There are some questions in academic publishing that sound accusatory even when they are not meant that way. This is one of them: how can anyone publish more than one paper a day?
Publication counts are blunt instruments. They tell us something has been indexed, but they do not tell us exactly how much work an individual did, what kind of contribution they made, how the collaboration was organised, or whether the record reflects writing, supervision, analysis, funding, infrastructure, editing, or something else entirely.
Still, when the numbers become very high, the question is worth asking. Not because high productivity is automatically suspicious, but because very high productivity forces us to ask what we are actually counting.
The starting point
I recently looked at a Scopus extract taken on 6 July 2026. At that point, 187 calendar days of the year had passed. If weekends are excluded, there had been 133 weekdays.
The extract identified authors who had published in 2026 and had authored at least 133 Scopus indexed papers records during this year. That is, these were authors whose publication count was equivalent to publishing more than one publication per working day. Some had more than 187 publications, which means they published more than one article per calendar day, so far, in 2026.
The highest count in the extract was 423. That is about 2.26 publications per calendar day, or around 3.18 publications per weekday. Those numbers invite reflection.
A necessary caveat
This is not an allegation about any individual author. It is not a claim that anyone has done anything wrong, nor is it an attempt to shame named researchers. I am deliberately not naming individuals, because the issue is not primarily about people. It is about systems.
There are many possible explanations for very high publication counts. It may be entirely legitimate or reflect disciplinary norms. It might be that it reflects senior authorship in large research groups or the way databases index material. Book chapters, conference papers, letters, reviews, editorials, corrections, or records that are added in batches may also skew the results of the search.
That is precisely why the question is interesting. A raw publication count looks simple but once we examine it closely, it becomes much less so.
Not everything counted is a journal article
One important point is that the Scopus export was not just journal articles. After removing duplicate records, there were 3,116 unique Scopus records in the dataset. Of these, 2,441 were articles (about 78%).
The remaining records included 337 book chapters, 208 reviews, 43 letters, 35 conference papers, 24 errata, 19 editorials and a small number of other document types. That does not make the counts invalid, but it does make them more complicated.
If we say someone has “published 200 papers”, many would hear “200 research articles”. But databases may be counting a wider range of outputs. A review is not the same as an original research article. A book chapter is not the same as a journal paper. An erratum is certainly not the same kind of scholarly contribution as a full empirical study.
This distinction matters because publication counts are often used casually in appointments, promotions, rankings and reputational claims. The headline numbers is often not put into context with the underlying data.
Some records may arrive in clusters
The book chapter data is especially revealing. A large proportion of the book chapters in the extract came from a small number of sources, including book series and edited volumes. This suggests that some publication counts may rise sharply because a volume or set of chapters has been indexed together, rather than because an author has produced a new paper every day.
That is not a criticism. Edited collections, book series and conference-related outputs are a legitimate part of the scholarly record. However, they behave differently from individually submitted journal articles spread across a year.
This is one reason why publication velocity can be misleading. The database records may appear on a timeline, but the work behind them may have taken place over months or years. What looks like daily productivity may partly be the result of indexing patterns.
Authorship position tells another story
A further issue is author position. In the Scopus extract, the selected authors were rarely first authors. A rough analysis of author position suggested that only about 1.5% of the selected author appearances were first-author positions. Around 60% were middle-author positions, and about 38% were last-author positions.
This must be interpreted with care. In some fields, first author usually signals the person who did most of the work. In others, author order is alphabetical. In some disciplines, the last author may be the senior scholar, principal investigator or laboratory head. In large collaborations, author position may not carry the same meaning that it does in a two-author paper.
Even with those caveats, the pattern matters. These counts do not necessarily mean that one person is personally writing hundreds of papers in a few months. They may mean that some researchers are attached to many collaborative projects, sometimes as senior figures, supervisors, group leaders or contributors to a shared research infrastructure.
Again, this does not make the numbers wrong. It simply means they need interpretation.
Collaboration changes the meaning of productivity
The co-authorship data also helps explain what may be happening. Across the unique records, the average number of authors per article was just over eight. Only a very small number of articles were single-authored. Hundreds of records had ten or more authors, and some had a much larger number of authors.
