It’s not exactly like the classic tragedy of the commons, where the commons collapses because everyone is trying to use it in their own interest, without coordination and regulation.
The tragedy of the COVID science-communications commons happens precisely because individual scientists and teams are contributing to the commons furiously but without coordination, in hopes that their contribution will advance our common understanding.
This is how science has worked for decades. It usually works out OK, because we have filtering authorities between us and the research. Doctors, for instance, to put the latest health studies into context for our situations.
But without the CDC and the National Academies being allowed to play their roles of interpreting COVID science for the public and policymakers, citizens and journalists and Science Twitter are adjudicating the science and data on the fly. This iterative science without context can easily lead to “knowledge” that flows from one’s own identity, not the body of knowledge.
Example: Emily Oster (whose COVID Explained reference resource and ParentData newsletter I admire as shining examples of filtering scientific authority) writes for The Atlantic about new data she and other researchers have gathered on COVID infection in reopened schools.
The findings: Almost 200,000 students in schools across 47 states show an infection rate of 0.13 percent among students and 0.24 percent among staff. That’s much lower, Oster says, than the rates of infection authorities feared this summer when reopening was discussed. “Even in high-risk areas of the country, the student rates were well under half a percent,” she writes.
Oster’s ultimate argument: While the risk from reopened schools will never be zero, by not reopening, we are also putting students at risk from school closures.
How might this data and argument be received in the current COVID science-communications commons?
Since Oster doesn’t give us guidance on the range of opening regimens used across those 47 states and 200,000 students, the “reopen schools now!” crowd will seize on this data to reopen schools now, regardless of how it’s done. (Do we know yet if/how reopening approaches matter? Is it responsible to issue data like this without that guidance?)
Others — COVID skeptics, let’s call them — might seize on the data to say: See, kids were supposed to be spreading it like wildfire, and they’re not. Why doesn’t this apply to other situations? As Oster notes, NY Governor Andrew Cuomo plans to close schools in COVID hotspots but not businesses as “mass spreaders.”
Some of you might remember that I wrote last year about grimpact, the concept that some research (e.g., the Lancet study linking the MMR vaccine to autism) has a contagious negative impact that ordinary research checks and balances can’t control.
Yesterday I interviewed one of the authors of a forthcoming paper on grimpact, Gemma Derrick, for an episode of my soon-to-launch podcast. Derrick reminded me that, while grimpact might start with a single study, its impacts are usually so wide ranging and complex that grimpact is a systems failure.
Resolved: We are in a similar situation with the pandemic and COVID research. Even well-intentioned releases of findings such as Oster’s risk uptake in all sorts of narratives contrary to researchers’ intentions. Unless researchers are exceedingly careful to outline not just their findings but how they should be interpreted by policymakers and the public, those findings are liable to catalyze grimpact.
Years ago Dan Kahan reframed the social polarization around a growing number of scientific questions — the validity of climate change, the safety of GMOs and vaccines — as a question of identity rather than science illiteracy or mass manipulation by moneyed interests.
It’s actually quite rational for people to conform to the dominant positions in their communities or cultural groups, he argued, rather than those of some distant scientific expert. This “conflict between knowing what is known and being who we are,” Kahan said, increasingly defines the science-communications environment.
Insisting on “what is known” in the iterative, study sense without contextualizing those findings in the “what is known” aggregate sense risks our knowledge being who we are, we what prefer to see, rather than what is.