The book has nine chapters, and it loosely divides into three parts, with three chapters in each part.
The first part concerns the ninety topics that the model divides the articles into. Chapter 1 is about how and why I made the choices I did in providing the inputs to the model. Chapter 2 goes through each of these ninety topics one at a time. As well as producing some automated statistics and graphs for each topic, and listing which articles are in each topic, I make some small comments about the topic. These are mostly about the content of the topic and its place in philosophical history, though I also spend a lot of time talking about how the model made its division into topics. Most of the comments here are short, though occasionally I decide that one topic needs 2500 words or more. Chapter 3 is about my attempts to make a legible graph of all ninety topics through time. I run through a lot of different representations of the data; most of them are failures, but some of them are more interesting failures than others.
The second part looks at what happens if instead of making a ninety-way division into somewhat novel topics, a twelve-way division into familiar topics is tried. I divide the articles up into common contemporary categories, like epistemology, ethics, metaphysics, and philosophy of science, and I look at the trends in these categories. Chapter 4 goes over the trends in the twelve categories. Chapter 5 goes over how I made these divisions, with a special focus on where the categories do, and do not, run into each other. And Chapter 6 looks at one of these categories: epistemology. This is in part for self-interested reasons; it’s the field I work in. But it’s in part because the data about epistemology were so surprising. Epistemology, as it is currently practiced, is basically invisible in the journals before World War II. And the most famous part of contemporary epistemology, the so-called Gettier problem about the relationship between knowledge, truth, justification, and belief, plays a surprisingly small role in recent years.
The third part looks at further applications of the model. The first six chapters had used years as the main unit of temporal measurement. In chapter 7, I use more coarse-grained measures. First I look at the trends over five “eras” in philosophy, and then over twelve decades. One benefit of doing things this way is that as well as looking at what the model says, I can look at trends in the underlying data directly, and see how well the model is tracking reality. In chapter 8, I look at outliers along various dimensions, both to see where extreme events have been happening and to put some stress on the model. If its most outlandish claims are true, and I think several of them are, then there is more confidence in its more mundane claims. And in chapter 9, I try to look beyond the model. I use the model to compare the early years of the journals with some famous books that were published around the same time. Then I look at how articles in Philosophers’ Imprint in 2019 compare to what is seen before 2013. (The big story is the resurgence of interest in historical figures outside the standard canon.) And finally I look at something that almost blew up the project: the very distinctive vocabulary of twenty-first-century philosophy.