I found the title to be phrased very weakly compared to the abstract.
> We study gender and race in high-impact entrepreneurship using a tightly controlled randomized field experiment. We sent out 80,000 pitch emails introducing promising but fictitious start-ups to 28,000 venture capitalists and angels. Each email was sent by a fictitious entrepreneur with randomly assigned gender and race. Female entrepreneurs received 9% more interested replies than males pitching identical projects and Asians received 6% more than Whites. Our results suggest that investors do not discriminate against female or Asian entrepreneurs when evaluating unsolicited pitch emails and that future research on investor biases should focus on networks and in-person interactions.
Indeed, reading further into the article they seem to be trying to answer, “At what stage in the funding pipeline do VCs become biased against women?”.
It’s interesting that they don’t entertain the possibility that the gap might be caused by something other than bias (at least so far... I’m only 6 pages in). For example:
> Combating bias requires understanding how and where it manifests. Combating bias requires understanding how and where it manifests. In light of the substantial gender imbalance in real-world investments, our results suggest a larger-than-expected bias against female entrepreneurs in other settings.
They seem to be trying to combat bias without having even established that bias is the cause. Indeed, they take the statistically significant discrimination in favor of women in the initial stage as evidence that there must be even more bias against women in later stages.
Given that they haven’t cited any research that would explain why it must be bias and not some other factor, I wonder why the paper is written with this assumption? Perhaps the authors felt it would be poorly received if it so much as kept an open mind about other possible causes? Or maybe this is just common knowledge in the field?
"It’s interesting that they don’t entertain the possibility that the gap might be caused by something other than bias"
Imagine a medicinal study that would concentrate on the hypothesis that sinners get cholera as a divine retribution for their sinful lives, and would not even entertain other possible causes, such as ... dirty drinking water.
We would rightly locate such a study into, say, 1840, but definitely not 2021.
That is where authors of this study belong mentally. Into the science of the era when Lincoln was young.
Look up 1854 Broad Street cholera outbreak. That was when the scientific breakthrough regarding bad water took place - and many actually refused to accept the results.
Before that, the most "scientific" theory about cholera outbreaks was the miasma theory, but religious and pseudoreligious beliefs about divine punishment or influence of the stars were not fringe yet.
To be clear, my earlier comment was made in jest. I’m familiar with the Broad Street outbreak, but I’m not aware that religious theories were commonplace among scientists of the time. Notably that science wasn’t taken seriously by society more broadly doesn’t mean that the science of the time was “tainted by religion” (I say this as a religious person). Perhaps we’re making different points: mine is that science today is contaminated by a fervor resembling religion (though I don’t want to overstate the problem—overwhelmingly I think the effect is very low for the time being and I suspect it is highest in areas that are most pertinent to the ideology in question, which thankfully tends not yet to be the hard sciences or engineering disciplines lest our bridges fail, buildings collapse, and rockets explode on the launchpad).
The whole thing is written from the assumption that investors discriminate against women and nonwhites, and that the purpose of research is to confirm this pre-existing belief, rather than find out the objective truth.
> [..] future research on investor biases should focus on networks and in-person interactions.
Read: the results contradicted our hypothesis, so rather than update our hypothesis, let's shift the focus of research in hopes that we find evidence to support it.
This is exactly how science should work. You can't perform a study, look at the data and pick a result that suits your bias. You're supposed to suggest a hypothesis, and conduct your experiment. If the results contradict your hypothesis, it doesn't mean the opposite of your hypothesis is true, simply that your hypothrsis was false, and that's ok.
It's also more impressive that they have simply published their results, rather than burying them and running another experiment.
So what if they had found bias, do they say “look we found bias!” Or do they do additional studies to make sure it’s not an aberration or improper methods?
So you think the data is only relevant to the hypothesis you decided it's relevant for before you collect it?
"Have you seen the fire sir?"
"I have only seen smoke"
"But have you seen the fire?"
"It's irrelevant because I was only looking for smoke!".
I mean I know they teach it in naive introductory experiment design in some soft science departments but c'mon it's neither smart nor correct. If you need a separate experiments for everything because otherwise you will run into "one of the 100 hypothesis is bound to be correct" problem then your priors are too weak, you're relying on getting lucky anyway and just end up discarding useful datapoints.
If it's 5 out of 100 hypothesis fitting your data or 5 hypothesis out of 100 experiments passing "statistical significance" check doesn't matter at the end of the day. Both lead to shaky conclusions.
The data being relevant depends on the experiment design (how it's collected). It doesn't depend on what you thought it's relevant for beforehand.
The reason you don’t collect some data and then see what curves you can fit to it is exactly the problem you describe. “Eureka, a ninth-order polynomial function fits the data quite closely!”
You can’t look at your A/B test results every morning and stop the test the moment one measurement “shows significance”. That’s not how it works.
You just don't run an A/B test for 6 months hoping that a new design increases sales, get results pointing that the new design reduces sales by 90%, and then go make another 6 months long test to make sure the sales indeed fell.
Acknowledging the numbers on that single dimension are different from what you expected isn't the same as testing a bunch of different dimensions. And if your hypothesis does not allow for it, you completely failed at rational thinking.
Well, you can test multiple hypotheses at the same time. You just can't decide what the hypotheses are after you collect the data because you can't reasonably determine the correction factor.
> If the results contradict your hypothesis, it doesn't mean the opposite of your hypothesis is true, simply that your hypothrsis was false, and that's ok.
I don’t think the parent was arguing that the paper should claim the opposite is true, but perhaps recognizing that the findings support the opposite hypothesis, concretely that men and non-Asians are discriminated against in early stage investment pitches. Of course, a perfectly valid response might be, “that is unconventional in these kinds of papers” (I don’t know).
From omission it seems they reply less to black and white men. But these groups are large, however, sadly I don’t think it’d be easy to test on feigned education/class, so we won’t know what causes the bias.
If you’re curious about why they didn’t include black names:
> After long and thoughtful consideration, we discarded the idea of assigning
African-American names to our fictitious entrepreneurs. First, there has been a concern about the
ability to disentangle race and socioeconomic perception by using distinctly African-American names
(Fryer and Levitt (2004)). Second, and most importantly, African-American entrepreneurs are woefully
underrepresented in high-impact entrepreneurship (less than 1%, see Gompers and Wang (2017)). This poses a substantial challenge for our setup, because even names that are disproportionately likely to be African-American in the general population (such as “Martin Jackson”) may not be perceived as African-American by investors in this context. Studying discrimination against African-Americans and other underrepresented minorities in high-impact entrepreneurship remains an important problem.
"In an attempt to increase workplace diversity, the Australian public service implemented a .. trial removing all mention of gender and ethnicity from applications.
It was found that removing gender from thousands of applications made women less likely to advance through the recruitment process compared to cases where gender was visible.
The trial found that a woman's name on an application made the candidate 2.9% more likely to get job interviews.
Its counter-productive to institute gender and diversity requirements at (tech) companies, where the core problem is at the fundamental immigration level.
For example, 74.5% of H1B migrants to the USA are from India, and 78.4% of them are male:
If we instituted gender and equality quotas at the migration level - ie. maximum 10% of the total yearly intake from any one country, and maximum 49% males from any one country, then we would a create a much more diverse talent pipeline.
Fairness for High-Skilled Immigrants Act - to eliminate the 7% per country-cap on green card applicants, among other things, which would have ended the painfully long wait for thousands of green card hopefuls.
I think it’s worth noting that that finding is not universal, and other studies do find the opposite. My brief skim through Google scholar does seem to show a fairly divided field here.
It's impossible to control for the culture of the organizations who are reviewing the applicants.
In the US, if you sent anonymized resumes to old, large companies in Industry X and then sent them to new, small companies in Industry Y, you are likely to get very different results.
Then your results become very dependent on how well you randomize those organizations, which is very difficult. If you get a few more "X" orgs instead of "Y" orgs, your results look totally different.
"Minorities may be particularly likely to experience disadvantage when they apply to ostensibly pro-diversity employers."
