards recent arrivals who either have uncertain visa status or aren't yet at native speaking English proficiency surely? Whereas you'd have to imagine the vast majority of black applicants meet both of those requirements with ease.
sto_hristo 6y ago
It's the same with truly blind dating, isn't it? If you deprive yourself from the knowledge of the gender of your candidate for partner, you'd become a truly inclusive pansexual astral being in the dating scene.
CydeWeys 6y ago
Women: +9 to +10% chance of callback relative to men Black, Hispanic, and Asian: -8 to -13% chance of callback relative to White people. I wish they had broken out the other ethnicities separately in the abstract. The reasons that Black and Hispanic people might be getting fewer callbacks relative to whites are likely quite different from the reasons that Asian people might be getting fewer callbacks. I'm making my way through the main paper but there's a lot of tables in there that would take me a lot of reading to decipher and it's really not clear which are best to use for any purpose. The tables do break out the separate ethnicities separately though (along with callback/interview/offer rates, not just callback) and it does appear that Black, Hispanic, and Asian very much do not have the same experience. In particular, the graph on page 22 seems to show that, when it comes to receiving offers, female candidates have a 29.5% advantage in receiving offers, Black 4%, -21% Asian, and -24% Hispanic. The previous column (received interview) is much worse for Asian, Black, and Hispanic applicants though; all were significantly less likely to receive interviews than whites. Anyway, there's lots of potentially good data in here, assuming you trust their methodology, but I personally feel like I need someone who knows this stuff better to write up a longer abstract based on all this data to really explain it to me properly.
- dcolkitt 6y ago
  As far as I can tell, the paper doesn't seem to control for citizenship or immigration status. It seems likely that Hispanic and Asian job-seekers, especially in Silicon Valley, would be much more likely to be from overseas and therefore require a work visa.
  - CydeWeys 6y ago
    I don't know about Hispanic per se but I definitely see that being true of Asians, and yes, it's a potential confounding factor. Would love to know if the longer paper addresses it.
godelzilla 6y ago
"Preferences"
tpoacher 6y ago
This paper is a prime example of not accounting for Simpson's paradox: "These numbers suggest that women and White applicants are proportionally more likely to get hired compared to their counterparts." No, you haven't given us the men/women breakdown by ethnicity. It may actually be that there is an over-representation of women in the white category compared to other ethnicities, and therefore the bias towards hiring females carries with it a bias towards hiring white. However it's possible that if you compare ethnicities separately between men and women you might find no racial discimination exists. (and vice versa for ethnicity vs gender). The fact that they don't show these breakdowns is a major weakness of this study. Or strength. Depending on whether the desired metric is scientific correctness, or political marketability.
at_a_remove 6y ago
At this one job, we had only two remotely viable candidates for an open position. I was on the hiring committee, as I often was in those days. Candidate A: Had worked in the industry, had all of the qualifications, already chock-full of some interesting ideas I wanted to hear more of from the interview alone. Excited at the prospect. Candidate B: Had never worked in the industry, had only a handful of qualifications, barely responsive. Seemed indifferent to getting the job. Additionally, not too fluent in English, to the point where it was more than a little difficult to communicate. Candidate A was a white man, Candidate B was a recent immigrant and a woman. The immediate supervisor for the position -- a woman -- wanted Candidate A, as did most others. However, the person running the show said, out loud I might add, that our group already had "too many pale males." I would like to repeat that: too many pale males. A significant glance was then cast at me and the guy in the wheelchair on the hiring committee, both being not-particularly-dark men. Presumably by "virtue" of our disabilities we would automatically be down for the Diversity Squad. Candidate B was hired and turned out exactly as she was in the interview: disinterested in doing the job, lacking even some bare understanding of how to accomplish many things, always trying to find ways to do her grad school homework while on the job and pushing off her duties on someone else, rather than trying to learn her tasks. Her poor English was a significant barrier. She remained a leaden weight until she went off to be someone else's problem. She wasn't a drag due to her skin color or sex, but she was hired because of those things. My guess is that this kind of discrimination (I use that word specifically) goes on all the time in at least some segments of the industry.
godelzilla 6y ago
HN claims to be non-ideological but, whenever there's a post on race, gender, etc., the anti-racist and anti-sexist viewpoints are downvoted or flagged just for explaining reality. Meanwhile the milquetoast, uncritical, ignorant, and "alt-right" are widely supported. Some people here might know "how to code", but it's clear they never learned analysis, criticism, empiricism, etc.

