The journal Rhetoric Review published a resonant article “The Controversy behind the Controversies” ( https://doi.org/10.1080/02773945.2025.2484162 ), which explains why modern science is in a difficult situation. It is about two large-scale problems at once:
the spread of fake publications and the generation of a large number of scientific articles;
the inability of many honest studies to stand out among the sea of monotonous scientific articles.
Network editorial offices and business on scientific indicators
Every year, there are more and more scientific articles — and this is not always good news. Part of this growth is artificial: it is a consequence of the competition of the scientist’s indicators. For some, it is a sport. Some are under pressure from the ideas of their academic community, as in Kazakhstan. In Ukraine, higher education institutions also actively compete in rankings. Hence the need for a large number of publications.
One of the most famous cases is the withdrawal of over 11,000 articles by the well-known publishing house Wiley after discovering massive violations in Hindawi journals. But, as practice has shown, retraction does not produce a cleaning result: the databases now overlap with each other, so you can’t clean everything from the Internet.
According to estimates, in 2022 alone, more than 70 thousand fake publications could appear in scientific databases.
These are no longer exceptions — this is the scientific industry. And this is a modern reality.
Another problem in the world of high-quality scientific articles is that many existing journals have put online editorial offices under their control. Most of them are from Malaysia, Indonesia and similar countries.
Honest science that doesn’t work
Even worse: even honest research is often impossible to repeat. In psychology, biomedicine, sociology — a third of the results are simply not confirmed. The reason?
focus only on positive results;
suppressing negative or “inconvenient” data;
intentionally or accidentally adjusting statistics.
The statistical threshold “p < 0.05” has become a magic number: if the result passes, you can publish. This has led to phenomena such as:
p-hacking – testing everything in a row until something significant comes out
HARKing – coming up with a hypothesis after receiving the results
cherry-picking – choosing only “convenient” data
The American Statistical Association has already stated:
“Statistically significant” – don’t even use this phrase.
The system encourages quantity, not quality
When an author pays for publication, the main goal is not quality, but volume. This is beneficial for publishers who do not pay authors, but earn on each text.
One of the critical conclusions:
“Research is funded by the university → the scientist writes an article → the publishing house takes money for publication → the same university buys access back.” This is how the cycle of scientific publications looks like now.
The thing is that someone has to fund the achievements. Ideally, it should be universities. But, in economically weaker countries, it is the scientist himself who finances everything. He has to teach, finance his own research, and be in business so as not to lose the opportunity to live a decent life. And, a modern scientist, now, is almost a businessman. Which requires a lot of consulting, outsourcing, and lives in the modern monetary and marketing paradigm.
AI is a new player with two faces
With the advent of ChatGPT and other large language models, writing has become easier, but so has creating pseudoscience.
Today, there are no reliable ways to detect whether an article was written by artificial intelligence or a person.
Retractions do not save
Yes, there is a mechanism for withdrawing problematic articles (retraction). But it is slow and ineffective. Many fake publications continue to be cited even after retraction, forming a “polluted” scientific environment.
Journals under question?
More and more scientists are doubting: are traditional journals needed, which publish slowly, expensively and sometimes dishonestly?
The alternative is preprints, open source and data publications. Article depositories. But all systems can be hacked. That is, everything will repeat itself, even if the changes are global. Commercial structures are very adaptive. And while a scientist is an investor in himself and strives to be significant in the ratings, the situation will simply reproduce itself.
But this creates a new danger: without interpretation, data is not knowledge.
Databases are growing uncontrollably. Therefore, their quality is no longer able to be controlled by anyone.
Conclusion: Science as a search for truth is under threat
The authors of the article warn: we risk turning science into a stream of meaningless data, instead of leaving it a space for joint interpretation, doubts and dialogue.
Real science is not just data, but a meaningful understanding of data.
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