Reaching ‘Herd Immunity’ from Covid Is Unlikely in the U.S., Experts Now Believe

Disingenuous statements aside, the people in charge of policy clearly don't care enough to follow the rules themselves. They've put covid patients in nursing homes, ignored their own lockdown rules and intimidated people at religious worship. There's no doubt in my mind that we were deliberately lied to about the severity of this virus

The biggest problems seem to be with scientists who don't actually work in labs, people that in industry we'd call data scientists. There's nothing to ground them in the real world, no clear research directions or high level goals, and it's too easy to just manipulate the data or ignore data that disproves prior papers. It's possible your friends are better because they work in labs.

But there's also another possibility, and it's not a pleasant one to ask about, but have you actually downloaded and read papers published by your friends? One thing that becomes apparent when you dig into this is that researchers are very willing to give their friends/colleagues a heavily hedged conclusion, whilst telling the public that their conclusion is not merely unarguable fact, but also an absolute scientific consensus that demands immediate government action. This is part of the reason why academics are losing trust; open access has happened, the internet has happened, and now it's easy to download their papers to see the contradictions for yourself. An example would be Flaxman et al 2020 which attempted to prove that lockdowns worked. It set up a model that could only conclude that lockdowns worked (because it had no component to represent any sort of natural decline and for other reasons), and admitted half way through that this made the results unrealistic. But by the time those same researchers were publishing press releases on the university website and giving interviews, they were claiming there was now solid proof that lockdowns had saved millions of lives. Same people, totally different stories and in ways that were not innocent mistakes. Journalists deserve at least some blame for not treating their sources adversarially but the deception was originally coming from the researchers, not the press. A related problem seen in the UK is the way that predictions assigned near 100% certainty are suddenly rewritten as having been mere "scenarios" the moment someone corners a scientist and shoves a graph of real measurements in their face.

And then there are the other issues.

One is surely filtering related. When you look at the composition of the SAGE advisory council in the UK, you discover that one influential member is a lifetime member of the British Communist Party! Another is in an open relationship with a woman who's a part of Extinction Rebellion. Their leader was a man who apparently shocked his friends when he joined GlaxoSmithKline because of his lifelong open hatred for corporations and pharma firms of any kind. These people aren't at all normal or representative of the general population's views, so how does that happen? Some of it is that academia selects for people who want to be judged by impact rather than e.g. their salary size. And some of it must be a question of who chases after advisory roles to governments. A double selection effect, in other words.

Another is the certainty aspect that you allude to. The most influential "scientists" are actually modellers, not scientists. They insist that they are scientists, but the scientific method is MIA in fields like epidemiology. If you read their papers you'll find lots of predictions and no followups to measure the accuracy of the predictions. It's just one long run of model outputs, presented alongside the inevitable policy recommendations, but when you go digging through a reverse citation search to look for followups where the model accuracy is calculated, you come up with nothing. Why are the most influential scientists these people? Well, exactly because they use their models to generate policies. They tell politicians, "our scientific models say X will happen if you do Y and if you don't there will be an enormous crisis that everyone will blame you for". The politicians meanwhile feel they can't push back, even if they intuit the truth that the claim is scientifically unsupportable, because academics are very good at making jargon filled and very technical arguments involving lots of maths. Some papers have obvious errors, but when they're pointed out academics just blast people with even more pseudo-science along with many claims of criticising in bad faith, not being legitimate, etc. You need to have copious free time and an extremely high degree of confidence with logic, stats and programming to correctly see through the BS they are capable of generating. The media can't do it and immediately fall in line, politicians then then feel they have to follow. The only people who do push back end up being a motley assortment of bloggers, often retired or out-of-field, who have the free time and career immunity to wade through the morass pointing out the errors. Journals rarely publish them of course, because they also can't bite the hand that feeds them, and science journalists don't know how to evaluate arguments except via reference to institutional hierarchies so just ignore them. But most people don't have those limits, so more and more people find the articles written by those newly-born "skeptics", read them, realise the arguments make sense and their faith in science declines. The institutions wail about disinformation without realising that they're the ones generating it.

The whole system is locked in this feedback loop and because academia is so heavily government funded there's no obvious way to break it. There are no penalties for doing bad science, as even many scientists will admit, but plenty of rewards. So public confidence in research will continue to fall until it reaches the same level as journalists or politicians, perhaps even less given that those people are at least in direct competition with each other whereas academics aren't (or rather, the competition they're in does not select for anything the public cares about). Eventually you will get a new generation of politicians who openly attack scientists in the same way that Trump openly attacked the press. There will be calls for defunding which will be responded to with more bans, more censorship, more street protests and more chaos. What comes after? Only the future knows.

Its EASY to have draconian and blanket restrictions. Its HARD to sit down and come up with more reasonable policy that balance risk and preserving some semblance of liberty.