Working Papers

Given the importance of bystanders in conflict settings, public passivity in the face of human rights violations has long represented a major concern among scholars, policymakers, and organizations working to reduce violence. Yet in contexts of large-scale criminal violence, people often stigmatize victims because they perceive them to be involved with criminal groups. Human rights NGOs thus create counter-narratives to mobilize solidarity and advance peacebuilding. How can they do so? This study focuses on Mexico’s War on Drugs, which triggered one of the most significant contemporary humanitarian crises, leaving over 110,000 disappeared. After providing one of the first systematic analyses of citizens’ misperceptions about these victims (N = 1,800), I conduct a large-scale experiment (N = 2,524) and test the effectiveness of two persuasion strategies: hearing personal narratives and changing perceptions of social norms. Participants were randomly assigned to either a control group or to one of two audiovisual treatments: the testimony of the mother of a victim of disappearance or a message that reveals how common it is to help victims. The results indicate that both treatments reduced stigma and increased inclusionary behavior in the form of an anonymous letter supportive of the disappeared. The behavioral—but not the attitudinal—effects mostly survived but decayed during a follow-up survey conducted two weeks later, suggesting the need to repeat these messages. These findings stress how human rights campaigns can elicit solidarity among indifferent populations.

The world faces an unprecedented immigration humanitarian crisis, requiring leaders to abide by the law and protect undocumented immigrants’ rights. Yet, governments across the world have increasingly responded to the arrival of immigrants with militarization and repression, often with the support of local populations. For human rights organizations, one of the pressing challenges is to improve citizens’ attitudes toward undocumented immigrants, including promoting rejection of state violence, but how can they do so? We first document citizens’ support for anti-immigrant state violence and then experimentally test whether media campaigns combining real-life information messages with a perspective-getting approach—learning about immigrants’ personal experiences—can reduce citizen support for state violence and increase demands for justice. We conduct our study in Mexico, where similarly to many other countries authorities have turned to the militarization of borders and detention of hundreds of thousands of immigrants. Participants were randomly assigned to a control group or exposed to (1) a real-world information media campaign run by an international humanitarian organization intended to educate the public about the rule of law, (2) a testimony from an undocumented immigrant we interviewed during our fieldwork, victimized by Mexican security forces, or (3) a combination of the information and testimony treatments. We find that the testimony significantly reduced support for state violence, while the information message begat demands to hold perpetrators accountable. Media campaigns that combine immigrants’ personal narratives and information on the rule of law evoked powerful emotions conducive to public condemnation of state violence and demands for justice. 

How can deeply polarized societies confronting histories of mass atrocities mitigate partisan-motivated opposition to accountability? While scholars of transitional justice (TJ) suggest that broad support is necessary for effective accountability, it is unclear how societies achieve it. Using two original surveys, we assess attitudes toward accountability in Mexico at a time when a putative leftist president and victims’ organizations independently demand truth and justice for atrocities committed under right-wing governments in the Dirty War (1965-1985) and the War on Drugs (2006-2018). Although our observational results reveal that the president’s leftist followers are more likely to support – and right-wing citizens to oppose – TJ, we experimentally show that both sides reject allegations against their own parties. Amidst polarization, two additional experiments reveal that participation of autonomous victims’ organizations mitigates partisan-motivated opposition, because citizens see them as guarantors of unbiased TJ processes. Our findings highlight the crucial contribution of victims’ voices to democratic accountability.

Students of authoritarian rule debate whether the presence of multiple parties in the legislature stabilizes dictatorships or promotes their demise. We show that authoritarian regimes face a quandary: allowing for multipartism reduces the risk of bottom-up revolt, but paves the way for protracted top-down democratization. Concessions to the opposition diminish the long-term benefits of authoritarian rule and empower regime soft-liners. We provide evidence from Latin America—a region with a broad range of authoritarian regimes—and test our theory using survival models, instrumental variable estimators, random forest ensembles, and two case studies. Our theory explains why rational autocrats accept multipartism, even though this concession may ultimately undermine the regime. It also accounts for democratic transitions that occur when the opposition is fragmented and in the absence of a stunning authoritarian defeat.

Scholars use categorical classifications to understand the evolution, causes, and consequences of political regimes. Yet existing categorical classifications have important limitations. Binary classifications tend to focus exclusively on elections and consequently code as democracies hybrid regimes that hold reasonably free and fair elections but routinely violate democratic rights. Extant non-binary classifications often operationalize regime types in ways that do not consistently match their definitions. We address these shortcomings by introducing a new categorical classification of political regimes. We develop coding rules based on a procedural, non-minimalist understanding of political regimes to classify the regime type of every independent country in the world between 1900 and 2020 in four categories using data from V-Dem: democracies, semi-democracies, electoral authoritarian regimes, and closed authoritarian regimes. This classification has important advantages over existing work. It reflects contemporary theoretical understandings of the variety of regimes in the world in an internally consistent way; it is based on a clear and reproducible set of coding rules; and it relies on more and better data than other measures. We illustrate how appropriately classifying regimes better accommodates theoretical expectations and empirical evidence, improving construct validity.