That doesn't quite fit the narrative. Also, the study examines the practice of "resume whitening" as something that some minority applicants (less than 50%, so a minority) do to combat their expectations of potential bias.
It does not say anything itself about whether such bias exists.
Second study:
"Male recruiters’ perceptions of applicants’ work experiences did not differ depending on applicant gender. However, female recruiters perceived male applicants’ resumes to re- port more work experiences than resumes of female applicants."
So female recruiters discriminate against females, male recruiters don't discriminate. Also doesn't fit the narrative.
Third link only got me an error message.
Anyway, I don't think any of these studies actually supports your assertion.
The first one might be because companies that make a big deal about being pro diversity have already identified a problem and are trying to combat it by making big deal (not necessarily by doing anything else), whereas normal companies don't need to advertise that because they already have a wide variety of employees.
Nobody prevents Indian women to apply for H1B jobs in US.
> Its counter-productive to institute gender and diversity requirements at (tech) companies, where the core problem is at the fundamental immigration level.
I don't see anything counterproductive in blind recruitment. It's a normal practice, along with randomizing resume review in a few big companies in places like India, or China exactly because the issue of nepotism, bigotry, casteism, classism, and people slipping their university fraternity members into the company is so severe there.
Is it? The data in the original comment indicates that Chinese H1B applications are substantially more female heavy than most countries. So unless you're prepared to argue that Canada and the UK are "suppressing female H1B applicants in systemic ways" even more than China, or you have some other source of data indicating a bias, there has to be another explanation.
The story could plausibly be true if restricted to just India, although even then I think you've gotta confront the fact that the UK's gender balance is only marginally closer to 50/50.
These type of studies were performed after years and years of efforts to push for a more diversified work force. I’d be interested if their is a way to do a comparison with years prior and see if and when a shift started happening.
Yes, in France there was a large scale "anonymous CV" experiment, and going against what was expected, made people from minorities or poor neighbourhoods more disadvantaged.
Just shooting from the hip here, but isn't that expected because their CVs would be worse due to the current climate putting them at a disadvantage? My gut feeling is that you need to have that system in place for many years to even the playing field first. Starting with fresh graduates getting equal chances, and then slowly letting that effect build up year after year.
Psychologist here, and yes this is commonly done in studies where you have access to that information. However these statistical controls are imperfect at best due to things like generational effects of education. E.g., first generation educated behaves differently from a long line of educated family members in ways that are sometimes hard to define and difficult to measure.
Well, from the article: "This result, which the researchers themselves describe as "unexpected", could be linked to the fact that the named CV allows the recruiter to be more sympathetic to shortcomings in the application letter ("gaps" in the curriculum, little experience)."
That shows two things: inequality is real, and some recruiters are actively trying to compensate for it, which has a positive effect overall.
The inequality problem is unfortunately a very tough nut to crack, that would require several decades of consistent policy, which is completely unattainable in the current political situation (with governments randomly changing policies every few years in a direction or another).
no, we are need to allow people who have desiers to come here 4 good life n success, no filter for sex. in India IIT is 64% man, so you are only penalise unfair men by these action. we are needing to let almost any person who want to be in America to be here not have a nother restricting.
but point is same: if we are creating quota for female to imigrate that has unfair penalisation on men. we are ought to have admit almost any person who is desiring for to be here and working.
Why does India get penalized if they generate 50% of the people interested in a tech H1B (they don't - it's a thought experiment). Why is 49% preferable to 30% or 51% or 70%? Why not split male and female applicants into two pools and hire accordingly? Meaning if you get 70% of your applicants from men, hire 70% male and 30% female. If the following year it's 60/40, hire 60/40.
Or better yet, fix the pipeline issues rather than put in arbitrary caps and quotas that serve only to reduce the overall quality of candidate pools.
Organizations hire for their needs, not to have exactly equal numbers of people across arbitrary metrics. The issue with "maximum 10% of the total yearly intake from any one country" is that it's a feel good statistic on paper, but it ends up having the real effect that it instantly puts top talent out of reach for US companies (all other things being equal, countries with more population will have more people of exceptional talent).
As long as there aren't as much women studying all kinds of engineering, you're going to see disparaties in the workforce. Lets stop trying to force equal distribution but rather equal opportunity.
Funny thing to see is that as a country becomes MORE developed, women tend to be LESS inclined to attend STEM studies.
This is the main problem. It’s hard. We could fix it if we were despotic and put people into tracks like the USSR who turned out lots of talented women in STEM, but were not and Film, TV and YT, etc highlight the easy life of glamour and fame, etc. So you end up with a million wanna be starlets and fewer women in STEM than statistics would have.
Let “Hollywood” glamorize STEM, propagandize it and you’ll get a better pool of talent. Instead the proposition is to scrape the bottom of the barrel harder.
Why exactly is it a problem if people are CHOOSING to do something on their own accord? Other than the political gestapo having to swallow their pride, I don't see freedom of career choice as a negative.
Some people want to sell their solution, so obviously they are looking for a problem.
There is a lot of opportunity in the diversity industry, even though things like diversity training do not seem to have any effect, not even shielding companies from lawsuits.
Their does seem to be an inverse correlation between what we consider free and rich societies and despotic poor societies and their equality in STEM fields.
You need not look far, even very conservative countries such as Belarus have stronger representation in IT than a much more liberal society such as Sweden.
One reason why in less free countries, women and girls choose STEM in a higher proportion is that choosing STEM fields was a better economical decision compared to other jobs, rather than being forced into it for ideological reasons by their states.
> Funny thing to see is that as a country becomes MORE developed, women tend to be LESS inclined to attend STEM studies.
Stem jobs are relatively shitty jobs... paid well, but work schedule can be relatively screwed up. If you add enterpreneurship to that, it makes the work-life balance even worse. Women on average prefer better work-life balance, and men prefer careers where they can get higher and earn more.
In some countries (less developed), the only way to lead a realatively OK life is to get a stem degree and work something related to that. In more developed countries, the job market (and social support) makes it possible to live OK even with a "worse" degree (ie. the ones where you can't get a job with in less developed countries).
Exactly this, but this points toward the conclusion that equality is going to be hard to achieve as men and women have different goals and ambitions.
When you remove the "survival" aspect of going to highly paid STEM job you get women who choose less technical jobs and huge disparity in number of women in tech.
Personally I don't think that is an issue at all but I feel I am in the minority, at least when we look at the decision making level.
I wondered why they didn't report results for black versus white. Interestingly, they didn't run that:
"After long and thoughtful consideration, we discarded the idea of assigning
African-American names to our fictitious entrepreneurs. First, there has been a concern about the
ability to disentangle race and socioeconomic perception by using distinctly African-American names
(Fryer and Levitt (2004)). Second, and most importantly, African-American entrepreneurs are woefully
underrepresented in high-impact entrepreneurship (less than 1%, see Gompers and Wang (2017)). This poses a substantial challenge for our setup, because even names that are disproportionately likely to be African-American in the general population (such as “Martin Jackson”) may not be perceived as African-American by investors in this context."
It's an interesting point, are there any unambiguously African-American names? I wouldn't have guessed Martin Jackson was African-American, but I'm English.
"are there any unambiguously African-American names"
Something like DeShawn is almost certainly going to be a black person, but that would have socioeconomic perception issues as the text points out. It's an interesting point though. I had a look for data and couldn't really find much of use.
The part you quoted seems to say exactly that: there are unambiguously African-American names, but they are associated with low-class, low education backgrounds. Which might confuse the statistics as then the choice would not be purely about race but race and socioeconomic status.
That seems an odd take. Should we look for pure discrimination against any group, that isn't related precisely to the associations people make?
I mean, it's possible. Faced with two people who (they believe) have identical backgrounds, I may discriminate against the black one purely because I dislike black people. But equally, I may have imperfect knowledge about two people, and knowing that one is black makes me associate them - consciously or not - with different things. That might then affect my willingness to give them a job.
This is close to the difference between "taste-based" and "statistical" discrimination, in economists' terms.* Normally we care about both, so why not try to find out about it?
It also seems unlikely that Asian names are free of associations, including e.g. associations about being hard working and/or nerdy, which might matter in a study like this.
