Suchergebnisse

If voters are to hold governments to account for the state of the economy, they must know how it has changed. Indeed, this is a prerequisite for democratic accountability. Yet the perceptions that voters report often show signs of clear partisan bias. At present, we do not know if this bias is real or instead due to priming in political surveys. To test this, I assign subjects at random to either a political or nonpolitical survey. I then record their economic perceptions and compare the results for each group. I show that political surveys do worsen partisan bias, though only among supporters of the incumbent party. Still, much partisan bias remains unexplained, even in the nonpolitical condition. So, while economic perception items remain biased, we can at least be sure that most people respond to them in a similar way no matter the survey context.

Coronavirus upended British politics in 2020 but where does it fit into the ideological map of party competition? Recent British elections have seen a shift from economic left–right competition between the major parties to competition on the cultural (liberal–authoritarian) dimension, most notably in terms of the issues of immigration and membership of the European Union. Using British Election Study data from June 2020, we find that coronavirus attitudes fall primarily onto the traditional economic left–right dimension, with left-wing voters more willing to make economic sacrifices of various types to reduce infections. However, more draconian coronavirus measures (such as fining or imprisoning those who violate the coronavirus rules) are most supported by voters who score high on authoritarianism. We show that the structure of coronavirus attitudes puts the Conservative government in a difficult position where many steps it takes to reduce infections risk alienating its core economic right-wing vote.

AbstractSocial norms are important in explaining why people vote, but where do those norms come from and is social pressure motivated by partisanship? In this article, we use political discussion network data to examine the role of party identification in shaping the relationship between injunctive norms, civic duty and voter turnout. More specifically, we examine the extent to which both the application of injunctive norms and their impact on turnout is affected by shared partisan identification. We find that citizens are more likely to perceive normative pressure to vote from fellow partisans, a phenomenon we refer to as "partisan pressure". However we do not find consistent evidence for the hypothesis that turnout is more closely related to the approval or disapproval of discussants who share a partisanship. By separating the role of social pressure from that of normative beliefs we also demonstrate that injunctive norms affect voter turnout both directly and indirectly by increasing civic duty.

Can artificial intelligence accurately label open-text survey responses? We compare the accuracy of six large language models (LLMs) using a few-shot approach, three supervised learning algorithms (SVM, DistilRoBERTa, and a neural network trained on BERT embeddings), and a second human coder on the task of categorizing "most important issue" responses from the British Election Study Internet Panel into 50 categories. For the scenario where a researcher lacks existing training data, the accuracy of the highest-performing LLM (Claude-1.3: 93.9%) neared human performance (94.7%) and exceeded the highest-performing supervised approach trained on 1000 randomly sampled cases (neural network: 93.5%). In a scenario where previous data has been labeled but a researcher wants to label novel text, the best LLM's (Claude-1.3: 80.9%) few-shot performance is only slightly behind the human (88.6%) and exceeds the best supervised model trained on 576,000 cases (DistilRoBERTa: 77.8%). PaLM-2, Llama-2, and the SVM all performed substantially worse than the best LLMs and supervised models across all metrics and scenarios. Our results suggest that LLMs may allow for greater use of open-ended survey questions in the future.

The 2019 UK General Election had seismic consequences for British politics. After three years of political turmoil following the 2016 referendum on Britain's membership of the European Union (EU), the 2019 election marked a victory for the Leave side of the Brexit debate, putting to rest questions of a second referendum and any chance of Parliament blocking the Withdrawal Bill. The United Kingdom left the EU on January 31, 2020. Although there were clear consequences for Britain's EU membership, there is debate about whether 2019 was a "Brexit election" (Prosser 2020)—even a critical election (Green 2021)—or the continuation of long-term realignments in British politics (Cutts et al. 2020; Jennings and Stoker 2017). By most accounts, Brexit dominated the 2019 election as a political issue, but whether this represents a key moment in a process of realignment of voters in Britain remains to be seen.

Das CSES Module 5 (2016-2021) legt den Schwerpunkt auf "the politics of populism", also auf Populismus. Es erforscht länderübergreifend den Zusammenhang zwischen dem Aufstieg von populistischen Parteien und der Verteilung von "populistischen" Einstellungen innerhalb der Bevölkerung. Hauptziel des Moduls ist es, die Auffassungen der BürgerInnen von politischen Eliten, gesellschaftlichen "Out-Groups" und nationaler Identität sowie die sich hieraus ergebenden Implikationen für repräsentative Demokratien zu analysieren. Die Daten erlauben es Forschenden somit, die Variation im Wettbewerb politischer Eliten und "populistischer" Einstellungen über Demokratien hinweg mit einzubeziehen, und zu untersuchen, wie solche Wahrnehmungen das Wahlverhalten von BürgerInnen beeinflussen.