3 ms·

A certain biomed firm has in its annual report that xx% of its engineers are female. It has a goal of increasing this to yy% by %year%. Most of the eligible a

by yakult 10y ago

A certain biomed firm has in its annual report that xx% of its engineers are female. It has a goal of increasing this to yy% by %year%. Most of the eligible applicants are male. This is easily observed in university graduate numbers as well as stated in their report. These are pretty smart business people. I can't imagine they're doing this without knowing it will impact the bottom line to potentially have to pass up on promising candidates for not having the right sexual organ (which, unless things go very wrong, will not be utilized in their work). Yet this is depressingly common. I am guessing that they have weighed the cost of inefficiency against the improved corporate image - or, put another way, against the decreased media pressure - and chose the lesser of two evils. Maybe an example outside of US will make it a bit easier to see: http://www.npr.org/sections/parallels/2016/09/29/495665329/for-affirmative-action-brazil-sets-up-controversial-boards-to-determine-race http://www.npr.org/sections/parallels/2016/09/29/495665329/f...

erikpukinskis 10y ago
You are assuming without data that the old hiring process was fair and those women will do less for that firm than other new employees. I am assuming without data that those old hiring practices were bad predictors of success, and those women will do more for the firm than the average new hire. In absence of data you rely on the assumption that hiring practices and corporate practices in general are mostly smart. In the absence of data I rely on the assumption that hiring practices and corporate practices in general tend to be nepotistic and unrelated to performance. To me, the best affirmative action just takes demographics and uses them as motivation to find bad performance metrics.
- yakult 10y ago
  Eligible candidates for most jobs are not 50:50 in gender. For some fields it may be 90:10. This means a perfectly fair selection process will select 90 men and 10 women for every 100 jobs, or at least in this ballpark. Affirmative action is mostly policed by media pressure. The media does not give a shit about the above math. They will read the line in the annual report that says '90% of our engineers are male' and name and shame you on twitter. Alternatively, being more politically correct than your peer competitors is a way to virtue-signal and you get little award badges to put on your website. The politically correct ratio is 50:50. Let's say you have 100 available jobs and 1000 candidates, 900 men and 100 women. To enforce 50:50, you choose the best 50 men out of 900 and best 50 women out of 100. Your hypothesis is that affirmative action unlocks economic benefits. This is asserting that the marginal female engineer who is better than 50% of her peers is superior to the marginal male engineer, who is better than 94% of his peers. Additionally, the difference must be large enough to overcome the inefficiency of messing with market mechanisms. This is an extraordinary claim and would require extraordinary evidence. What about the effect of nepotism? Let's say the hiring manager really doesn't like women, and the selection ends up 95:5. Five marginal female engineers are replaced by five marginal male engineers. Compared to the huge skewing above, this is a blip on the radar. Note I am not saying it is not a problem, I am saying the current solution is on average much worse. I do not doubt that for some pathological cases affirmative action actually does have a positive effect on the bottom line. But this will only happen when the company is badly screwing up recruitment. On the other hand, companies with saner, optimized hiring processes are penalized with an arbitrary ratio. The effect here is to boost inefficient businesses and penalize relatively efficient ones.
  - erikpukinskis 10y ago
    > This means a perfectly fair selection process will select 90 men and 10 women for every 100 jobs, or at least in this ballpark. How does one know what the correct target ratio is for their field? You have blind faith in market mechanisms. I have blind faith in the general equality of the sexes. I'm not saying I'm right, I fully acknowledge it's an article of faith. I'm just hoping I can get to acknowledge that your belief in male superiority in certain fields is also an article of faith.
    - yakult 10y ago
      >How does one know what the correct target ratio is for their field? One can look at the distribution of m:f in the list of eligible applicants, or more generally in university graduate numbers. It will be subject to noise, but the 'natural' outcome should be at least in the same ballpark. >I have blind faith in the general equality of the sexes. I'm not saying I'm right, I fully acknowledge it's an article of faith. Blind faith is not necessary here. Nor is a belief in 'male superiority in certain fields'. I agree that given equal qualifications, gender should not affect performance to a great degree, yet affirmative action vastly skews recruitment to one side in this case and only makes sense if it turns out gender does affect performance and women are somehow vastly better (without this effect being picked up and accounted for by the market).

by yakult 10y ago

erikpukinskis 10y ago

You are assuming without data that the old hiring process was fair and those women will do less for that firm than other new employees. I am assuming without data that those old hiring practices were bad predictors of success, and those women will do more for the firm than the average new hire. In absence of data you rely on the assumption that hiring practices and corporate practices in general are mostly smart. In the absence of data I rely on the assumption that hiring practices and corporate practices in general tend to be nepotistic and unrelated to performance. To me, the best affirmative action just takes demographics and uses them as motivation to find bad performance metrics.

yakult 10y ago
Eligible candidates for most jobs are not 50:50 in gender. For some fields it may be 90:10. This means a perfectly fair selection process will select 90 men and 10 women for every 100 jobs, or at least in this ballpark. Affirmative action is mostly policed by media pressure. The media does not give a shit about the above math. They will read the line in the annual report that says '90% of our engineers are male' and name and shame you on twitter. Alternatively, being more politically correct than your peer competitors is a way to virtue-signal and you get little award badges to put on your website. The politically correct ratio is 50:50. Let's say you have 100 available jobs and 1000 candidates, 900 men and 100 women. To enforce 50:50, you choose the best 50 men out of 900 and best 50 women out of 100. Your hypothesis is that affirmative action unlocks economic benefits. This is asserting that the marginal female engineer who is better than 50% of her peers is superior to the marginal male engineer, who is better than 94% of his peers. Additionally, the difference must be large enough to overcome the inefficiency of messing with market mechanisms. This is an extraordinary claim and would require extraordinary evidence. What about the effect of nepotism? Let's say the hiring manager really doesn't like women, and the selection ends up 95:5. Five marginal female engineers are replaced by five marginal male engineers. Compared to the huge skewing above, this is a blip on the radar. Note I am not saying it is not a problem, I am saying the current solution is on average much worse. I do not doubt that for some pathological cases affirmative action actually does have a positive effect on the bottom line. But this will only happen when the company is badly screwing up recruitment. On the other hand, companies with saner, optimized hiring processes are penalized with an arbitrary ratio. The effect here is to boost inefficient businesses and penalize relatively efficient ones.
- erikpukinskis 10y ago
  > This means a perfectly fair selection process will select 90 men and 10 women for every 100 jobs, or at least in this ballpark. How does one know what the correct target ratio is for their field? You have blind faith in market mechanisms. I have blind faith in the general equality of the sexes. I'm not saying I'm right, I fully acknowledge it's an article of faith. I'm just hoping I can get to acknowledge that your belief in male superiority in certain fields is also an article of faith.
  - yakult 10y ago
    >How does one know what the correct target ratio is for their field? One can look at the distribution of m:f in the list of eligible applicants, or more generally in university graduate numbers. It will be subject to noise, but the 'natural' outcome should be at least in the same ballpark. >I have blind faith in the general equality of the sexes. I'm not saying I'm right, I fully acknowledge it's an article of faith. Blind faith is not necessary here. Nor is a belief in 'male superiority in certain fields'. I agree that given equal qualifications, gender should not affect performance to a great degree, yet affirmative action vastly skews recruitment to one side in this case and only makes sense if it turns out gender does affect performance and women are somehow vastly better (without this effect being picked up and accounted for by the market).