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Comment by candiodari | Hacker News Reader

You do realize there is a million negative results for every one positive result? This is equally easy to game, maybe easier.

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Yes, and knowing what's been tried and what has failed is important.

I think what's being pointed out is that "researchers" could pump out hundreds of easy to test negatives every day if a negative result was just as incentivised.

I do agree though, negatives are just as important when the intent is to prove/disprove a meaningful hypothosis.

A negative result won't make a career. I don't think there's much danger when requiring negative results going onto a repository of over incentivising negative results. You can't mandate Nature or Cell publishes negative results.

we tried using 0.1 mL, it didn't work

we tried using 0.11 mL, it didn't work

we tried using 0.12 mL, it didn't work

we tried using 0.13 mL, it didn't work

If someone really tested those hypotheses, let them publish. I doubt they'll get funding so it'll be on their own dime. In practice people do run experiments like that, but they only publish the 1/4 trials that is successful.

Look to physics for how negative results should be published. There typically has to be reason to suspect some dosage range should work, in which case that sequence of studies you describe would be perfectly valid if it's within that range.

    we tried using 0.10 mL, it didn't work
    we tried using 0.11 mL, it didn't work
    we tried using 0.13 mL, it didn't work
    we tried using 0.15 mL, it didn't work
    we tried using 0.17 mL, it didn't work
    we tried using 0.16 mL, it didn't work
    we tried using 0.18 mL, it didn't work
    we tried using 0.20 mL, it didn't work
    we tried using 0.14 mL, it didn't work
    we tried using 0.12 mL, it worked so we published

Do you want to know the ones that "didn't work" existed? Or are you happy with just the one that "worked" being written up in isolation?

i don’t want to know about each test that didn’t work as a separate publication, that’s for sure!

That's true, we would need a way to collect this data so it's easily seen as part of a whole.

E.g. if you search for eggs and cholesterol you should find all studies with their summarized results on whether eggs are ok or not for your cholesterol, grouped by researcher, so if somebody does 200 studies to find the one positive it's instantly visible.

You would read a meta-study that summarizes those tests - especially because they might potentially made by different labs, and the fact that one of them worked might be actual a real effect caused by some other difference in the experiment.

Especially for small effect size and suppressing what didn't work, this is one obvious way of many to perform p-hacking for publication acceptance.

https://en.wikipedia.org/wiki/Replication_crisis

Why would someone want to game a negative result? Nobody ever becomes famous for saying my approach doesn't work. (As long as science is open, to make sure there is actually good work done by researchers before reaching this neg result.)

To have their name on a publication, which is a currency in the academic world.

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