* Though, I don't think it's identical. You might dislike someone (taste-based discrimination) based on your associations with their ethnicity. And you might predict purely from their ethnicity, holding everything else constant, that they would do worse in a job (statistical discrimination). (E.g. if it's a sales job and you believe buyers are racist.)
From abstract: ” Female entrepreneurs received 9% more interested replies than males pitching identical projects and Asians received 6% more than Whites. Our results suggest that investors do not discriminate against female or Asian entrepreneurs when evaluating unsolicited pitch emails and that future research on investor biases should focus on networks and in-person interactions.”
In other words: The preferred results were not found (females are oppressed) so we ignore wrong-think results (males seem to be) and continue to hunt evidence for preferred results elsewhere.
Your summary is incorrect. They are not taking their results to indicate that their assumption is incorrect, but rather that the anti-female bias must be even stronger elsewhere to overcome the significant pro-female bias at initial stages.
We generally agree, though not violently :). I was pointing out that the effect is a bit bigger than the parent suggested. The authors aren’t abandoning their priors about anti-female bias; on the contrary they aren’t even recognizing that this evidence challenges those priors—they assume that the evidence to prove their priors must exist elsewhere and in sufficiently large effect as to counteract and dominate this pro-female bias.
Note that I think it’s a fine thing to stick to one’s priors until they’ve been conclusively disproven, but recognition when the evidence obviously challenges one’s priors is my baseline for good faith. That said, I suspect this paper is written as it was because the authors thought their careers might be in danger for merely suggesting that the disparity might have a cause beyond discrimination.
That's the problem - their results show a bias against white and/or male entrepreneurs in this study on gender and race, yet don't point this out and suggest that we should look for negative female/asian bias elsewhere. The results speak for themselves but the abstract and mindset is indicative of what they were really looking for in the first place.
> yet don't point this out and suggest that we should look for negative female/asian bias elsewhere
I’m confused, the study does suggest we look for anti-female bias elsewhere. Indeed, the authors seem to argue that it must exist elsewhere, and more powerfully so in order to explain the gender gap.
> must exist elsewhere, and more powerfully so in order to explain the gender gap.
Why is anti-female bias the only possible explanation of the gap? Why is that the only acceptable hypothesis? It's a possibility, it might even be probable, but there seems to be an exclusionary focus both in your comments and in the abstract.
I think the point is that there is a bias against males and white reducing the the chance of equity of opportunity, and this seem to be because the focus is consistently on equality of outcome.
I'm not so sure it's so clear cut. What if you want to find the truth and advance our collective understanding without risking your career by putting too fine a point on your research and offending the powerful ideologues who have demonstrated time and again their ability to make life hard for dissenters? Having read a bit of the article, it seems like they've done a good job of using subtext to point out that the data doesn't fit the narrative without making their subversion too obvious. Perhaps we would argue that they should be forthright about their dissent, but that's also easy to say for us who have little to lose. Moreover, I don't necessarily think it's a good idea for scientists to weigh in too much on ideological affairs, even if it means they support my priors (which may or may not be what you're suggesting). Thinking like that is what got us into this mess in the first place.
> that the anti-female bias must be even stronger elsewhere to overcome the significant pro-female bias at initial stages
From a strictly scientific standpoint, you can’t really draw such “must be” conclusions. It could also very well be that the input into the existing funnel is low; I.e that there is a lower percentage of female founders because females make a lower percentage of the applicant pool.
And, to be clear, the disparity could also be due to stronger biases further into the investment process!
It’s just that we don’t know whether it’s the former or the latter (or some combination), and based on the research here it is inappropriate to draw that specific conclusion. That’s not a scientific approach.
> Combating bias requires understanding how and where it manifests. In light of the substantial gender imbalance in real-world investments, our results suggest a larger-than-expected bias against female entrepreneurs in other settings.
The reasoning appears to be something like, "Because there is a disparity, there must be an anti-female bias somewhere and since there's only a pro-female bias here, the elsewhere anti-female bias must be so strong as to overcome the pro-female bias here to produce the disparity". There seems to be an implicit assumption that disparities are proof of bias when in fact bias is one of many potential causes of disparities.
Indeed. It can't be that hard to first look at all applications for funding, and then see which ones actually get funded. It wouldn't surprise me that there would be an overall pro-female bias. It wouldn't fit certain political agendas though.
I didn’t see any mention of it in the study but I’d hazard a guess that most VCs are heterosexual men and that might be a factor in an initial preference for women’s pitches, other things being equal.
> The preferred results were not found (females are oppressed) so we ignore wrong-think results (males seem to be)
It's true that any discrimination in favour of one group would be discrimination against the opposite.
But as a middle-class white guy at a big tech company, whose boss is a middle class white guy whose boss is a middle class white guy whose boss is a middle class white guy whose boss is a middle class white guy whose boss is a middle class white guy whose boss, the CEO, is a rich white guy... I don't feel very oppressed.
it's not ignore. I think they'd be remiss to not mention the detail SOMEWHERE in their study, but I'd consider it bad science to conclude some other fact that your experiment/observational study was not designed for.
They should design an experiment suitable to justifying that conclusion, if that's what they wanted to prove. at best, the author's should conclude on that particular thread, "more research is needed."
I never understand why classify people on their looks. Talking primarily about the US. There is such a wide spectrum of white people coming from different cultures. Also, you're considered Asian if you're a Chinese immigrant but also if you were born in the US to Chinese descent let's say. The main common thing between the two groups is looks. Same for Africans and African Americans who are both classified as blacks but have very different culture. Then there is the latino group who once the lose their accent and don't look so latino anymore they drift to the white group...
I don't understand how that follows from the parent comment?
The comment rightfully points out that in the US people are mostly classified by their superficial looks vs their actual ethnicity.
Which leads to the situation that quite a diverse field of ethnicities and cultures are boiled down to very generalized "white/black/yellow/whatever" groups.
Case in point: The recent shooting in a Colorado grocery store was, rather quickly, tried to be framed as "white extremism" due to skin color of the perpetrator and footage of his arrest going public.
When said perpetrator is actually a Syrian who became a naturalized US citizen by the name of "Ahmad Al Aliwi Alissa, of Arvada", which is about the least "white" name one could come up with.
Or for another example: The Nazis are regularly evoked as an example of racism and white supremacy, when the vast majority of people killed by the Nazis were actually "white", just not the right kind of "white".
That's why in Europe racism often isn't based on color of skin, but rather on accents, ethnic looks and family names, as skin color alone is not enough to differentiate the out-group from the rest: A white British person is just as white as a white Polish person, yet that doesn't mean that the two of them will consider themselves as part of the same ethnic or cultural group.
That idea only exists in the heads of people who evoke some allegedly unified "European culture" to stipulate that Europe is "racially homogeneous" because it's only made up of "white people".
You could make a similar argument about ethnics groups instead of race. Every categorization is a generalization until you get down to a single individual.
Races are just as valid as specific ethnic groups, they just have a broader definition. You don't have to list and compare each and every ethnic group separately to say that the European culture(s) are overall much different from, let's say, African culture(s).
> You could make a similar argument about ethnics groups instead of race.
Colloquially they are pretty much interchangeable as rarely anybody uses "race" in the proper modern anthropological context. Which is problematic in its own right as it keeps rather outdated concepts alive even when the scientific community, for the most part, considers them untenable.
> You don't have to list and compare each and every ethnic group separately to say that the European culture(s) are overall much different from, let's say, African culture(s).
You don't need to but if you don't it often ends up with generalizations where there are not "European culture(s)" or "African culture(s)" but only the singular versions of them and the only differences are made out between these two.
But in actuality neither Europe nor Africa are culturally homogeneous. Some cultural groups in Europe and Africa can have more in common than comparing European with European/African with African groups due to the wide diversity among cultural groups even inside the same geographical region.
A reality that's too often lost in the discourse when cultures are compared like they are monolithic blocks, particularly when these blocks are defined by color of skin.
> Colloquially they are pretty much interchangeable as rarely anybody uses "race" in the proper modern anthropological context.
