rando289

I can't remember a story like this without horrible data: numbers without much context from which no good conclusions can be drawn.

> it's not enough to just look within the 'hire' cohort.

Enough for what? Why not? They specifically have a "score", not just a hire / no hire decision. Sure it would be better, but you don't make any convincing argument why their analysis is not valuable.

> designed to be a Classifier, typically tuned with an emphasis on having a low false positive rate.

classifier of what? Why is classifier capitalized? I don't think so.

How do you check that? I've found reporting on race in tech to just be absolutely horrible with numbers. Whole stories where the only number is "Google repots X percent of Y race." It tells me absolutely nothing without comparing that to demographics of where google has offices, and what the demographics of cs students are, among other things, and I've never seen that info.

Your 48% is very wrong. From the abstract:

"Our results showed that although casual contributors are rather common (48.98% of the whole population of contributors in the projects analyzed), they are responsible for only 1.73% of the total number of commits."

I didn't say they were clueless. I said their pr is clueless. Some pr person said "there is no risk" relating to it security of a large organization. That is obviously false, and clueless.

"Our systems and our customers’ information were never at risk.", their pr team is clueless. Security is not binary.

So it's proprietary?

"we still don't know how." No one is stating the obvious: we would know more if we had the source code.

Ahh, thank you so much. I read it as "are kind of forgetting" instead of "are a kind of forgetting.", even looking back a few times.

What does forgetting mean here? Is it like forgettable? Google failed me.

My 12 year old ipod has fm radio, I think a smartphone could do it.