60 karma · joined March 8, 2013
It's part of a bigger problem seen here in Europe (at least for those who don't move away.) Online work profiles like Linkedin are an obsession here -- and these sites are all oriented around highlighting school and businesses associations, instead of around the list of projects one's worked on. Useless for hiring.
This illustrates the two very different approaches to the problem of getting hired:
A) If you convince school to certify you -> you will convince a company to hire you.
B) If you achieve relevant work -> a company will hire you to perform more work.
I study food, fragrance, software and other types of product preferences. In the studies I've done, often people's very subjective preferences (or so we assume) turn out to be highly clustered into just one or two clusters of highly similarly-preferenced people. Sometimes when you'd assume there would be total disagreement, there's actually total preference agreement.
Each sample of the type of data that I'm often dealing with tends to be nested in nature. Yes, I do have a script that can flatten out the nested dicts into a regular table, but that always results in a blowup into hundreds of columns.
Nice suggestion to share the raw data. I've never seen a researcher do that, I think many don't even save the raw data to disk before extracting what they want, but I always try to.
Your concerns about ranking-context and the general difficulty of ranking are, however, well placed. Solving the ranking problem, for the general case, is a first-class problem on the same level of difficulty as computer vision or language processing.
Personally, I think the world deserves a better approach to solving general ranking.