Maxim Lott: getting to the truth of the matter

Razib Khan's Unsupervised Learning

About a month ago, during a COVID-19 wave, I saw a Substack post, How to Get Paxlovid Quickly, If You Get Covid - How to get the 89%-effective Covid cure called Paxlovid, despite government red tape, shared across various group chats. For non-Americans, the utility of such a post and the question of why the government couldn’t distribute this drug and communicate its utility might require some explanation. If you are an American, you probably don’t need an explanation. The post's author, Maxim Lott, is behind the Substack Maximum Truth, where, in his words, he “uses data to answer important questions that the shallow media ignore.” Lott is also the force behind Election Betting Odds. There are two kinds of punditry. There are the pundits who when posed questions reflect and then hold forth. Then, there are pundits who when confronted with a question search for data and analyze what they find to generate results and then produce an informed opinion. Lott is in the second category.

In this episode of Unsupervised Learning Razib and Lott discuss “where we are” more than two years into the COVID-19 pandemic through the lens of data. They reflect on their expectations in February 2020 and how things have panned out. They also discuss the politicization of COVID-19 and being caught in the middle of ideological arguments inadvertently, as attitudes toward issues like masks and border controls seem to chart flips in tribal valence in the blink of an eye. Finally, Razib and Lott also discuss the utility of instruments like betting markets to gauge the strength of opinions and judgments. This allows us to go into the future with more tools to understand the world with our heads rather than our hearts.