Following Kuhn's definition for a scientific paradigm, I'm focusing on:
1) social phenomena
2) that we can predict with enough accuracy to be useful
3) using technical skills that require special training.
I've found surprisingly few examples that satisfy all of these criteria. Only three, in fact.
- Aptitude testing
Prediction: How well will a person perform in school, a given job, the Army, etc.?
Technical skill: Psychometrics - Microeconomics
Prediction: What effect will various market interventions have on the price, quantity supplied, etc. for a specific good?
Technical skill: Producer, consumer, and game theory - Election polling
Prediction: Who will win in a given election?
Technical skills: Survey design, sampling theory
What areas *should* we be able to predict? We have all kinds of new tools as social scientists. It seems like we should be ready to tackle some new challenges.
4 comments:
what about search & retrieval?
wel, yes. I forgot to put that one in. Google & co. are pretty good at finding documents to match search queries and make users happy.
Well, your #2 is a really, really big umbrella.
I might add psychological biases and their implications for things like choice architecture and effective marketing.
@TRPol: Yes, microecon is a big category. (But not as big as some economists would have you believe.) I'd call it the biggest success in social science so far.
Psych/marketing is a good one too. The individual effects tend to be small, but in aggregate, they can add up to real money. My impression of lot of this work (remembering back to my training in PR and marketing) is that it tends to be pretty context specific. Pricing point models for toothpaste work very differently from pricing point models for computer.
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