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It puzzles me that the most significant problem with open access receives little mention, in discussions on HN: it changes the incentives structure of publicati

by baghira 11y ago

It puzzles me that the most significant problem with open access receives little mention, in discussions on HN: it changes the incentives structure of publication, from one where the publisher has to please the ones buying the journal to one where the it has to please the people paying to submit articles. This is what makes the situation profoundly more complex compared to other application of copyright, say in the software industry, where clearly switching to an open source model doesn't change the incentives i.e. who assesses the quality of software. The long term effects on academia of switching to a model where the taxpayer gives money to scientists to pay for open access submssion of their research are hard to evaluate, and do no get enough though (imho). That clearly doesn't mean that there aren't bad journals that are not OA, nor that for the benefit of the public some sort of arrangement shouldn't be found for older research: I'm a big believer in "faster decaying" copyright in general, and mandating that all publications describing research that is publicly funded become OA after, say, 30 years, would help significantly.

sawwit 11y ago
> … it changes the incentives structure of publication, from one where the publisher has to please the ones buying the journal to one where the it has to please the people paying to submit articles. I always thought publishing will be free/payed by taxes in an open access world like on arXiv.org.
- baghira 11y ago
  Right, but in that case you lose completely the crucial gatekeeping function. Already now arxiv.org is full of papers with glaring technical and conceptual mistakes. Imagine what would happen if submissions to arxiv.org where they way one decides who to promote. At the cost of being a retrograde, I believe that this sort of things cannot be settled simply "the google way" i.e. 1. Count the citations. 2. Make a list. 3. Profit. You need to "force" people to review their papers, correct mistakes, and in a sense establish what is worth other people time. Journal editors and reviwers screw up all the time, no doubt, but the burden of proof is on those arguing that "drop it on arxiv, let the review count do the scoring" is a better system. Also, once you drag the taxpayer in, you have to figure out who polices the archive, least it becomes crackpot central: should they be elected? Should they be appointed? Who should pay them? What about conflicts of interest?
  - exgrv 11y ago
    Members of the editorial board of scientific journals are not paid. So nothing prevents having a completely free and open access journal, which is peer reviewed. As a matter of fact, such journals already exist in some fields (e.g. the Journal of Machine Learning Research[1], which is the best journal in machine learning). [1] https://en.wikipedia.org/wiki/Journal_of_Machine_Learning_Research https://en.wikipedia.org/wiki/Journal_of_Machine_Learning_Re...
    - baghira 11y ago
      Yes, but the editorial board is not the only cost component of a journal. I'm somewhat skeptical of how much the model in which "the scientists" do all the work of publishing a journal can scale, but I'd be glad to be proven wrong. I'll admit my comment was influenced by some proposed models (e.g. in the UK), arguing for the allocation of taxpayer resources to "buy" open access for research.
      - sawwit 11y ago
        > I'm somewhat skeptical of how much the model in which "the scientists" do all the work of publishing a journal can scale, but I'd be glad to be proven wrong. I'm quite optimistic. There are already strong explicit indicators for the worth of a publication. If a paper comes from a university, for example, you can likely already be assured that it's worth reading. If it has a name with good reputation on it, that's an even better piece of evidence. If a paper has interesting content, it will be shared in the community. Also, Google isn't just ranking by a explicit measures, but mostly by PageRank, i.e. a measure how how well a certain item is woven into the network of links (plus possibly hundreds of heuristics). PageRank could likely be applied to a publication system as well. In that case the network links could be co-authorships, associations with accredited universities, and perhaps other things. And let us not forget that the vast majority of researchers are actually truth seeking and concerned about the impact they make on the world. Things might become a little bit noisier, but at the same time the feedback-loops become shorter, as we're seeing it in the machine learning field.

by baghira 11y ago

sawwit 11y ago

> … it changes the incentives structure of publication, from one where the publisher has to please the ones buying the journal to one where the it has to please the people paying to submit articles. I always thought publishing will be free/payed by taxes in an open access world like on arXiv.org.

baghira 11y ago
Right, but in that case you lose completely the crucial gatekeeping function. Already now arxiv.org is full of papers with glaring technical and conceptual mistakes. Imagine what would happen if submissions to arxiv.org where they way one decides who to promote. At the cost of being a retrograde, I believe that this sort of things cannot be settled simply "the google way" i.e. 1. Count the citations. 2. Make a list. 3. Profit. You need to "force" people to review their papers, correct mistakes, and in a sense establish what is worth other people time. Journal editors and reviwers screw up all the time, no doubt, but the burden of proof is on those arguing that "drop it on arxiv, let the review count do the scoring" is a better system. Also, once you drag the taxpayer in, you have to figure out who polices the archive, least it becomes crackpot central: should they be elected? Should they be appointed? Who should pay them? What about conflicts of interest?
- exgrv 11y ago
  Members of the editorial board of scientific journals are not paid. So nothing prevents having a completely free and open access journal, which is peer reviewed. As a matter of fact, such journals already exist in some fields (e.g. the Journal of Machine Learning Research[1], which is the best journal in machine learning). [1] https://en.wikipedia.org/wiki/Journal_of_Machine_Learning_Research https://en.wikipedia.org/wiki/Journal_of_Machine_Learning_Re...
  - baghira 11y ago
    Yes, but the editorial board is not the only cost component of a journal. I'm somewhat skeptical of how much the model in which "the scientists" do all the work of publishing a journal can scale, but I'd be glad to be proven wrong. I'll admit my comment was influenced by some proposed models (e.g. in the UK), arguing for the allocation of taxpayer resources to "buy" open access for research.
    - sawwit 11y ago
      > I'm somewhat skeptical of how much the model in which "the scientists" do all the work of publishing a journal can scale, but I'd be glad to be proven wrong. I'm quite optimistic. There are already strong explicit indicators for the worth of a publication. If a paper comes from a university, for example, you can likely already be assured that it's worth reading. If it has a name with good reputation on it, that's an even better piece of evidence. If a paper has interesting content, it will be shared in the community. Also, Google isn't just ranking by a explicit measures, but mostly by PageRank, i.e. a measure how how well a certain item is woven into the network of links (plus possibly hundreds of heuristics). PageRank could likely be applied to a publication system as well. In that case the network links could be co-authorships, associations with accredited universities, and perhaps other things. And let us not forget that the vast majority of researchers are actually truth seeking and concerned about the impact they make on the world. Things might become a little bit noisier, but at the same time the feedback-loops become shorter, as we're seeing it in the machine learning field.