A meta-thread on my take of how to "read" science as a scientist. This is to arm non-scientists about how to navigate a world where one sees the "leading edge" of science develop as we do now in COVID.
(Context: I am an expert in human genetics and computational biology - data science in biology. As Deputy Director General of @embl I have the pleasure of being involved in a lot of science in a strategic way both inside @embl and internationally).
The first point is that most scientists have sets of observations about the real world which are solid - they have been measured multiple times; multiple groups found the same thing; ideally measured in different ways.
Any understanding of the world has to be consistent - or at least maximally consistent - with these solid observations. (when one set of solid observations does not fit it feels very very uncomfortable to a scientist)
"Solid observation" might be experiments; might be observation of complex phenomena in the world; might be observation + theory. In each case there is a sub-discipline like art/standard practice to be "solid".
For most scientists we're only lead practitioners in a handful areas - ie, we could have done the analysis or experiment ourselves. But we also usually have a broad appreciation of our surrounding penumbra of science, knowing the obvious "gotchas" and going out for here...
There is a semi instinctive of what solid observations look like in science. One hallmark is that it is the stuff experts agree on so quickly they don't even argue about it - it is solid enough that the experts move quickly onto areas of more productive disagreement.
this gives the first slightly counter intuitive thing about reading leading edge science - you need to read from the outside what is *not* being said so much, because thats the solid ground. It's often quite hard to work out in fact.
*Occasionally* the (previous) solid ground shifts significantly. It is rare that it turns into pure quicksand rather more like a tectonic plates moving (we thought this fitted here, but actually... it fits like this). This is tremendously exciting when it happens but it is rare
Far more common in science is this progressive "solidification" of observations from a solid core. That's pretty much where we are with SARS_CoV_2 - progressive growth of observations, solidifying more and more ground around us.
In my head, on top of this solid ground of observations is a theory/model of how it all fits together - a sort of intellectual super-structure. This super-structure is personal to each scientist (though often the core bits agree).
Let's call this superstructure "understanding" and from it scientists predict useful experiments or observations to do next - on the "marshy edge" of the solid ground - science is not a random walk in experiments or observations, rather it has a structure.
Unlike solid observations there is much debate between scientists at some point of their respective personal super-structures; indeed, scientists will often rush their conversations straight to the points of disagreement which can get quite heated!
So - it looks like scientists disagree alot often. This is ... the nature of science and exploring the world. When done productively the argument resolves down to "well if I am right, this experiment or observation will say X, but if you are right, it will say Y".
(sometimes it is not productive; sometimes arguments are stomped on too much or sometimes arguments get so heated and personal it messes up the progression. These are all sort of meta-failure modes of a region of science)
To "read" science from the outside therefore you need to find that common core of understanding standing on the common ground of agreed solid observations. Over time the common ground grows, and the edifice of common understanding grows with it.
It is a category mistake to blindly trust one scientist over another (though we all carefully burnish our track records of being right) and any good scientist will change his or her mind in an instant when presented with clear data.
(scientists who cling onto their own opinions in the face of data either have to be so conservative they can never progress or just become pseudo-scientists that endless discard things that don't fit. All good scientists get things wrong regularly - they just move on quickly!).
So - look for "missing space" often of agreement between scientists rather than focusing on the disagreements (and scientists when you are communicating for a broad audience, I think it's best to a quick sketch of key solid ground things and why it is so solid)

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More from @ewanbirney

2 Jan
Another bright day in London but with a pretty grim outlook here short term - but better mid to long term for COVID.
Context: I am an expert in human genetics and computational biology; I know a variety of experts in the COVID world from testing, infectious epidemiology, virus evolution, clinical trials and ICU clinical work.
COIs: I am a longstanding consultant to Oxford Nanopore, which make a COVID test (LamPORE) and portable DNA/RNA sequencing machines and I am a participant on the Oxford/AZ vaccine trial.
Read 25 tweets
30 Dec 20
A brief explainer on endpoints and efficacy on Vaccines as it's clear we're going to have a lot of chit chat on vaccines as a topic to discuss.
First off - let's step back and recognise that it is *awesome* that we have 3 COVID vaccines that are safe + work , and most likely more in 2021 (I suspect the Chinese vaccines will get regulated in more and more places; for a variety of reasons the Russian one will be complex)
This should frankly be enough. End of discussion - over to the eye watering logistics about vaccinating as many people across the globe as fast as possible. We're 0.06% into 7 Billion people as of today.
Read 25 tweets
27 Dec 20
A note for I think journalists about the "377 deaths under 60" being the cost for COVID for the UK. This a bonkers positioning statement and is definitely not something trying to shed light on the extremely nasty problem we have in front of us.
The main thing is that what has been aimed for throughout, from the start, is not having a catastrophic capacity demand on the NHS (or any healthcare service). Simply healthcare services cannot cope at some point and then, straightforwardly, many people die, for many reasons.
In this situation, one can aim to do this more rationally ("triage") or not (obviously, more rationally, better) but there is no magic bullet, or emergency button to press. Field hospitals are useful, but they have to be staffed. Healthcare capacity is a fragile thing.
Read 25 tweets
24 Dec 20
Some COVID thoughts on this bright, beautiful Christmas Eve morning in London.
Context: I am an expert in genetics and computational biology; I know and chit-chat with experts in viral phylogeny, infectious epidemiology, immunology + testing. I have a COI that I am a consultant to Oxford Nanopore that make a COVID test. I am also on the AZ vaccine trial
Reminder: SARS_CoV_2 is an infectious virus which causes a nasty disease in a subset of people, often leading to death. If we let the virus go through the population not only would many people get this disease, but also healthcare systems would be overwhelmed.
Read 25 tweets
20 Dec 20
Final thread in a series of 3 - what does this new variant mean for the next stages of the pandemic?
So - first off, if the biology has changed, we need to check all the biological and clinical parameters, some of them urgently. Most obviously do the vaccines work against them. There are good reasons to think this is v. likely which I outlined yesterday.
Briefly they are 1. The vaccine trials all happened with a mixture of different variants circulating (as happens everywhere - there's far more than this B.1.1.7 strain circulating). The fact all 3 work in this mixture is reassuring.
Read 17 tweets
20 Dec 20
Now, a more technical tweet thread to give updates on the science - which is moving fast. Again, I recommend following @arambaut, @firefoxx66, @EBIgoldman, @The_Soup_Dragon, @pathogenomenick and @jcbarret along with others to stay on the cutting edge of this
Most important has been the paper by the @CovidGenomicsUK consortium on the new variant, here: virological.org/t/preliminary-…
(This is super-rapid pre-print on virological.org - other people will pick over this no doubt - but the openness of the data and quality of analysis from this group means this is super solid, and any updates on discussion likely to happen fast)
Read 14 tweets

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