The success of protests depends on whether they favorably affect public opinion: nonviolent resistance can win public support for a movement, but regimes counter by framing protest as violent and instigated by outsiders. The authors argue that public perceptions of whether a protest is violent shift based on the framing of the types of action and the identities of participants in those actions. The article distinguishes between three dimensions: (1) threat of harm, (2) bearing of arms and (3) identity of protesters. Using survey experiments in Israel and the United States, the study finds support for framing effects. Threat of harm has the largest positive effect on perceptions of violence and support for repression. Surprisingly, social out-groups are not perceived as more violent, but respondents favor repressing them anyway. Support for repressing a nonthreatening out-group is at least as large as support for repressing a threatening in-group. The findings link contentious action and public opinion, and demonstrate the susceptibility of this link to framing.

Media framing of epidemics was found to influence public perceptions and behaviors in experiments, yet no research has been conducted on real-world behaviors during public health crises. We examined the relationship between Italian news media coverage of COVID-19 and compliance with stay-at-home orders, which could impact the spread of epidemics. We used a computational method for framing analysis (ANTMN) and combined it with Google’s Community Mobility data. A time-series analysis using vector autoregressive models showed that the Italian media used media frames that were largely congruent with ones used by journalists in other countries: A scientific frame focusing on symptoms and health effects, a containment frame focusing on attempts to ameliorate risks, and a social frame, focusing on political and social impact. The prominence of different media frames over time was associated with changes in Italians’ mobility patterns. Specifically, we found that the social frame was associated with increased mobility, whereas the containment frame was associated with decreased mobility. The results demonstrate that the ways the news media discuss epidemics can influence changes in community mobility, above and beyond the effect of the number of deaths per day.

Do coups affect patterns of political violence like violations of physical integrity rights? Do these patterns vary depending on whether coups succeed or fail? We argue that political uncertainty from coups decreases respect for physical integrity rights. Post-coup regimes preemptively repress as a show of strength to deter threats from those excluded from power and settle scores through cycles of retaliation. Additionally, we argue that the retaliation cycle of score settling will last longer after a failed coup because of informational problems that emerge when targeting opponents. Employing data on coups and physical integrity rights from 1980 to 2015, we find coup failure and success to be negatively associated with respect for physical integrity rights, and the cycle of retaliation lasts longer after failed coups.

This research project uses econometric methods and comparative, cross-national data to see whether violations of human rights increase the likelihood of the onset or escalation of violent protest, terrorism and/or civil war. The findings show that these types of violent internal conflict will occur and escalate if governments: (1) torture, politically imprison, kill, or “disappear” people, (2) do not allow women to participate fully in the political system, including allowing them to hold high level national political office, and (3) do not allow women to participate fully in the economic life of the nation by ensuring equal pay for equal work, by encouraging their entry to the highest paid occupations, and by protecting them from sexual harassment at their workplaces. These types of violations of human rights and the existence of large horizontal inequalities in societies independently produce an increased risk of the onset and escalation of many forms of violent internal conflict. The results also provide some evidence for the argument that there is a trade-off between liberty and security.

Human trafficking affects millions of people globally, disproportionately harming women, girls and marginalized groups. Yet one of the main sources of data on global trafficking, the annual Trafficking in Persons (TIP) Reports, is susceptible to biases because report rankings are tied to political outcomes. The literature on human rights measurements has established two potential sources of bias. The first is the changing standards of accountability, where more information and increased budgets change the standard to which countries are held over time. The second is political biases in reports, which are amended to comply with the interests of the reporting agency. This letter examines whether either of these biases influence the TIP Reports. In contrast to other country-level human rights indicators, the State Department issues both narratives and rankings, which incentivizes attempts to influence the rankings based on political interests. The study uses a supervised machine-learning algorithm to examine how narratives are translated into rankings, to determine whether rankings are biased, and to disentangle whether bias stems from changing standards or political interests. The authors find that the TIP Report rankings are more influenced by political biases than changing standards.

Human rights measurement efforts have been confronted with concerns of bias practically since quantitative measurement efforts began in the late 1970s and early 1980s. By and large, attacks have focused on biases to the source materials on which these measurement efforts rely—namely, the annual human rights reports produced by Amnesty International and the US Department of State. We take stock and seek to distinguish conceptually distinct types of bias that have been conflated in the past, yet plausibly affect human rights measures. In addition to revisiting reporting bias or organizational bias long identified in the literature, we also disentangle two types of bias that have been of concern more recently: bias attributable to changing standards and information effects. For each type of bias we identify, we provide an empirical implication as to the effect on human rights measures and, importantly, its spatial or temporal variation.