Comment by Manuel_D | Hacker News Reader

Comment by Manuel_D | Hacker News Reader

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> You addressed the wrong argument. The intent is to give groups that are disadvantaged in the hiring process a chance. The intent is equity. Your example distorts that by shifting the balance in favor of an already advantaged group.

Then anonymize the resumes so that recruiters can't tell which candidates are men or women, or which is white, Asian, Black, etc. You don't eliminate discrimination by setting caps on how many interviewees can belong to each race. It certainly could be the case that whites are advantaged (curious why you focus on whites despite Asians being far more overrepresented, by the way). Put the proverbial veil between the candidate and the hiring manager, and we'll find out the truth.

One of my previous workplaces rejected proposals to anonymize our interview process, on the grounds that it would inhibit our diversity initiatives. Interviewing.io did an experiment relative to gender with anonymized phone interviews, and the result were the opposite of the traditional narrative [1].

1. https://blog.interviewing.io/we-built-voice-modulation-to-ma...

Blinding an interviewer by changing pitch/modulating the voice does little to erase the actual disadvantage. Few are arguing "people that sound like women are discriminated against", they're saying that the systems are set up in such a way that there is a bias against women that encompasses the evaluation of their experience, their work profiles, the topics they're interested in, the projects they've completed previously, etc. It's a systemic disadvantage, and that experiment isn't getting at the issue being claimed.

As just one example, women still do the majority of child rearing, especially babies. People who want children make that choice, but men typically take a few weeks out of their career whereas women take months or more. That's a systemic disadvantage women suffer.

> there is a bias against women that encompasses the evaluation of their experience, their work profiles, the topics they're interested in, the projects they've completed previously, etc.

Actually, studies specifically aimed at measuring tech jobs indicate preferences favoring women candidates: https://news.ycombinator.com/item?id=25069644

People frequently compare the rates of women in tech relative to the general population, not the pool of tech workers. This is misleading, when in fact most companies are quite balanced in terms of gender representation - relative to the representation of women in the field. 80% of nurses being women isn't a sign of men being disadvantaged any more than 80% of coders being men.

working link for the paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3672484

Silicon Valley is hardly representative of tech as a whole.

> That's a systemic disadvantage women suffer.

That's, perhaps, a systemic disadvantage mothers suffer. Tilting the tables advantages childless women most of all (and would be illegal discrimination against men, were the law to be enforced). Similar to how Ivies' affirmative action helps the children of African despots more than disadvantaged Americans.

The New York Philharmonic Orchestra introduced blind auditions due to racism concerns - in the 1970ies. New York Times launched a campaign in 2020 to put an end to blind auditions as the orchestra is not diverse enough.

> The New York Philharmonic Orchestra introduced blind auditions due to racism concerns - in the 1970ies. New York Times launched a campaign in 2020 to put an end to blind auditions as the orchestra is not diverse enough.

There's your "white guilt" in action. Meanwhile, at the end of the day, everybody (regardless of skin colour) just wants to attend a damn fine musical performance. The fuck do I care if the musicians are black, white, young, old, fat, or skinny?! NONE of those are relevant attributes to being a talented musician who can perform well on a team!

> curious why you focus on whites despite Asians being far more overrepresented, by the way

Asians are often referred to as "white" or "lily-white" in the context of hiring and college admissions.

> curious why you focus on whites despite Asians being far more overrepresented, by the way

I picked your example. Also, I'm not in the US. Apologies for failing at the intricacies of US-centrism.

Anonymous CVs are an interesting idea, and indeed how most of the studies measuring biases (not just on gender, but also things like perceived origin of name) are constructed.

But you're not going to get everyone to do them.

> Interviewing.io did an experiment relative to gender with anonymized phone interviews

If voices were so representative gender, we wouldn't have a severely worse pay gap for trans women. These are more systemic issues that start with gender roles and expected acceptable behaviors themselves.

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