84 points by elsewhen 6y ago

> Using matched sample analyses and controlling for a rich set of job and applicant attributes found in applicants’ resumes and LinkedIn profiles, we find that women are 9-10% more likely to receive a callback compared to men, whereas Black, Hispanic, and Asian applicants are 8-13% less likely to receive a callback compared to White applicants. These outcome gaps do not cancel-out in the later stages, as female and White applicants are more likely to receive an interview and offer How accurate this is, however, depends a lot on how well controlling for applicant attributes worked. > An obvious set of confounders is the applicant’s objective qualifications such as years of experience, educational attainment, and field of study, all of which affect the outcome of an application. It is widely known that many of these attributes differ across demographic groups – for example, women are less likely to major in STEM subjects, Asian Americans are more likely to have graduate degrees (Camilie Ryan and Kurt Buaman 2015). To account for these confounds, we control for total years of experience, average tenure, educational attainment (associate or less, bachelors, masters, and doctorate), field of study, and rank of the university attended (Top 10, 21-50, 51-10, ). For experience controls, we use the total number of years of experience at the time of application parsed from resume text. For average tenure, we divide the total years of experience by the number of jobs held. For university rank, we parse the Education section of the applicant’s LinkedIn profile and join this against the U.S News Global University Rankings list. If an applicant attended multiple universities, we take the lowest rank. For the field of study, we parse the Education section of the applicant’s LinkedIn profile and bucket them into one of the following categories: Technical – mathematics, computer science, engineering, economics, etc. Business – business administration, finance, accounting, marketing, etc. Law – law and legal studies. Science – natural sciences such as biology, chemistry, etc. Other – all other majors. > An applicant’s professional and social network is another important signal that employers use to screen applicants (Fernandez and Weinberg 1997; Sterling 2014). Since one’s network tends to be demographically homogeneous, the effect of gender and race could be confounded by these affiliations. We control for this in two ways. First, we use a Referral indicator from the ATS, which indicates whether an applicant has a referral from an existing employee of the firm. Second, we identify whether an applicant has worked at the company’s talent competitor. We identify a company’s talent competitors by taking the top 10 companies from which its current employee pool comes from based on all of LinkedIn data. For example, to identify Company A’s talent competitors, we first search for all the employees of Company A using all of LinkedIn data. Once these employees are identified, we look at the previous company these employees worked at before joining Company A. We then aggregate these previous companies by count, and take the top 10 companies from which Company A’s current employee pool comes from. > Finally, an applicant’s skills, previous job responsibilities, and fit for the job to which they applied are perhaps the most important factors in determining the success of an application. We operationalize this using a text-analytics method called Word2Vec to measure the similarity between skills and competencies listed in the applicant’s resume and the job description (Mikolov et al. 2013). To do so, we first train a Word2vec model on a corpus of resumes. Using this model, we transform each document (i.e resumes and job descriptions) into a vector representation based on skills listed in each document, and measure the cosine similarity between the resume vector vR and job description vector vJ . The higher the cosine similarity between the job description and resume vector, the better the fit. This type of approach is often used in automatic application screening tools I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes, which means I'm not sure I trust the callback numbers. Submitting identical resumes with different demographic characteristics seems like a much more appropriate experimental approach here? As for whether candidates receive an offer, they don't have anything here where they have actually evaluated the candidates' skills. I've given over 200 technical interviews, and resumes are just not that good a predictor of technical competence. It really doesn't seem to me like they have good enough controls to run this as a correlational experiment.

