| ▲ | gcr 4 hours ago | |||||||||||||||||||
I'd personally like to see top conferences grow a "reproducibility" track. Each submission would be a short tech report that chooses some other paper to re-implement. Cap 'em at three pages, have a lightweight review process. Maybe there could be artifacts (git repositories, etc) that accompany each submission. This would especially help newer grad students learn how to begin to do this sort of research. Maybe doing enough reproductions could unlock incentives. Like if you do 5 reproductions than the AC would assign your next paper double the reviewers. Or, more invasively, maybe you can't submit to the conference until you complete some reproduction. | ||||||||||||||||||||
| ▲ | azan_ 3 hours ago | parent | next [-] | |||||||||||||||||||
The problem is that reproducing something is really, really hard! Even if something doesn't reproduce in one experiment, it might be due to slight changes in some variables we don't even think about. There are some ways to circumvent it (e.g. team that's being reproduced cooperating with reproducing team and agreeing on what variables are important for the experiemnt and which are not), but it's really hard. The solutions you propose will unfortunately incentivize bad reproductions and we might reject theories that are actually true because of that. I think that one of the best way to fight the crisis is to actually improve quality of science - articles where authors reject to share their data should be automatically rejected. We should also move towards requiring preregistration with strict protocols for almost all studies. | ||||||||||||||||||||
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| ▲ | dataflow 3 hours ago | parent | prev [-] | |||||||||||||||||||
Is it time for some sort of alternate degree to a PhD beyond a Master's? Showing, essentially, "this person can learn, implement, validate, and analyze the state of the art in this field"? | ||||||||||||||||||||
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