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Ask HN: Could we create and scale a low-/no-cost scientific publishing platform?

6 points by ozb ↗ HN
The modern scientific publishing industry charges seemingly exorbitant subscription (or author) fees, given its reliance on unpaid academics for not only the research itself, but also editors, board members, and peer reviewers. The Journal of Machine Learning Research seems to provide evidence that this service can be provided for a fraction of the cost (<$10/article) at least in some circumstances; on the other hand, the non-profit PLOS network still charges $1339/article for open-access publication. Could we do better, at least for some larger segment of the market than is currently served by no-fee open-access journals? What services would have to be provided? How much would that actually cost, in money, volunteer hours, or compute resources?

3 comments

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trinovantes
arXiv already exists

You're not paying for the infrastructure of getting published. You're paying for the prestige of getting published under the journal's name.

d--b
Yes scientific publishing is a total ripoff. University people don’t pay for reading articles, so they don’t do anything about the insane prices, and they care much more about publishing in some notorious journal than being paid for it. They hope to get career advancement from papers.

The problem is that it’s easy to setup a journal, but how to become a respected journal in the field is the hard part…

jnakayama
As you mention, the services can already be provided at a fraction of the cost. I think the key problem is the trust/reputation that established publishers provide. There is massive demand for "trusted publication space" and the price develops accordingly.

I've been thinking about how to remove trust from this process and haven't come up with anything good yet, although I desperately want to believe that it's possible...

I do think that a good solution would be able to disrupt the current system though, the current scientific performance metrics (citation count, H-index, etc.) are almost entirely based on "real-estate" in trusted publication space (i.e. they only factor in publications in established sources) and they are extremely prone to Goodhart's law, so they become less and less useful to navigate the literature.