> NNNNNNNNNNNNDNNNNNNNNNNND
If the pattern resembles this for a group that represents over 50% of the broader population (women and some subset of males), I'd argue that it's highly possible there are other, possibly discriminatory, factors at play.
If the pattern resembles this for a group that represents over 50% of the broader population (women and some subset of males), I'd argue that it's highly possible there are other, possibly discriminatory, factors at play.
A non discriminatory hiring process should reflect the demographics of the workers in the given field (other factors like geography matter too). Why would we expect, say, pediatricians (80% female) to have 50% men?
Achieving a 50/50 split between men and women in a field that's 80% one gender requires hiring one gender at 4x the rate of the other. This line of thinking is what leads companies to set up discriminatory hiring practices in pursuit of DEI goals.
The even government office of non discrimination compliance agrees: https://www.dol.gov/agencies/ofccp/faqs/AAFAQs
> The purpose of affirmative action is to ensure equal employment opportunities for applicants and employees. It is based on the premise that, absent discrimination, over time a contractor’s workforce generally will reflect the demographics of the qualified available workforce in the relevant job market.
> Does one feel as if they would face an uphill battle trying to get hired in a field that is 80% their other?
What people feel is hard to quantify. But what we can quantify is the call back rates of male and female applicants. Tech companies are more likely to call back women: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3672484
HN discussion at the time: https://news.ycombinator.com/item?id=25069644
A good illustration of this concept is the "equality vs. equity" cartoon, with people of different heights trying to look over a fence. https://interactioninstitute.org/wp-content/uploads/2016/01/...
I understand why a lot of folks, especially technically-minded folks, bias for equality of opportunity exclusively. This is essentially what a meritocracy is. There's lots of good things about equality of opportunity and meritocracies, but they also have problems, and one of those problems is that, generalizing, they both tend to reflect and reinforce pre-existing biases, and in particular implicit biases. This is exactly the kind of problem that DEI initiatives are trying to address.
I don't really want to litigate the pros and cons of these two concepts, I just want to point out that they both exist, and that initiatives like DEI can have as goals improving one or the other or both.
It's fine if you say, when doing hiring, you're only interested in equality of opportunity. That's probably the position that most people who are anti-DEI would take. But I think it's also fine if you say, when doing hiring, you're interested in both equality of opportunity and outcome. Both are valid.
Also, think through the implications of this photo in the context of hiring: https://interactioninstitute.org/wp-content/uploads/2016/01/...
What's really the difference between having a group of candidates standing on a box, and lowering the bar for those candidates? At the end of the day, whether it's standing on a box or lowering the bar the end result is the same: some candidates are considered to have met expectations despite not reaching the same heights as others.
I highly encourage you to think through whether this is a good metaphor to use to justify DEI in a workplace setting.
It's not a question of scope. Equality and equity are not equally valid concepts in hiring. The former is required by law, even if it produces an inequitable outcome. There is no "balance" between respecting candidates civil liberties and achieving your preferred demographic distribution.
The whole exercise feels like an effort to take attention off of the problem of income inequality by instead framing it as an issue of identity. Under this framing, "fair" means we have parity in male and female CEOs - never mind that those CEOs are still making 300x or more of what "frontline" workers make. Why not focus on pushing for higher wages in female dominated fields like teaching or nursing?
[1] https://www.zippia.com/sanitation-worker-jobs/demographics/
It's -- "if important career X has way more men than women, is this a good thing, at a net societal level, regardless of <whatever> that can explain why this is the case?"
Nobody is looking for complete and perfect parity in all influential careers. The intent is just to make sure that, for the highest-impact careers, we should work towards making them representative of our society, as much as possible
Your question implies serval beliefs, which may or may not be true. And that others may, or may not share.
For one, I don’t think the average developer has a ton of say on how products get made. So that’s not likely the power you’re seeking to ensure changes hands? Market forces and legal structure pretty much ensure enshitification and other outcomes which many would likely consider sub optimal.
