3 ms·
there are a lot of "bad science" problems and people tend to get them mixed up. Here's a list of all the things I can think of, roughly ordered by my opinion o
by throw18376 3y ago
there are a lot of "bad science" problems and people tend to get them mixed up.
Here's a list of all the things I can think of, roughly ordered by my opinion of seriousness:
1. Fraudulent data in real publications in real journals, even sometimes the most prestigious journals like Science, Nature, Cell. (cases in article are this situation.) Worst of all is when it has a real impact on policy, or leads to bad investment in a new technology that can't work.
2. P-hacking, questionable research practices, etc. without fraud, by "legitimate" academics. This happens everywhere but seems to be a bigger problem in social sciences especially branches of psychology. Real-world impact has been less severe but does cause problems and wasted money sometimes. The worst impact is probably that it causes some young researchers to waste their careers on dead-end lines of research.
3. Really badly done studies to legitimate dubious supplements. Subcase of 2. I actually rate these as less severe, because the average consumer of dubious supplements is not reading these pointless studies, and supplements are basically unregulated, so I don't think getting rid of these studies would make much difference.
4. Completely fake garbage papers in paper mill journals. Not just fake data but outright total nonsense. These are ignored by most scientists, so less severe, but are a concern for the people who fund scientists, and they can cause real trouble if they end up in a meta-analysis.
I only write this list because so much of the discussion of fraud and bad research seems to conflate all of them together. But they're all distinct.
I had mentally accepted p-hacking and paper mill garbage, but seeing Nobel-prize-winning labs publish photoshopped blots in top journals has shaken my faith in our scientific institutions far more.
- throwawayqqq11 3y ago5. HARKing: "Hypothesis after results known" is also a problem to produce even "legitimate" papers by discarding the original hypothesis after negative findings and come up with a new one that fits the data. Its similar to p-hacking and also skews science into "promising" dead-ends. > but seeing Nobel-prize-winning labs publish photoshopped blots And they were caught because they edited poorly which could be detected automatically or by human eyes. Think about well versed image manipulators or generative AI... I think this erosion of trust is the worst, AI can produce and it will propably come.