This chapter draws on the original cross-national dataset of counterrevolutions to examine global patterns and historical trends in counterrevolutionary emergence and success. It begins with a series of statistical analyses that support core elements of the theory. Counterrevolutions are much less likely to topple radical-violent revolutions than moderate-unarmed ones – a finding that holds across two different measures of these types. Subsequent analyses shed light on the mechanisms behind this relationship: loyal armies and powerful foreign sponsors are key to defeating counterrevolution, whereas robust parties matter less. Next, the chapter shows that counterrevolutions are most likely to emerge following revolutions with medium levels of violence, which leave the old regime with both the capacity and interest to launch a challenge. Further, there is little support for four alternative explanations, particularly when it comes to counterrevolutionary success. Next, the chapter evaluates how key events during the post-revolutionary transition (like land reforms and elections) affect the likelihood of counterrevolution. It concludes with an exploration of the decline in counterrevolution since 1900 (followed by an uptick in the last decade), which it traces to a combination of the changing nature of revolution and shifts in the distribution of global power.

This chapter analyzes the popular dimensions of Egypt’s 2013 counterrevolution, using an original dataset of protests during the post-revolutionary transition. It shows that Egypt’s revolutionaries were unable to consolidate the social support of the revolution, and that this failure allowed counterrevolutionaries to channel broad disaffections with revolutionary rule into a popular movement for restoration. The dataset covers the final eighteen months of the transition and includes approximately 7,500 contentious events sourced from the major Arabic-language newspaper Al-Masry Al-Youm. These data reveal, first, the extent to which social mobilization persisted after the end of the eighteen-day uprising. The transition period was awash with discontent and unrest, much of it over nonpolitical issues like the deterioration of the economy, infrastructure problems, and unmet labor demands. Second, statistical analyses show that this discontent came to be directed against Mohamed Morsi’s government. The earliest and most persistent anti-Morsi protests emerged in places where the population had long been highly mobilized over socio-economic grievances. Later, they also began to emerge in places with large numbers of old regime supporters. Ultimately, these two groups – discontented Egyptians and committed counterrevolutionaries – came together to provide the social base for the movement that swept the military back to power.

This appendix provides a comprehensive overview of statistical network models, building from fundamental concepts to advanced frameworks. It begins with essential mathematical background and probability theory, then introduces the foundations of random network models. The appendix covers a range of models, including Erdös-Rényi, stochastic block models (both a priori and a posteriori), random dot product graphs, and their generalizations. Each model is presented with its parameters, generative process, probability calculations, and equivalence classes. The appendix also explores degree-corrected variants and the Inhomogeneous Erdös-Rényi model. Throughout, we emphasize the relationships between models and their increasing complexity, providing a solid theoretical foundation for understanding network structures and dynamics.

This chapter lays the foundation of probability theory, which has a central role in statistical mechanics. It starts the exposition with Kolmogorov’s axioms of probability theory and develops the vocabulary through example cases. Some time is spent on sigma algebras and the role they play in probability theory, and more specifically to properly define random variables on the reals. In particular, the popular notion that ‘the probability for a real variable to take on a single value’ is critically analysed and contextualised. Indeed, there are situations in statistical mechanics where some mechanical variables on the reals do get a non-zero probability to take on a single value. Moments and cumulants are introduced, as well as the method of generating functions, which prepare the ground as efficacious tools for statistical mechanics. Finally, Jaynes’s least-biased distribution principle is introduced in order to obtain a priori probabilities given some constraints imposed on the system.

This chapter presents material on statistics, from the basic principles of the classification of data to normal distribution. We go on to discuss types of the null hypothesis, types of error and different methods of statistical analysis depending on the type of data set presented.

Starting with George Lukacs’ complaint that naturalist works are incoherent because of their superfluous detail, this chapter argues that incoherence was in fact an effective literary aesthetic for seeing and managing details at a large scale. The large scale that was particularly salient to American naturalism was the global one of American imperial expansion during the Progressive Era, and the essay argues that American empire is a useful framework for understanding naturalism as a literary movement because it brought together an investment in incoherent form with statistical and biopolitical technologies that, like naturalist works, proliferated details. Naturalism in this American context isn’t a failed version of realism. Nor does its incoherence register an inability to represent empire as an emergent global order. Instead, naturalism developed the realist project with a set of conventions that powerfully (and problematically) expressed the form of an emerging and efficacious large-scale global order.

This chapter offers a summary of the main findings of each chapter of the book.

The discovery of anaesthesia transformed the human condition, and unplanned awareness returns a patient to the nightmare that was surgery before anaesthesia and effective analgesia. Significant advances in the pharmacology and technology of anaesthesia have still not brought reliable means of monitoring its depth much closer, although because awareness is such a serious complication, considerable research effort has been dedicated to the search for methods of detection. Some of these remain research tools or are not yet in widespread use, but you should have some idea about which of them may in due course find their way into clinical practice. Most current interest centres around bispectral index (BIS) monitoring, with recommendations both from the Association of Anaesthetists and from NICE, which are summarised in this section, and it is likely that the oral will focus more on BIS than on the other technologies.

This chapter provides an introduction to the main themes of the book and why this is a book about the misuse of language, just as much as the misuse of numbers. Statistics are never just numbers, for the numbers have to be labelled. Because politicians are so distrusted at present, people expect politicians to manipulate statistics. This opening chapter introduces readers to a number of excellent recent books about statistics, most of which have been addressed to non-specialist readers. The topic of statistics is a broad one and can sustain a variety of books with different slants. Unlike other books on statistics, this one looks directly at manipulation and how it occurs. A recurring theme of the book is that the political manipulation of statistics is not typically a single act, but politicians will often manipulate their statisticians to manipulate the official statistics on their behalf. This opening chapter also comments on the book’s style of writing. The authors write aim to write in a clear and non-technical way, and to give special emphasis to the ways that politicians manipulate language when manipulating numbers.

Stefanie Markovits’ chapter thinks about counting and accountability, and how they inform literary representations of the military man, one of the most visible of war’s outcomes in mid-Victorian Britain. Markovits reflects on this period as one which saw ‘the rise of statistics as a discipline of social science and a method of statecraft in Britain’, and with it the growing need for accountability in public affairs. The figure of the soldier is both hero and statistic, individual and number, in a period where fiction, philosophy, and popular commentary, were preoccupied with how individuals realised their fully individualised potential. The soldier’s cultural and political potency is enabled because his being is aligned with the numbers that account for him. In the work of Tennyson, Harriet Martineau, and Dickens we see how ‘the mid-century soldier becomes such a potent figure precisely because his “type” aligns so closely with numbers’.

Three Stanford-educated Chicanos took the stand in support of MAS, and these witnesses were central in Judge Tashima’s final ruling. Specifically, they detailed in a scholarly way the academic integrity of the department, the efficacy of taking the classes, and also demonstrated how state representatives used racist “code words” in cementing their opposition to the program. We detail their times testifying, how the state desperately tried to trip them up.

This chapter links the creation of MAS to the historical creation of Ethnic Studies – setting the record straight on the nature of this type of education amidst massive amounts of local and national misinformation. It details what MAS was, the effects of the program on student academic success, while examining how critically engaged, educated Mexican American students came to be seen as such a “threat” to the state.