I've read through this paper a couple times and started looking at its data.
https://www.nature.com/articles/s41586-023-06767-1
I'm predicting it now before I get further into reviewing this: this paper is wrong for all the reasons you'd suspect and isn't going to hold up to any scrutiny.
But managers and non-scientists everywhere are going to use it to reign in remote workers and say that it's "supported by the science".
After reviewing "Remote collaboration fuses fewer breakthrough ideas" more thoroughly, I believe it should be retracted. Here is a write-up of why this is the case:
I can summarize the problems with this paper as follows:
1. Confounded relationships between the explanatory and response variables that are not properly adjusted for,
2. Ill-defined response variable that is insufficiently explored and whose quantitative value does not match the interpretation the authors suggest,
3. Large amounts of data with NaNs that are not discussed,
4. A large dataset with most of its variance contained in < 1% of the overall data,
...
Like I say in the blog post, the most likely explanation for the observations the authors make it Berkson's paradox:
https://en.wikipedia.org/wiki/Berkson's_paradox
The authors do not adjust for the web of confounding relationships that exist in their data, the most important relating to publication year, time since publication, and the COVID-19 pandemic.
Now I feel some sense of professional obligation to submit a "letter of concern" to the journal, but I can't find any links to do this directly.
It seems like I'm supposed to email Nature's main address to kick start the process. Does anyone have a better idea about how to do this?
@jrhawley When I was involved in something like this back in 2009, we submitted it as a "brief communication arising", a category that I think is now "matters arising":
@bstacey That was the tip I needed, thank you! I found the page:
https://www.nature.com/nature/editorial-policies/correction-and-retraction-policy
@jrhawley thanks so much for this!! I think funding is an underdiscussed confounding factor.
IMHO: Funding is highly concentrated to a few rich universities which produce some great research, while poorer academics need to take any collaborator they can get leading to more geographic dispersion.
@PhilippBayer Right, me too. I don't study productivity and the "economics of science", but from all the PIs I've talked to about running their labs, funding is the thing that PIs spend most of their time working on because it so drastically impacts the type of research they are able to do in their labs.
How can that not affect the types of papers you can publish and how widely they'll be read/cited? How is that not an important factor in how local/remote your projects and collaborations are?
James Hawley, PhD
Blake C. Stacey
Philipp Bayer