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We Need to Talk
Americans today are affectively polarized: they dislike and distrust those from the opposing political party more than they did in the past, with damaging consequences for their democracy. This Element tests one strategy for ameliorating such animus: having ordinary Democrats and Republicans come together for cross-party political discussions. Building on intergroup contact theory, the authors argue that such discussions will mitigate partisan animosity. Using an original experiment, they find strong support for this hypothesis – affective polarization falls substantially among subjects who participate in heterogeneous discussion (relative to those who participate in either homogeneous political discussion or an apolitical control). This Element also provides evidence for several of the mechanisms underlying these effects, and shows that they persist for at least one week after the initial experiment. These findings have considerable importance for efforts to ameliorate animus in the mass public, and for understanding American politics more broadly.
Embracing Philanthropic Environmentalism
This book addresses urban ecology, green technology, problems with climate change prediction, groundwater contamination, invasive species and many other topics, and offers a guardedly optimistic interpretation of humanity's place in nature and our unique caretaker role. Drawing upon scholarly and media sources, the author presents a common-sense analysis of environmental science, debunking eco-apocalyptic thinking along the way. Compromised science masquerading as authoritative is revealed as a fundraising and policy-influencing crusade by the environmental elite, overshadowing unambiguous problems like environmental racism.
Digital Communication and Populism in Times of Covid-19
This book examines different dimensions of digital communication and populism in times of the COVID-19 pandemic. While doing so, it discusses views, opinions, and research results regarding the conditions, experiences, constraints, benefits, and challenges related to the topic - not only using theoretical and methodological approaches but also practical perspectives. The COVID-19 (SARS-CoV-2) pandemic significantly accelerated the technological revolution presenting many social, economic, and political challenges, as it pushed the world into cyberspace to ensure social distancing. At the same time, many populist protests expressed in the digital public sphere massively gained importance duri...
Public Opinion and Democracy in Poland
"If representation is one of the most important aspects of representative democracy, then a precondition for representation is a rational public. Without a public that holds rational and stable policy preferences, there would be nothing for elected officials to represent. The public opinion and representation literature has so far focused mainly on developed Western democracies, finding not only rational public opinion, but also a fair amount of representation. Post-communist literature, on the other hand, focuses very little on aggregate public opinion and representation and offers mixed conclusions. Following the footsteps of Page & Shapiro (1992), the focus of this thesis is an analysis of aggregate Polish public opinion using an original dataset of public opinion encompassing the years 1981-2011. Additionally, a brief analysis of representation is conducted, utilizing long-term trends in policy preferences among Poles. The findings are presented not only in light of current debates in the post-communist and public opinion and representation literatures, but also within the broader debates about democracy." --
Machine Learning for Experiments in the Social Sciences
Causal inference and machine learning are typically introduced in the social sciences separately as theoretically distinct methodological traditions. However, applications of machine learning in causal inference are increasingly prevalent. This Element provides theoretical and practical introductions to machine learning for social scientists interested in applying such methods to experimental data. We show how machine learning can be useful for conducting robust causal inference and provide a theoretical foundation researchers can use to understand and apply new methods in this rapidly developing field. We then demonstrate two specific methods – the prediction rule ensemble and the causal random forest – for characterizing treatment effect heterogeneity in survey experiments and testing the extent to which such heterogeneity is robust to out-of-sample prediction. We conclude by discussing limitations and tradeoffs of such methods, while directing readers to additional related methods available on the Comprehensive R Archive Network (CRAN).
Corona, the Lockdown, and the Media
Corona, the Lockdown, and the Media investigates media influence on policies to contain the COVID-19 pandemic. Bernhagen and Kybelka propose that news reporting on the pandemic pitches human impact against economic consequences of the virus and of restrictive policy measures designed to contain it. They argue that the use of these frames influences governments’ decisions to enact or lift lockdown measures. Using time series data from England, France, and Germany, the authors show that news reporting on COVID-19 was indeed characterized by these media frames. However, there is no evidence of media influence on government policy. Instead, the authors find that anti-pandemic policy decisions were responsive to public opinion in these countries.
Undue Hate
How to understand the mistakes we make about those on the other side of the political spectrum—and how they drive the affective polarization that is tearing us apart. It’s well known that the political divide in the United States—particularly between Democrats and Republicans—has grown to alarming levels in recent decades. Affective polarization—emotional polarization, or the hostility between the parties—has reached an unprecedented fever pitch. In Undue Hate, Daniel F. Stone tackles the biases undergirding affective polarization head-on. Stone explains why we often develop objectively false, and overly negative, beliefs about the other side—causing us to dislike them more tha...