monoideism 6y ago
> I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes, You're in the tech industry and you honestly are skeptical that recruiters and hiring managers at most companies aren't extremely eager, to say the very least, to hire female candidates?
- iguy 6y ago
  But regardless of whether the outcome fits your priors or not, you may wish to know whether the study has decent evidence, or is just noise. And GP has a good point. The authors have some automated scheme for grading how well-qualified people are. The recruiters also have some such scheme. If these two schemes differ, and the distributions aren't identical between the groups being compared, then you will detect group differences like what they see. To label these differences bias in the recruiter's process, you must be confident that you have less bias in your process. The details of this correction are going to be crucial.
  - monoideism 6y ago
    Yes, it's a good point. I made a snap response, and was wrong to do so. I just get tired of the ideological nonsense I see so often propogated by a certain group in the tech industry.
  - thu2111 6y ago
    Yes, but the list of criteria they use for controls is pretty reasonable and more importantly, unbiased by woke ideology. We all know many firms have a very strong bias towards women that grades them as more well qualified (desirable to hire), so we'd expect a re-run using purely objective metrics to detect that. The outcome of this study isn't a surprise, the only surprise is that the bias is "only" 10%.
- jefftk 6y ago
  That the bottom line results be plausible is not enough. It matters whether the study is a good source of evidence for its claims. Otherwise none of us have any reason to update our views in response, and the study has no value as information.

reader5000 6y ago

They capitalized "white". They are on the wrong side of history.

nailer 6y ago
Are you complaining about the capitalisation of racial groups, or the capitalisation of a specific racial group?
- reader5000 6y ago
  https://apnews.com/article/9105661462 https://apnews.com/article/9105661462
  - eznzt 6y ago
    >AP’s style is now to capitalize Black in a racial, ethnic or cultural sense, conveying an essential and shared sense of history, identity and community among people who identify as Black Ironically, pretending all blacks come from the same ethnic or cultural background is a very ignorant (and racist) thing to do.
    - eplanit 6y ago
      The AP is proving that journalism is dead.
  - ihsw 6y ago
    That is asinine.
  - nailer 6y ago
    OK so the latter. This is racist against both white people that somehow don't deserve capitalisation based on their skin color and black people in the US who don't share the limited concept of black the AP uses.
  - monoideism 6y ago
    So if they don't capitalize "white", because that's what white supremacists do, what does that say about capitalizing "black"? A good number of the people pushing the "Black" spelling are openly Afrocentric, or profess to be.

einpoklum 6y ago

Key point of the abstract: Women: +9 to +10% chance of callback relative to men Black, Hispanic, and Asian: -8 to -13% chance of callback relative to White people. Anyway, kudos (I guess?) to the researchers for choosing the absolutely most fashionable subject they could possibly study in this day and age.

ginko 6y ago
Would be interesting to separate Asian applicants into their own group.
- belly_joe 6y ago
  They do in their model. Being Asian carries with it the worst relative odds of being hired, though it is not responsible for the overall negative non-white male coefficient (Black and Hispanic applicants also have negative coefficients in the logit)
  - dbsmith83 6y ago
    Seems to make sense relative to each other. D&I initiatives often times target Black and Hispanic candidates, but not Asian since they are not underrepresented.
- CydeWeys 6y ago
  And also separating out Indian, Chinese, and Other Asian. The majority of many tech workforces are broadly Asian, along with over half of the global population. It doesn't make sense to lump them all in together. It may be acceptable in other industries in the US where Asian representation is in line with the US standard of ~6%, but certainly not in tech. If a single bucket accounts for more than half of your entire sample, and that bucket can trivially be broken down further into sub-buckets, then you should absolutely do so. This is something that tech in particular just keeps getting wrong over and over. E.g. look at the 2019 Google diversity report [1] -- on page 52 it shows that 55.5% of new tech hires in the most recent year were Asian, vs 0.7% for the smallest category (Native American). Break out that 55.5%, please! [1] https://kstatic.googleusercontent.com/files/25badfc6b6d1b33f3b87372ff7545d79261520d821e6ee9a82c4ab2de42a01216be2156bc5a60ae3337ffe7176d90b8b2b3000891ac6e516a650ecebf0e3f866 https://kstatic.googleusercontent.com/files/25badfc6b6d1b33f...

lettergram 6y ago

I always try to give the recruiter no indication of race or gender. Frankly, if we all did that it would remove the bias. The challenge is, I suspect they ask for race & gender is intentionally requested to add bias. I’ve worked with recruiters and part of the job is indeed targeting “under represented” groups to improve the figures.

