> As with prior layoffs

When all of your outcomes result in same treatment of the same group of individuals, there just might be a little fire to that smoke.

"Might" is a delightfully cop out word. Anything "might" be true.

I read that “might” sarcastically.

It was very sarcastic.

Ok. Asian Americans are consistently over represented in US higher education, especially in math-heavy fields. What discriminatory practices by these institutions are causing this?

Disparate outcomes do not conclusively determine disparate treatment

Disparate outcomes most definitely imply disparate treatment, at least enough to merit further investigation

So how does this work? Asian Americans are vastly over represented relative to their population in higher education. This "implies" they've been receiving special treatment or favoritism?

Pretty much; might or might not; "suggest" may be a better word. It means there may be something to check into.

What OTHER advantages, disadvantages, preparation levels, etc. are working for and/or against that group?

Can those factors account for the differential?

What is the groups' actual relative performance in the situation (i.e., do they tend to perform at|above|below the level to which they have risen, e.g., legacy college admissions with "Gentleman's Cs" are performing below)?

And so forth.

The point is that statistical disparities are not conclusive, but are most often indicative of some kind of structural favoritism, like smoke to fire. Not always, and you can always cherry-pick some counter-example, but the default assumption is that it merits investigation.

FWIW, I didn't flag you. Just wanted to say you're accusing me of a straw man, but when I give a particular example that is a concrete example within a general statement, that's not a straw man.

Between the two of us, I am looking at a well-researched and widely understood example of why a disparate outcome doesn't actually imply what we would intuitively think, while you are talking about metaphors of smoke and "taking closer looks" as if those justify angrily jumping to conclusions.

If you have some sort of correlation coefficient to justify jumping to conclusions even mildly, I'd appreciate that contribution. But "something isn't equal" isn't even necessarily reason to look into something further, let alone a reason to presume the cause. Nothing is ever equal. Equality is a fictional concept, and doing deep dives into every example of it would exhaust our collective resources.

IDK what's the story, My comment is non-displaying and it looks like yours is flagged.

In any case, none of this conversation is at the level of a dissertation, neither enough time or space.

The start was a seven-word comment with a tone I read that was entirely dismissive of even the concept that IBM could be practicing ageism.

It cannot be dismissed so easily (and I have family working there trying to evade exactly those ageist axes to get to retirement with full benefits).

The point of the smoke/fire is that a single good counter-example of disparate results likely not implying discrimination does not disprove all examples. The fact remains, such statistics remain a good starting point.

You have many words, but beyond the first general wave of the hands that statistics do not imply discrimination and one non-correlating example, I've missed where you provided any info or evidence to show IBM is not practicing ageism, in particular to effectively cut pensions.

Since IBM are clearly managing the workforce for profit, the multiplier of cutting older people is far larger; you save not only a few years of higher salaries, but also up to decades of zeroed or reduced pensions. Pretty strong financial incentive.

I think you're right that IBM is considering in particular the most effective cost savings strategy. And it happens that older people are more effective in cost reduction. But that's not ageism.