Science is undergoing a wrenching evolutionary change. In fact, most of what we consider to be carried out in the name of science is dubious at best

Paradigm Wars

By Max Borders
How human networks bring down science hierarchies

Since I wrote the following, circumstances have been such that we are now clearly in a war of method paradigms. Let’s call one paradigm Science Hierarchies and the other Science Networks. As you’re reading this, reflect on the dogmas of COVID and public health. Reflect on the dogmas of climate science. Just think about how truth-seekers operating in information networks are increasingly able to outperform well-paid experts anointed by bureaucrats. And believe that it is a war. The censorship campaigns let us know.

Science is undergoing a wrenching evolutionary change.

In fact, most of what we consider to be carried out in the name of science is dubious at best, flat wrong at worst. It appears we’re putting too much faith in science — particularly the kind of science that relies on reproducibility.

In a University of Virginia meta-study ([link removed]) , half of 100 psychology study results could not be reproduced.

Experts making social science prognostications turned out to be mostly wrong, according to political science writer Philip Tetlock’s decades-long review ([link removed]) of expert forecasts.

But there is perhaps no more egregious example of bad expert advice than in the area of health and nutrition. As I wrote for Future Frontiers ([link removed]) :

For most of our lives, we’ve been taught some variation on the food pyramid. The advice? Eat mostly breads and cereals, then fruits and vegetables, and very little fat and protein. Do so and you’ll be thinner and healthier. Animal fat and butter were considered unhealthy. Certain carbohydrate-rich foods were good for you as long as they were whole grain. Most of us anchored our understanding about food to that idea.

“Measures used to lower the plasma lipids in patients with hyperlipidemia will lead to reductions in new events of coronary heart disease,” said the National Institutes of Health (NIH) in 1971. (“How Networks Bring Down Experts (The Paleo Example),” March 12, 2015)

The so-called “lipid theory” had the support of the US surgeon general. Doctors everywhere fell in line behind the advice. Saturated fats like butter and bacon became public enemy number one. People flocked to the supermarket to buy up “heart healthy” margarines.

And yet, Americans were getting fatter.

But early in the 21st century something interesting happened: people began to go against the grain (no pun intended) and they started talking about their small experiments eating saturated fat. By 2010, the lipid hypothesis — not to mention the USDA food pyramid — was dead. Forty years of nutrition orthodoxy had been upended.

Now, of course, the experts are joining the chorus from the rear ([link removed]) .

The Problem Goes Deeper

But the problem doesn’t just affect the soft sciences, according to science writer Ron Bailey:

The Stanford statistician John Ioannidis sounded the alarm about our science crisis 10 years ago. “Most published research findings are false,” Ioannidis boldly declared in a seminal 2005 PLOS Medicine article ([link removed]) . What’s worse, he found that in most fields of research, including biomedicine, genetics, and epidemiology, the research community has been terrible at weeding out the shoddy work largely due to perfunctory peer review and a paucity of attempts at experimental replication.

Richard Horton of the Lancet writes ([link removed]) , “The case against science is straightforward: much of the scientific literature, perhaps half, may simply be untrue.” And according to Julia Belluz and Steven Hoffman, writing in Vox ([link removed]) ,

Another review found that ([link removed]) researchers at Amgen were unable to reproduce 89 percent of landmark cancer research findings for potential drug targets. (The problem even inspired a satirical publication called the Journal of Irreproducible Results.)

Contrast the progress of science in these areas with that of applied sciences such as computer science and engineering, where more market feedback mechanisms are in place. It’s the difference between Moore’s Law and Murphy’s Law.

So what’s happening?
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Read the rest of this article and others like it on our website ([link removed]) .

Max Borders is Senior Advisor to The Advocates, you can read more from him at Underthrow ([link removed]) .

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