No, actually the comparison is rather apt given the way some subjects are treated - as quasi-religious dogma where criticism is being treated as heresy. Critics

No, actually the comparison is rather apt given the way some subjects are treated - as quasi-religious dogma where criticism is being treated as heresy. Critics of the leading narrative around the changing climate are called "climate deniers" who are "anti-Science" and either uneducated knuckle-draggers or nefarious plotters in the pockets of the enemy - usually the fossil fuel industry. Critics of the narrative around SARS2 are called "anti-vaxxers" and "Science-deniers" who do not "listen to The Science™" and probably are *-ists and *-phobes as well. The parallel is clear, this is how critics of the narrative around the movement of the Earth, Sun, stars and planets were treated in the 1600's. In that case it was the power of the established Church which saw its monopoly on "truth" threatened by some upstart with a telescope. If his revelations about the orbits of the planets was accepted it would undermine their interpretation of scripture which would undermine their authority so they lashed out to silence the heretic. There is a striking resemblance to the way critics of current narratives are treated, as heretics who need to be silenced before their wayward teachings can poison the populace. This is now how science tends to be done and it is not how science (with a small 's') should be done. Everything should be open to criticism, theories should be mercilessly attacked. The more these attacks falter, the strong the theory will be. Should the attacks succeed in proving the theory wrong everybody will benefit from it. In the discussion around climate models this means the models need to be subjected to rigorous and merciless testing to find their flaws. They should be tested against historical data, the code should be scrutinised for everything from simple errors to the use of fudge factors and 'magical constants' or 'damping mechanisms' or any other such unproven/unprovable manipulations of the data. If the models withstand these tests and actually manage to follow historical data on which they have not been tested to a reasonable degree of accuracy they will be the stronger for it and their predictive ability will be far higher. This would be a good thing for everyone involved.