Interesting, I only checked a couple of papers and they seemed to be in legit medical journals. The science mag article raises scepticism, but I couldn't find a study which claims that it is all wrong. Not all claims of correlations with 2D:4D are well established, some may be non-existing. This seems to be what the literature is about.
@Bill_St do you have an opinion on this?
While the first impression is that this is just a prank, it becomes clear from the data and sources that there is some genuine science behind it.
Where it is particularly relevant is with the scare stories.
Small differences can have a big psychological effect and we have to be particularly careful with even larger apparent differences when they are applied to small data sets.
Examples of such differences would be :
Death rates of PWD in hospitals
Immunity resulting from vaccination.
Taking the first, many are panicking that twice as many T2 and 3 1/2 times as many T1, die of Coronavirus and translate that into T2 are at double the risk and T1 are at almost 4x the risk.
But the data set is just of those PWD treated in hospital, more specifically in ICU, because those were the only ones tested in the small data set used from early China.
It ignores the vast numbers who do not go to hospital and thus were not tested.
The second is even more important that we take great care.
The Abbott antibody test seems highly useful with percentages such as 100% and 99.6% quoted.
(reliable results with 99.6% specificity and 100% sensitivity)
But can we say those percentages mean that if we get a positive from the test then we are quite safe to just ignore the virus until we can find out if the antibodies are in fact long lasting?
To make such assumptions would be wrong and potentially dangerous.
Statistics can be misleading which may be why the Government statisticians put a hold on these tests.
I’ll leave it up to them with their fancy diagrams to explain
why lower prevalence means you are less safe.
https://assets.publishing.service.g...ponses-covid-19-antibody-testing-13042020.pdf
Numbers can be so misleading - particularly to the vast majority.
Just look at how many try to believe that BGM and HbA1c readings are accurate to a fraction of a percent just because the number is shown to a decimal place.
Just look at the crazy reliance on giving detailed numbers of deaths and infections to a single figure when considering hundreds of thousands. Is this deliberate?
Numbers can be used by Both “scientists” and politicians to obscure information.
What I particularly liked about the 2D/4D paper is that here was something simple that everyone could just look at their hand and make a judgement of comparative risk.
What I particularly disliked was the attending mass of numbers that completely obscured the level of that risk.
All too often papers are not written to be understood by many people. How many actually contain a clear diagram or graphical abstract?
Such as this which I really like : Not often you see such as this published in a peer reviewed paper in a Medical Journal
We can give information rather than just numbers.
A similar confusion I regularly see is the BG level for driving- How often do we hear “Five to Drive” in the U.K.?
Catchy phrase that is easy remembered and often quoted But something that is wrong.
Just Four to Drive does not sound right.
How much better than the numbers and text put out by the DVLA (and most D organisations) is the one put out by the CAA for aircraft pilots (who you would reasonably expect to fully understand numbers and texts)
We can use numbers but particularly now should do so with care to ensure understanding and clarity.