The jianghu has always harbored vice, but even vice has its "rules." When Zhao Gao pointed at a deer and called it a horse, he at least bothered to make the fake look convincing. Today, some published masterpieces in top journals can't even be bothered to change the pose of a dead mouse. Fraud is supposed to be a craft — yet some have turned it into assembly-line shoddy goods. This not only chills those who do honest research, but disgraces the entire "fraud industry" — even its professional pride is gone. If Grandmaster Zhao Gao knew, he would walk away in disgust.
🗡️ The Grandmaster's Legacy: Even Deception Requires Craftsmanship
Fraud has existed since antiquity. Zhao Gao's "calling a deer a horse" was power politics on the surface, but it contained a hidden doctrine of "passing off the fake as real": you must convince others, or it doesn't count. For millennia, this dark craft carried a twisted professional ethic — never release a fake that isn't convincing enough.
I have seen real "artisans" of fakery. A counterfeit Moutai team would polish molds repeatedly for a single hexagonal gift box, studying even the micro-textures of anti-counterfeit labels. Their motto was blunt: the fake must look more real than the real thing. Absurd as it sounds, there was a warped pride in it. They at least respected their "work" and the invisible rules of the trade.
Now look at today's academic jianghu. In some top-journal papers, the last digits of data dance in unison — 2, 3, 4, 8, 5 taking turns, as if the numbers were doing a square dance. Two groups of 13 data points, with eight identical and three matching to every decimal place. Over 200 values ending in nothing but 0 or 5, like a rock-paper-scissors game. Did reviewers truly not see it, or did they look the other way? Failing the most basic rule — "numbers should have variation" — this is no longer fraud; it is open mockery of fraud.
> Note: "Abnormal last-digit distribution" is a simple statistical check for data authenticity. Real experimental data, affected by measurement error and biological variation, should show roughly uniform or natural digit endings. When massive amounts of data cluster on a few endings, fabrication or template-based manipulation is highly likely. Such amateur mistakes should be caught by the first line of defense — the fact that they slip through suggests the gatekeepers are exhausted or numb.
🐭 The Mice's Silent Protest: What Does Identical Death Posture Reveal?
The most laughable part: mice that "died identically." In the same paper, two mice show exactly the same death posture, with even the background lighting and shadows looking copy-pasted. Did the mice agree to pose together before dying? Or did the fraudsters think "one died this way, so the other should too"? Not even bothering to "shoot another angle" — academic fraud has been reduced to a Ctrl+C, Ctrl+V children's game.
Imagine a true forger "artisan" facing mouse photos: he would adjust lighting, change poses, maybe add a few different hairs for "realism." Instead? Were the mice camera-shy, or were the fraudsters just lazy? This laziness insults not only the mice's remains but the IQ of the entire fraud industry.
> Note: Image duplication or high similarity is a high-risk signal in research misconduct detection. Modern tools (iThenticate, image-similarity algorithms) can catch this easily — but if even human reviewers turn a blind eye, the gatekeeping is effectively nonexistent. A genuine professional forger would at least avoid such an obvious blunder.
📊 Collective Data Cheating: From the "Busiest Five-Person Group" to Gresham's Law of Fraud
Even more absurd is the "busiest five-person group": across papers from provinces and cities everywhere, the same five names — Zhang Jiwei, Lin Guorui, Lin Wenshu, Lin Yanan, Jiang Yiyun — keep appearing. They can't even be bothered to invent new fake names, relentlessly shearing the same flock. What does that leave for those who genuinely take pains to craft fake names, fake affiliations, and fake CVs?
This is the classic cycle of "bad fraud driving out good fraud." The sloppier the fraud, the faster the output; the more carefully one polishes data and images, the more "inefficient" one appears. Over time, fraudsters with "professional pride" get marginalized, and the whole ecosystem's credibility collapses — until journals and experts start wondering: is this data genuinely fake, or fake-ly genuine?
🦁 The Art of Fraud in Jin Yong's Novels: Persians and Tian Boguang's Ranking Wisdom
Characters in Jin Yong's novels actually had more method to their deception. Zhao Min, inventing a ranking for the Persian Ming Cult envoys, declared: "Xie Xun, the Golden-Maned Lion King, ranks three thousand five hundred and ninth in the Central Plains Ming Cult." Precise, oddly specific, mixing odd and even — utterly convincing. Linghu Chong fooled Tian Boguang with: "Ranked second in the world fighting seated, eighty-ninth fighting standing." The numbers were coherent and self-consistent.
Compare that with certain papers today, where data looks like it passed through the same abacus, with no variation or logic. Even con artists in wuxia novels understand the art of storytelling better than some "National Excellent Young Scientists." What a cruel irony for the academic jianghu.
> Note: Through such details, Jin Yong was really writing about the art of the "believable lie" — a fake must have internal consistency and supporting details to fool experts. Once academic fraud abandons even this basic skill, it degrades from "deception" to "self-deception."
🛡️ Total Collapse of the Defenses: Experts, Journals, and Academic Committees
Experts, journals, and academic committees have long been the first line of defense maintaining the "order of fraud." They should catch amateur errors and keep shoddy fakes out of circulation. The reality: highly overlapping data groups, 200+ abnormal digit endings, copy-pasted mouse photos — works that should have been intercepted have appeared in top journals in broad daylight.
The cost of this collapsed defense is the trust breakdown of the entire academic ecosystem. Honest researchers are squeezed out by "counterfeit goods"; journal credibility is overdrawn; young scholars learn the wrong lesson — that fraud can be this casual.
💡 Restoring the "Rules of the Trade": Quality Audits and Lifetime Bans
The jianghu demands fairness. Proposals: establish a regularized "fraud quality audit mechanism" with automated plus human screening of digit distributions, image similarity, and data logical consistency. Have fraudsters watch films like *Project Gutenberg* to learn what "professionalism" means — even forgery should be done to perfection. Create a unified "academic fraud integrity archive," with accountability and lifetime bans for the obviously lazy and shoddy.
As Yu Zecheng lectured Li Ya in *Lurk*: "You claimed no one else could make a fake like this... Open your eyes and look at the world — a fake tape like this could be made by two nineteen-year-old White Russian kids!"
You people just don't understand the basic principles of fraud — even fakes need principles.
🌌 Conclusion: Stop Shaming the Grandmaster
Academic fraud was always an undercurrent; now even the undercurrent is filthy. Those who casually fabricate data, copy mouse photos, and reuse fake names are not only deceiving colleagues — they are insulting the history and dignity of an entire "industry." True artisans, righteous or villainous, all understand: if you can't make the fake look real, you don't deserve a place in the jianghu.
May the day come when fraudsters recover that warped sense of pride — at the very least, stop letting mice die so undignified a death, and stop letting the numbers dance in such perfect unison. Somewhere above, Grandmaster Zhao Gao may be waiting to see a real "passing off the fake as the real."
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References 1. Jin Yong, *The Heaven Sword and Dragon Saber* — Persian Ming Cult rankings and the fictional art of deception. 2. TV series *Lurk* (潜伏) — the dialogue between Yu Zecheng and Li Ya on the principles of fake recordings. 3. Film *Project Gutenberg* (无双) — on professional pride and detail control in forgery. 4. Compilation of exposés from the Gungun (耿同学) academic-misconduct series — analysis of data duplication and image anomalies in top-journal papers. 5. Sociological reflections on the "busiest five-person group" phenomenon — the industry crisis of "bad fraud driving out good fraud."