Seems like a straw man to be honest, but I don't know, maybe it's true. Not sure what the "modern" context is either, since some people were trying to convince me that "according to the science" biology basically doesn't exist or that you're born as a blank slate, but oh well.
> Some cultural groups in Europe and Africa can have more in common than comparing European with European/African with African groups due to the wide diversity among cultural groups even inside the same geographical region.
Any example?
> But in actuality neither Europe nor Africa are culturally homogeneous.
That's right, but there is much more overlap within Europe and Africa respectively in terms of basically everything you can think of than between them.
> A reality that's too often lost in the discourse when cultures are compared like they are monolithic blocks, particularly when these blocks are defined by color of skin.
Again, the same thing can be said about ethnic groups. Ethnic groups are not a monolith either.
Plus, a skin color is one of the features of an ethnic group. There are no asian Nigerians, there are no black Ukrainians, etc. Sure, you might become a citizen or marry a person of some ethnic group, but that doesn't necessarily make you a part of it.
It's true skin color is a feature of an ethnic group. But it's not a unique feature. Most of the middle east is white (a bit darker than the average white American but still white). In the US they are classified as white even though they have very little in common with the majority group of white Americans. Basically what I really want to say is that environment is the main thing that defines people, not skin color. The environment someone is raised in is far more important than skin color. African Americans for example makes much more sense to me as a classification than blacks.
> The environment someone is raised in is far more important than skin color. African Americans for example makes much more sense to me as a classification than blacks.
So you want to essentially just exclude from blacks, like what, Sub-Saharan Africans? I don't know American demographics in detail, but I imagine that African Americans have to make up an overwhelming majority of the black population, so would that really make any difference? Or is it just another rebranding? Breaking things down to specific ethnic groups is surely useful in some cases, but is it really for everything? And I'm not sure what the point of that even is or what problem is it supposed to fix. It's still skin color, just a little bit more specific. I mean, you can be a white kid raised in the exact same environment as African Americans and that doesn't make you an African American in any stretch of imagination.
I wouldn't mind being more specific about it, but I just don't get why replacing race with ethnic groups would change anything. Maybe I'm reading too much into it, but my impression is that you want to reject race just for historical reasons, but at the same time you want to keep ethnicities around, because you're still not crazy enough to take it to its full logical conclusion, go full Lysenkoism and deny genetics all together. Probably going to change in near future and this seemingly progressive idea will be considered as a serious thought crime, but hey, what do I know.
Er... I'd argue this is the root cause, the US has some systemic historical issues with people of a certain appearance. They had to, because of the relative melting pot of culture, you couldnt really pick a pole from a frenchman if they both spoke American English. Not the case for other groups.
I agree. In the last 5-10 years the belief that race encodes all useful information about a person seems to have caught on among certain political circles to the extent that overt displaces of prejudice seem to be a signal that indicates ingroup membership.
There was a brief period during which the popular aspiration was to deny or try to combat our racial biases, but we seem to be increasingly giving ourselves over to them.
> I never understand why classify people on their looks.
Because it's easy. Our brains are expert pattern matching machines. The things we see immediately cause our brain to act and match based on the prior data it holds. What's the easiest thing to see about a person that relays the most information to our brain? The color of their skin, what they're wearing, their hairstyle, etc.
> For our entrepreneurial email senders, we opted to use distinctively East-Asian (i.e., Asian) and Western-European (i.e., White) last names, both paired with common American first names that are distinctively female or male. Asians are overrepresented in the U.S. venture capital space, relative to their fraction of the U.S. population. Gompers and Wang (2017) report that 11% of U.S. entrepreneurs backed by venture capital firms are Asian, as are 11% of U.S. VCs, compared to 5% of the U.S. labor force. Despite this, past audit studies uniformly find strong discrimination against Asians (see Section 4 for more details). Correspondence studies that look at discrimination against both Asian and Black applicants often find that both groups face similar level of discrimination (e.g., Wood, Hales, Purdon, Sejersen, and Hayllar (2009); Booth, Leigh, and Varganova (2012); and Milkman, Akinola, and Chugh (2012)). This bias extends to Asians who do not appear to be foreigners. For example, Oreopoulos (2011) finds that Asians with English first names, Canadian university degrees, and several years of Canadian work experience get 21% fewer callbacks than similar White Canadian job applicants.
That effect seems quite large. Doesn’t that indicate (rather conclusively?) a large amount of pro-Asian bias?
Just like it happens with software development, in some specific contexts nobody needs to know who you are, what you identify with or what you do when naked for your results to be considered worthy of evaluation or compensation. Focus on letting your product shine and be free to be yourself in total privacy, it's an advantage many persons unfortunately don't have.
We're spending so much time and energy to quantify various 'biases' ; only to find there is no bias. This is good. We're finally living is a post-racial society with no specific group discrimination.
Now if western societies can move on from affirmative action policies and all the other nonsense at the top of their daily agenda while China leaves them all in the dust.
This is not surprising to me. For all I've seen "non-white non-male" is generally given priority in all kinds of areas, certainly in start-up interest. It's considered "hip" to associate with these "non-white non-male" groups, irregardless of their actual performance in whatever area they were prioritized. (To a certain extent at least, they can't be completely nonperforming) Being able to show that you have included these groups in whatever way your organization works, gives you advantages in press situations foremost, but also in other ways such as meeting arbitrary quotas set by higher-ups and HR dept.s in your organization.
This is however, given two equal applications. Such as this study shows. I would be knocking down open doors to state that white men are over represented in the "STEM/Entrepreneurship" areas. What needs to be addressed is what the underlying cause is to this over representation. For all I see there are two potential causes:
1) Non-white non-males are given less ability to grow in the "STEM/Entrepreneurship" fields as students and/or children by society.
2) White men are able to outperform those other groups by some inherent quality.
Worth noting is also that simply stating 2) as a potential cause of this difference is more or less a hatecrime in most settings, and academia would do well not to touch in attempting to work with that hypothesis if they wish to keep tenure and funding. Nevertheless, 1) seems to be partially disproved by studies just like the one above, showing that white men are in fact given less ability to grow in "STEM/Entrepreneurship" areas, as by the bias shown towards the Asian and Female applications.
What is your basis for "white guys outperform other groups" in this specific scenario (entrepreneurship)? Perhaps VCs know that women and Asians outperform white guys and hence this bias.
I think there are other options besides 1 and 2. For example, 3) non-white non-males experience different cultural pressures (or a different culture altogether) and have different expectations set by their family/peers/selves and and their careers when it comes time to work towards a profession.
Is there a basis for the positive bias towards Asians and women here? If I have to follow the logic of a lot of statements in this thread perhaps VCs show a positive bias due to experience (better returns)? See https://www.google.com/amp/s/www.forbes.com/sites/allysonkap...
Many similar studies have been done and almost always destroy the leftists dogmas about X, Y or Z being oppressed.
Belonging to a minority actually appears to boost your chances of being hired (shown by studies leaving, or hiding, the name of the applicants).
Being a women in a company with a boss, reduces the gender paygap compared to what it is for freelancers: the more women are on their own (dentists, baker, founder of a sport's club, etc...), the bigger the gap compared to the male dentists, bakers, founders of sport's club... An interesting fact which leaves a lot of leftists in error 500 mode.
No, I might have argued that about usenet when I was first exposed to the internet in the early 90s, but I'm not nearly so naive today. Endless flamewars that never change minds. The same people saying the same shit time and time again. Dogmas don't die, they simply fade away when their adherents do.
As a 'white' father of 3 who has been unemployed for the past few years I can tell you that this paper is sole crushing. Its a monument to how backwards common perception is to reality. Its a declaration from academia to never stop finding ways at punishing (me, my wife and 3 daughters) for my sin of being born white/male/pre1990. From what I have seen, people like me are under-represented in most office environments. Next time you are in an office (in NA at least), look around. Who are the black suited MBAs in charge not hiring? Even the abstract of the paper leads me to believe the the universe is a simulation because why else would it want to destroy opportunities for me and my family and simultaneously assuming, and tying to prove in a lab, that I am the modern Satan.
