Jérôme-Speziari 2010), with an initial deployment of political-economy models based on
regression analysis. Later, these models were rivaled by publicopinion polling approaches …

The expectations of voters regarding election outcomes appear to be mostly influenced by
their own political preferences. This raises two important questions. First, once partisan …

In the last 40 years or so, scholars have proposed a vast array of models and approaches to
predict election outcomes in a variety of democracies. Election forecasting has garnered …

Background: Knowing the needs of the bioimaging community with respect to research data
management (RDM) is essential for identifying measures that enable adoption of the FAIR …

The leading approaches to scientific election fore-casting in the United States consist of
structural models, prediction markets, and opinion polling. With respect to the last, by far the …

Partisan preferences usually stand out as the major driving force behind voters' expectations
about election outcomes. Apart from partisan preferences, however, purely individual‐level …

The emergent literature on citizen forecasting suggests that the public, in the aggregate, can
often accurately predict the outcomes of elections. However, it is not clear how citizens form …

With respect to the German case, the first two approaches—polls and models—perhaps
have been the most popular. However, relatively little work has been done deploying citizen …

Political divisions in the lead-up to the 2020 US presidential election were large, leading
many to worry that heighted partisan conflict was so stark that partisans were living in …

Human dynamics and sociophysics build on statistical models that can shed light on and
add to our understanding of social phenomena. We propose a generative model based on a …