1,720,995 research outputs found
Replication Data for "Moral Language Use by U.S. Political Elites"
No full textReplication data for:
Wang, S. N. & Inbar, Y. (2020). Moral language use by U.S. political elites. Psychological Science
Replication Data for: When Do People Prefer Carrots to Sticks? A Robust “Matching Effect” in Policy Evaluation
No full textData for all studies reported in:
Evers, E. R. K., Inbar, Y., Blanken, I., & Oosterwijk, L. D. (2016). When do people prefer carrots to sticks? A robust “matching effect” in policy evaluation. Management Science
Replication Data for: When Do People Prefer Carrots to Sticks? A Robust “Matching Effect” in Policy Evaluation
No full textData for all studies reported in:
Evers, E. R. K., Inbar, Y., Blanken, I., & Oosterwijk, L. D. (2016). When do people prefer carrots to sticks? A robust “matching effect” in policy evaluation. Management Science
Replication Data for: Re-Examining the Diffusion of Moralized Rhetoric From Political Elites
No full textDDR loadings for positive and negative moral language in tweets from Members of Congress
Mapping Attitudes Towards Controversial Technologies
Full text linkNew technologies in agriculture, reproduction, medicine, and elsewhere can provide significant social benefits, but may also pose significant risks. Consequently, it is important to understand which technologies will be adopted or rejected by the public, and why. Seven studies presented here examine underlying regularities in laypeople’s technology evaluations. Studies 1a-1b provide evidence for underlying regularities in technology evaluations, such that evaluations of superficially quite different technologies tend to cohere across individuals. Dimension reduction of people’s ratings of a wide range of technologies recovers three groups, which I label Contaminating, Playing God, and Mainstream. Attitudes towards these groups of technologies: (1) are associated with distinct individual differences (Studies 1-2b); (2) fall into distinct areas of a psychological risk perception space (Study 3); (3) are differentially affected by a manipulation of deliberative processing (Study 4). Finally, Study 5 investigates the extent to which technological risk assessments are grounded in moral convictions and are treated as sacred values. Implications of this work for technology developers and policy makers are also discussed.Ph.D
Moral Language Across the Political Spectrum
No full textAcross two studies, we analyzed ideological differences in moral language use based on the moral categories posited by Moral Foundations Theory (MFT): fairness, harm, authority, purity, and ingroup loyalty. In Study 1 we used word counting to assess the moral language used on U.S. political talk shows, finding some support for MFT: Democrats used more language related to fairness and Republicans used more language related to authority. Republicans also used more language related to morality in general. No other differences were significant. In Study 2, we analyzed the Tweets of members of the 115th U.S. Congress, and found that Democrats used more moral language across all MFT categories than Republicans. A time series analysis revealed that these differences are larger after the 2016 Presidential election. These findings suggest that there are differences in moral language use across the political spectrum, and that these differences may be affected by political events.M.A.2019-11-23 00:00:0
Moral Language Across the Political Spectrum
Full text linkAcross two studies, we analyzed ideological differences in moral language use based on the moral categories posited by Moral Foundations Theory (MFT): fairness, harm, authority, purity, and ingroup loyalty. In Study 1 we used word counting to assess the moral language used on U.S. political talk shows, finding some support for MFT: Democrats used more language related to fairness and Republicans used more language related to authority. Republicans also used more language related to morality in general. No other differences were significant. In Study 2, we analyzed the Tweets of members of the 115th U.S. Congress, and found that Democrats used more moral language across all MFT categories than Republicans. A time series analysis revealed that these differences are larger after the 2016 Presidential election. These findings suggest that there are differences in moral language use across the political spectrum, and that these differences may be affected by political events.M.A.2019-11-23 00:00:0
Mapping Aversion to Controversial Scientific Technologies
No full textTechnologies in agriculture, reproduction, medicine, and elsewhere promise significant social benefits, but may also pose significant risks. Understanding which technologies will be adopted or rejected by the public—and why—is important. Across five studies assessments of risks, benefits, and acceptability of a range of technologies were examined. Two studies found evidence for a ‘clustering’ effect of technological attitudes: evaluations of risks associated with different technologies tend to vary together, and attitudes towards technologies within each cluster are differentially predicted with individual difference measures. A third study showed that manipulating processing style alters subsequent evaluations of technologies, and that the effects are different across clusters. The final two studies first replicated and expanded upon a foundational technological risk assessment study by Fischhoff et al. (1978). Together, these findings suggest the need for a more nuanced and updated paradigm for technological risk
assessment that incorporates individual-level characteristics to predict technological aversionM.A
Mapping Aversion to Controversial Scientific Technologies
Full text linkTechnologies in agriculture, reproduction, medicine, and elsewhere promise significant social benefits, but may also pose significant risks. Understanding which technologies will be adopted or rejected by the public—and why—is important. Across five studies assessments of risks, benefits, and acceptability of a range of technologies were examined. Two studies found evidence for a ‘clustering’ effect of technological attitudes: evaluations of risks associated with different technologies tend to vary together, and attitudes towards technologies within each cluster are differentially predicted with individual difference measures. A third study showed that manipulating processing style alters subsequent evaluations of technologies, and that the effects are different across clusters. The final two studies first replicated and expanded upon a foundational technological risk assessment study by Fischhoff et al. (1978). Together, these findings suggest the need for a more nuanced and updated paradigm for technological risk
assessment that incorporates individual-level characteristics to predict technological aversionM.A
Motivators and Consequences of Moral Rhetoric
Full text linkWhen do politicians moralize, and what consequences does moralization have? In the current research, I combine language analysis techniques and experimental manipulations to measure the moral rhetoric of U.S. political elites and test the consequences of this moral rhetoric. I draw upon the literature on Moral Foundations Theory and social identity theory and use techniques from natural language processing to measure the moral rhetoric expressed in language on Twitter and in Congressional speeches. I find that moralization increased after the 2016 U.S. Presidential election, particularly for Democrats. I also find evidence of a more general effect of political power, such that U.S. political elites moralize more when they are in the political minority. Messages containing negative moral rhetoric diffused more widely on Twitter. I also present evidence that positive moral rhetoric can motivate political action and reduce affective polarization for political independents, and that moral rhetoric can shift independents’ political ideology.Ph.D
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