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Overt fraud is rare, but sometimes the line of fraud is worryingly thin. Sure, making up data is fraud, but what about stopping your experiment early? Discarding some perfectly good data points? Tweaking your model until it just falls below p=0.05? These are all real things that are depressingly common in real studies published in prestigious journals. Sketchy correction factors, unsound data collection methodologies, baffling experimental design, the list goes on and on.

Something like a third of all published studies fail to replicate in the worst offending fields, and even more fail to replicate at the original effect size or greater. The incentive structure of the entire institution is screwed. Pessimism is warranted here, if you open a journal you should keep in mind that for most fields there’s a double-digit chance that what you’re reading will fail to replicate at all and even more that it’ll fail to replicate at the same of greater effect size.