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"de" : "A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine behavioral and survey data in a web tracked sample of N=1376 German citizens to investigate differences in ChatGPT activity (usage, visits, and adoption) during the first 11 months from the launch of the service (November 30, 2022). Guided by a model of technology acceptance (UTAUT-2), we examine the role of socio-demographics commonly associated with the digital divide in ChatGPT activity and explore further socio-political attributes identified via stability selection in Lasso regressions. We confirm that lower age and higher education affect ChatGPT usage, but neither gender nor income do. We find full-time employment and more children to be barriers to ChatGPT activity. Using a variety of social media was positively associated with ChatGPT activity. In terms of political variables, political knowledge and political self-efficacy as well as some political behaviors such as voting, debating political issues online and offline and political action online were all associated with ChatGPT activity, with online political debating and political self-efficacy negatively so. Finally, need for cognition and communication skills such as writing, attending meetings, or giving presentations, were also associated with ChatGPT engagement, though chairing/organizing meetings was negatively associated. Our research informs efforts to address digital disparities and promote digital literacy among underserved populations by presenting implications, recommendations, and discussions on ethical and social issues of our findings.",
"en" : "A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine behavioral and survey data in a web tracked sample of N=1376 German citizens to investigate differences in ChatGPT activity (usage, visits, and adoption) during the first 11 months from the launch of the service (November 30, 2022). Guided by a model of technology acceptance (UTAUT-2), we examine the role of socio-demographics commonly associated with the digital divide in ChatGPT activity and explore further socio-political attributes identified via stability selection in Lasso regressions. We confirm that lower age and higher education affect ChatGPT usage, but neither gender nor income do. We find full-time employment and more children to be barriers to ChatGPT activity. Using a variety of social media was positively associated with ChatGPT activity. In terms of political variables, political knowledge and political self-efficacy as well as some political behaviors such as voting, debating political issues online and offline and political action online were all associated with ChatGPT activity, with online political debating and political self-efficacy negatively so. Finally, need for cognition and communication skills such as writing, attending meetings, or giving presentations, were also associated with ChatGPT engagement, though chairing/organizing meetings was negatively associated. Our research informs efforts to address digital disparities and promote digital literacy among underserved populations by presenting implications, recommendations, and discussions on ethical and social issues of our findings."
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"pref" : "The published Stata syntax file (do-file) and dataset (partial version of the 2022 Inequality Barometer) can be used to replicate the results reported in the article.\n\nClimate change and most climate policies affect and reinforce different forms of inequalities. For instance, climate change policies that aim to change consumer behavior by increasing the price tag of goods and services that cause carbon emissions often carry a disproportionately higher burden (in terms of financial cost) to those with lower incomes. They can thereby either exacerbate existing income inequalities or contribute to generating new ones. Meanwhile, refraining from engaging with climate mitigation policies will incur other detrimental societal costs: the financial burden and the harmful consequences of climate change that future generations will have to bear if nothing is done. In this paper, we examine how the immediate economic inequality citizens face from climate mitigation policies (regarding carbon taxation) weighs against the long-term generational inequalities future generations will experience. We study how both types of inequality relate to policy support for climate change mitigation policies in the context of Germany. The German case is of special interest because a recent court ruling of the Federal Constitutional Court allows us to test whether making people aware of a new legal reality can bridge the gap between the economic and generational inequality. Our findings using a between-subjects survey experiment fielded among German citizens (N=6,319) in 2022 show that immediate economic concerns trump future generational concerns, generally making citizens less supportive of the policy. This negative support is however somewhat mitigated by the supportive signal from the court ruling.",
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"pref" : "This replication package refers to a paper entitled 'Who should pay for higher education?' which has not yet been published. The reference will be added as soon as the paper is published. \nThe debate over free versus tuition-based higher education centers on their significant social, economic, and political consequences, particularly regarding social mobility and economic inequality. However little is known about public preferences for higher education finance, especially when the potential choice set of policy options is broadened and when equity considerations become more salient. We conduct a survey experiment on a representative sample of the German population (N=6208) to study this. We find that making respondents aware of the inequalities of the free system, makes respondents more supportive of all tuition fee systems. Regardless of experimental variation, respondents are more supportive of alternative tuition fee policies that depend on the students' downstream income, or on their parental income. This support increases with the experimental information treatments. The published Stata syntax file (do-file) and the dataset (a partial version of the 2020 Inequality barometer published under https://doi.org/10.7802/2740) can be used to replicate the results in the article.",
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