[xab31]

Seconded. I work as a data analyst in medical research (bioinformatics postdoc). I am often introduced as a statistician, even though I'm not, because I can do a bit more than a t-test.

The situation in research is exactly as you describe -- we are figureheads who are put into place and highly pressured to confirm whatever hypothesis a PI wants for their latest grant or paper. They would never ask us to commit fraud, only perhaps to "double check" an analysis 10 times until it shows what they want to see.

If I were working for a company, this would at least be understandable, as companies don't even have a theoretical commitment to truth and scientific integrity, and there are no real consequences to a faulty analysis.

But it is immensely galling to see in research. Here we are, paid by the public to supposedly pursue truth and improve human health, and instead the job is to constantly be finding ways to avoid fraud and fabrication without pissing off the collaborator. The result is, as you say, useless analyses if the analyst is honest, and fabrications if they are not.

There is absolutely no doubt in my mind that this is one of the key reasons the ROI on science has declined drastically in the last few decades. It makes me laugh bitterly every time I see (increasingly frequently) political exhortations for plebeians to "trust the science".