[cjbprime]

FWIW, I think you're actually being insufficiently pessimistic, and also the example effects I mentioned (publication bias and multiple hypotheses) exist in the zone where both are true -- the researchers observed something, and also the research claims are false.

Peer review is regularly completely inadequate. As an example, consider the amyloid hypothesis for Alzheimer's, which just this week was likely discovered to be actively fraudulent after nearly 20 years, thousands of papers, and thousands of scientists spending their entire research careers on it.

[dahart]

Again, while I think those things may be true sometimes, they aren’t the biggest problem we have in terms of science. And I feel like choosing to frame it the way you’re framing it is intentionally ignoring how often things go right, how often people are sincere and honest and competent and right.

We already know peer review isn’t perfect, but it’s also probably a lot better than the layman’s attempt to discriminate good science from bad. We don’t have a ton of data of how many papers are rejected either. But, one high profile example isn’t a particularly scientific way to establish that all of science is actively bad. It’s one bad example, and yes it’s awful that one case can have such wide ranging ramifications, but you’re downplaying the thousands of papers, and thousands of scientists who assumed the research was valid and did good faith work on top of it.

If anything, the practical reaction to your example should be that papers that go high profile need replication studies very quickly, not that we should assume as a lay person that all science is wrong.