With the skyrocketing number of papers published in the 20th and 21st centuries, a major reservation academics have about the scholarly publication system is one of too many papers being published. On one hand, it is harder to keep up with the output and find the papers that are worth reading due to the relatively narrow focus each researcher has compared to all the topics out there. On another, proliferation of low-quality papers that tend to be published in predatory or near-predatory journals.
One vector here is the ‘more papers equals more citations, equals more funding’ system still in effect at many universities. Thankfully though, it is in decline after universities realized how easy it is to game the citation system and H-index. Many have or are in the process of implementing the narrative and other context criteria over publication quantity as the main decision factors.
Is more knowledge and research results a bad thing? No, even if it is applied research. If they are well attributed with tags, a few clicks take care of filtering out what you are not interested in. Are low-quality papers a problem? They benefit mostly the rogue publishers. For authors, they mostly do not lead to much in the long run. The minimum quality bar is thus a useful one and easily implemented.
Ruling out the outlying predatory publishers, what causes the heaps of papers scholars are not interested in? It is easy to blame publishers at large, but looking at the root of the problem, it is the combination of the university incentives and funding system. A publication is an aftermath of the work done.
Every single incremental study or improvement of any technology done by a researcher, or an engineer, is funded by a university, research institute, or company. Therefore it is the funders who are at the origin of the flood of marginally cited papers.
Globally it is nearly impossible to establish a system to prevent that. But the consequences of unrestrained publishing are felt most by those relying on the system every day at work - the researchers. For example, first-year graduate students doing a review of the state of the art can end up with a thousand papers to read. Which is overwhelming, to say the least.
Although AI tools are already able to condense papers into an informative paragraph speeding the process up, the long-term solution might require the involvement of all the players in the ecosystem. There will not be less publications any time soon. More developing countries are pouring money into new research bodies every day.
A way to go about the issue of finding the papers that are interesting for you may be to keep names of people worth following and a record of DOIs of papers that one considers important. Share it with colleagues and collaborators, and update it as one goes. Many likely do that already. There is no need to shield oneself from anything but distill out papers that are relevant based on the pool of well-cited authors and their collaborators/students. Since the ‘hidden genius paper’ that changes everything is statistically unlikely, there is no need to worry about the universe of all other papers.
How would you go about solving the problem of too many papers? Let us know in the comments.
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