As a science writer, I’ve been reading scientific papers for 30 years. I’d guess that I’ve read tens of thousands of them, in search of new advances to write about, or to do background research for stories. While I’m not a scientist myself, I’ve gotten pretty comfortable navigating around them.
One lesson I’ve learned is that it can take work to piece together the story underlying a paper. If I call scientists and simply ask them to tell me about what they’ve done, they can offer me a riveting narrative of intellectual exploration. But on the page, we readers have to assemble the story for ourselves.
Part of the problem may be that many scientists don’t get much training in writing. As a result, it can be hard to figure out precisely what question a paper is tackling, how the results answer it and why any of it really matters.
The demands of peer review — satisfying the demands of several different experts — can also make papers even more of a chore to read. Journals can make matters worse by requiring scientists to chop up their papers in chunks, some of which are exiled into a supplementary file. Reading a paper can be like reading a novel and realizing only at the end that Chapters 14, 30, and 41 were published separately.
The coronavirus pandemic now presents an extra challenge: There are far more papers than anyone could ever read. If you use a tool like Google Scholar, you may be able to zero in on some of the papers that are already getting cited by other scientists. They can provide the outlines of the past few months of scientific history — the isolation of the coronavirus, for example, the sequencing of its genome, the discovery that it spreads quickly from person to person even before symptoms emerge. Papers like these will be cited by generations of scientists yet to be born.
Most won’t, though. When you read through a scientific paper, it’s important to maintain a healthy skepticism. The ongoing flood of papers that have yet to be peer-reviewed — known as preprints — includes a lot of weak research and misleading claims. Some are withdrawn by the authors. Many will never make it into a journal. But some of them are earning sensational headlines before burning out in obscurity.
In April, for example, a team of Stanford researchers published a preprint in which they asserted that the fatality rate of Covid-19 was far lower than other experts estimated. When Andrew Gelman, a Columbia University statistician, read their preprint, he was so angry he publicly demanded an apology.