I am 100% onboard for what openRxiv are planning and their vision for the future. I genuinely believe that this is the best path forwards

qed is a very interesting platform that is focussed on helping authors rather than being a quality control step which absolutely gets our support. This is a very exciting development and a big step towards expanding what feedback actually is. This did cause a lot of discussion on social media, with many positioning this as “review” instead of “feedback”. More in The Scientist.

Within days of the above news, Life Science Editors announced their own pilot with qed

Excellent resource for those just starting out

This is the sequel to the Strain on Scientific Publishing, which we covered on the podcast this year. Also covered here.

I’m not overly confident in this, although the direction change is needed it does feel somewhat toothless. I’m not particularly keen to see PRC explicitly mentioned - for reasons I’ve been vocal about enough. See this covered in Science which additional comments from others.

A brand new network for Open Science from Bonfire

With publishers profiting from licencing academic work for training AI this is something that may just come to a head next year.

This is enormously recommended!

The SCOPE framework is great (& surprising that DORA didn’t create it), if you’re not familiar with it already

I’m not a fan of yet more declarations, even if I do agree with the points within. We really need some coordinated effort from the many, many, existing declarations. We also need more community and advocacy organisations dedicated to working on the things these declarations keep…declaring. Change comes from effort.

“Acquiring the Karger journals will provide OUP with many more downstream transfer destinations, helping OUP to publish more of the articles that get rejected by their higher impact journals” - nothing more needs saying.

Yet more evidence in favour of a lottery system.

This is important evidence in how LLM use impacts learning

This has been compared (unfavourably) to HHMI’s funding strategy which is very interesting. Too much money does seem to be wasteful past a certain point.

A strong warning against relying on AI for peer review. This links very well with our best practices for preprint review services that use AI

a very humanities-focussed view that to my ears sounds like “preprint your work”

Provenance of records - from authors to data - is only going to become more important.

I struggle so much with the messaging from DeSci. In one post, peer review is essential, in another it shouldn’t be implicitly trusted (which doesn’t seem to fit with their broader comms actually). This is an org that seem focussed entirely on themselves, not doing good because it’s the right thing to do.