Source Themes

Unintended Effects of Cordons Sanitaires on the Electoral Success of Isolated Parties: Counterfactual Agent-Based Simulations in an Artificial Weimar Republic with Coalition-Directed Voters
Ruling out forming coalition governments with parties critical of liberal democracy, i.e., establishing cordons sanitaires vis-à-vis these parties, is often seen as a crucial contribution to safeguarding liberal democracy. However, little is known about whether cordons sanitaires are effective in reducing the vote share of parties isolated in this way. Specifically, the effects of cordons sanitaires on voting induced by changes in voters’ expectations of post-electoral government formation remain unclear. I address this research gap by conceptualizing cordons sanitaires as a specific class of pre-electoral coalition signals and drawing on theoretical knowledge about the electoral expectation-induced consequences of coalition signals. I integrate these theoretical insights into a formal agent-based model of dynamic party competition and perform counterfactual simulations in an artificial democracy calibrated to resemble the 1930s Weimar Republic. The results show that the vote share of an artificial NSDAP increases when a cordon sanitaire is erected against it. By illustrating the theoretical possibility (not inevitability) of these unintended expectation-induced consequences, the paper provides important implications for research on the mainstream parties’ response to radical parties.
Unintended Effects of Cordons Sanitaires on the Electoral Success of Isolated Parties: Counterfactual Agent-Based Simulations in an Artificial Weimar Republic with Coalition-Directed Voters
Observing Many Researchers Using the Same Data and Hypothesis Reveals a Hidden Universe of Uncertainty
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, namely 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.
Observing Many Researchers Using the Same Data and Hypothesis Reveals a Hidden Universe of Uncertainty