On the other hand, if she hadn't wasted her time on this useless study she might have done more useful studies and her career would be better than it is right now. She might have gotten even better grants if she hadn't made this error, and maybe fewer other people would have gotten grants. Maybe those other people being more careful helped them rather than hurt them.
I don't see how speculating like this is very useful.
I'm saying the downside of making the mistake (for her) might be larger than the upside of making the mistake. I don't think that's obviously wrong.
But my real main point is that speculation of this kind (in either direction) isn't very productive.
It is easy to think over these lines in hindsight[1], but it is much harder to do it when there are no known mistakes. Obviously they had some plausible hypothesis, which predicted and explained results. The more strong result is, the better for hypothesis.
I mean it was possible and maybe wise to suspect bug because results are too good. But it is hard from a cognitive standpoint. She describes bug as hard to find even after she found that results do not reproduce. It was even more hard to find this bug when there were less reasons to believe that there is a bug.
I'm sorry but you seem to have skipped reading the main part of the article. The paper was not retracted:
"The editor and publisher were understanding and ultimately opted not to retract the paper but to instead publish a revised version of the article, linked to from the original paper, with the results section updated to reflect the true (opposite) results."
Maybe with a strong effect for every single subject a little more skepticism would have been warranted in the first place? Some manual spot checking if possible, or using a minimal independent implementation of the analysis code?
Who knows if she'd gotten her grant, her assistant professorship without the publication of this incorrect finding. Who knows who didn't get any of that because they were a bit too careful in their work.