einpoklum 6y ago
Well, you do give them their name, that's a strong indication of race and gender for most people, isn't it?
- lettergram 6y ago
  Sure, my name is unisex though. Race might be obtained, but honestly even that is questionable
  - st1x7 6y ago
    It only seems questionable because of your specific name. If your first name was Zhang or Priya, your race would also be quite obvious.
  - BoorishBears 6y ago
    > Race might be obtained, but honestly even that is questionable If you mean "irrevocably determined with a 100% certainty" maybe... But you know, most people who think their name doesn't give away their race, are a certain race... - Funny that this is really such an uncomfortable truth for some people here... I'm a black guy with a Ghanaian name, so I laughed out loud reading the comment. It's not like black people aren't allowed to have "euro-centric" names, but, surprise surprise, Caucasians represent a large majority of people with those names Likewise there are names that almost no Caucasians have (like mine) If someone is reading your resume intent on being biased, a name like "Austin Walters" is going to appear as... a white guy. There black guys named Austin Walters but they're also not conducting a census... if someone really wants to discriminate against you based on race, your name is plenty to go on. https://www.mynamestats.com/First-Names/A/AU/AUSTIN/chart-distribution-by-race.svg https://www.mynamestats.com/First-Names/A/AU/AUSTIN/chart-di... https://www.mynamestats.com/Last-Names/W/WA/WALTERS/chart-distribution-by-race.svg https://www.mynamestats.com/Last-Names/W/WA/WALTERS/chart-di... Again, they're not conducting a science study, an 80% chance is plenty for the kind of person trying to discriminate... Likewise, someone who reads my name, which uses consonants in a way that English doesn't usually ( causing people to mispronounce my very simple last name even when reading it verbatim) will instantly assume I'm black. It's something I accept as a person with a very black name, it tells you the main audience of HN is this is really such a revelation for some of you lol

Communitivity 6y ago

Surprising study results regarding women being more likely to receive a callback than men. From personal experience and the teams I've been on, women have always been in the minority, along the lines of 8-10 men for every two women. However, I am not in Silicon Valley. We need more studies in this area. I'd also like to see studies that include other possible sources of discrimination (gender identity, age) that are known to exist in some areas. Without those other sources included in the data it's possible those sources could be skewing the data. One scenario might be that most of the women were young (20s-early 30s), while many of the men were older (late 30s to early 50s). Just one possible scenario, I'm not saying that was the case. But in that scenario the bias could be against older candidates rather than for female ones.

jackfrodo 6y ago
There's a contradiction in your second sentence, I'm not sure what your meaning is. >women have always been in the majority, along the lines of 8-10 men for every two women.
- nicoburns 6y ago
  From context I think they meant that "men have always been in the majority".
- Communitivity 6y ago
  Yes, thanks - it was meant to be minority. I've fixed in the original post.
GhostVII 6y ago
There are less women in the tech industry, so it is very possible for them to be more likely to get a callback and still be underrepresented.
giantg2 6y ago
The graph on page 13 was interesting. The gender distribution of applicants stays about the same, but the gender distribution for hires has dropped for men and risen for women. So were the women previously dropping out of the workforce? Do we now have men dropping out of the workforce? Or are they simply being reshuffled among the various companies within the industry? I ask this because there are other studies that say the industry in the US is facing a shortage of tech workers, so it seems unlikely to be that a significant number of people would be dropping out, or that this study accurately represents the industry as a whole.

SuoDuanDao 6y ago

I'm reminded of a quip I came across in the conversation around the George Floyd killing - "Being a black man in America is like being a man only more so". I guess in the case of SV hiring outcomes, this is literally true!

candu 6y ago

There's a fascinating study on orchestra auditions, where it was found that performing blind auditions (where the interviewee's identity is hidden to the interviewer) led to more equitable gender representation: https://gap.hks.harvard.edu/orchestrating-impartiality-impact-%E2%80%9Cblind%E2%80%9D-auditions-female-musicians https://gap.hks.harvard.edu/orchestrating-impartiality-impac... IMHO, if the tech industry wants to live up to its narrative of meritocracy, this is one obvious improvement over existing processes. No, it won't take care of pipeline problems; no, it won't solve the "tipping point" problem (i.e. where candidates of underrepresented groups are dissuaded by a lack of pre-existing representation, making it very hard to go from zero to one, so to speak). That said, we're uniquely positioned as an industry to do this - technical interviews are similar to auditions in that they hinge on skill-based performance - so why not? It can't be any less arbitrary than asking random questions about manhole covers and light bulbs. I'd posit that even the "show your thinking process" parts could be done in this way - e.g. via text chat, or inline comments, or maybe even using voice obfuscation and/or neutral avatars.

