Live data from Hacker News

Hiring discrimination: a problem for men in female-dominated occupations

journals.plos.org

621–630 of 666 posts

Re: Hiring discrimination: a problem for men in female-dominated occupations

#621
post #184

There are very concerning patterns developing at the moment in the DEI space. DEI efforts, and often those leading them, are increasingly the most biased and close minded parts of the organization. Spreading selected stereotypes and often solving concerns about “discrimination” by being very biased and inequitable. For example at my last company a report showed that slightly fewer of a certain minority were promoted.…

I think DEI efforts can greatly vary. I know that we've worked really hard to ensure that we don't disadvantage anyone -- but it's harder than it sounds. DEI is often dealing in zero sum spaces. For example, most of the staff is white males. We try hard to hire the best person for the role, but we've instituted a policy where we mandate interviewing underrepresented groups. Not that we will hire them, but that we wil…

> Not that we will hire them, but that we will interview them.

to the extent that the policy causes you to interview people that are obviously less qualified and won't get hired... damn, that's really bad news for the candidate.

Can you imagine that you're a Star-bellied Sneetch and waste day after valuable day of time interviewing for jobs that you won't get hired for, brought in because you happened to have a star-belly and not because you were among the most obvious fits for the job? Talk about being disadvantaged by systematic racism.

In the aggregate, sure, its still probably better for them to be extended the interview... but the wasted time chews up a chunk of that benefit.

Since your post expresses the view that you go through more interviews due to your laudably-motivated-diversity program than you would otherwise, which means you're also wasting more applicatints time than you would otherwise... perhaps you should suggest that you company pay a reasonable wage to ever person that makes it to an in person interview as a way of offsetting the negative externality?

I don't think it would be all that unreasonable once you consider the man-hour cost you're already putting in to interview the candidate, ... paying the candidate would have a similar cost to having one more person on the panel and would go a long way to make sure you're not burdening job hunters with your interviewing practices.

Re: Hiring discrimination: a problem for men in female-dominated occupations

#622
post #605

Earlier quoted context omitted.

No. Not I. But I will say this: > pressure on HMs to hire more women despite 95% of applicants being male is something I've done myself, not to hold anything against the applicants coming in but because HMs have a significant amount of control over the funnel of applications coming in. I want them hustling to encourage women, minorities, veterans, old-timers, re-inventors, people with nonstandard educational paths--p…

> I want them hustling to encourage women, minorities, veterans, old-timers, re-inventors, people with nonstandard educational paths I'm a vet. This is a band-aid and I'd discourage you from thinking this way because it's short term at best. If you want to hire more vets then companies need to find where vets are. Some of us use our VA benefits and get a degree, others meet the stress of post-separation and collapse.…

That's exactly my point! But to find these additional sources, recruiters have to do the work; these are sources they may never have explored before.

Re: Hiring discrimination: a problem for men in female-dominated occupations

#623
post #540

Earlier quoted context omitted.

No. Not I. But I will say this: > pressure on HMs to hire more women despite 95% of applicants being male is something I've done myself, not to hold anything against the applicants coming in but because HMs have a significant amount of control over the funnel of applications coming in. I want them hustling to encourage women, minorities, veterans, old-timers, re-inventors, people with nonstandard educational paths--p…

You divide candidates into such stereotypical categories why not throw all of that labeling away and get to know each candidate as unique humans with different skills/personalities and make judgements on those? It's like you are judging a tasting contest by the color of icing instead of eating it.

When it comes time to determine qualifications, we of course do that. But if that's the point where you decide to start caring about the pipeline, you've already lost.

Re: Hiring discrimination: a problem for men in female-dominated occupations

#624

Earlier quoted context omitted.

Yes and no to fresh engineers being good. I’ve met many fresh engineers that integrated and soon outperformed their older peers in a couple months. My first engineer position I went from new hire to lead on most projects in about a year. I was surprised and dumbfounded how much better I was than my peers (expect one he was amazing and I learned a lot from him). There a lot of good and bad engineers and experience doe…

Single data point. It doesn't prove or disprove anything. I have seen 60 yo folks jump on a project and literally turn it around in weeks. > I was surprised and dumbfounded how much better I was than my peers Self-Humbled

Not really, I really expected to be very lacking in experience and aptitude. I did poorly in school and I have really bad ADHD and Tourette’s. My expectations as an engineer were to do well enough to keep a job; never expected I’d be a natural at writing software.

Re: Hiring discrimination: a problem for men in female-dominated occupations

#625
post #551

Earlier quoted context omitted.

To add to your list: - referral bonuses, but only for diversity hires - hiring freezes, except diversity hires

Referral bonus to fix a problem of a funnel ... Does not sound wrong. Sound actually very smart. Hiring freezes except diversity hires ... Sounds wrong.

Financially incentivizing people to hire people of a particular race or gender doesn't sound wrong to you?

If it were "white" or "men", people would have a cow, and rightfully so. But encouraging discrimination in the reverse direction is just fine?

Re: Hiring discrimination: a problem for men in female-dominated occupations

#626
post #551

Earlier quoted context omitted.

Referral bonus to fix a problem of a funnel ... Does not sound wrong. Sound actually very smart. Hiring freezes except diversity hires ... Sounds wrong.

Financially incentivizing people to hire people of a particular race or gender doesn't sound wrong to you? If it were "white" or "men", people would have a cow , and rightfully so. But encouraging discrimination in the reverse direction is just fine?

No post body was provided.

Re: Hiring discrimination: a problem for men in female-dominated occupations

#628

Earlier quoted context omitted.

Check the chess grandmasters distribution. Or Go.