It’s very profitable to pitch “neo-natal” progeny of recent immigration (>1965) with those with European ancestries which carry natural inter-generational momentum. Trying to find an “equalizing” rainbow trail is a violent red herring, yet has perpetual support because it’s sympathizing.
You’re not alone. Many of us feel the same way. This system will always hate us, we have to start supporting each other. Give it time. We’re going to make it friend.
White men especially in America tend to pathologically see the world through an individualistic lens and ignore their identity. Things will change as more and more of us start to become conscious of the identity for which the system hates us.
All the systems you mentioned have more far more white men than the US as a whole, so are you arguing that white men hate themselves?
US: 60% white[1]; 49% male[1]; ~31% white & male[2]
Media: 75% white[3]; 50% white & male
Academia: 40% white & male[4]
College Professors: 53% white & male[5]
House: 73% white[5]
Senate: 89% white[5]
All elected offices in the US in 2014: 65% white & male[2]
President: 100% white & male
I'm too lazy to keep going, but I feel like I've made my point. Neither white people nor white men are underrepresented in any position of power or wealth. So how can it be that these systems (that people in their demographic control) are against them?
First you made a logical leap. Simply because these institutions may be nominally majority white does not preclude the ability for them to biased against whites. I never claimed these institutions were minority white, only that they were biased against whites, so you also attacked a straw man.
You also did not address the widespread corporate training material adopted from Robin D’Angelo. If the system were biased towards whites, why would it train its employees to shun their white identity? Would you consider a system whose corporations asked their employees to “be less black” biased against black people?
What percentage of Biden’s cabinet do you consider white?
>pathologically see the world through an individualistic lens and ignore their identity.
Pathologically? That's the healthy and correct way to see the world. Seeing through a lens filtered by 'identity' (you obviously mean race and gender) is flawed.
Victims of racism and gender bias... which include both whites and blacks, men and women... need to avoid becoming sexist and racist in response. It'll drag us all down.
> we have to start supporting each other. Give it time. We’re going to make it friend.
This won't happen. In my opinion they are too 'principled' to support each other. Supporting each other has the connotations of a union or a mob. 'White' men, who in my opinion is statistically among the most capable category are collectively their own enemies, by bending backward to accommodate the 'minority' even when individuals from these 'minorities' are incompetent.
it's a bit much to extrapolate from a single study in one area. even just reading the conclusion the authors share a few possible limitations of the study even within the field of startup investment
As a non-American this is so bizarre to me. You get people so full of concern for the hypothetical woman in banking making 100k a year who just can't get that promotion, or the hypothetical black Harvard graduate who gets rejected from tech jobs, while they only show disgust for the unemployed guy living in a trailer with his family and friends ODing dropping dead like flies, simply because of the color of his skin.
I'm curious where you're from, because this trend seems to be occurring all over the western world (for example they yellow-vest protests in France, etc.)
That's because you probably value independence and critical thinking. You are probably teaching your kids to focus on personal growth, learn from the work environment, look for opportunities, be competitive and keep increasing their own bargaining power. At least, that's what I'm teaching mine.
Except, this makes you a threat to the corporations. They don't want you. They want to have someone replaceable, who will fulfill their corporate duties at the minimum possible rate. Who will never challenge their superior, and will be thankful for the opportunity to join the ranks, rather than thinking on how to go independent.
This paper examines discrimination based on startup founders' gender, race, and age by early-stage investors, using two randomized controlled trials with real venture capitalists. The first experiment invites U.S. investors to evaluate multiple randomly generated startup profiles, which they know to be hypothetical, in order to be matched with real, high-quality startups from collaborating incubators. Investors can also donate money to randomly displayed startup teams to show their anonymous support during the COVID-19 pandemic. The second experiment sends hypothetical pitch emails with randomized startups' information to global venture capitalists and compares their email responses by utilizing a new email technology that tracks investors' detailed information acquisition behaviors. I find three main results: (i) Investors are biased towards female, Asian, and older founders in "lower contact interest" situations; while biased against female, Asian, and older founders in "higher contact interest" situations. (ii) These two experiments identify multiple coexisting sources of bias. Specifically, statistical discrimination is an important reason for "anti-minority" investors' contact and investment decisions, which was proved by a newly developed consistent decision-based heterogeneous effect estimator. (iii) There was a temporary, stronger bias against Asian founders during the COVID-19 outbreak, which started to fade in April 2020.
I'd want to know the gender and race of the recipient VCs as well. Did female or Asian VCs have the same response profile as male or white VCs?
Apparently, both female and male investors had a slight bias towards female entrepreneurs, pg. 31:
"Both VCs and angels are more likely to respond to female entrepreneurs, although the difference is statistically significant only for angels (70% of our sample). Some angels in our sample are less experienced, as gauged by the number of investments they are recorded to have made. These less experienced angels have a statistically significant 13% higher interested reply rate to our female entrepreneurs, while the more experienced angels have an 8% higher reply rate and VCs have a 7% higher rate."
It seems a positive outcome, however, I'd like to go one 'why' deeper. Why did the female investors prefer female entrepreneurs (see fig. 2, pg. 29)? Were their reasons different than the male investors' reasons?
Also, why would less experienced investors be more likely to prefer female entrepreneurs than more experienced investors?
The author's correctly identify the limitation that the research does not account for bias subsequent to meeting the email authors, but as others have pointed out, it does not mention the limitation that they did not send out pitches proportional to the real world. This is an incredibly obvious causal explanation, and puts in a bad light the scientific integrity of the authors. Which is a shame, because their actual study is interesting and seems fairly rigorous.
I read through the actual paper to see if they mentioned this limitation somewhere, not just the abstract, and could not find it. If someone else managed to spot some small clause buried in those pages, please mention where.
On a different note, why are academic papers so unnecessarily long? There was a lot of repetition in this one.
That would be nice, but you can't have an experiment that does that. You can conduct empirical research to try to answer that question, but that has its own problems and limitation. Overall, like most research, this paper is a piece of data that provides a bit more understanding than we had before.
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[ 0.22 ms ] story [ 259 ms ] thread> We study gender and race in high-impact entrepreneurship using a tightly controlled randomized field experiment. We sent out 80,000 pitch emails introducing promising but fictitious start-ups to 28,000 venture capitalists and angels. Each email was sent by a fictitious entrepreneur with randomly assigned gender and race. Female entrepreneurs received 9% more interested replies than males pitching identical projects and Asians received 6% more than Whites. Our results suggest that investors do not discriminate against female or Asian entrepreneurs when evaluating unsolicited pitch emails and that future research on investor biases should focus on networks and in-person interactions.
Are they implying that investors do discriminate against non-Asian males? Why write it the other way around.
Maybe that's how the hypothesis under test was phrased?
It’s interesting that they don’t entertain the possibility that the gap might be caused by something other than bias (at least so far... I’m only 6 pages in). For example:
> Combating bias requires understanding how and where it manifests. Combating bias requires understanding how and where it manifests. In light of the substantial gender imbalance in real-world investments, our results suggest a larger-than-expected bias against female entrepreneurs in other settings.
They seem to be trying to combat bias without having even established that bias is the cause. Indeed, they take the statistically significant discrimination in favor of women in the initial stage as evidence that there must be even more bias against women in later stages.
Given that they haven’t cited any research that would explain why it must be bias and not some other factor, I wonder why the paper is written with this assumption? Perhaps the authors felt it would be poorly received if it so much as kept an open mind about other possible causes? Or maybe this is just common knowledge in the field?
Imagine a medicinal study that would concentrate on the hypothesis that sinners get cholera as a divine retribution for their sinful lives, and would not even entertain other possible causes, such as ... dirty drinking water.
We would rightly locate such a study into, say, 1840, but definitely not 2021.
That is where authors of this study belong mentally. Into the science of the era when Lincoln was young.
You give far too little credit to 1840 and far too much to 2021.
Before that, the most "scientific" theory about cholera outbreaks was the miasma theory, but religious and pseudoreligious beliefs about divine punishment or influence of the stars were not fringe yet.