jefftk 6y ago
> performing blind auditions (where the interviewee's identity is hidden to the interviewer) led to more equitable gender representation There has recently been quite a bit of pushback on this: https://www.nytimes.com/2020/07/16/arts/music/blind-auditions-orchestras-race.html https://www.nytimes.com/2020/07/16/arts/music/blind-audition... > It can't be any less arbitrary than asking random questions about manhole covers and light bulbs. Asking random questions about manhole covers and lightbulbs doesn't work very well! Don't take that as your comparison.
- travisoneill1 6y ago
  Well of course the people who want to hire by race want to get rid of blind auditions!
in3d 6y ago
You may want to read https://statmodeling.stat.columbia.edu/2019/05/11/did-blind-orchestra-auditions-really-benefit-women/ https://statmodeling.stat.columbia.edu/2019/05/11/did-blind-... “One of the more interesting findings of the study that I have not often seen reported: overall, women did worse in the blinded auditions.”

protomyth 6y ago

And once again a race study that doesn't list Native Americans at all. It would be nice if they remembered 2% of the US population, since certain policies ("Actual Name") have discriminated against Native Americans because of the ignorance of silicon valley firms. AIHEC and American Indian College Fund (collegefund.org) could really use the help to get placements for students.

lumberjack 6y ago
They don't care about you because you're not a politically influential demographic. Notice how the demographic that dominates this debate is the second most privileged and influential demographic in the country: white women; yet they are portrayed as being some powerless minority. It's always powerful demographics fighting each other. Nobody cares about the actual minorities that have no representation. That is almost tautological.
bradlys 6y ago
If it makes you feel better, you're not alone - middle eastern is never broken out either. In fact - we're grouped with white people. Some of us are white passing - some of us are very much not. Fun article about it... https://www.latimes.com/projects/la-me-census-middle-east-north-africa-race/ https://www.latimes.com/projects/la-me-census-middle-east-no... I can tell ya - after 9/11 - being middle eastern sure didn't feel like being white!

deleted 6y ago

[deleted]

simonebrunozzi 6y ago

Obligatory mention of the Google engineer, James Damore, fired for the internal memo on gender discrimination [0]. Latest news on the subject: [1]. So relevant, in fact, to deserve its own Wikipedia page [2]. [0]: https://www.nytimes.com/2017/08/07/business/google-women-engineer-fired-memo.html https://www.nytimes.com/2017/08/07/business/google-women-eng... [1]: https://www.mercurynews.com/2020/05/14/former-google-engineer-fired-over-memo-drops-discrimination-lawsuit/ https://www.mercurynews.com/2020/05/14/former-google-enginee... [2]: https://en.wikipedia.org/wiki/Google%27s_Ideological_Echo_Chamber https://en.wikipedia.org/wiki/Google%27s_Ideological_Echo_Ch...

godelzilla 6y ago
His memo was about "gender discrimination"? Sure, keep telling yourself that.

meraar8 6y ago

OK.

treeman79 6y ago

Personal experience. Got hired into a company that did everything possible to avoid hiring straight white men. Everything was completely dominated by not offending anyone over anything. Unless you were the aforementioned group. Turns out there simply isn’t a lot of the right race/gender/sex. I’m sure that’ll be different as time progresses, but for now there is clearly some catching up to do. So it was all jr developers. A couple of which truly cared about technology, and I see good things in their future. The rest were the most arrogant sexist bigots imaginable. Most days were filled with hatred. Full rant fest about how evil “my kind” were. But it wasn’t personal as I was clearly one of the good ones... So yeah, n=1 personal experience. But crude that echo chamber was scary.

osipov 6y ago
If it was just n=1, then we wouldn't have this brilliant social commentary: https://www.youtube.com/watch?v=pZy4QXLKHlI https://www.youtube.com/watch?v=pZy4QXLKHlI
- treeman79 6y ago
  Wow. That was exactly my experience. I tried so hard to stay out of it and just code. That really upset several people.
fraktl 6y ago
So what you're saying is that.. I am responsible for my happiness, and that other people are not to blame for the choices I made in regards to my behavior and life, especially straight white men? Wow, that's a hard cookie to swallow. (for the ones who read this far, what I wrote is sarcastic).
throwawaympfsin 6y ago
That's one of the reasons I left tech and went to work for an investment bank. At least here no one pretends to be in it to "make the world a better place" or whatever agenda tech companies are selling nowadays. YMMV

