The idealized (Science 1) / realpolitik (Science 2) dichotomy is both real and at first depressing. I also did a PhD in machine learning, and became quite disillusioned after seeing how the sausage was made, and how different the process is from how I had imagined it. At the same time -- engaging in 'game change' within Science 2 (perhaps not as a PhD, but after you have some security), is I think one of science's highest moral callings. The aim is not necessarily to inch Science 2 towards an impossible Science 1, but to help science to take itself more seriously (it really is a messy social process & there are ways that social process can work better or worse towards the public good -- itself a scientific question) -- and contribute towards science 2 becoming a better (and ideally better-at-self-improving) science 2.
I really think a lot of it falls on the funding agencies. While communication is key, there need to be some real questions answered. If a professor has 100 researchers under him and is churning out 2 papers per day how much is he really an expert? If his cousin is getting a PhD under him without doing the legwork shouldn't he be fired? Should we keep funding the same person excessively? It doesnt help that professors often rely on immigrant labor meaning that they can have a real choke hold over the lives of their staff. I really think there should be upper limits of what a professor can get away with, they need to be answerable to how tax payer money is being burned.
I think you’re pointing out a very important point; it seems like everyone pretends that you can ‘scale up’ scientific research, when it’s more like a service (that doesn’t scale). One problem might be that the people allocating the funding also stand to gain from pretending that they can “supervise” infinite amounts of research with no diminution of quality.
