Working the Crowd: Citizen Forecasting, Sophistication and Diversity in Canadian Federal and Provincial Elections

Abstract According to the “miracle of aggregation” principle, in the absence of systematic biases, errors in individual judgments within a population should cancel each other out and lead to a correct decision at the aggregate level. This article explores potential individual- and group-level correlates of the accuracy of citizens’ electoral expectations and investigates how potential markers of political sophistication—namely, educational attainment and political interest—could be used to improve upon the raw aggregation of citizens’ forecasts using massive survey datasets collected during six Canadian national and provincial election campaigns between 2011 and 2022 ( n = 279,003). We find that while educational attainment and interest increase the probability of a correct forecast at the individual level, delegating the forecasting task based on these variables does not necessarily lead to improvements in the accuracy of aggregate-level predictions. At the group level, we fail to uncover any evidence that sociological or informational diversity increases forecasting accuracy.