evaluations

These are not honest evaluations of human value, but rather honest evaluations of the market value of a human.

The outputs of multiple evaluations of `(,arg a b c) can obviously share the (a b c) part.

Even though they've won their case, it shouldn't surprise us if they keep even more documentation on employee evaluations.

The quitters that never logged back in were not further tested by you for later stage evaluations.

We're just resources for arresting cops and prosecuting attorneys, anonymous metrics on performance evaluations and resumes.

With fair evaluations would that result in even splits across sex (or race, for that matter)?

That's why humans developed concepts of trust and reputation - heuristics for making evaluations that would be prohibitively expensive otherwise.

My bet is that if conversation works in your company, performance evaluations would also work.

I doubt a machine making such simple evaluations would be able to make those kinds of decisions at all.

Debating the merits or pros/cons of any given tool is different from binding any self-evaluations to your choices, or evaluating others based on theirs.

RenderMan is now free for all non-commercial purposes, including evaluations, education, research, and personal projects.

They had a set of criteria to perform evaluations of numbers.

If you mean "correlation" to only refer to the population that passed fizzbuzz, then it is to be expected that the final positive/accepted interview evaluations don't correlate.

"Don’t rely on self-nominations or self-evaluations" I think this is the big thing that should be rallied around.

I pointed out in feedback to one of the testing companies a while back that they had no empirical basis for believing their evaluations didn't reject more qualified candidates for less qualified ones in terms of ability to do the actual job, I got a reply saying, "No, we have all kinds of empirical data!

" What would happen if we embraced this and just made all information freely available?" Included in that 7% of the OPM data theft: Intelligence applications, their private data (names, DOB, medical & psych evaluations), interviews of referees, personal information and possibly assessments.

Ignorance + Overvaluation + Greed = Artificial Evaluations.