> And a common rebuttal to the objection is that systemic racism is often difficult to untangle in a way that produces a neat chain of cause and effect (not least of which because discrimination can happen unconsciously or secretly)

We have a "disparate impact" and nobody can prove what proportion of it is due to things like parental income or childhood education as opposed to racism on the part of the employer. Because the former considerations are real contributors, the metric can regularly be expected to exceed the threshold even if the contribution of racism by the employer was zero. Doesn't that imply that we're essentially accusing people of racism at random?

> because the impact exists whether intent can be shown or not, the desire remains to ameliorate that impact.

The median household income for Asian Americans of Indian ethnicity is more than double those of Burmese ethnicity:

https://en.wikipedia.org/wiki/List_of_ethnic_groups_in_the_U...

This is objectively a disparate impact and likely shows up in several other metrics in addition to income. Disparate results can almost universally be obtained by arbitrarily segmenting the population into different groups and comparing the midpoints. Americans of Australian ancestry have a higher median income than those of Irish ancestry, Bolivians higher than Cubans. The result is often because the lower down group has a history of being oppressed.

What reasoned means can we use to determine which groups get the benefit of these methods to ameliorate the disparity and which don't? What should be done about the inherent impossibility of doing them simultaneously, e.g. because hiring a South African woman over a Haitian man would reduce the disparity on one axis while increasing it on another? Notice that considering each group separately could result in unconditional liability because either available alternative puts you over the threshold for one group or the other.

> If the issue happens upstream of the defendant to a claim - generally an organization being sued by an individual with fewer resources - it incentivizes such entities to push for changes upstream, so that they don't get stuck with the bill.

Do we want to apply this logic to other things? The median income in California and New York are significantly higher than they are in Alabama or West Virginia and they have higher ranked public schools. We can correspondingly expect that when applicants from different states apply for the same job, the ones from California and New York (even if they're the same race etc.) are more likely to be selected because they had more advantages growing up, even though none of them chose where they were born.

By the same reasoning we should then have the federal government penalize employers for hiring the applicants from the more affluent states so that it "incentivizes such entities to push for changes upstream, so that they don't get stuck with the bill." Does it make sense to do that?

What evidence would disprove the claim that systemic racism is the cause of a persistent disparity?

To the contrary, companies have been found liable for discrimination solely based on having the wrong percentages outcomes in its objective hiring assessments: https://en.wikipedia.org/wiki/Griggs_v._Duke_Power_Co.

You are selectively adhering to the letter of the law, when the practical effects are already well known and studied. One is not obligated to ignore literature, nor abstain from doing a simple extrapolation from the incentives placed on the table.

There is a large body of literature concerning the question "does disparate-impact enforcement cause employers to alter hiring behavior in ways unrelated to actual productivity or discrimination?" and the answer is largely "yes". As you suggested elsewhere in this discussion, Google may be useful.

"Races" aren't qualified for anything. Neither are star signs or favorite Hogwarts houses.

Individuals are qualified or unqualified. If a company happens to end up with less than 1/4 Ravenclaws or not very many Virgos, it doesn't mean hate is a reason. It could be that the Ravenclaws that applied were a bit less qualified than those from the other houses.

I guess my point is, doing the statistical analysis for race and gender and drawing conclusions, while being completely blind to the one single factor any sane hiring manager should be focusing on -- actual qualifications for the role -- doesn't make any sense.

Eliminate the double negative, and you're making the same statement as the comment above.

There are many other potential explanatory factors than your simple binary. Black people in America started in a very bad and difficult position, only a few generations ago, with huge racial discrimination, no money, and generational distrust of institutions. That is a factor that will affect what you see today without any current system of racial discrimination or inferiority.

It's not used to measure discrimination. It's used to identify outcomes that appear to be potentially discriminatory. You have to do the legwork afterwards.

Like. If I am evaluating a developer on lines of code written, I am a bad manager. But if an engineer has 40% fewer lines of code than the team median, it's absolutely ok for me to go, "Interesting. What's the story there? Are they slower or is there some other factor?"

Same idea -- this is purely a fast, first pass metric that can quickly assess if something warrants a deeper evaluation.

How would you like me to define "starting point" in a way that you believe you'll be able to understand?

If you are trying to say "more data needed, headline misleading" you should say that instead of misrepresenting the 4/5ths rule. Also the word "can" implies uncertainty of conclusion. This isn't ridiculous, the authors point out that this is the first large scale study of this topic. Nothing has been "proven" here, it's showing that this warrants further investigation and attention.

Do you read many academic papers, because you seem to be having a rough go here.