Chess statistics do not show evidence of a significant difference: https://en.chessbase.com/post/what-gender-gap-in-chess

That is obviously garbage statistics, isn't it? The conclusion they've drawn about the female distribution is based entirely on the performance of one female player. And they're obfuscating rank ordering with rating gap.

Also, for an unexplained reason, they only consider Indian players. That's weird, isn't it? Why Indian? Let's investigate.

Using the Oct 20th 2020 data, since the Oct 6th 2020 data isn't available on the FIDE website, we could look Chinese players (birthday I picked China because they're a large country and because the top active female player is Chinese.

Of the top Chinese players, the ordering is 8 males, 1 female (Hou, Yifan), 12 males, 1 female (Xie, Jun), then 3 M, 1 F, 5 M, 1 F, 1 M, 1 F, 2 M, 1 F, and so on.

The overall Chinese female percentage is 30.47%. Here's a table of percentage over rating threshold, with cumulative sums shown.

                M       F       M Sum   F Sum   FSum/(MSum+FSum)
    2800        0       0       0       0       -
    2700        5       0       5       0       0.00%
    2600        10      1       15      1       6.25%
    2500        15      4       30      5       14.29%
    2400        38      10      68      15      18.07%
    2300        55      10      123     25      16.89%
    2200        76      31      199     56      21.96%
    2100        89      40      288     96      25.00%
    2000        48      29      336     125     27.11%
    1900        42      17      378     142     27.31%
    1800        42      25      420     167     28.45%
    1700        27      15      447     182     28.93%
    1600        27      11      474     193     28.94%
    1500        13      14      487     207     29.83%
    1400        9       2       496     209     29.65%
    1300        3       4       499     213     29.92%
    1200        1       3       500     216     30.17%
    1100        2       1       502     217     30.18%
    1000        0       3       502     220     30.47%
Here's the data for India:

                M       F       M sum   F sum   FSum/(MSum+FSum)
    2800        0       0       0       0       -
    2700        3       0       3       0       0.00%
    2600        10      0       13      0       0.00%
    2500        16      2       29      2       6.45%
    2400        38      0       67      2       2.90%
    2300        68      9       135     11      7.53%
    2200        150     11      285     22      7.17%
    2100        321     31      606     53      8.04%
    2000        556     57      1162    110     8.65%
    1900        591     42      1753    152     7.98%
    1800        750     66      2503    218     8.01%
    1700        920     53      3423    271     7.34%
    1600        1321    74      4744    345     6.78%
    1500        1585    117     6329    462     6.80%
    1400        2135    129     8464    591     6.53%
    1300        2671    141     11135   732     6.17%
    1200        2962    165     14097   897     5.98%
    1100        2566    139     16663   1036    5.85%
    1000        1592    139     18255   1175    6.05%
What is going on there?

It is worthwhile to check out India having filtered out the inactive players:

            M       F       M sum   F sum
    2800    0       0       0       0       -
    2700    3       0       3       0       0.00%
    2600    9       0       12      0       0.00%
    2500    13      2       25      2       7.41%
    2400    30      0       55      2       3.51%
    2300    36      8       91      10      9.90%
    2200    44      6       135     16      10.60%
    2100    47      7       182     23      11.22%
    2000    56      11      238     34      12.50%
    1900    51      8       289     42      12.69%
    1800    72      7       361     49      11.95%
    1700    128     6       489     55      10.11%
    1600    179     3       668     58      7.99%
    1500    234     7       902     65      6.72%
    1400    370     8       1272    73      5.43%
    1300    493     10      1765    83      4.49%
    1200    605     14      2370    97      3.93%
    1100    513     18      2883    115     3.84%
    1000    296     20      3179    135     4.07%
There is a big pile of low-rated Indian men with FIDE ratings, while mediocre women aren't interested. Note that the article fallaciously compares the male average to the female average as if that means something.

If we were to compute the article's bogus statistical argument about the top woman, a more appropriate female percentage to use would be more like 12.69%, the maximum on that list, before the hoard of mediocre males, instead of 6.1%.

It would make more sense to base our statistics on the set of all the world's active players, instead of one woman from a particular country against an irrelevant percentage. Here is that data:

            M       F       M sum   F sum   Fsum/(Msum+Fsum)
    2800    2       0       0       0       -
    2700    32      0       32      0       0.00%
    2600    186     1       218     1       0.46%
    2500    437     11      655     12      1.80%
    2400    1049    39      1704    51      2.91%
    2300    1928    87      3632    138     3.66%
    2200    3385    156     7017    294     4.02%
    2100    5699    231     12716   525     3.96%

Re: Hiring discrimination: a problem for men in female-dominated occupations

#629
post #551

Earlier quoted context omitted.

Referral bonus to fix a problem of a funnel ... Does not sound wrong. Sound actually very smart. Hiring freezes except diversity hires ... Sounds wrong.

Financially incentivizing people to hire people of a particular race or gender doesn't sound wrong to you? If it were "white" or "men", people would have a cow , and rightfully so. But encouraging discrimination in the reverse direction is just fine?

It is about the funnel and not the hiring. I assume here that the funnel is anyway full of white men and the hiring decision itself is non discriminatory.

Re: Hiring discrimination: a problem for men in female-dominated occupations

#630

Earlier quoted context omitted.

Chess statistics do not show evidence of a significant difference: https://en.chessbase.com/post/what-gender-gap-in-chess

That is obviously garbage statistics, isn't it? The conclusion they've drawn about the female distribution is based entirely on the performance of one female player. And they're obfuscating rank ordering with rating gap. Also, for an unexplained reason, they only consider Indian players. That's weird, isn't it? Why Indian? Let's investigate. Using the Oct 20th 2020 data, since the Oct 6th 2020 data isn't available on…

You seem passionate about proving something but I can't tell what it is.
Post reply on HN