How do you know if a finding in social science is, well, real? Students of science are taught not to take the results of a single study as the absolute truth. The rule of thumb is to seek out systematic reviews, or meta-analyses, which pull together lots of studies looking at the same question and weigh their rigor to come to a more fully supported conclusion. But can we trust all this meta-science? Positive, confirmatory findings often make their way into the published literature, while negative findings collect dust in file drawers.

Sometimes it seems surprising that science functions at all. In 2005, medical science was shaken by a paper with the provocative title "Why most published research findings are false."1 Written by John Ioannidis, a professor of medicine at Stanford University, it didn't actually show that any particular result was wrong. Instead, it showed that the statistics of reported positive findings was not consistent with how often one should expect to find them. As Ioannidis concluded more recently, "many published research findings are false or exaggerated, and an estimated 85 percent of research resources are wasted."2 It's likely that some researchers are consciously cherry-picking data to get their work published.

Every year the US government spends $5 billion on cancer research. And yet more than 8 million people still die every year from the disease--despite the frequent refrain that a cure is just around the corner. Scientists today are exploring more promising new technologies than ever before: whole-genome sequencing, liquid biopsies, mRNA vaccines, AI-powered imaging analysis. But that doesn't necessarily mean they're more promising. No number of flashy new disruptors can fix cancer research's real problem: much of its data can't be trusted, because it was never validated.