A lot more academics call for better public engagement and more creative academic thinking than actually do better public engagement and more creative academic thinking. The History Manifesto practices what it preaches. As an academic (far) outside the field of history, I was able to digest this short book easily and to grasp the authors' description of the movements of thought in the field -- the history of history.
They argue that in the latter half of the 20th century, long-term history gave way to focused microhistories, and that long-term history is coming back. They don't argue that microhistories should go away, but that the tools developed for such deep-dives into archival materials can now be applied to longer spans of time and bigger datasets. Microhistory in massive parallel, if you will.
I think they're right, and I especially appreciate the well-chosen examples of what they're talking about. As a chemist who constantly strays into geological and biological history, I am all for the parallel movement in natural history (although I was hoping to find a little more inspiration for my own natural history thoughts than I did here). If anything, their critiques of evolutionary biology should be more intense.
The only thing that tugs at me is a sense that they already know where their field will lead -- that the conclusions of new history will take down the ideas of those rival laissez-faire economists who always show up as dramatic foils in this narrative. Awareness of your own biases is crucial when designing these new historical studies and this book is more about inspiring new methods than in cautioning on the wrong turns that can be taken when implementing new methods. They're basically arguing that "cliometrics" should return as a data-driven historical field of study (while arguing that the ones really qualified to interpret such data must be trained historians) but they also honestly present the fact that the first studies to use this term back in the 70s were embarrassingly flawed. Why were they flawed? I would like to dig down more into how these flaws can be prevented from happening. Most of all, I want to be surprised by the data, so "knowing the result before it starts" is something to avoid.
The only reason I can even make a critique like that is because this book genuinely talks about important and foundational issues, and that's the sign of a good book.