So, e.g. areas with lots of blacks are (generally) poor/crime prone/low trust because there's more blacks and blacks are poor/criminal/low trust. It's not the mixture of people per se, but their relative proportions. Different causal mechanism.
Certainly no Nazi. However, his issue is that he is apparently unable to distinguish between main effects of populations and diversity effects (this is an interaction). They are saying the outcome is explained by the main effects, not the interactions.
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It's easy, you just include both the interactions and the main effects and see which predicts what. See here for an example of US counties. Racial diversity is associated with worse outcomes, until one adds the main effects and IQ. http://rpubs.com/EmilOWK/racial_homogeneity_study_2017 …
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The key to understanding it is that a given area can have high diversity for multiple reasons. An area with a 50-50 White-Asian split has high diversity, but is not expected to perform poorly because composite groups perform well.
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My study above (rpubs) used an aggregate metric composed of some 20 different social indicates. Read the original study (2016) if curious. Putnam didn't control properly for main effects I suspect.
End of conversation
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