This changes the meaning of the publication count. A single-authored paper and a paper with 50 authors are both counted as one full publication for each listed author. That is how many publication databases work. It is simple, convenient and easy to understand at first glance.
But it also creates a problem. If every author receives a full count for every publication, then raw publication totals can grow very quickly in highly collaborative settings. A researcher involved in many teams can accumulate a large number of publication records without necessarily making the same kind of contribution to each one.
That may be entirely appropriate. Collaboration is central to modern research. Complex problems often require large teams, specialised equipment, shared datasets, advanced methods and multiple institutions. But the more collaborative research becomes, the less useful simple publication counts become as measures of individual contribution.
Fractional counting gives a different picture
One way to think about this is fractional counting. Instead of giving every author one full publication credit, each publication is divided by the number of authors. A two-author paper gives each author half a paper, a ten-author paper gives each author one tenth, … and so on.
Fractional counting is not perfect. It can undervalue leadership, supervision, data ownership, conceptual contribution and the invisible labour that makes research possible. But it does show how different the picture can look when contribution is not treated as all-or-nothing.
In the dataset, the most prolific author had 382 unique records visible in the export. On a simple full-count basis, that is an extraordinary number. But when those records are counted fractionally by number of co-authors, the figure drops to around 59.6 publications. If only document type “article” is counted, the fractional total falls slightly further.
That is still highly productive. But it is no longer the same story as more than two publications every calendar day.
So what are we measuring?
This is the question that matters most. When we see a very high publication count, what are we measuring?
We may be measuring intellectual contribution, collaboration or lab leadership. Alternatively, we may be measuring access to large teams, large datasets or productive research networks.
In some cases, we may also be measuring authorship cultures that deserve closer scrutiny. If someone is listed on hundreds of papers, it is fair to ask what their contribution was. Authorship should not simply be a reward for status, funding, seniority or proximity to a project.
That concern should be directed at the systems and norms, not at public speculation about individuals. The more useful question is not “how did this person do it?” but “what would we need to know before interpreting this number responsibly?”
What would better transparency look like?
A better system would not rely so heavily on raw counts. It would distinguish between document types. It would make contribution statements more visible and searchable. It would allow readers, committees and evaluators to see whether an author contributed to conceptualisation, data collection, analysis, writing, supervision, funding acquisition, project administration or review.
It would also make author position easier to interpret across disciplines. In some fields, author order communicates a great deal. In others, it communicates very little. A publication list without disciplinary context is often a poor guide to contribution.
Most importantly, evaluation systems should stop treating volume as if it speaks for itself. A count is a starting point for questions, rather than the final answer.
Why this matters for universities
Universities often say they care about quality, integrity and contribution. Yet many internal and external systems still reward volume. We count publications because they are visible. We count them because they are available. We count them because they are easy to compare, even when the comparison is not very meaningful.
This creates a risk. If publication volume becomes a proxy for excellence, then people will naturally optimise for publication volume. Some will do so through genuine collaboration and exceptional productivity. Others may be tempted by honorary authorship, guest authorship, salami slicing, paper mills, special issue networks or other questionable practices.
That does not mean high-volume publishing is automatically problematic. It does means that high-volume publishing deserves scrutiny.
A better question
So, how can anyone publish more than one paper a day?
The answer is they probably don’t, at least not in the way the phrase suggests. They may be part of many teams, may hold senior roles across multiple projects, may be listed on outputs that were developed over long periods and indexed close together, they may be publishing different types of scholarly outputs, and may work in fields where large authorship teams are normal.
But the question is still valid because it exposes the weakness of simple metrics. A publication count looks objective, but it can hide enormous variation in contribution, role, effort and meaning.
Perhaps the real question is not whether someone can publish more than one paper a day. The real question is why our systems still treat that number as though it explains itself.
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About the Author
Professor Graham Kendall is Vice-Chancellor of GlobalNxt University, Malaysia, and an Emeritus Professor at the University of Nottingham. Over the past 25 years, he has published more than 300 peer-reviewed papers and has served as Editor-in-Chief and Associate Editor of several international journals. Through Publishing with Integrity, he explores the ethical, governance and practical challenges facing scholarly publishing, encouraging greater transparency, integrity and informed debate across the global research community.