[vharuck]

If I understand the parent commenter, here's a common example from population-level statistics like public health:

"State X saw a mortality rate last year that was statistically significantly higher than the national rate. We should focus our intervention there."

The null hypothesis is that the risks of death are exactly the same in the state vs the nation. That may work with experimental sample sizes, but at the population level you'll often have massive sample sizes. A statistically significant difference is not interesting by itself. It's just the first hurdle to jump before even discussing the importance of the difference. But I've seen publications (especially data reports with sprinklings of discussion) focus entirely on statistical significant differences in narrative next to tables.

This isn't P-hacking an experiment, but it is abusing and misunderstanding statistical significance to make decisions.