If you read the whole paragraph, it's obvious what the writer intended to convey: that health research often assumes that there is one average, representative person, and everybody else is clustered around that person in a normal distribution. The author asserts that this is wrong, because people are dissimilar in more complex ways, and instead often fall into different clusters, rather than one bell curve.

In my opinion, the author's assertion is correct; we've seen in the past that research failed to find how medication affects women in specific ways, because that research was based on the premise that people are largely the same, and thus failed to specifically test the effects on each gender individually.

The sentence people quote out of context is, by itself, confusing and weird, and thus should not have been written that way. But in context, it's obvious what the writer intended to convey, and the intent is in no way anti-scientific.

I tend to agree, and go even further. The idea of averages and normal distribution means are grossly over-used in medicine and social discourse. They can sometimes be useful for population level discussions, but rarely personal healthcare or decision making.

Medicine and public policy is plagued by advice and recommendations for the average person, but the average person does not exist. 50% will be above average, and 50% will be below.

You are adding nuance to the underlying concept and failing to see how the wielders of the concept don't have that nuance.

Take BMI; first, i've seen arguments against BMI using the "there is no baseline normal" argument just like the original statement you quoted. Second, i've seen arguments that BMI as a concept is just invalid and rationales / facts that lend credence to the concept of BMI are somehow invalid. Finally, there's the inevitable ad hominem: it must be bigots who use the phrase BMI.

Her main point was absolutely defensible. Making embarrassingly false statements should never have gotten past the editors of a scientific publication.

Honestly, just to protect the author who clearly did not have the background to be expected to get that statement entirely correct, which is truly fine. But not fine for the publication.

If they are science communicators and they are writing things that can be explained reasonably easily in such confusing and weird ways, shouldn't they be fired?

> that health research often assumes that there is one average, representative person, and everybody else is clustered around that person in a normal distribution.

But complex clustering isn’t more or less true than the normal distribution in general, it just depends what you’re talking about.

That’s why railing against “the so-called normal distribution” comes across as inappropriate for a serious publication, it is suspiciously lacking nuance. Then one wonders how/why the nuance has gone missing. Politics masquerading as empiricism is an especially gross bait and switch.