I'm a career scientist and here's why I suspect this won't take off:
(1) A lot of research is trash and not reproducible. Over the last 5 years I've found it's usually not even worth my time to read half the papers I read unless its in Nature or a top journal. Even then the ROI is minimal.
(2) It takes quite a bit of knowledge to appreciate and read a paper. In grad school, it took 4-6 hours of work to go through a paper. Do I really want to have a discussion on the 10,000 ft view of a paper? Probably not. Do I want to spend 4-6 hours really appreciating the nuances of a valid paper? Probably not.
(3) As alluded to by (1) and (2), most researchers (at least in my anecdotal experience) are spread so incredibly thin, as someone who would want to provide insight on some incredibly niche topic, I am already overbooked for my time between work and outside responsibilities.
I think you're going to find that the garden you're trying to grow doesn't have the adequate catalyst/buy-in. You might be better off creating a version where the paper is summarized by a GPT model and that 10,000 ft summary is discussed by the general public.
I think the argument is that it's not for career scientists.
I gave up wanting to get into academia once I found how awful the working conditions are. Now I'm in a more comfortable life, I'd love to have access (ie: visibility) on recent developments and research.
If the return isn't there for career scientists, and it takes them 4-6hrs to read a paper properly, then can non-specialists really get much out of the process?
May I hijack the topic and ask you a somewhat related question?
Given the understandably overpolluted with garbage world of scientific research, how would look for some studies with reasonable credibility?
It's my understanding that top journal or sorts sources are likely infused with money from large corporations pushing studies for their favour. At same time smaller sources are full of crap as you noticed.
Top journals have good research in them, they cannot be bought like that. The downside is that they get caught in the hype, and only publish articles likely to be more glossy.
The way to clean garbage from gems is to spend half a decade plus in grad school (literally).
If you just want to enjoy reading about the latest & greatest in science, then Science & Nature are good reading. But for any real perspective you need to read non-academic writing from those researchers willing to exert that effort.
People differ, fields differ. I am a professional scientist too, when I go for a deep dive into a topic, I read 5-6 papers a day and take notes.
I stopped reading comics and started to just read interesting papers from adjacent fields a few years ago. Nature and Science are nice examples, most people I know treat these as entertainment magazines ( unless of course they get a paper in, than it’s the ist important thing ever).
Quality of publications varies a lot, but PNAS, Cell, IEEE are usually good sources and as long as one avoids purely computational studies one is usually on the safe side. Few people fake their experimental dat.
(1) A lot of research is trash and not reproducible. Over the last 5 years I've found it's usually not even worth my time to read half the papers I read unless its in Nature or a top journal. Even then the ROI is minimal.
(2) It takes quite a bit of knowledge to appreciate and read a paper. In grad school, it took 4-6 hours of work to go through a paper. Do I really want to have a discussion on the 10,000 ft view of a paper? Probably not. Do I want to spend 4-6 hours really appreciating the nuances of a valid paper? Probably not.
(3) As alluded to by (1) and (2), most researchers (at least in my anecdotal experience) are spread so incredibly thin, as someone who would want to provide insight on some incredibly niche topic, I am already overbooked for my time between work and outside responsibilities.
I think you're going to find that the garden you're trying to grow doesn't have the adequate catalyst/buy-in. You might be better off creating a version where the paper is summarized by a GPT model and that 10,000 ft summary is discussed by the general public.