This book did an excellent job at what it intended to do. I think it crystallized a lot of the problems with practices and uses of statistical modeling and interpretation that I've thought about quite a bit--especially through the covid years--but not quite been able to put into words. Unfortunately, I doubt that the people who most need to read this book--that is, the people who build the models and see themselves as maximally rational makers of science, or the policy makers who (ostensibly) use those models to inform their decisions or (more usually) pick and choose the models that support their pre-determined decisions in the name of 'following the science'--are actually going to read it and benefit from it through changing their thinking. 

More likely it's going to be read by people who already mostly agree with it, and who will like it and nod and say, 'Ah yes, that's what I've always felt but couldn't quite articulate.' (Which, in a way, is almost like politicians choosing the models to 'support' their decisions by finding which models give them the results they like.)

I could be wrong, of course. I hope I am. But I doubt it.