Academia Has a Fraud Problem

Academia Has a Fraud Problem

Former Harvard President Claudine Gay is not an isolated example. There are plenty more.

Peter Boghossian writes at Substack:

Why Is Academia A Fraud Factory?

Academia is a fraud factory. Last year, 10,000 research papers were retracted—and those are just the ones that got caught. Entire lines of literature are fabricated out of whole cloth. Plagiarism is rampant. Universities are protecting and hiding fraud—they’re keeping serial plagiarists on the payroll. They don’t even fire Pretendians (people pretending to be Native Americans who hold positions of authority), despite their lip service, land acknowledgments, and ostensible deference to Native Americans’ lived experiences.

A curious person might wonder: Why? How could this happen? Why would anyone hide corruption or deny it or look the other way—especially when it undermines the legitimacy of their disciplines and the academy itself?

There are plenty of reasons. Here are a few:

• Ideology. Many academics don’t see research as a way to discover facts about an objectively knowable world. Instead, they view research as a tool to create the world they want—a world that’s just, fair, equitable, and free of oppression. Their goal isn’t to uncover the truth; it’s to craft a narrative that aligns with their vision of justice. To make this happen, they describe how they think things should be and cherry-pick methods to support those conclusions (Action Research).

When this mindset takes over, research goals shift. It’s no longer about trying to falsify claims; research is about verifying narratives to fit preexisting beliefs of how the world should operate.

• Career Advancement. Not all fraud is ideological—sometimes it’s just about climbing the ladder. This kind of corruption is especially common in the soft and hard sciences, where data fabrication boosts publication records, improves reputations, and increases grant money. Academic fraud, by its nature, is difficult to discover. If I had to guess, I’d estimate that around 15% of papers are flat-out fraudulent (data fabrication), and another 25% are less obvious but still bogus (e.g., p-hacking). Although these estimates could be low given the replication crises in various fields.

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