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I'm going to venture a wild guess and say this was before Goodhart's Law had it's way with that measure.
There's also the Mathew Effect, where people give credit to the most famous scientist just because it adds prestige. But can sometimes lead to people like Einstein getting solo credit for things he just briefly mentioned.
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Surely people are Goodhart'ing it, but either they're not very good at it yet or they're not trying very hard. The first two math department heads I looked up, at a large top-50 research university, were at [edit: approximately] 1.5 (for a relatively young guy, to be fair) and [edit: approximately] 2.5.
It's a metric that's somewhat designed to counter Goodharting of simpler "publication count" metrics. Divide your research up into "Least Publishable Unit" chunks, and you get more papers, but then the people who want to cite you end up only citing the most relevant chunk and killing your citations-per-paper.
[edit: the "Formatting help" link says you need to double up the ~ character on both sides of text to create a strikethrough, and the preview text rendered fine, but in the thread my pair of single tildes turned into a strikethrough...]
They are, though. The insanely skewed citation distribution is exactly what you'd expect from people figuring the optimal way to game the system. You're not getting anywhere by autistically focusing on your own reaserch, and hoping others will find it interesting enough to cite. You band together, and boost each other up. There's little individual glory in it for most people, which is why it looks like "they're not very good at it yet, or they're not trying very hard", but that's the best way for them to keep a stable job until they get their big break.
You see this on literally every social network, academia is no different, and the original statement about how much citations which kind of scientist will get, implicitly assumes people won't figure out how these systems work.
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