Note: There's a (very gray) "View All" button in the top-right of the slideshow. I was just going to complain about the hypocrisy of stuffing a list of purportedly successful women into a photo slideshow in a cynical attempt to increase page views.
Note: There's a (very gray) "View All" button in the top-right of the slideshow. I was just going to complain about the hypocrisy of stuffing a list of purportedly successful women into a photo slideshow in a cynical attempt to increase page views.
You also brought up #BlackLivesMatter, after 3 seconds of googling I get things like:
https://occamsrazormag.wordpress.com/2015/11/22/extreme-anti...
There is a lot of irony in this type of racism.
Why "#BlackLivesMatter"? Why not "#AllLivesMatter" or "#StopPoliceBrutality"?
All these things do is foster tribalism.
Why do we see women and minorities as fair game to be tokens for our social engineering and clickbait?
Have we stopped to ask any of these women if they want to be on our special-interest gendered side-shows, or whether they'd prefer to be part of the "main" competition instead?
To me this is like entering female athletes into the paralympics on the basis of their gender. Without any evidence of their consent.
Is your premise is that female founders are a fundamentally separate group from founders in general?
FWIW, I think it's a great idea and a good way to encourage women to join a field that they perceive as not being welcoming to them but I don't have any hard data to support this (and don't think I need any)
It's so broad a classification I'd have trouble seeing how it created biased framing. It's just a more precise way of saying "the professions" (in the traditional sense of medicine, the law, accounting, and engineering).
Why use the classification at all, if it so broad? If you use "all professions", you get perhaps things like garbage men and miners who are worse than tech? So you can always select a filter that makes tech look worst.
I think with some goodwill, you could see the point I was trying to make.
How do you support the rather extraordinary claim that the technology professions have markedly larger gender imbalance compared to other cognitive non-routine professions? From the data I saw, 2014 numbers placed technology professions around the 70%-30% gender distribution which puts it directly into the majority of professions of any kind.
The two extremes: Fair distribution (40%-60% or closer to 50%/50%) has as group a rather poor 10% of all employed people. Unsurprising, it has about the same number of women and men that works in those professions.
The second extreme are those with 90%-10% or higher, and if I remember right about the top professions in that list, it was topping with midwife nurse (99.7%), nurse with dentist specialization (99.4%) and carpenters that construct floors (99%). Going down from that you got several other specializations of nurses, mechanics, midwifes, construction workers, and kindergarten teachers (94%). You have to travel really far into the list to reach professions with as high gender equality as 70%-30%. To name a few cognitive non-routine professions at the 80%-20%, we got professions like veterinarian, psychologist, librarian, and teacher, all with worse gender distribution than technology professions.
Another issue is the promulgation and veneration of taboo, protected groups as being automatically special proportional to an university-proscribed, identity/attribute(s) neoliberal caste system. Bollocks.
I think such lists come from a positive intention for there to be less arbitrary discrimination and to motive likely-targeted/underrepresented individuals to succeed. I'm not sure how a special list helps motivate people with fundamental confidence, but instead may temporarily confer false confidence based on non-skill attribute(s) except by an inkling of almost getting on a generic list.
No, it is more like giving them separate awards, like the mens 400m and the womens 400m.
Some was certainly deserved, although I'm not sure about the proportionality of the 20th "No, seriously, Elizabeth Holmes is a terrible terrible person!" - article.
Some was offensive, misogynistic, backwards bullshit that I can only hope is highly correlated with the writer's chances at next year's Darwin awards – like about 90% of anything ever written about Ellen Pao.
Some was in between – Marissa Meyer comes to mind.
I have no idea why about a third of men feel threatened by the whole idea, but I believe those are problems that need to be addressed offline. I've seen a few cases where some measures to reduce discrimination succeeded even with some initial scepticism. 1:1 talks seem to work quite well, as does starting with something blatantly obvious (dropping the photo requirement for applicants and blinding the names are two common options in my country). Once you get a team above a certain threshold (around 35% women I'd say) the whole dynamic shifts. Suddenly there's picnics and Tuesday morning runs and journal clubs etc. That's something that everyone notices and I believe it has dramatic impact.
The effects continue with any other measure of diversity you can introduce: having a few different nationalities around is an improvement, having someone with a completely different background can be a plus (met a 75-year old office manager once who was beloved at her startup) etc.
That's not to condone the backlash, of course.
But perhaps we ought to stop focusing on identity politics - and start treating women as people, not tokens in our social engineering project.
Unfortunately, very few efforts seem to focus on immediately applicable solutions like this that solve the problem (if there is one) fundamentally.
None of the Big Tech companies for example (Google / Facebook / Apple / Microsoft come to mind) currently do application blinding where possible, as far as I know. All of them however are very eager to promote movements like Girls Who Code because it's generally good PR and (I think) because it increases the available labor pool for them.
As for "Girls Who Code" as PR - does it increase the popularity of these firms with male coders, too? My personal impression with Google is that they are not interested in hiring male coders anymore...
I can't think of many scenarios that would give you that impression. Did google personally reject you for being a man?
I haven't seen any effort to attract male talent. Of course having more women on the team will probably make a company more attractive to men, but I doubt that is the only thing they should bank on to attract men.
Just kidding - I didn't write a paper about it, nor did I conduct a rigorous study. Most of the Google Ads I have seen came via various Google Twitter accounts, like https://twitter.com/lifeatgoogle (Life at Google seems to be dedicated to hiring people for Google).
So my filter bubble might be to blame. I haven't seen the video you mentioned which features a man.
(Edit: I just scrolled through the first several dozen tweets from "Life At Google - I think there is definitely a bias to only show female engineers there.... However, it is of course only one Google Twitter account dedicated to hiring, I don't know how many others exist. Maybe it was created explicitly to target women and minorities, but then maybe they should somehow say so).
But if I had to guess, I'd say these large companies are actually quite fair in their hiring processes. Discrimination at that step in the process seems to be more common at smaller or older companies. The worst, most blatant actual case I have seen was the IT dept at a medium-sized bank.
At FB and Google I'd guess "career advancement" is more susceptible to biases. As company tries to create "shallow hierarchies", the risk of competition devolving into the law of the jungle increases (but, as I said, only guessing. Have no experience with them).
How about blinding during resume screening? Replace female or male names with a number or made up names. Phone screening even maybe, using some kind of audio processing. I have never heard of these companies using any such process.
Edit: Looks interviewing.io did such a process, here are the results – https://blog.interviewing.io/we-built-voice-modulation-to-ma...
Out of interest I googled the hits on HN for Holmes and 2016's other medical industry bête noir, Martin Shkreli. Holmes wins by 325 to 141, although I'd personally be hard pressed to say which of them was more terrible.
It's like arguing apples should be the same as oranges because they are both fruits.