alt Hacker NewsIt is useful to distinguish between "effective" scientific fraud, where some set of fraudulent papers are published that drive a discipline in an unproductive direction, and "administrative" scientific fraud, where individuals use pseudo-scientific measures (H-index, rankings, etc) to make allocation decisions (grants, tenure, etc). This article suggests that administrative scientific fraud has become more accessible, but it is very unclear whether this is having a major impact on science as it is practiced.
Non-scientists often seem to think that if a paper is published, it is likely to be true. Most practicing scientists are much more skeptical. When I read a that paper sounds interesting in a high impact journal, I am constantly trying to figure out whether I should believe it. If it goes against a vast amount of science (e.g. bacteria that use arsenic rather than phosphorus in their DNA), I don't believe it (and can think of lots of ways to show that it is wrong). In lower impact journals, papers make claims that are not very surprising, so if they are fraudulent in some way, I don't care.
Science has to be reproducible, but more importantly, it must be possible to build on a set of results to extend them. Some results are hard to reproduce because the methods are technically challenging. But if results cannot be extended, they have little effect. Science really is self-correcting, and correction happens faster for results that matter. Not all fraud has the same impact. Most fraud is unfortunate, and should be reduced, but has a short lived impact.
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>methods are technically challenging.
And finanacially too..
>Science really is self-correcting..
When economy allows it....
The distinction between effective and administrative fraud is useful and I think underappreciated. A lot of the conversation in these threads conflates the two, which makes it hard to reason about what actually needs fixing.
I want to push back a little on "science is self-correcting" though. It's true in the limit, but correction has a latency, and that latency has real costs. In fields like nutrition, psychology, or pharmacology, a fraudulent or deeply flawed result can shape clinical guidelines, public policy, and drug development pipelines for a decade or more before the correction lands. The people harmed during that window don't get made whole by the eventual retraction.
The comparison I keep coming back to is fault tolerance in distributed systems. You can build a system that's "eventually consistent" and still have it be practically broken if convergence takes too long or if bad state propagates faster than corrections do. The fraud networks described in TFA are basically an adversarial workload against a system (peer review) that was designed for a much lower rate of bad input. Saying the system self-corrects is accurate, but it's not the same as saying the system is healthy or that the current correction rate is adequate.
I think the practical question isn't whether science corrects itself in theory but whether the feedback loops are fast enough relative to the rate of fraud production, and right now the answer seems pretty clearly no.