> [..] future research on investor biases should focus on networks and in-person interactions.
Read: the results contradicted our hypothesis, so rather than update our hypothesis, let's shift the focus of research in hopes that we find evidence to support it.
It's also more impressive that they have simply published their results, rather than burying them and running another experiment.
Publish and make recommendations for future research, exactly as this paper does.
"Have you seen the fire sir?" "I have only seen smoke" "But have you seen the fire?" "It's irrelevant because I was only looking for smoke!".
I mean I know they teach it in naive introductory experiment design in some soft science departments but c'mon it's neither smart nor correct. If you need a separate experiments for everything because otherwise you will run into "one of the 100 hypothesis is bound to be correct" problem then your priors are too weak, you're relying on getting lucky anyway and just end up discarding useful datapoints.
If it's 5 out of 100 hypothesis fitting your data or 5 hypothesis out of 100 experiments passing "statistical significance" check doesn't matter at the end of the day. Both lead to shaky conclusions. The data being relevant depends on the experiment design (how it's collected). It doesn't depend on what you thought it's relevant for beforehand.
You can’t look at your A/B test results every morning and stop the test the moment one measurement “shows significance”. That’s not how it works.
You just don't run an A/B test for 6 months hoping that a new design increases sales, get results pointing that the new design reduces sales by 90%, and then go make another 6 months long test to make sure the sales indeed fell.
Acknowledging the numbers on that single dimension are different from what you expected isn't the same as testing a bunch of different dimensions. And if your hypothesis does not allow for it, you completely failed at rational thinking.
No, the hypothesis is only valid before the data is collected.
> Have you seen the fire sir?" "I have only seen smoke" "But have you seen the fire?" "It's irrelevant because I was only looking for smoke!".
It's actually more like:
"Have you seen fire at x?"
"There's smoke at Y"
All that means is that something is true about Y, not that x isn't on fire.
I don’t think the parent was arguing that the paper should claim the opposite is true, but perhaps recognizing that the findings support the opposite hypothesis, concretely that men and non-Asians are discriminated against in early stage investment pitches. Of course, a perfectly valid response might be, “that is unconventional in these kinds of papers” (I don’t know).
> After long and thoughtful consideration, we discarded the idea of assigning African-American names to our fictitious entrepreneurs. First, there has been a concern about the ability to disentangle race and socioeconomic perception by using distinctly African-American names (Fryer and Levitt (2004)). Second, and most importantly, African-American entrepreneurs are woefully underrepresented in high-impact entrepreneurship (less than 1%, see Gompers and Wang (2017)). This poses a substantial challenge for our setup, because even names that are disproportionately likely to be African-American in the general population (such as “Martin Jackson”) may not be perceived as African-American by investors in this context. Studying discrimination against African-Americans and other underrepresented minorities in high-impact entrepreneurship remains an important problem.
With so much scamming and the different phishing attacks, do you respond to random inquiries? That would seem rather naive, if true.
"In an attempt to increase workplace diversity, the Australian public service implemented a .. trial removing all mention of gender and ethnicity from applications.
It was found that removing gender from thousands of applications made women less likely to advance through the recruitment process compared to cases where gender was visible.
The trial found that a woman's name on an application made the candidate 2.9% more likely to get job interviews.
Leaders have now been told pause the trials"
https://www.abc.net.au/news/2017-06-30/bilnd-recruitment-tri...
Its counter-productive to institute gender and diversity requirements at (tech) companies, where the core problem is at the fundamental immigration level.
For example, 74.5% of H1B migrants to the USA are from India, and 78.4% of them are male:
https://www.uscis.gov/sites/default/files/document/data/h-1b...
If we instituted gender and equality quotas at the migration level - ie. maximum 10% of the total yearly intake from any one country, and maximum 49% males from any one country, then we would a create a much more diverse talent pipeline.
http://www-2.rotman.utoronto.ca/facbios/file/Whitening%20MS%...
https://www.alexandria.unisg.ch/19805/1/Cole%20et%20al.%2020...
https://d1wqtxts1xzle7.cloudfront.net/36436480/Gender_et_bia...
In the US, if you sent anonymized resumes to old, large companies in Industry X and then sent them to new, small companies in Industry Y, you are likely to get very different results.
Then your results become very dependent on how well you randomize those organizations, which is very difficult. If you get a few more "X" orgs instead of "Y" orgs, your results look totally different.
First study:
"Minorities may be particularly likely to experience disadvantage when they apply to ostensibly pro-diversity employers."
That doesn't quite fit the narrative. Also, the study examines the practice of "resume whitening" as something that some minority applicants (less than 50%, so a minority) do to combat their expectations of potential bias.
It does not say anything itself about whether such bias exists.
Second study:
"Male recruiters’ perceptions of applicants’ work experiences did not differ depending on applicant gender. However, female recruiters perceived male applicants’ resumes to re- port more work experiences than resumes of female applicants."
So female recruiters discriminate against females, male recruiters don't discriminate. Also doesn't fit the narrative.
Third link only got me an error message.
Anyway, I don't think any of these studies actually supports your assertion.
> Its counter-productive to institute gender and diversity requirements at (tech) companies, where the core problem is at the fundamental immigration level.
I don't see anything counterproductive in blind recruitment. It's a normal practice, along with randomizing resume review in a few big companies in places like India, or China exactly because the issue of nepotism, bigotry, casteism, classism, and people slipping their university fraternity members into the company is so severe there.
Not even perception in India?
The story could plausibly be true if restricted to just India, although even then I think you've gotta confront the fact that the UK's gender balance is only marginally closer to 50/50.
https://www.lemonde.fr/societe/article/2011/04/04/le-cv-anon...
That shows two things: inequality is real, and some recruiters are actively trying to compensate for it, which has a positive effect overall.
The inequality problem is unfortunately a very tough nut to crack, that would require several decades of consistent policy, which is completely unattainable in the current political situation (with governments randomly changing policies every few years in a direction or another).
but point is same: if we are creating quota for female to imigrate that has unfair penalisation on men. we are ought to have admit almost any person who is desiring for to be here and working.
Or better yet, fix the pipeline issues rather than put in arbitrary caps and quotas that serve only to reduce the overall quality of candidate pools.
http://paulgraham.com/95.html
Funny thing to see is that as a country becomes MORE developed, women tend to be LESS inclined to attend STEM studies.
Let “Hollywood” glamorize STEM, propagandize it and you’ll get a better pool of talent. Instead the proposition is to scrape the bottom of the barrel harder.
There is a lot of opportunity in the diversity industry, even though things like diversity training do not seem to have any effect, not even shielding companies from lawsuits.
https://www.psychologytoday.com/us/blog/how-we-work/201203/d...
It sound like BS. Have you learned it in school?
You need not look far, even very conservative countries such as Belarus have stronger representation in IT than a much more liberal society such as Sweden.
One reason why in less free countries, women and girls choose STEM in a higher proportion is that choosing STEM fields was a better economical decision compared to other jobs, rather than being forced into it for ideological reasons by their states.
I doubt that the choice was involuntary.
Stem jobs are relatively shitty jobs... paid well, but work schedule can be relatively screwed up. If you add enterpreneurship to that, it makes the work-life balance even worse. Women on average prefer better work-life balance, and men prefer careers where they can get higher and earn more.
In some countries (less developed), the only way to lead a realatively OK life is to get a stem degree and work something related to that. In more developed countries, the job market (and social support) makes it possible to live OK even with a "worse" degree (ie. the ones where you can't get a job with in less developed countries).
When you remove the "survival" aspect of going to highly paid STEM job you get women who choose less technical jobs and huge disparity in number of women in tech.
Personally I don't think that is an issue at all but I feel I am in the minority, at least when we look at the decision making level.
"After long and thoughtful consideration, we discarded the idea of assigning African-American names to our fictitious entrepreneurs. First, there has been a concern about the ability to disentangle race and socioeconomic perception by using distinctly African-American names (Fryer and Levitt (2004)). Second, and most importantly, African-American entrepreneurs are woefully underrepresented in high-impact entrepreneurship (less than 1%, see Gompers and Wang (2017)). This poses a substantial challenge for our setup, because even names that are disproportionately likely to be African-American in the general population (such as “Martin Jackson”) may not be perceived as African-American by investors in this context."