ChrisMarshallNY 6y ago

The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/fitness/attractiveness/age (I'm an old fart, so I can tell you a thing or two about ageism in tech) becomes apparent. I have heard story after story from peers (around my age), about passing numerous rounds of phone and test interviews, only to see the interviewer's face fall, as soon as they walk in the door. It's happened to me, but, thankfully, before being flown out (if it's a contract application, then we're on the hook for the cost), and revealing the age. It happens with highly qualified older white guys, so I'm sure that it will happen with other distinguishing characteristics. The simple fact of the matter is, is that people have certain traits they are looking for, and the final call is always a "gut feeling." I've learned to just avoid all the agita by making it clear that I'm "of a certain age," right up front. I don't get many offers, but at least I don't have those blasted recruiters, gushing about my résumé, only to shred my contact card, as soon as they find out I'm old (I guess the industry is crawling with 32-year-olds with 30 years' experience). I don't think it's a good idea to have AIs do the selection (as has been suggested numerous times -usually by folks in the AI business). Humans need to work with humans. If an AI puts someone into a situation where they are treated like garbage by their managers and/or co-workers, then they will be miserable (and unproductive); especially if they have done something like uproot their lives to move somewhere (I have also heard many stories from people that have uprooted their lives to go to "the perfect" job, only to come back, a few months later, broken and cynical). If the people involved don't want to work with someone like me, then I don't want to work with them. That's easy for me to say, though. It can really stink, when you're hungry and need the work.

coldcode 6y ago
Happened to me I aced everything and when the interview walked into the room I saw it on their face (too old). Thankfully that only happened once and the company wen under at some point thereafter so good thing I didn't get hired.
secondcoming 6y ago
This is absolutely one of my nightmares. I'm turning 40 soon and I know my opportunities of being paid to write software will become more and more limited.

bookmarkable 6y ago

Are we still going to call it Silicon Valley when everyone is remote?

giantg2 6y ago

So according to this, high-potential women are receiving a pay premium. But I thought the BLS listed tech jobs as one of the few industries that does have an actual wage gap favoring men?

imglorp 6y ago

Okay, honest question coming from ignorance. In computing at least, there's a well known diversity disparity going back to STEM graduation rates. It seems financial is a similar boat: Wells Fargo recently claimed a “limited talent pool" but got criticized by AOC for lacking "talent to recruit Black workers". Obviously society, including industry, could do more to get kids into school. But right now, in the resume pile, what should employers be doing, and why is "not enough X talent" not a good defense? https://www.washingtonpost.com/business/2020/09/23/wells-fargo-ceo-black-employees/ https://www.washingtonpost.com/business/2020/09/23/wells-far...

deleted 6y ago
[deleted]
benjaminjosephw 6y ago
The pipelines have problems for sure but this study was about whether or not a focus on diversity in hiring was effective. I think the important bit is here: > Our results in light of these considerations suggest that the push for diversity without any effort towards inclusion is unlikely to be sustainable in the long term.
jdmichal 6y ago
There's a lot of implicit assumptions around this stuff that actually matter a lot, and the demographics of the actual candidate pool [0] as opposed to the general population is a huge one. I would venture that most people pushing diversity agenda want representation to match the general population, but that may not be supported the candidate pool. As you point out, it's well studied that women don't graduate with STEM degrees at a rate that matches the general population. That means that for every company that matches general population for women in STEM fields, there's other companies that literally cannot unless they hire unqualified women from outside the candidate pool. [0] I'm defining this as the group of all possible people who are qualified to be hired into a role.

HideousKojima 6y ago

Personal anecdote: I knew someone who worked as a recruiter at Boeing a few years ago, and she told me the pressure from higher ups to give preferential treatment to female applicants was crazy. She said they couldn't explicitly discriminate, but would use things like "Women in Tech" events to try to increase their female applicant pool.

JansjoFromIkea 6y ago

Searched the article for "visa" and "migrant" found no results, surely that hugely skews the data with respect to Asians? I fully imagine there is bias towards Asians within SV but it'd be heavily weighted towards recent arrivals who either have uncertain visa status or aren't yet at native speaking English proficiency surely? Whereas you'd have to imagine the vast majority of black applicants meet both of those requirements with ease.

sto_hristo 6y ago

It's the same with truly blind dating, isn't it? If you deprive yourself from the knowledge of the gender of your candidate for partner, you'd become a truly inclusive pansexual astral being in the dating scene.