Take a step back on the supply side. CS education isn't a requirement, though only 20% of CS undergrads are female.[0]
I'm curious what your stance is on the swathe of asians who got negatively handicapped for checking "asian" on their college applications.
[0] https://www.scientificamerican.com/article/there-are-too-few...
I get why the majority of jobs that require a lot of upper body strength (lumberjacks as you mentioned) would continue to be majority male, but in other jobs to me it seems like it's mainly networks and socialization that causes gender imbalances. There's no reason more men can't become pediatricians or school teachers. They can obviously do the job, and did in the past!
For tech jobs, I often see people saying that men are more interested in numbers and things, so it's biological that men would gravitate towards tech. I used to think that sounded like a plausible explanation, but then I read that women make up 60% of accountants, and other examples like that. Seems like accounting was just more socially accepting of women, otherwise by that argument accounting would be majority male too.
One example that I thought was quite interesting was that 65% of realtors are women, but in commercial real estate it's only 35% women. It would be quite a stretch to come up with a biological argument for the real estate example.
In my view, a non-discriminatory hiring process is one that accounts for the very real human behaviours that 1) people feel more comfortable with people who are similar to them, and 2) when jobs skew dramatically towards one gender/race it creates a social barrier to people from outside that group getting hired and accepted by the team. If we just completely ignore how humans actually behave, we accidentally end up with a discriminatory hiring process without anyone wanting do anything bad. I have no doubt that some implementations of affirmative action are terrible and discriminatory. But I think ignoring human tendency to feel drawn to people similar to themselves, and thus inadvertently discriminate is a mistake as well.
1. https://interviewing.io/blog/voice-modulation-gender-technic...
If coding interviews were done with cameras off, and voice masked so gender can't be known, how would that be more subject to bias than with the camera on and the gender known to the interviewer?
When orchestras put a veil between the auditioner and the evaluators, that made the process more biased? That's new to me.
And again, if the bias comes from people's tone then the interview can be conducted over text. Or have a transcript of the interview that is used by the hiring committee, to ensure that a "high confidence and authoritative tone" doesn't introduce bias. Bias can be eliminated. And if the disparity remains the same, the disparity is not due to bias.
And how do we know if the hiring disparity is due to bias? The details of the hiring process are absolutely relevant, because the notion that the hiring disparity is due to bias is a claim about the details of the hiring process.
My main issue with a lot of DEI programs is that they don't try to eliminate bias. They just assume disparities are due to bias and work towards "fixing" those assumed biases with explicit discrimination. The problem is that when you actually try to measure and quantify bias in tech, the results often aren't what DEI advocates assume. E.g. https://www.pnas.org/doi/10.1073/pnas.1418878112
This is why there's such a a strong pushback against anonymizing interviews and other bias mitigation measures. What happens if your interviews and applications are all anonymized and the hiring disparity remains? The justification for "fixing" the representation is now a lot weaker since it's harder to claim it's due to bias. "Let's address bias in our hiring process" is a lot more popular than "let's set quotas". So the people who want quotas try to claim that they're just fixing bias by setting quotas.
You don't eliminate biases by focusing on the gender ratio of the orchestra. You eliminate biases by putting a veil between the auditioner and the evaluators. We all know this, but some people feel compelled to pretend that they're working towards eliminating biases when in reality they're working towards achieving certain demographics outcomes.
The hostility to anonymized interviews stems from the fact that one cannot discriminate in favor of particular demographics. This is the goal of the above commenter, as stated here: https://news.ycombinator.com/item?id=42830509
> The only things that do reduce discrimination in the short term is rules that deliberately relatively advantages the discriminated class and in the long term, socio-cultural shift.
This isn't reducing discrimination. This is deliberately engaging in discrimination to change demographic outcomes.
We could have avoided a lot of confusion if DEI advocates were honest that their goals are not to eliminate discrimination but rather to employ employ affirmative action to achieve more equitable outcomes. If that's your goal, then of course anonymized hiring doesn't work: if you can't tell which candidate belongs to which demographic, then you don't know who to give advantage to.