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My advisor was guilty of pushing me to do #2. "Your original hypothesis was disconfirmed? Find one that the data does not disconfirm and that'll lead to a foll

My advisor was guilty of pushing me to do #2. "Your original hypothesis was disconfirmed? Find one that the data does not disconfirm and that'll lead to a follow-up paper!" I dropped out of grad school because I assumed this was the norm.

Aperocky 7y ago
That may not be a wrong assumption.
unlinked_dll 7y ago
I feel like evidence dis-confirming a hypothesis is as valuable as confirming it. How many other grad students are going to attempt the same experiment/concept if null results are never published? I wish there was more praise for negative results in publication, because whether confirmed or not, the knowledge has value.
- bonoboTP 7y ago
  I think it's partially embarrassing when that happens. Hindsight is 20/20, and people will think it was obvious that it wouldn't be the way you expected. It's hard to argue that I had justification to think that novel intervention X would have an effect. It turns out it doesn't. Science is often very specialized, there's little chance others would have the very same idea. If it works out, the argumentation would have to be reversed: my idea was very novel and non-obvious but as I show it actually works, which no one would have guessed. The negative result story only works if the research community would have very strongly expected to see the effect, almost reversing the role of the null and the alternative.
  - thfuran 7y ago
    >The negative result story only works if the research community would have very strongly expected to see the effect, almost reversing the role of the null and the alternative Depends what you mean by "works". If you mean "is reasonably publishable in the current academic climate, then I agree. If you mean "has value", then I disagree.
    - bonoboTP 7y ago
      I mean "sufficiently impresses and/or catches the attention of others, especially other scientists".
- FabHK 7y ago
  > I feel like evidence dis-confirming a hypothesis is as valuable as confirming it. In particular as that would mitigate problem #3 above ("3. The third, and hardest to solve, problem is not factoring in the whole population of experiments.")

Aperocky 7y ago

That may not be a wrong assumption.

unlinked_dll 7y ago

I feel like evidence dis-confirming a hypothesis is as valuable as confirming it. How many other grad students are going to attempt the same experiment/concept if null results are never published? I wish there was more praise for negative results in publication, because whether confirmed or not, the knowledge has value.

bonoboTP 7y ago
I think it's partially embarrassing when that happens. Hindsight is 20/20, and people will think it was obvious that it wouldn't be the way you expected. It's hard to argue that I had justification to think that novel intervention X would have an effect. It turns out it doesn't. Science is often very specialized, there's little chance others would have the very same idea. If it works out, the argumentation would have to be reversed: my idea was very novel and non-obvious but as I show it actually works, which no one would have guessed. The negative result story only works if the research community would have very strongly expected to see the effect, almost reversing the role of the null and the alternative.
- thfuran 7y ago
  >The negative result story only works if the research community would have very strongly expected to see the effect, almost reversing the role of the null and the alternative Depends what you mean by "works". If you mean "is reasonably publishable in the current academic climate, then I agree. If you mean "has value", then I disagree.
  - bonoboTP 7y ago
    I mean "sufficiently impresses and/or catches the attention of others, especially other scientists".
FabHK 7y ago
> I feel like evidence dis-confirming a hypothesis is as valuable as confirming it. In particular as that would mitigate problem #3 above ("3. The third, and hardest to solve, problem is not factoring in the whole population of experiments.")