- cross-posted to:
- science@beehaw.org
- cross-posted to:
- science@beehaw.org
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I think we need a fundamentally different approach to scientific publishing. It’s completely absurd that there’s probably a bunch of unintended replication studies because the research groups can’t know that their study has already been done.
And the expectation to actually read that avalanche of articles in even a niche subject is absolutely bonkers. 95% of articles are effectively write-only and will never have any impact whatsoever.
Agreed and I wonder if this isn’t a job that an AI might be able to help with: reading all the papers and at the very least, looking for key research subjects to compile for readers?
The site Semantic Scholar and Perplexity AI do a good job of using ML to help with that but the problem with scientific publishing is fundamental to it’s business model which needs to be uprooted to make modern science feasible
There’s also scite.ai Assistant
Didn’t know about that one, thanks!
Two organizations that are trying to make a difference:
The Journal of Trial and Error.
[The journal’s editor-in-chief was interviewed by Nature.]SURE: Series of Unsurprising Results in Economics
I found out about these today by the comments linked below:
So is Nature itself taking any steps to address the issue?
