A lot of data science is about capturing messy social concepts. For instance, a company that hires out temps might be interested in people who are 'reliable'. How does a computational social scientist go about constructing a measure like that? 
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Incorrectly, I'd imagine. 'Reliability' is a damn good example of a "messy social concept." My (idealized) procedure would include first interviewing whoever does the hiring and whoever tasks the temps to see if I can elicit their loss functions for it.
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Indica or Sativa? ;)
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