I'm afraid most people here criticizing her normal distribution remarks are oversimplifying it much more than her.
I'm afraid most people here criticizing her normal distribution remarks are oversimplifying it much more than her.
If on the other hand she is saying that a problem in healthcare is that significantly different sub-populations are lumped together resulting in inappropriate benchmarks for some sub-populations, that is more palatable. Even if this latter interpretation is not true, at least it isn't false by definition.
The problem with the claim lies in the attempt to associate a strictly technical concept (the normal distribution) to $GENERIC_BAD_STUFF with nothing more than vague wordplay.
Also, just FYI, you have it the other way around. When you sample from a population, you (usually) assume a certain distribution (at most you infer parameters). For example, if you're sampling for opinion polls, you would actually want to oversample minorities and then correct back.