CydeWeys 6y ago

Women: +9 to +10% chance of callback relative to men Black, Hispanic, and Asian: -8 to -13% chance of callback relative to White people. I wish they had broken out the other ethnicities separately in the abstract. The reasons that Black and Hispanic people might be getting fewer callbacks relative to whites are likely quite different from the reasons that Asian people might be getting fewer callbacks. I'm making my way through the main paper but there's a lot of tables in there that would take me a lot of reading to decipher and it's really not clear which are best to use for any purpose. The tables do break out the separate ethnicities separately though (along with callback/interview/offer rates, not just callback) and it does appear that Black, Hispanic, and Asian very much do not have the same experience. In particular, the graph on page 22 seems to show that, when it comes to receiving offers, female candidates have a 29.5% advantage in receiving offers, Black 4%, -21% Asian, and -24% Hispanic. The previous column (received interview) is much worse for Asian, Black, and Hispanic applicants though; all were significantly less likely to receive interviews than whites. Anyway, there's lots of potentially good data in here, assuming you trust their methodology, but I personally feel like I need someone who knows this stuff better to write up a longer abstract based on all this data to really explain it to me properly.

dcolkitt 6y ago
As far as I can tell, the paper doesn't seem to control for citizenship or immigration status. It seems likely that Hispanic and Asian job-seekers, especially in Silicon Valley, would be much more likely to be from overseas and therefore require a work visa.
- CydeWeys 6y ago
  I don't know about Hispanic per se but I definitely see that being true of Asians, and yes, it's a potential confounding factor. Would love to know if the longer paper addresses it.

godelzilla 6y ago

"Preferences"

tpoacher 6y ago

This paper is a prime example of not accounting for Simpson's paradox: "These numbers suggest that women and White applicants are proportionally more likely to get hired compared to their counterparts." No, you haven't given us the men/women breakdown by ethnicity. It may actually be that there is an over-representation of women in the white category compared to other ethnicities, and therefore the bias towards hiring females carries with it a bias towards hiring white. However it's possible that if you compare ethnicities separately between men and women you might find no racial discimination exists. (and vice versa for ethnicity vs gender). The fact that they don't show these breakdowns is a major weakness of this study. Or strength. Depending on whether the desired metric is scientific correctness, or political marketability.

at_a_remove 6y ago

At this one job, we had only two remotely viable candidates for an open position. I was on the hiring committee, as I often was in those days. Candidate A: Had worked in the industry, had all of the qualifications, already chock-full of some interesting ideas I wanted to hear more of from the interview alone. Excited at the prospect. Candidate B: Had never worked in the industry, had only a handful of qualifications, barely responsive. Seemed indifferent to getting the job. Additionally, not too fluent in English, to the point where it was more than a little difficult to communicate. Candidate A was a white man, Candidate B was a recent immigrant and a woman. The immediate supervisor for the position -- a woman -- wanted Candidate A, as did most others. However, the person running the show said, out loud I might add, that our group already had "too many pale males." I would like to repeat that: too many pale males. A significant glance was then cast at me and the guy in the wheelchair on the hiring committee, both being not-particularly-dark men. Presumably by "virtue" of our disabilities we would automatically be down for the Diversity Squad. Candidate B was hired and turned out exactly as she was in the interview: disinterested in doing the job, lacking even some bare understanding of how to accomplish many things, always trying to find ways to do her grad school homework while on the job and pushing off her duties on someone else, rather than trying to learn her tasks. Her poor English was a significant barrier. She remained a leaden weight until she went off to be someone else's problem. She wasn't a drag due to her skin color or sex, but she was hired because of those things. My guess is that this kind of discrimination (I use that word specifically) goes on all the time in at least some segments of the industry.

godelzilla 6y ago

HN claims to be non-ideological but, whenever there's a post on race, gender, etc., the anti-racist and anti-sexist viewpoints are downvoted or flagged just for explaining reality. Meanwhile the milquetoast, uncritical, ignorant, and "alt-right" are widely supported. Some people here might know "how to code", but it's clear they never learned analysis, criticism, empiricism, etc.