Don't lump in actual fraud with incorrect data analysis. The former is far more serious than the latter. In a long career, most scientists (even very good ones) will probably make mistakes in data analysis. Very few will commit outright fraud.
I'm drawing attention to the irony inherent in both these cases. To wit, a study on dishonesty suffering from dishonesty, and a study on rigor suffering from lack of rigor.
And sure, mistakes in data analysis are entirely possible. But there are lines to be drawn, always. Ariely and Gino, and now Protzko, Krosnick and company are not in the category of reasonable and honest mistakes.
On the other hand, even something with widespread effects such as the mess Excel created for genetics papers is not something that most people would find as deliberate sabotage.
Like too much refined sugar, this is too much refined irony. What is going on?
1: https://www.theatlantic.com/science/archive/2023/08/gino-ari...