Purr-fect Citations: How a Cat Became the World’s Most Cited Academic
Meet Larry, the Scientific Cat
Larry — a fluffy, slightly overweight cat — has achieved what many postdocs or even professors only dream of: becoming the most cited “author” in his field. Obviously, Larry has never written a word or attended a conference. His main activities? Napping, demanding food, and scratching furnitures. Yet, there he is — the most cited author without lifting a paw.
How Did We Get Here? The h-index metrics
It all started with a researcher in mathematics — and Larry’s owner — who created a fake scientific name, Larry Richardson, for citation testing. By generating fake papers that auto-cited each other, uploading them to ResearchGate, and then deleting them (after they had already been indexed by Google Scholar), the citations and paper titles remained. The result? Larry Richardson’s h-index and citation count in Google Scholar skyrocketed.
For context, the h-index measures the number of papers (X) that have each been cited at least X times. For example, an h-index of 3 means having 3 papers with at least 3 citations each. If you build a pool of articles that cite each other in a closed loop, the h-index can climb quickly.
And yes — this is an actual metric used for recruitment, grant decisions, and promotions.
The h-index is supposed to:
- Balance quantity (number of papers) and quality (citations).
- Avoid overemphasis on one “blockbuster” paper.
But (because there is always a "but" in science);
- Depending on the database, the value may differ (Google Scholar usually gives higher h-index than Scopus or Web of Science, since it indexes more sources).
- It doesn’t account for authorship order or contribution (a first-author paper counts the same as being somewhere-lost-in-the-middle).
- It is biased by career length (early-career researchers naturally have lower h-indexes).
The Lesson Larry Taught Us About Academic Metrics
Larry’s case is a purr-fect (sorry, had to) example of the flaws in academic metrics like the h-index. Human scientists spend years writing grants, peer reviewing, presenting at conferences, publishing their work, and hoping the right peers cite them. Yet Larry’s story shows how easily one can manipulate h-index records through Google Scholar — without doing the work. And that is absolutely devastating.
Larry’s story exposes the absurdity (as also noted in the original paper linked at the end of this post): if a cat can “win” without doing the work, perhaps the rules need rewriting. Don’t you agree?
The Academy Journey Summarized In Numbers
Academic success is never just about numbers — it’s shaped by skill, persistence, collaboration, and luck. Metrics like the h-index try to capture achievement but often flatten it into something misleading.
Still, researchers can’t ignore them. Careers, funding, and recognition are tied to these scores, so we play the game even while doubting its fairness. That’s the irony: chasing a number we know doesn’t tell the whole story.
Again, Larry’s case puts it in perspective — if a cat can rise to the top by exploiting loopholes, without doing the actual work, perhaps it’s time we rethink how we measure scientific value.
Exclusive Interview with Larry Richardson! (just for fun)
This last part is just for the pleasure of writing without the pressure of increasing my h-index ;-D
Q: Larry, congratulations on your incredible academic success. What’s your secret?
Larry: “Rigorous daily routine: meow, nap, stretch, sunbathe.”
Q: Advice for early-career researchers?
Larry: “Be visible. Conferences, posters, networking — these matter as much as your publication list. But don’t neglect publishing regularly.”
Q: Thoughts on academic metrics?
Larry: “If I can beat the system, maybe the system is broken.”
Q: What’s next for you?
Larry: “Nap. Snacks?”
For more details about the case;
ScienceAdviser: Meet Larry, the world’s most highly cited cat | Science | AAAS
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