The short general version of my argument is: feedback > filtering

I would agree that preregistration is one way to make p-values more useful. They may be the best way to determine what the researcher originally intended to measure, but they're not the only way to know if that was the only thing a researcher measured. I've found asking questions often works.

If we're talking strictly about properly run RCTs, then I would agree, preregistration is close to free relatively speaking. But that's because a properly conducted RCT is such a big undertaking that most filtering initiatives are going to be relatively small. But RCTs aren't the only kind of study design out there. They are the gold-standard, yes, in that they have the greatest robustness, but their major drawback is that they're expensive to conduct properly relative to alternatives.

Science already has a pretty strong filter. Researchers need to spend 8 years (and usually much more than that) after high school working towards a PhD. They then have to decide that what they're doing is the best way to analyze a problem, or if they're still in grad school, their professor has to approve it, and they have to believe in it. Then two or more other people with PhDs who weren't involved in the research (editor and peer reviewer(s)) have to review what the researcher did, and come to the conclusion that the research was properly conducted. I don't view this as principally a filtering problem. Filtering can improve quality, but it also reduces the number of possible ways to conduct research. The end result of excessive filtering to me is that everybody ends up just doing RCTs for everything, which is extremely cost-inefficient, and leads to the problem of everybody chasing funding. If nobody with less than a million on their credit can conduct a study, I think that's a problem.