Aren't they equivalent in their potential to allow post-hoc data mining?

Whether it's a clinical trial, or a psychological study with n participants, or a look at how changes in x soil conditions affects the y tree. Anything where data samples are taken and statistically analyzed is prone to p-hacking and after-the-fact hypothesis changes.

This example happens to be for a narrow set of studies: clinical trials for cardiovascular drugs/supplements. The take away from that graph applies broadly.