It's an interesting point, are there any unambiguously African-American names? I wouldn't have guessed Martin Jackson was African-American, but I'm English.
Something like DeShawn is almost certainly going to be a black person, but that would have socioeconomic perception issues as the text points out. It's an interesting point though. I had a look for data and couldn't really find much of use.
The part you quoted seems to say exactly that: there are unambiguously African-American names, but they are associated with low-class, low education backgrounds. Which might confuse the statistics as then the choice would not be purely about race but race and socioeconomic status.
I mean, it's possible. Faced with two people who (they believe) have identical backgrounds, I may discriminate against the black one purely because I dislike black people. But equally, I may have imperfect knowledge about two people, and knowing that one is black makes me associate them - consciously or not - with different things. That might then affect my willingness to give them a job.
This is close to the difference between "taste-based" and "statistical" discrimination, in economists' terms.* Normally we care about both, so why not try to find out about it?
It also seems unlikely that Asian names are free of associations, including e.g. associations about being hard working and/or nerdy, which might matter in a study like this.
* Though, I don't think it's identical. You might dislike someone (taste-based discrimination) based on your associations with their ethnicity. And you might predict purely from their ethnicity, holding everything else constant, that they would do worse in a job (statistical discrimination). (E.g. if it's a sales job and you believe buyers are racist.)
In other words: The preferred results were not found (females are oppressed) so we ignore wrong-think results (males seem to be) and continue to hunt evidence for preferred results elsewhere.
Note that I think it’s a fine thing to stick to one’s priors until they’ve been conclusively disproven, but recognition when the evidence obviously challenges one’s priors is my baseline for good faith. That said, I suspect this paper is written as it was because the authors thought their careers might be in danger for merely suggesting that the disparity might have a cause beyond discrimination.
I'm using this phrase the next time my daughters are playing and they start to yell at each other.
I’m confused, the study does suggest we look for anti-female bias elsewhere. Indeed, the authors seem to argue that it must exist elsewhere, and more powerfully so in order to explain the gender gap.
Why is anti-female bias the only possible explanation of the gap? Why is that the only acceptable hypothesis? It's a possibility, it might even be probable, but there seems to be an exclusionary focus both in your comments and in the abstract.
If your goal is to "find evidence for X" instead of "find out the truth" (wherever that leads you), you're a terrible scientist.
I think it is pretty clear which is happening in this case, no?
From a strictly scientific standpoint, you can’t really draw such “must be” conclusions. It could also very well be that the input into the existing funnel is low; I.e that there is a lower percentage of female founders because females make a lower percentage of the applicant pool.
And, to be clear, the disparity could also be due to stronger biases further into the investment process!
It’s just that we don’t know whether it’s the former or the latter (or some combination), and based on the research here it is inappropriate to draw that specific conclusion. That’s not a scientific approach.
Where does it mention that there is an overall anti-female bias?
The reasoning appears to be something like, "Because there is a disparity, there must be an anti-female bias somewhere and since there's only a pro-female bias here, the elsewhere anti-female bias must be so strong as to overcome the pro-female bias here to produce the disparity". There seems to be an implicit assumption that disparities are proof of bias when in fact bias is one of many potential causes of disparities.
It's true that any discrimination in favour of one group would be discrimination against the opposite.
But as a middle-class white guy at a big tech company, whose boss is a middle class white guy whose boss is a middle class white guy whose boss is a middle class white guy whose boss is a middle class white guy whose boss is a middle class white guy whose boss, the CEO, is a rich white guy... I don't feel very oppressed.
They should design an experiment suitable to justifying that conclusion, if that's what they wanted to prove. at best, the author's should conclude on that particular thread, "more research is needed."
The comment rightfully points out that in the US people are mostly classified by their superficial looks vs their actual ethnicity.
Which leads to the situation that quite a diverse field of ethnicities and cultures are boiled down to very generalized "white/black/yellow/whatever" groups.
Case in point: The recent shooting in a Colorado grocery store was, rather quickly, tried to be framed as "white extremism" due to skin color of the perpetrator and footage of his arrest going public.
When said perpetrator is actually a Syrian who became a naturalized US citizen by the name of "Ahmad Al Aliwi Alissa, of Arvada", which is about the least "white" name one could come up with.
Or for another example: The Nazis are regularly evoked as an example of racism and white supremacy, when the vast majority of people killed by the Nazis were actually "white", just not the right kind of "white".
That's why in Europe racism often isn't based on color of skin, but rather on accents, ethnic looks and family names, as skin color alone is not enough to differentiate the out-group from the rest: A white British person is just as white as a white Polish person, yet that doesn't mean that the two of them will consider themselves as part of the same ethnic or cultural group.
That idea only exists in the heads of people who evoke some allegedly unified "European culture" to stipulate that Europe is "racially homogeneous" because it's only made up of "white people".
Races are just as valid as specific ethnic groups, they just have a broader definition. You don't have to list and compare each and every ethnic group separately to say that the European culture(s) are overall much different from, let's say, African culture(s).
Colloquially they are pretty much interchangeable as rarely anybody uses "race" in the proper modern anthropological context. Which is problematic in its own right as it keeps rather outdated concepts alive even when the scientific community, for the most part, considers them untenable.
> You don't have to list and compare each and every ethnic group separately to say that the European culture(s) are overall much different from, let's say, African culture(s).
You don't need to but if you don't it often ends up with generalizations where there are not "European culture(s)" or "African culture(s)" but only the singular versions of them and the only differences are made out between these two.
But in actuality neither Europe nor Africa are culturally homogeneous. Some cultural groups in Europe and Africa can have more in common than comparing European with European/African with African groups due to the wide diversity among cultural groups even inside the same geographical region.
A reality that's too often lost in the discourse when cultures are compared like they are monolithic blocks, particularly when these blocks are defined by color of skin.
Seems like a straw man to be honest, but I don't know, maybe it's true. Not sure what the "modern" context is either, since some people were trying to convince me that "according to the science" biology basically doesn't exist or that you're born as a blank slate, but oh well.
> Some cultural groups in Europe and Africa can have more in common than comparing European with European/African with African groups due to the wide diversity among cultural groups even inside the same geographical region.
Any example?
> But in actuality neither Europe nor Africa are culturally homogeneous.
That's right, but there is much more overlap within Europe and Africa respectively in terms of basically everything you can think of than between them.
> A reality that's too often lost in the discourse when cultures are compared like they are monolithic blocks, particularly when these blocks are defined by color of skin.
Again, the same thing can be said about ethnic groups. Ethnic groups are not a monolith either.
Plus, a skin color is one of the features of an ethnic group. There are no asian Nigerians, there are no black Ukrainians, etc. Sure, you might become a citizen or marry a person of some ethnic group, but that doesn't necessarily make you a part of it.
So you want to essentially just exclude from blacks, like what, Sub-Saharan Africans? I don't know American demographics in detail, but I imagine that African Americans have to make up an overwhelming majority of the black population, so would that really make any difference? Or is it just another rebranding? Breaking things down to specific ethnic groups is surely useful in some cases, but is it really for everything? And I'm not sure what the point of that even is or what problem is it supposed to fix. It's still skin color, just a little bit more specific. I mean, you can be a white kid raised in the exact same environment as African Americans and that doesn't make you an African American in any stretch of imagination.
I wouldn't mind being more specific about it, but I just don't get why replacing race with ethnic groups would change anything. Maybe I'm reading too much into it, but my impression is that you want to reject race just for historical reasons, but at the same time you want to keep ethnicities around, because you're still not crazy enough to take it to its full logical conclusion, go full Lysenkoism and deny genetics all together. Probably going to change in near future and this seemingly progressive idea will be considered as a serious thought crime, but hey, what do I know.
There was a brief period during which the popular aspiration was to deny or try to combat our racial biases, but we seem to be increasingly giving ourselves over to them.
