[TheCoelacanth]

I don't think it's quite as obvious of an error as you are suggesting.

They were trying to correct for scenarios like this: Hypothetically, Canadians are twice as generous as Americans and twice as religious, but religious Canadians are equally generous as non-religious Canadians and religious Americans are equally generous as non-religious Americans. On the surface, it appears that religious people are more generous, but really it's just that Canadians are more generous.

Instead of treating the countries as discrete groupings, they treated them as points on a spectrum with each country being assigned an arbitrary place on the spectrum.

If #3 happened to be China, they would be assuming that people in China should very similar to people in the US and Canada, because 1 vs. 3 on a scale that goes to 200 is hardly any difference at all, but really the numbers are just arbitrary identifiers.

[tastygreenapple]

I'm a data scientist and this is an incredibly embarrassing 'n00b' error to make. If these researchers were using anything other than deep learning, it's almost certain that each parameter of the model was manually selected. That the author made the mistake is bad, that no one caught the error is a disaster.