Elections as Windows of Opportunity? Civic Space in Democratic and Backsliding Regimes

This study investigates how backsliding regimes and consolidated democracies differ in their treatment of civic space during electoral and non-electoral periods, using high-frequency data from the Machine Learning for Peace project. Analyzing seven aspects of civic space, including censorship, arrests, and protests, the research reveals that backsliding regimes engage in significantly more censorship and arrests during non-electoral periods and intensify censorship efforts in the six months preceding elections. Surprisingly, few significant differences exist between regime types during the actual election month, suggesting strategic behavior by aspiring autocrats. Electorally vulnerable backsliding regimes exhibit distinct patterns, using fewer legal actions and experiencing more significant post-election protest reductions. Additionally, these more vulnerable regimes make fewer arrests pre-election but employ more violence and less censorship during the election month compared to their more secure counterparts. These findings indicate that democratic backsliding is more pronounced between elections, emphasizing the need for sustained attention to governance practices during non-electoral periods to safeguard democratic institutions