My name's Neil, and I'm helping a group of scientists and physicians publish visual summaries of the latest COVID-19 research at https://www.researchexplained.org
Our goal is to stop the spread of misinformation by making it easy for people to understand the latest scientific research without being a subject matter expert.
It's difficult to determine whether a news headline is really supported by the source paper. The study could have faulty methodology or the news source could misrepresent the conclusions drawn by the researchers. While the scientific community relies on peer reviews to promote high quality papers, the general public is not qualified to review every paper, both due to lack of context and time. Instead, they rely on summaries from mainstream media sources, who tend to report on papers before they have passed the necessary peer review process. This creates a gap between when a paper is posted and when it is vetted and accepted by the community.
While this has always been an issue, the problem is more dangerous right now. With the ongoing pandemic, preprint studies are getting a lot of media attention without proper explanation of the caveats that come with that (no peer review, preliminary data, etc).
To combat this, we are creating objective summaries of the quantitative facts presented in a paper, along with a rating of the media's coverage to highlight any issues. There's been a fair bit of discussion around COVID-19 studies on HN lately, so I'm curious to hear what you all think of this approach! We just started, so only have 3 explanations published so far, but will be publishing 1-2 per week. This is a purely volunteer-driven effort that we're doing on the side to try to help how we can.
The idea was partially inspired by Distill (https://distill.pub), which is an excellent ML publication.