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Morgenstern, Sandra (2023): Inclusion of videos in seminar design. Washington, DC [APSA Preprints] more
Morgenstern, Sandra (2023): Quantitative measurements of migration decision making: How a more differentiated measurement perspective provides new insights on gender imbalances. [20th IMISCOE Annual Conference, Warsaw, July 03rd to July 06th, 2023] more
Morgenstern, Sandra, and Felix Jäger (2023): Can emotions explain how threat rhetoric shapes preferences for freedom versus security?. [PolMETH Europe, London, June 19th to June 20th, 2023] more
Morgenstern, Sandra, and Julia Kleinewiese (2023): Can (s)he be protected? Experimental evidence on vulnerabilities to exploitative labour migration offers in Tanzania. [9th Annual Conference on Migration and Diversity, Berlin, October 11th to October 13th, 2023] more
Morgenstern, Sandra, and Marc Helbling (2023): Migration aspirations and the perceptions of the political, economic and social environment in Africa. International Migration, 61, issue 6, pp. 102-117. more
Murr, Andreas, Richard Traunmüller and Jeff Gill (2023): Computing quantities of interest and their uncertainty using Bayesian simulation. Political Science Research and Methods, 11, issue 3, pp. 623 - 632. more
Müller, Klara (2023): Election Outcomes as Drivers of Panel Attrition? Investigating Winner-Loser Effects in Post-Election Survey Participation. [WAPOR 76th Annual Conference, Salzburg, September 19th to September 22nd, 2023] more
Müller, Klara (2023): Political Events as Drivers of Survey Nonresponse? Effects of Election Outcomes on Individuals’ Willingness to Participate in Surveys. [EPOP 2023 Conference, Southampton, September 08th to September 09th, 2023] more
Müller, Philipp, and Ruben L. Bach (2023): Populist alternative news use and its role for elections: Web-tracking and survey evidence from two campaign periods. New Media & Society, 25, issue 10, pp. 2663–2683. more
Müller, Philipp, Chung-hong Chan, Katharina Ludwig, Rainer Freudenthaler and Hartmut Wessler (2023): Differential Racism in the News: Using Semi-Supervised Machine Learning to Distinguish Explicit and Implicit Stigmatization of Ethnic and Religious Groups in Journalistic Discourse. Political Communication, 40, issue 4, pp. 396-414. more

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