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Comment by hntrader | Hacker News Reader

"controlling for ... ethnicity"

There's significant signal buried in here that is likely not controlled for, depending on how granular their controls are.

White-German and White-Italian are much more (10-13 percent) likely to be conservative leaning than White-Irish or White-British.

Hispanic-Cuban are more likely to be conservative leaning than Hispanic-Mexican.

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Their section about demographics controls in the paper was really unclear (kinda surprised you can get this published being so vague).

What does a final number with the controls active even mean? I doubt accuracy was identical within each grouping they used. Even the groupings are really unclear in the paper (at most 4 ethnic groups，no idea how they did age, etc.)

Now, what would be interesting is to build a model that accounts for this "knowledge" and see if it can beat the out-of-the-box classifier :-) I'd assume it can, and the question is: how far can a bit of manual modeling bring us?

Maybe they asked the wrong questions, but I think that's the point of the questionnaire model.

Sure, but I thought was that building an ML model that considers the questionnaire results (or existing similar findings) would be a very interesting next step.

In the US or generally?

In the US

The words conservative and liberal have wildly other meanings outside of the US. Even in the US they are not well agreed upon (especially the definitions, people seem to know which one to pick though when they have to).

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