Because it's easy. Our brains are expert pattern matching machines. The things we see immediately cause our brain to act and match based on the prior data it holds. What's the easiest thing to see about a person that relays the most information to our brain? The color of their skin, what they're wearing, their hairstyle, etc.
> For our entrepreneurial email senders, we opted to use distinctively East-Asian (i.e., Asian) and Western-European (i.e., White) last names, both paired with common American first names that are distinctively female or male. Asians are overrepresented in the U.S. venture capital space, relative to their fraction of the U.S. population. Gompers and Wang (2017) report that 11% of U.S. entrepreneurs backed by venture capital firms are Asian, as are 11% of U.S. VCs, compared to 5% of the U.S. labor force. Despite this, past audit studies uniformly find strong discrimination against Asians (see Section 4 for more details). Correspondence studies that look at discrimination against both Asian and Black applicants often find that both groups face similar level of discrimination (e.g., Wood, Hales, Purdon, Sejersen, and Hayllar (2009); Booth, Leigh, and Varganova (2012); and Milkman, Akinola, and Chugh (2012)). This bias extends to Asians who do not appear to be foreigners. For example, Oreopoulos (2011) finds that Asians with English first names, Canadian university degrees, and several years of Canadian work experience get 21% fewer callbacks than similar White Canadian job applicants.
That effect seems quite large. Doesn’t that indicate (rather conclusively?) a large amount of pro-Asian bias?
We're spending so much time and energy to quantify various 'biases' ; only to find there is no bias. This is good. We're finally living is a post-racial society with no specific group discrimination.
Now if western societies can move on from affirmative action policies and all the other nonsense at the top of their daily agenda while China leaves them all in the dust.
No it’s not. The article has confidence intervals and findings are statistically significant.
Unless you have some nonstandard definition of “margin of error”.
While I generally I agree with you, let’s not come to correct conclusion using incorrect premises, this approach won’t help anyone.
This is however, given two equal applications. Such as this study shows. I would be knocking down open doors to state that white men are over represented in the "STEM/Entrepreneurship" areas. What needs to be addressed is what the underlying cause is to this over representation. For all I see there are two potential causes:
1) Non-white non-males are given less ability to grow in the "STEM/Entrepreneurship" fields as students and/or children by society. 2) White men are able to outperform those other groups by some inherent quality.
Worth noting is also that simply stating 2) as a potential cause of this difference is more or less a hatecrime in most settings, and academia would do well not to touch in attempting to work with that hypothesis if they wish to keep tenure and funding. Nevertheless, 1) seems to be partially disproved by studies just like the one above, showing that white men are in fact given less ability to grow in "STEM/Entrepreneurship" areas, as by the bias shown towards the Asian and Female applications.
FYI it's either "regardless" or "irrespective".
And I don't think there needs to be an inherent difference in ability. A difference in interest would also explain things.
Belonging to a minority actually appears to boost your chances of being hired (shown by studies leaving, or hiding, the name of the applicants). Being a women in a company with a boss, reduces the gender paygap compared to what it is for freelancers: the more women are on their own (dentists, baker, founder of a sport's club, etc...), the bigger the gap compared to the male dentists, bakers, founders of sport's club... An interesting fact which leaves a lot of leftists in error 500 mode.
Please don't sneer, including at the rest of the community.
Please don't use Hacker News for political or ideological battle. It tramples curiosity.
https://i.imgur.com/wusW5Rn.jpg
Ending the drug war is better politics.
Do you currently feel that white men are not supportive of one another? Or were you referring to a subcategory of white men?
> Give it time
What do you expect time to change?
> Things will change as more and more of us start to become conscious of the identity for which the system hates us.
And then what will you do?
Media, academia, corporate hiring, government policy. Places where “be less white” is official policy. [1]
> And then what will you do?
Form advocacy organizations, lobby groups, PACs, legal defense funds. Same thing every other organized group does.
[1] https://www.entrepreneur.com/article/366132
US: 60% white[1]; 49% male[1]; ~31% white & male[2]
Media: 75% white[3]; 50% white & male
Academia: 40% white & male[4]
College Professors: 53% white & male[5]
House: 73% white[5]
Senate: 89% white[5]
All elected offices in the US in 2014: 65% white & male[2]
President: 100% white & male
I'm too lazy to keep going, but I feel like I've made my point. Neither white people nor white men are underrepresented in any position of power or wealth. So how can it be that these systems (that people in their demographic control) are against them?
1. https://www.census.gov/quickfacts/fact/table/US/IPE120219
2. https://www.washingtonpost.com/news/the-fix/wp/2014/10/08/65...
3. https://journalistsresource.org/race-and-gender/newsroom-div...
4. https://nces.ed.gov/fastfacts/display.asp?id=61
5. https://www.americanbar.org/content/dam/aba/administrative/g...
You also did not address the widespread corporate training material adopted from Robin D’Angelo. If the system were biased towards whites, why would it train its employees to shun their white identity? Would you consider a system whose corporations asked their employees to “be less black” biased against black people?
What percentage of Biden’s cabinet do you consider white?
Pathologically? That's the healthy and correct way to see the world. Seeing through a lens filtered by 'identity' (you obviously mean race and gender) is flawed.
Victims of racism and gender bias... which include both whites and blacks, men and women... need to avoid becoming sexist and racist in response. It'll drag us all down.
This won't happen. In my opinion they are too 'principled' to support each other. Supporting each other has the connotations of a union or a mob. 'White' men, who in my opinion is statistically among the most capable category are collectively their own enemies, by bending backward to accommodate the 'minority' even when individuals from these 'minorities' are incompetent.
This is not supported either by anecdote or by data. It's true for some environments, but absolutely not most.
Except, this makes you a threat to the corporations. They don't want you. They want to have someone replaceable, who will fulfill their corporate duties at the minimum possible rate. Who will never challenge their superior, and will be thankful for the opportunity to join the ranks, rather than thinking on how to go independent.
Fortunately there are many opportunities now to take petty savings and ramp up some moral autonomy.
https://arxiv.org/abs/2010.16084
This paper examines discrimination based on startup founders' gender, race, and age by early-stage investors, using two randomized controlled trials with real venture capitalists. The first experiment invites U.S. investors to evaluate multiple randomly generated startup profiles, which they know to be hypothetical, in order to be matched with real, high-quality startups from collaborating incubators. Investors can also donate money to randomly displayed startup teams to show their anonymous support during the COVID-19 pandemic. The second experiment sends hypothetical pitch emails with randomized startups' information to global venture capitalists and compares their email responses by utilizing a new email technology that tracks investors' detailed information acquisition behaviors. I find three main results: (i) Investors are biased towards female, Asian, and older founders in "lower contact interest" situations; while biased against female, Asian, and older founders in "higher contact interest" situations. (ii) These two experiments identify multiple coexisting sources of bias. Specifically, statistical discrimination is an important reason for "anti-minority" investors' contact and investment decisions, which was proved by a newly developed consistent decision-based heterogeneous effect estimator. (iii) There was a temporary, stronger bias against Asian founders during the COVID-19 outbreak, which started to fade in April 2020.
Apparently, both female and male investors had a slight bias towards female entrepreneurs, pg. 31:
"Both VCs and angels are more likely to respond to female entrepreneurs, although the difference is statistically significant only for angels (70% of our sample). Some angels in our sample are less experienced, as gauged by the number of investments they are recorded to have made. These less experienced angels have a statistically significant 13% higher interested reply rate to our female entrepreneurs, while the more experienced angels have an 8% higher reply rate and VCs have a 7% higher rate."
It seems a positive outcome, however, I'd like to go one 'why' deeper. Why did the female investors prefer female entrepreneurs (see fig. 2, pg. 29)? Were their reasons different than the male investors' reasons?
Also, why would less experienced investors be more likely to prefer female entrepreneurs than more experienced investors?
I read through the actual paper to see if they mentioned this limitation somewhere, not just the abstract, and could not find it. If someone else managed to spot some small clause buried in those pages, please mention where.
On a different note, why are academic papers so unnecessarily long? There was a lot of repetition in this one.