ElecMeter: An index for evaluating dissatisfaction of social decision-making

Understanding dissatisfaction in social decision-making is important for diagnosing structural features of collective outcomes that may be informative about differences in acceptance and cohesion. Existing electoral metrics typically focus on satisfaction or utility, overlooking dissatisfaction as an independent and socially meaningful factor. We introduce ElecMeter, a novel index for single-winner elections that defines voter dissatisfaction as the normalized rank of the elected candidate and incorporates both average and distributional features. A divergence-based component compares the observed distribution to benchmarks of maximal dissatisfaction, polarization, and neutrality using Jensen-Shannon divergence. Scores are aggregated via a generalized mean controlling sensitivity to extreme dissatisfaction. Simulations show that ElecMeter distinguishes electorates with similar average dissatisfaction but different distributional structures. Applied to the classic Breakfast Items dataset, ElecMeter consistently identifies winners across parameter settings and aligns with several classical voting rules, demonstrating internal robustness of the index. All code and data are available on GitHub, ensuring reproducibility.