undefined | Better HN

0 pointsgr3ml1n1y ago0 comments

Not really. Everything is downstream of the pressure on organizations to address disparate impact. Some examples:

When a company is under pressure to boost the number of X engineers, they quickly run into the 'pipeline problem'. There simply isn't enough X engineers on the market. So they address that by creating scholarship funds exclusively for race X.

When a school is under pressure to have the racial makeup of it's freshman class meet the right ratios, it has to adjust admission criteria. Deprioritize metrics that the wrong races score well on, prioritize those that the right races score well on. If we've got too many Y, and they have high standardized test scores? Start weighing that lower until we get the blend we're supposed to have.

The goal of the college is not to get the students with the strongest academic record: it's to satisfy the demand for the right ratios.

Repeat over and over in different ways at different institutions.

> Is there an example where colorblind hiring had a nil or opposite effect? In places I've seen, the opposite has happened. For example ...

The study underlying that post is a great example of another downstream effect of DEI efforts. That study did _not_ show what the headline or abstract claimed.

When you hide the gender of performers, it ends up either nil or slightly favoring men. That particular study has been cited thousands of times, and it's largely nonsense.

http://www.jsmp.dk/posts/2019-05-12-blindauditions/blindaudi...

0 comments

kenjackson1y ago

The study did show it. The author of this critique properly notes that Table 4 is not an apples to apples comparison. The author of the study notes that expanding the pool of women as used in Table 4 likely brought in less talented musicians disproportionately.

Table 5 does the more apples to apples comparison. The critique notes that sample size is too small, but it captures 445 blind women, 816 blind men, 599 non-blind women, and 1102 non-blind men auditions. That's certainly sufficient for a study like this.

The study also does reflect how when a population feel like there is less bias against them in a system they are more likely to participate -- even if that means on average the level of "merit" might go down, but those that make it through the filter will better reflect actual meritocracy -- and that's what this study showed as well.

gr3ml1nOP1y ago

No, it doesn't. This is a dramatic reach and complete misunderstanding of the stats. The data in table 5 is not statistically significant.

If you go down to table 6 (which is also incredibly weak), it shows the opposite: men are advancing at a higher rate than women in blind auditions.

Andrew Gelman reviewed the link as well and agreed:

https://statmodeling.stat.columbia.edu/2019/05/11/did-blind-...

kenjackson1y ago

Table 5 is stat sig. There’s not a p-value given but the effect sizes are large. The knit place it’s not is the semi-final and final rounds with their smaller sizes.

And table 6 shows blind auditions significantly increased the chances of women advancing from the preliminary round and winning in the final round. However women were less likely to advance past semifinals when auditions were blind. But still a net win.

Gellman is focused on the “several fold” and “50% claims” it made. But the paper shows 11.6 and 14.8 point jumps, which are supported by the paper.

1 more reply

j / k navigate · click thread line to collapse

0 pointsgr3ml1n1y ago0 comments

Not really. Everything is downstream of the pressure on organizations to address disparate impact. Some examples:

The goal of the college is not to get the students with the strongest academic record: it's to satisfy the demand for the right ratios.

Repeat over and over in different ways at different institutions.

> Is there an example where colorblind hiring had a nil or opposite effect? In places I've seen, the opposite has happened. For example ...

The study underlying that post is a great example of another downstream effect of DEI efforts. That study did _not_ show what the headline or abstract claimed.

When you hide the gender of performers, it ends up either nil or slightly favoring men. That particular study has been cited thousands of times, and it's largely nonsense.

http://www.jsmp.dk/posts/2019-05-12-blindauditions/blindaudi...

0 comments

kenjackson1y ago

gr3ml1nOP1y ago

No, it doesn't. This is a dramatic reach and complete misunderstanding of the stats. The data in table 5 is not statistically significant.

If you go down to table 6 (which is also incredibly weak), it shows the opposite: men are advancing at a higher rate than women in blind auditions.

Andrew Gelman reviewed the link as well and agreed:

https://statmodeling.stat.columbia.edu/2019/05/11/did-blind-...

kenjackson1y ago

Table 5 is stat sig. There’s not a p-value given but the effect sizes are large. The knit place it’s not is the semi-final and final rounds with their smaller sizes.

Gellman is focused on the “several fold” and “50% claims” it made. But the paper shows 11.6 and 14.8 point jumps, which are supported by the paper.

1 more reply

j / k navigate · click thread line to collapse