Election cycles and global religious intolerance.

Mass elections are key mechanisms for collective decision-making. But they are also blamed for creating intergroup enmity, particularly while they are underway; politicians use polarizing campaign strategies, and losing sides feel resentful and marginalized after results are announced. I investigate the impact of election proximity-that is, closeness to elections in time-on social cleavages related to religion, a salient form of group identity worldwide. Integrating data from ∼1.2 million respondents across 25 cross-country survey series, I find no evidence that people interviewed shortly before or after national elections are more likely to express negative attitudes toward religious outgroups than those interviewed at other times. Subgroup analysis reveals little heterogeneity, including by levels of political competition. Generalized social trust, too, is unaffected by election calendars. Elections may not pose as great a risk to social cohesion as is commonly feared.

Voter information campaigns and political accountability: Cumulative findings from a preregistered meta-analysis of coordinated trials.

Voters may be unable to hold politicians to account if they lack basic information about their representatives' performance. Civil society groups and international donors therefore advocate using voter information campaigns to improve democratic accountability. Yet, are these campaigns effective? Limited replication, measurement heterogeneity, and publication biases may undermine the reliability of published research. We implemented a new approach to cumulative learning, coordinating the design of seven randomized controlled trials to be fielded in six countries by independent research teams. Uncommon for multisite trials in the social sciences, we jointly preregistered a meta-analysis of results in advance of seeing the data. We find no evidence overall that typical, nonpartisan voter information campaigns shape voter behavior, although exploratory and subgroup analyses suggest conditions under which informational campaigns could be more effective. Such null estimated effects are too seldom published, yet they can be critical for scientific progress and cumulative, policy-relevant learning.