Since its creation in 1991, the Constitutional Court has played an important role in the Colombian context because of the broad political, economic, cultural, and social impact of its decisions. Several rulings, however, have triggered fierce criticism, putting into question the very legitimacy of the court. This chapter seeks to identify some of the factors that contribute to improve the legitimacy of high courts in the eyes of the country’s citizens, especially when they hand down controversial rulings. The chapter reports a vignette survey experiment on college students aimed at determining under what conditions citizens are more likely to provide diffuse support to the court or to what extent the court’s legitimacy depends on its performance (specific support). It hypothesizes that the legitimacy of the court is affected by the way in which its decisions are framed and justified, and finds that by wording and framing judicial rulings so that they convey a sense of principled reasoning and neutrality, the court helps translate specific support into diffuse support. Specifically, decisions based on scientific reasoning are more suitable to achieve that goal than other types of argument, including those based on legal norms and precedent.

Conjoint survey experiments have become a popular method for analyzing multidimensional preferences in political science. If properly implemented, conjoint experiments can obtain reliable measures of multidimensional preferences and estimate causal effects of multiple attributes on hypothetical choices or evaluations. This chapter provides an accessible overview of the methodology for designing, implementing, and analyzing conjoint survey experiments. Specically, we begin by detailing a new substantive example: how do candidate attributes affect the support of American respondents for candidates running against President Trump in 2020? We then discuss the theoretical underpinnings and key advantages of conjoint designs. We next provide guidelines for practitioners in designing and analyzing conjoint survey experiments. We conclude by discussing further design considerations, common conjoint applications, common criticisms, and possible future directions.