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AbstractHow does terrorism affect citizens' political attitudes? Over the years, many scholars have tried to answer this question. This article performs a meta‐analysis on this literature, reviewing about 325 studies conducted between 1985 and 2020 on more than 400,000 respondents. The findings confirm that terrorism is associated—to a small but significant extent—with outgroup hostility, political conservatism and rally‐'round‐the‐flag effects. At the same time, the effects of terrorism vary widely, with studies on Islamist violence, conducted in the United States or Israel, and using cross‐sectional data yielding stronger results on average. Finally, the review reveals remaining gaps in this field of study, including a lack of research on non‐Islamist violence or conducted in non‐Western contexts. Taken together, this meta‐analysis consolidates existing evidence, determines which results hold across contexts, and identifies key gaps in our current knowledge. Its data can also be accessed interactively via a Shiny App.

How does terrorism affect citizens' political attitudes? Over the years, many scholars have tried to answer this question. This article performs a meta-analysis on this literature, reviewing about 325 studies conducted between 1985 and 2020 on more than 400,000 respondents. The findings confirm that terrorism is associated—to a small but significant extent—with outgroup hostility, political conservatism, and rally-'round-the-flag effects. At the same time, the effects of terrorism vary widely, with studies on Islamist violence, conducted in the United States or Israel, and using cross-sectional data yielding stronger results on average. Finally, the review reveals remaining gaps in this field of study, including a lack of research on non-Islamist violence or conducted in non-Western contexts. Taken together, this meta-analysis consolidates existing evidence, determines which results hold across contexts, and identifies key gaps in our current knowledge. Its data can also be accessed interactively via a Shiny App. ; publishedVersion

Reintegrating ex-combatants back into society is one of the most challenging, yet fundamental components to building sustainable peace. While previous work has extensively evaluated the reintegration trajectories of ex-combatants, there is still little understanding of how citizens think about reintegration. In this article, we systematically analyze which former fighters people prefer to reintegrate into society. Based on theories of threat and justice, we develop a heuristic framework that explains how information about the motivations and behavior of ex-combatants shapes public preferences about whom to reintegrate. We test this framework using a conjoint experiment conducted among approximately 2,000 (former) university students in Nigeria. We find that our respondents are more forgiving towards former fighters who were forced to join the insurgency and expressed remorse afterwards, while being less willing to reintegrate more militant and less repentant offenders. Similar informational cues shape respondents' evaluations of how successful the reintegration process would be and what punishment would be appropriate. Taken together, the results underscore the importance of perceptions of risk and fairness in driving attitudes towards reintegration. Finally, subgroup analyses revealed that these heuristics are broadly held across different demographic and conflict-related fault lines. While caution is warranted when generalizing these results, insights gained in this specific context are nonetheless an important step towards advancing our understanding of reintegration processes in conflict-affected countries.

Reintegrating ex-combatants back into society is one of the most challenging, yet fundamental components to building sustainable peace. While previous work has extensively evaluated the reintegration trajectories of ex-combatants, there is still little understanding of how citizens think about reintegration. In this article, we systematically analyze which former fighters people prefer to reintegrate into society. Based on theories of threat and justice, we develop a heuristic framework that explains how information about the motivations and behavior of ex-combatants shapes public preferences about whom to reintegrate. We test this framework using a conjoint experiment conducted among approximately 2,000 (former) university students in Nigeria. We find that our respondents are more forgiving towards former fighters who were forced to join the insurgency and expressed remorse afterwards, while being less willing to reintegrate more militant and less repentant offenders. Similar informational cues shape respondents' evaluations of how successful the reintegration process would be and what punishment would be appropriate. Taken together, the results underscore the importance of perceptions of risk and fairness in driving attitudes towards reintegration. Finally, subgroup analyses revealed that these heuristics are broadly held across different demographic and conflict-related fault lines. While caution is warranted when generalizing these results, insights gained in this specific context are nonetheless an important step towards advancing our understanding of reintegration processes in conflict-affected countries.

This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.