Yes exactly. I'm not suggesting that they spend half-time on empirical work, just that they've had a chance to work with raw data, and thereby understand how the sausage is made. Otherwise I think one overweights small incidental findings and theories can be overfit.
I've models where I capture the data, reproduce the data others have collected. I also have ones where I predict data that doesn't exist while I did the modelling. I also do qualitative modelling and/or theoretical modelling. But like I said I usually work with others' data.
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I also do experiments on models to further understand the models themselves. Like science on a deep network.
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This is why I am not sure in all this where I would fit in.
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Above I made a typo. I meant to link to http://redistrict.science — what kind of modelling is that? It uses data but it doesn't really predict anything in and of itself.
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I'd be say/guess in cognitive (neuro)science you span the part of the spectrum ranging from theoretical modeling to data modeling. (the 1 dimension is a simplification ofc). And your gerrymandering work is an example of mathematical/computational modeling for social engineering?
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Yeah, exactly. BTW TIL because I have no idea social engineering meant what you just used it as! I only knew it as: https://en.wikipedia.org/wiki/Social_engineering_(security) …
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Oh! That meaning I indeed did not mean. I constructed it on the fly, so perhaps I deviate from common usage.
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No, you used the right phrase! And I learned something! https://en.m.wikipedia.org/wiki/Social_engineering_(political_science) …
End of conversation
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