If a mobilized constituency for programmatism is one way out of a weak-state trap, then the state or external actors pushing for increased state capacity is another. I argue that intermediaries who informally link the state to citizens comprise a constituency against such a change, and may block this pathway out. The empirics in this chapter travel outside Senegal because observing resistance from intermediaries requires a real or perceived shock to state capacity. A within-country analysis in Mali first explores the types of local actors who would be willing to participate in a forthcoming local governance initiative to limit corruption and discretionary spending: performance-based financing of municipalities. The most embedded local leaders (who have operated longest and have the most social ties in the community) benefit more from clientelistic transfers from the mayor and are least willing to agree to monitor mayoral performance under the new initiative. Then, leveraging a recent coordinated set of field experiments evaluating formalization interventions, I tell the stories of backlash in three of the six country cases by intermediaries who benefit from the status quo.

Negative racial appeals have a long history in American politics. Chapter 4 synthesizes the literature on racial priming to highlight the mixed findings that have emerged. Some studies, especially those conducted in the 1990s and early 2000s, found that white Americans rejected negative racial appeals when they became explicit, but others, especially those conducted in the 2010s and beyond, no longer detect this backlash. The chapter explains these mixed findings with the theory of dominance destabilization: when white people feel that their dominance is unstable, their prejudice activates, and they come to approve of negative, explicit racial appeals. This chapter tests this claim with two original survey experiments. In the first experiment, it finds that a negative frame on diversification leads to an increased approval of racist rhetoric. Then, it tests the proposed causal mechanism (i.e., feeling threatened) directly, with an emotional induction experiment. It finds that feeling anxious and angry both motivate support for negative explicit racial appeals – but that anger does so more strongly. This chapter offers key evidence to make sense of the mixed findings in the racial priming literature, as it demonstrates that white Americans accept negative, explicit racial appeals when they feel threatened.

To set the stage, Chapter 3 demonstrates heterogeneity in white Americans' reactions to perceptions of threat to white dominance. It first outlines the different forms of perceived “threats” that groups can face and synthesizes existing literature on these topics. Then, using two original survey experiments, it demonstrates that partisanship and racial attitudes drive reactions to narratives about diversification among white Americans. It offers additional evidence from the 2016–2020 VOTER survey – a large, nationally representative survey – that these effects extend outside the experimental context. From these analyses, the chapter concludes that perceptions of status threat are polarized, such that Republicans are more likely to perceive threat in response to diversification compared to their Democratic counterparts. This chapter helps explain why we may expect reactions to explicit racial appeals to be polarized, as well as the first indication that electoral context plays a particularly important role in how white Americans understand threats to their dominance.

Previous chapters largely identify that it is Republicans and white Americans with higher levels of racial animus who accept racist rhetoric when threatened. However, the book’s theory about the way that whiteness is fundamentally linked to a desire for dominance would predict that a similar process could be at work for white Democrats as well. Chapter 6 introduces an original survey experiment that demonstrates that when white Democrats learn about a growing Latine population that is increasingly voting for the Republican Party, they come to feel threatened and, as a result, approve of negative, explicit racial appeals from a co-partisan politician. This provides troubling evidence of the way that a commitment to white dominance persists across partisan lines, and that the current arrangement we see (where Republicans accept and use negative racial appeals more than Democrats) is context-specific and unstable. This novel contribution casts doubt on recent findings that indicate white Democrats are increasingly egalitarian in their racial ideologies, as it demonstrates that they are willing to endorse racist rhetoric when they do not perceive the minoritized ethnoracial group as helping their partisan group interests.

How can mixed-method research add value to experiments? There is much to learn by adding qualitative components to experiments that can test for problems related to measurement; networks and spillover among experimental subjects; issues related to the meaning of treatments, outcomes, and other aspects of the experiment for participants; the exhaustiveness of the intended causal content of the treatment; and moderation effects related to subgroups of participants, or to differences across implementations of an experiment in divergent contexts. Some of these areas relate to the goal of theoretical generalization from the initial experiment, but most of them also have connections with the meaning and quality of the causal inference for the experiment at hand.

This chapter summarizes key themes from the book as a whole and offers general concluding thoughts.

Research designs can combine qualitative, quantitative, experimental, and data-science methods through careful planning, attention to details and assumptions, and methodological execution. This chapter introduces the book's perspective, arguing that designs that combine methods carefully and with close attention to their details will outperform designs where two or more methods are carried out in parallel and then compared. The chapter also considers a range of practical and philosophical questions related to whether it makes sense to combine methods. Is one method always best, such that it isn't worth trying? Do methods speak fundamentally different languages, such that there is no point? Are methods and problems inextricably linked, such that the question is irrelevant? We argue against each of these views.

This chapter examines what voters in Malawi know about donor activities in their communities, and how foreign aid changes voter behavior and beliefs about incumbent performance. I show using original survey data that aid recipients struggle to distinguish between the role of governments and donors in development funding. Next, I use experimental and panel data to test hypotheses about how foreign aid (and beliefs about foreign aid bargains) change voter behavior and perceptions of incumbent performance. The results are broadly consistent with the theoretical predictions in Chapter 3.

Chapter 6 delves into experiments, models, and simulations in mathematics, introducing powerful strategies for inquiry and representation. You will learn how to scaffold students’ understanding of mathematical concepts through modelling frameworks and interactive tools, enhancing conceptual understanding and problem-solving.

Mistakes and missteps in theory development and testing are inevitable but there are ways to decrease them. One way to detect potential problems is to outline the definitions, scope conditions, assumptions and finally derivations. Stripping down the theory to the simplest form helps spot definitions that are not precise or derivations that are not sound. Once done, it becomes easier to diagnose problems and think through potential solutions. Another way to find potential problems is to talk through your ideas with others—especially those you know to be skeptical. Having to explain your logic and then your potential tests with others can provide invaluable feedback and can make you rethink aspects of your formulations.

Concept formation is critical for many social scientific goals, yet it often appears neglected. This chapter underscores the importance of concepts in empirical work oriented toward causal inference, including experiments. It explores the role of conceptual hierarchies, typologies, and dichotomies both for causal attribution and for assessing generalizability. Using an example from the Metaketa Initiative, this chapter highlights the value of Sartori’s ladder of abstraction for fostering cumulative learning from experimental research. Wider use of the tools of concept formation can aid assessment of both the internal and external validity of causal claims.

Science is invariably based on some sort of data collection and further treatment of the data gathered. Data can come from pure observations, from structured observations (‘natural experiments’) or from experiments. The central importance of models in science is mentioned. It is discussed how the choice of statistics reflects the philosophy of science adopted by the scientist. Different research programmes use different statistics, in particular, depending on when and how they deal with variation. The relationship between falsificationism and the rejection of null hypotheses as a workaround for the Duhem-Quine thesis is discussed, as well as the role of significance thresholds and their associated problems. It is argued that predicted results are more reliable than chance findings. The pros and cons of having alternative hypotheses are discussed, and a short introduction to Bayesian statistics as an alternative to frequentist approaches is given. Systematic reviews and metaanalyses of data from several studies are introduced, and an example is given on how different types of evidence from many studies are combined to form the current consensus of rational opinion regarding a particular hypothesis.