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No! We should rigorously scrutinise epidemiologists and do lots and lots of competing analysis. What makes you think epidemiologists are so great? The one who

No! We should rigorously scrutinise epidemiologists and do lots and lots of competing analysis. What makes you think epidemiologists are so great? The one who has guided the UK's response has been severely criticised by fellow academics in the past for bogus low quality modelling. The Imperial College paper has basic errors and flawed assumptions that are obvious even to untrained laymen. I think you're wildly over-estimating how much statistical and logical training most academics get. This is one of the basic underlying problems that the replication crisis has exposed: an unending flood of academic papers, especially those doing modelling, that fall apart when examined by people with statistical and mathematical training. You're right that a 4 week bootcamp won't make someone a flawless handling of data. But it might still be a more rigorous form of training than epidemiologists get.

craftinator 7y ago
I agree with points from the parent comment, but more so from you. It's good to have experts who've rigorously studied historical practices and their outcomes; we can learn many things about which practices work best, and what mathematical relationships they reveal. But history is not an accurate predictor of the future, and theory is only a stepping stone for better testing (such as Great Britain's theory for herd immunity, which was a ground breaking theoretical approach to dealing with a pandemic). I think the most effective approach, which adds to your argument, is ensemble modelling from numerous, independent researchers from many fields. This is akin to how many people guessing at the number of gumballs in a container at the fair will average to the correct amount, while any single guess will not. There is a Freakonomics episode, Superpredictors, which demonstrates the use of this statistical approach for anticipating the outcome of voting in foreign politics.

craftinator 7y ago

I agree with points from the parent comment, but more so from you. It's good to have experts who've rigorously studied historical practices and their outcomes; we can learn many things about which practices work best, and what mathematical relationships they reveal. But history is not an accurate predictor of the future, and theory is only a stepping stone for better testing (such as Great Britain's theory for herd immunity, which was a ground breaking theoretical approach to dealing with a pandemic). I think the most effective approach, which adds to your argument, is ensemble modelling from numerous, independent researchers from many fields. This is akin to how many people guessing at the number of gumballs in a container at the fair will average to the correct amount, while any single guess will not. There is a Freakonomics episode, Superpredictors, which demonstrates the use of this statistical approach for anticipating the outcome of voting in foreign politics.